[GitHub] [incubator-mxnet] ckt624 commented on a change in pull request #15349: Numpy Tensordot Operator
ckt624 commented on a change in pull request #15349: Numpy Tensordot Operator
URL: https://github.com/apache/incubator-mxnet/pull/15349#discussion_r302852496
##
File path: tests/python/unittest/test_numpy_op.py
##
@@ -26,6 +26,151 @@
from mxnet.test_utils import check_numeric_gradient
from common import assertRaises, with_seed
import random
+import collections
+
+@with_seed()
+@npx.use_np_shape
+def test_np_tensordot():
+class TestTensordot(HybridBlock):
+def __init__(self, axes):
+super(TestTensordot, self).__init__()
+self._axes = axes
+
+def hybrid_forward(self, F, a, b):
+return F.np.tensordot(a, b, self._axes)
+
+def tensordot_backward(a, b, axes = 2):
+if (a.ndim < 1) or (b.ndim < 1):
+raise ValueError('An input is zero-dim')
+
+if isinstance(axes, collections.abc.Sequence):
+if len(axes) != 2:
+raise ValueError('Axes must consist of two arrays.')
+a_axes_summed, b_axes_summed = axes
+if _np.isscalar(a_axes_summed):
+a_axes_summed = a_axes_summed,
+if _np.isscalar(b_axes_summed):
+b_axes_summed = b_axes_summed,
+else:
+a_axes_summed = [i + a.ndim - axes for i in range(axes)]
+b_axes_summed = [i for i in range(axes)]
+
+if len(a_axes_summed) != len(b_axes_summed):
+raise ValueError('Axes length mismatch')
+
+a_axes_remained = []
+for i in range(a.ndim):
+if not (i in a_axes_summed):
+a_axes_remained.append(i)
+a_axes = a_axes_remained[:] + a_axes_summed[:]
+
+b_axes_remained = []
+for i in range(b.ndim):
+if not (i in b_axes_summed):
+b_axes_remained.append(i)
+b_axes = b_axes_summed[:] + b_axes_remained[:]
+
+ad1 = _np.prod([a.shape[i] for i in a_axes_remained]) if
len(a_axes_remained) > 0 else 1
+ad2 = _np.prod([a.shape[i] for i in a_axes_summed]) if
len(a_axes_summed) > 0 else 1
+bd1 = _np.prod([b.shape[i] for i in b_axes_summed]) if
len(b_axes_summed) > 0 else 1
+bd2 = _np.prod([b.shape[i] for i in b_axes_remained]) if
len(b_axes_remained) > 0 else 1
+
+out_grad = _np.ones((ad1, bd2))
+
+new_a = _np.transpose(a, a_axes)
+new_a_shape = new_a.shape[:]
+new_a = new_a.reshape((ad1, ad2))
+new_b = _np.transpose(b, b_axes)
+new_b_shape = new_b.shape[:]
+new_b = new_b.reshape((bd1, bd2))
+
+reverse_a_axes = [0 for i in a_axes]
+for i in range(len(a_axes)):
+reverse_a_axes[a_axes[i]] = i
+
+reverse_b_axes = [0 for i in b_axes]
+for i in range(len(b_axes)):
+reverse_b_axes[b_axes[i]] = i
+
+grad_b = _np.dot(new_a.T, out_grad).reshape(new_b_shape)
+grad_b = _np.transpose(grad_b, reverse_b_axes)
+grad_a = _np.dot(out_grad, new_b.T).reshape(new_a_shape)
+grad_a = _np.transpose(grad_a, reverse_a_axes)
+
+return [grad_a, grad_b]
+
+# test non zero size input
+tensor_shapes = [
+((3, 5), (5, 4), 1), # (a_shape, b_shape, axes)
+((3,), (3,), 1),
+((3, 4, 5, 6, 7), (5, 6, 7, 1, 2), 3),
+((3, 5, 4, 6, 7), (7, 6, 5, 1, 2), [[1, 3, 4], [2, 1, 0]]),
+((2, 2), (2, 2), 2),
+((3, 5, 4), (5, ), [[1], [0]]),
+((2,), (2, 3), 1),
+((3,), (3,), 0),
+((2,), (2, 3), 0),
+((3, 5, 4), (5, ), 0)
+]
+
+for hybridize in [True, False]:
+for a_shape, b_shape, axes in tensor_shapes:
+for dtype in [_np.float32, _np.float64]:
Review comment:
Don't support fp16 at CPU.
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[GitHub] [incubator-mxnet] roywei commented on issue #15452: fix nightly CI failure
roywei commented on issue #15452: fix nightly CI failure
URL: https://github.com/apache/incubator-mxnet/pull/15452#issuecomment-510776556
I have verified test_estimator passed. but test tutorials is still failing
due to other tutorials are failing. This change is needed nonetheless
```
--
Ran 2 tests in 341.805s
OK
build.py: 2019-07-12 01:33:11,865Z INFO Waiting for status of container
594316b5c329 for 600 s.
build.py: 2019-07-12 01:33:12,139Z INFO Container exit status: {'Error':
None, 'StatusCode': 0}
build.py: 2019-07-12 01:33:12,139Z INFO Container exited with success 👍
build.py: 2019-07-12 01:33:12,140Z INFO Stopping container: 594316b5c329
build.py: 2019-07-12 01:33:12,141Z INFO Removing container: 594316b5c329
```
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[GitHub] [incubator-mxnet] matteosal commented on issue #15497: [MKLDNN] Independent gradients requests check with respect to weights and bias of convolution
matteosal commented on issue #15497: [MKLDNN] Independent gradients requests check with respect to weights and bias of convolution URL: https://github.com/apache/incubator-mxnet/pull/15497#issuecomment-510787762 > @matteosal I tested your example with commit [9ca0428](https://github.com/apache/incubator-mxnet/commit/9ca042839b519c91963f77f694673557e9fddfc8), and it ran successfully without any exception. Could you test it again with commit [9ca0428](https://github.com/apache/incubator-mxnet/commit/9ca042839b519c91963f77f694673557e9fddfc8)? Ops sorry, I've missed that commit. Yes, it works on that This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] zixuanweeei commented on issue #15497: [MKLDNN] Independent gradients requests check with respect to weights and bias of convolution
zixuanweeei commented on issue #15497: [MKLDNN] Independent gradients requests check with respect to weights and bias of convolution URL: https://github.com/apache/incubator-mxnet/pull/15497#issuecomment-510794204 @matteosal Thanks. That's great. I am working on a unit test for this feature. Then we can merge it to master after further review and verification. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] mikemwx commented on a change in pull request #15302: [Numpy] Numpy hstack
mikemwx commented on a change in pull request #15302: [Numpy] Numpy hstack URL: https://github.com/apache/incubator-mxnet/pull/15302#discussion_r302873300 ## File path: tests/python/unittest/test_numpy_op.py ## @@ -860,6 +860,72 @@ def get_new_shape(shape, axis): assert_almost_equal(mx_out.asnumpy(), np_out, rtol=1e-3, atol=1e-5) +@with_seed() +@npx.use_np_shape +def test_np_hstack(): +class TestHStack(HybridBlock): +def __init__(self): +super(TestHStack, self).__init__() + +def hybrid_forward(self, F, a, *args): +return F.np.hstack([a] + list(args)) + +def get_new_shape(shape): +if len(shape) == 0: +l = random.randint(0,3) +if l == 0: +return shape +else: +return (l,) +shape_lst = list(shape) +axis = 1 if len(shape) > 1 else 0 +shape_lst[axis] = random.randint(0, 5) +return tuple(shape_lst) + +shapes = [ +(), +(1,), +(2,1), +(2,2,4), +(2,0,0), +(0,1,3), +(2,0,3), +(2,3,4,5) +] +for hybridize in [True, False]: +for shape in shapes: +test_hstack = TestHStack() +if hybridize: +test_hstack.hybridize() +# test symbolic forward +a = np.random.uniform(size=get_new_shape(shape)) +a.attach_grad() +b = np.random.uniform(size=get_new_shape(shape)) +b.attach_grad() +c = np.random.uniform(size=get_new_shape(shape)) +c.attach_grad() +d = np.random.uniform(size=get_new_shape(shape)) +d.attach_grad() +with mx.autograd.record(): +mx_out = test_hstack(a, b, c, d) +np_out = _np.hstack((a.asnumpy(), b.asnumpy(), c.asnumpy(), d.asnumpy())) +assert mx_out.shape == np_out.shape +assert_almost_equal(mx_out.asnumpy(), np_out, rtol=1e-3, atol=1e-5) + +# test symbolic backward +mx_out.backward() +assert_almost_equal(a.grad.asnumpy(), _np.ones(a.shape), rtol=1e-3, atol=1e-5) +assert_almost_equal(b.grad.asnumpy(), _np.ones(b.shape), rtol=1e-3, atol=1e-5) +assert_almost_equal(c.grad.asnumpy(), _np.ones(c.shape), rtol=1e-3, atol=1e-5) +assert_almost_equal(d.grad.asnumpy(), _np.ones(d.shape), rtol=1e-3, atol=1e-5) + +# test imperative +mx_out = np.hstack((a, b, c, d)) +np_out = _np.hstack((a.asnumpy(),b.asnumpy(), c.asnumpy(), d.asnumpy())) +assert_almost_equal(mx_out.asnumpy(), np_out, rtol=1e-3, atol=1e-5) + + Review comment: Done This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] mikemwx commented on a change in pull request #15314: [Numpy] Numpy dstack
mikemwx commented on a change in pull request #15314: [Numpy] Numpy dstack
URL: https://github.com/apache/incubator-mxnet/pull/15314#discussion_r302874471
##
File path: src/operator/numpy/np_matrix_op.cc
##
@@ -55,6 +55,67 @@ bool NumpyTransposeShape(const nnvm::NodeAttrs& attrs,
return shape_is_known(ret);
}
+bool DStackShape(const nnvm::NodeAttrs& attrs,
+ mxnet::ShapeVector *in_shape,
+ mxnet::ShapeVector *out_shape) {
+ using namespace mshadow;
+ ConcatParam param_ = nnvm::get(attrs.parsed);
+ CHECK_EQ(in_shape->size(), static_cast(param_.num_args));
+ mxnet::TShape dshape;
+ dim_t size = 0;
+ bool has_unknown_dim_size = false;
+ int axis = 2;
+ param_.dim = axis;
+ for (int i = 0; i < param_.num_args; ++i) {
+if ((*in_shape)[i].ndim() == 0) {
+ (*in_shape)[i] = mxnet::TShape(3, 1);
+} else if ((*in_shape)[i].ndim() == 1) {
+ mxnet::TShape t = mxnet::TShape(3, 1);
+ t[1] = (*in_shape)[i][0];
+ (*in_shape)[i] = t;
+} else if ((*in_shape)[i].ndim() == 2) {
+ mxnet::TShape t = mxnet::TShape(3, 1);
+ t[0] = (*in_shape)[i][0];
+ t[1] = (*in_shape)[i][1];
+ (*in_shape)[i] = t;
+}
+mxnet::TShape &tmp = (*in_shape)[i];
+if (tmp.ndim() > 0) {
+ CheckAxis(axis, tmp.ndim());
+ if (!mxnet::dim_size_is_known(tmp, axis)) {
+has_unknown_dim_size = true;
+ } else {
+size += tmp[axis];
+ }
+ tmp[axis] = -1;
+ shape_assign(&dshape, tmp);
+}
+ }
+
+ mxnet::TShape tmp = (*out_shape)[0];
+ if (tmp.ndim() > 0) {
+axis = CheckAxis(param_.dim, tmp.ndim());
+tmp[axis] = -1;
+shape_assign(&dshape, tmp);
+ }
+
+ if (dshape.ndim() == -1) return false;
+ CHECK_NE(dshape.ndim(), 0) << "zero-dimensional arrays cannot be
concatenated";
+
+ for (int i = 0; i < param_.num_args; ++i) {
+CHECK(shape_assign(&(*in_shape)[i], dshape))
+<< "Incompatible input shape: expected " << dshape << ", got " <<
(*in_shape)[i];
Review comment:
Thanks. Resolved.
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[GitHub] [incubator-mxnet] mikemwx commented on a change in pull request #15456: [Numpy] numpy compatible invert
mikemwx commented on a change in pull request #15456: [Numpy] numpy compatible
invert
URL: https://github.com/apache/incubator-mxnet/pull/15456#discussion_r302875177
##
File path: python/mxnet/ndarray/numpy/_op.py
##
@@ -1414,6 +1413,48 @@ def rint(x, out=None, **kwargs):
"""
return _unary_func_helper(x, _npi.rint, _np.rint, out=out, **kwargs)
+def invert(x, out=None, **kwargs):
+"""
+Compute bit-wise inversion, or bit-wise NOT, element-wise.
+Computes the bit-wise NOT of the underlying binary representation of
+the integers in the input arrays. This ufunc implements the C/Python
operator ~.
+For signed integer inputs, the two’s complement is returned.
+In a two’s-complement system negative numbers are represented
+by the two’s complement of the absolute value.
+This is the most common method of representing signed integers on
computers [1].
+A N-bit two’s-complement system can represent every integer in the range
-2^{N-1} to +2^{N-1}-1.
+
+Parameters
+--
+x : ndarray
+Only integer and boolean types are handled.
+out : ndarray or None
+A location into which the result is stored.
+If provided, it must have the same shape as the input.
+If not provided or None, a freshly-allocated array is returned.
+
+Returns
+---
+out : ndarray
+Bitwisely inverted elements of the original array.
+
+Examples
+
+>>> np.invert(np.array([13], dtype=np.uint8))
+array([242], dtype=uint8)
+
+Notes
+-
+This function differs from the original `numpy.invert
+`_
in
+the following way(s):
+
+- only ndarray or scalar is accpted as valid input, tuple of ndarray is
not supported
+- broadcasting to `out` of different shape is currently not supported
+- when input is plain python numerics, the result will not be stored in
the `out` param
+
+"""
+return _unary_func_helper(x, _npi.invert, _np.invert, out=out, **kwargs)
Review comment:
Thank you. Resolved.
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[GitHub] [incubator-mxnet] zoeygxy commented on a change in pull request #15346: numpy_split support param type fix; numpy_vsplit added
zoeygxy commented on a change in pull request #15346: numpy_split support param
type fix; numpy_vsplit added
URL: https://github.com/apache/incubator-mxnet/pull/15346#discussion_r302902846
##
File path: python/mxnet/numpy/multiarray.py
##
@@ -1835,6 +1835,83 @@ def split(ary, indices_or_sections, axis=0):
return _mx_nd_np.split(ary, indices_or_sections, axis=axis)
+@set_module('mxnet.numpy')
+def vsplit(ary, indices_or_sections):
+r"""
+vsplit(ary, indices_or_sections)
+
+Split an array into multiple sub-arrays vertically (row-wise).
+
+``vsplit`` is equivalent to ``split`` with `axis=0` (default): the array
is always split
+along the first axis regardless of the array dimension.
+
+Parameters
+--
+ary : ndarray
+Array to be divided into sub-arrays.
+indices_or_sections : int or 1 - D Python tuple, list or set.
+If `indices_or_sections` is an integer, N, the array will be divided
into N equal arrays
+along axis 0. If such a split is not possible, an error is raised.
+
+If `indices_or_sections` is a 1-D array of sorted integers, the
entries indicate where
+along axis 0 the array is split. For example, ``[2, 3]`` would result
in
+
+ - ary[:2]
+ - ary[2:3]
+ - ary[3:]
+
+If an index exceeds the dimension of the array along axis 0, an error
will be thrown.
+
+Returns
+---
+sub-arrays : list of ndarrays
+A list of sub-arrays.
+
+See Also
+
+split : Split an array into multiple sub-arrays of equal size.
+
+Notes
+---
+This function differs from the original `numpy.degrees
+
`_ in
+the following aspects:
+
+- Currently parameter ``indices_or_sections`` does not support ndarray,
but supports scalar,
+tuple
Review comment:
Good catch! Fixed.
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[GitHub] [incubator-mxnet] tingying2020 closed pull request #15350: Add operator arctan2 with its test code
tingying2020 closed pull request #15350: Add operator arctan2 with its test code URL: https://github.com/apache/incubator-mxnet/pull/15350 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] tingying2020 opened a new pull request #15519: [Numpy] arctan2, a new branch for pr.
tingying2020 opened a new pull request #15519: [Numpy] arctan2, a new branch for pr. URL: https://github.com/apache/incubator-mxnet/pull/15519 ## Description ## (Brief description on what this PR is about) ## Checklist ## ### Essentials ### Please feel free to remove inapplicable items for your PR. - [x] Changes are complete (i.e. I finished coding on this PR) - [x] All changes have test coverage: - Unit tests are added for small changes to verify correctness (e.g. adding a new operator) - Nightly tests are added for complicated/long-running ones (e.g. changing distributed kvstore) - Build tests will be added for build configuration changes (e.g. adding a new build option with NCCL) - [x] To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change ## Comments ## - Create a new branch and move code to it. @haojin2 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] braindotai commented on issue #15504: Saved model and then looked at the output of the same batch after loading, got different results!
braindotai commented on issue #15504: Saved model and then looked at the output
of the same batch after loading, got different results!
URL:
https://github.com/apache/incubator-mxnet/issues/15504#issuecomment-510829624
Make sure you are saving and loading the model from the same path. I've
tested the code below and it is working fine.
```python
for batch in data_iter:
model.forward(batch)
out1 = model.get_outputs()[0]
break
model.save_checkpoint('model', epoch = 0)
sym, arg_params, aux_params = mx.model.load_checkpoint('model', epoch = 0)
model.set_params(arg_params, aux_params)
model.forward(batch)
out2 = model.get_outputs()[0]
print(f'diff_output:{nd.abs(out1 - out2)}')
```
Output is all zeros.
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[GitHub] [incubator-mxnet] KhurramPirov commented on issue #15504: Saved model and then looked at the output of the same batch after loading, got different results!
KhurramPirov commented on issue #15504: Saved model and then looked at the
output of the same batch after loading, got different results!
URL:
https://github.com/apache/incubator-mxnet/issues/15504#issuecomment-510831907
I checked the path, I do it inside batch_callback and model.fit, can it be
the case(seems no), but nevetheless.
пт, 12 июл. 2019 г. в 13:03, Rishik Mourya :
> Make sure you are saving and loading the model from the same path. I've
> tested the code below and it is working fine.
>
> for batch in data_iter:
> model.forward(batch)
> out1 = model.get_outputs()[0]
> break
> model.save_checkpoint('model', epoch = 0)
> sym, arg_params, aux_params = mx.model.load_checkpoint('model', epoch = 0)
> model.set_params(arg_params, aux_params)
> model.forward(batch)
> out2 = model.get_outputs()[0]print(f'diff_output:{nd.abs(out1 - out2)}')
>
> Output is all zeros.
>
> —
> You are receiving this because you were mentioned.
> Reply to this email directly, view it on GitHub
>
,
> or mute the thread
>
> .
>
--
Khurram Pirov
skype: matrixrextended
mob: +7-916-439-53-76
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[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15468: Numpy compatible diagflat operator
haojin2 commented on a change in pull request #15468: Numpy compatible diagflat operator URL: https://github.com/apache/incubator-mxnet/pull/15468#discussion_r302921428 ## File path: src/operator/numpy/np_diagflat_op-inl.h ## @@ -0,0 +1,201 @@ +/* Review comment: Better put this op in `np_init_op` files. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] haojin2 merged pull request #15282: Numpy compatible eye
haojin2 merged pull request #15282: Numpy compatible eye URL: https://github.com/apache/incubator-mxnet/pull/15282 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[incubator-mxnet] branch numpy updated (19c7c6e -> 3ea5f8c)
This is an automated email from the ASF dual-hosted git repository. haoj pushed a change to branch numpy in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 19c7c6e fix memory override bug in multinomial (#15397) add 3ea5f8c numpy eye op (#15282) No new revisions were added by this update. Summary of changes: python/mxnet/ndarray/numpy/_op.py | 33 +- python/mxnet/numpy/multiarray.py | 29 - python/mxnet/symbol/numpy/_symbol.py | 33 +- src/operator/numpy/np_init_op.cc | 30 - src/operator/numpy/np_init_op.cu | 5 +- src/operator/numpy/np_init_op.h| 113 + src/operator/tensor/init_op.h | 40 +++- tests/python/unittest/test_numpy_op.py | 69 8 files changed, 314 insertions(+), 38 deletions(-) create mode 100644 src/operator/numpy/np_init_op.h
[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15468: Numpy compatible diagflat operator
haojin2 commented on a change in pull request #15468: Numpy compatible diagflat operator URL: https://github.com/apache/incubator-mxnet/pull/15468#discussion_r302921968 ## File path: tests/python/unittest/test_numpy_op.py ## @@ -28,6 +28,59 @@ import random +@with_seed() +@npx.use_np_shape +def test_np_diagflat(): +@npx.use_np_shape +class TestDiagflat(HybridBlock): +def __init__(self, k): +super(TestDiagflat, self).__init__() +self.k = k + +def hybrid_forward(self, F, a): +return F.np.diagflat(a, self.k) + +for hybridize in [True, False]: +for dtype in ['int32', 'float16', 'float32', 'float64']: +for shape_x in [(1,), # single element +(3, 3), # square +(), # scalar +(3, 0, 2), # zero-dim +(3, 4, 5), +]: +for k in range(-5, 6): +if dtype == 'float16': +rtol = atol = 1e-2 +else: +rtol = atol = 1e-5 + +test_diagflat = TestDiagflat(k) +if hybridize: +test_diagflat.hybridize() + +x = rand_ndarray(shape_x, dtype=dtype).as_np_ndarray() +x.attach_grad() + +np_out = _np.diagflat(x.asnumpy(), k) +with mx.autograd.record(): +mx_out = test_diagflat(x) +assert mx_out.shape == np_out.shape +assert_almost_equal(mx_out.asnumpy(), np_out, rtol=rtol, +atol=atol) +# test grad +mx_out.backward() +assert_almost_equal(x.grad.asnumpy(), _np.ones(x.shape), +rtol=1e-3, atol=1e-5) + +# test imperative once again +mx_out = np.diagflat(x, k) +np_out = _np.diagflat(x.asnumpy(), k) +assert_almost_equal(mx_out.asnumpy(), np_out, rtol=rtol, +atol=atol) + Review comment: 2 blank lines between functions. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15468: Numpy compatible diagflat operator
haojin2 commented on a change in pull request #15468: Numpy compatible diagflat operator URL: https://github.com/apache/incubator-mxnet/pull/15468#discussion_r302921755 ## File path: src/operator/numpy/np_diagflat_op-inl.h ## @@ -0,0 +1,201 @@ +/* Review comment: Seems like there's no `np_init_op-inl.h`, you could probably rename this `-inl.h` to that. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15468: Numpy compatible diagflat operator
haojin2 commented on a change in pull request #15468: Numpy compatible diagflat operator URL: https://github.com/apache/incubator-mxnet/pull/15468#discussion_r302922300 ## File path: src/operator/numpy/np_diagflat_op.cu ## @@ -0,0 +1,38 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +/*! + * Copyright (c) 2019 by Contributors + * \file np_diagflat_op.cu + * \brief CPU Implementation of numpy-compatible diagflat operator Review comment: `GPU Implementation`? Actually please move those registrations to `np_init_op` files. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] qqaatw edited a comment on issue #15484: Binding Model fails with simple_bind error
qqaatw edited a comment on issue #15484: Binding Model fails with simple_bind error URL: https://github.com/apache/incubator-mxnet/issues/15484#issuecomment-510480630 @Maicus I have the same problem as you, could you tell more in detail about the Target and the TargetCode Section? thanks. edited: Version 1.5.0b20190409 is fine but 1.5.0b20190712 has this problem. environment: 2080Ti & windows 10 x64 & cuda 10. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new branch for pr.
haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new
branch for pr.
URL: https://github.com/apache/incubator-mxnet/pull/15519#discussion_r302927677
##
File path: src/operator/numpy/np_elemwise_broadcast_op.cc
##
@@ -198,5 +198,74 @@
MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_minimum_scalar)
.set_attr("FCompute", BinaryScalarOp::Compute)
.set_attr("FGradient",
ElemwiseGradUseIn{"_backward_minimum_scalar"});
+inline bool Arctan2OpType(const nnvm::NodeAttrs& attrs,
+ std::vector* in_attrs,
+ std::vector* out_attrs){
+ CHECK_EQ(in_attrs->size(), 2U);
+ CHECK_EQ(out_attrs->size(), 1U);
+
+ TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(0));
+ TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(1));
+ TYPE_ASSIGN_CHECK(*in_attrs, 0, out_attrs->at(0));
+ TYPE_ASSIGN_CHECK(*in_attrs, 1, out_attrs->at(0));
+ //check if it is float16, float32 or float64. If not, raise error
+ if(in_attrs->at(0) > 2){
+ // do not support int now.
+ std::ostringstream os;
+ os << "Do not support `int` as input.\n";
+ throw ::mxnet::op::InferTypeError(os.str(), 0);
+ }
+ return out_attrs->at(0) != -1;
Review comment:
2-space indentations, please fix for all your code
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[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new branch for pr.
haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new
branch for pr.
URL: https://github.com/apache/incubator-mxnet/pull/15519#discussion_r302927529
##
File path: src/operator/numpy/np_elemwise_broadcast_op.cc
##
@@ -198,5 +198,74 @@
MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_minimum_scalar)
.set_attr("FCompute", BinaryScalarOp::Compute)
.set_attr("FGradient",
ElemwiseGradUseIn{"_backward_minimum_scalar"});
+inline bool Arctan2OpType(const nnvm::NodeAttrs& attrs,
+ std::vector* in_attrs,
+ std::vector* out_attrs){
Review comment:
```c++
inline bool Arctan2OpType(const nnvm::NodeAttrs& attrs,
std::vector* in_attrs,
std::vector* out_attrs){
```
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[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new branch for pr.
haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new
branch for pr.
URL: https://github.com/apache/incubator-mxnet/pull/15519#discussion_r302927764
##
File path: src/operator/numpy/np_elemwise_broadcast_op.cc
##
@@ -198,5 +198,74 @@
MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_minimum_scalar)
.set_attr("FCompute", BinaryScalarOp::Compute)
.set_attr("FGradient",
ElemwiseGradUseIn{"_backward_minimum_scalar"});
+inline bool Arctan2OpType(const nnvm::NodeAttrs& attrs,
+ std::vector* in_attrs,
+ std::vector* out_attrs){
+ CHECK_EQ(in_attrs->size(), 2U);
+ CHECK_EQ(out_attrs->size(), 1U);
+
+ TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(0));
+ TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(1));
+ TYPE_ASSIGN_CHECK(*in_attrs, 0, out_attrs->at(0));
+ TYPE_ASSIGN_CHECK(*in_attrs, 1, out_attrs->at(0));
+ //check if it is float16, float32 or float64. If not, raise error
+ if(in_attrs->at(0) > 2){
+ // do not support int now.
+ std::ostringstream os;
+ os << "Do not support `int` as input.\n";
+ throw ::mxnet::op::InferTypeError(os.str(), 0);
Review comment:
indentation here?
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[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new branch for pr.
haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new
branch for pr.
URL: https://github.com/apache/incubator-mxnet/pull/15519#discussion_r302927937
##
File path: src/operator/numpy/np_elemwise_broadcast_op.cc
##
@@ -198,5 +198,74 @@
MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_minimum_scalar)
.set_attr("FCompute", BinaryScalarOp::Compute)
.set_attr("FGradient",
ElemwiseGradUseIn{"_backward_minimum_scalar"});
+inline bool Arctan2OpType(const nnvm::NodeAttrs& attrs,
+ std::vector* in_attrs,
+ std::vector* out_attrs){
+ CHECK_EQ(in_attrs->size(), 2U);
+ CHECK_EQ(out_attrs->size(), 1U);
+
+ TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(0));
+ TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(1));
+ TYPE_ASSIGN_CHECK(*in_attrs, 0, out_attrs->at(0));
+ TYPE_ASSIGN_CHECK(*in_attrs, 1, out_attrs->at(0));
+ //check if it is float16, float32 or float64. If not, raise error
+ if(in_attrs->at(0) > 2){
+ // do not support int now.
+ std::ostringstream os;
+ os << "Do not support `int` as input.\n";
+ throw ::mxnet::op::InferTypeError(os.str(), 0);
+ }
+ return out_attrs->at(0) != -1;
+}
+
+NNVM_REGISTER_OP(_npi_arctan2)
+.set_num_inputs(2)
+.set_num_outputs(1)
+.set_attr("FListInputNames",
+ [](const NodeAttrs& attrs) {
+ return std::vector{"x1", "x2"};
+ })
+.set_attr("FInferShape", BinaryBroadcastShape)
+.set_attr("FInferType", Arctan2OpType)
+.set_attr("FCompute", BinaryBroadcastCompute)
+.set_attr("FGradient",
ElemwiseGradUseIn{"_backward_npi_arctan2"})
+.set_attr("FInplaceOption",
+ [](const NodeAttrs& attrs) {
+ return std::vector >{{0, 0}};
+ })
+.add_argument("x1", "NDArray-or-Symbol", "The input array")
+.add_argument("x2", "NDArray-or-Symbol", "The input array");
+
+NNVM_REGISTER_OP(_backward_npi_arctan2)
+.set_num_inputs(3)
+.set_num_outputs(2)
+.set_attr("TIsBackward", true)
+.set_attr("FResourceRequest",
+ [](const NodeAttrs& attrs) {
+ return std::vector{ResourceRequest::kTempSpace};
+ })
+.set_attr("FCompute",
BinaryBroadcastBackwardUseIn);
+
+MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_arctan2_scalar)
+.set_attr("FCompute", BinaryScalarOp::Compute)
+.set_attr("FGradient",
ElemwiseGradUseIn{"_backward_npi_arctan2_scalar"});
+
+MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_rarctan2_scalar)
+.set_attr("FCompute", BinaryScalarOp::Compute)
+.set_attr("FGradient",
ElemwiseGradUseIn{"_backward_npi_rarctan2_scalar"});
+
+MXNET_OPERATOR_REGISTER_BINARY(_backward_npi_arctan2_scalar)
+.add_argument("scalar", "float", "scalar value")
+.set_attr_parser([](NodeAttrs *attrs) { attrs->parsed =
std::stod(attrs->dict["scalar"]); })
+.set_attr("FCompute", BinaryScalarOp::Backward<
+ cpu, mshadow_op::arctan2_grad>);
Review comment:
```c++
.set_attr("FCompute",
BinaryScalarOp::Backward);
```
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[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new branch for pr.
haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new
branch for pr.
URL: https://github.com/apache/incubator-mxnet/pull/15519#discussion_r302928018
##
File path: src/operator/numpy/np_elemwise_broadcast_op.cc
##
@@ -198,5 +198,74 @@
MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_minimum_scalar)
.set_attr("FCompute", BinaryScalarOp::Compute)
.set_attr("FGradient",
ElemwiseGradUseIn{"_backward_minimum_scalar"});
+inline bool Arctan2OpType(const nnvm::NodeAttrs& attrs,
+ std::vector* in_attrs,
+ std::vector* out_attrs){
+ CHECK_EQ(in_attrs->size(), 2U);
+ CHECK_EQ(out_attrs->size(), 1U);
+
+ TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(0));
+ TYPE_ASSIGN_CHECK(*out_attrs, 0, in_attrs->at(1));
+ TYPE_ASSIGN_CHECK(*in_attrs, 0, out_attrs->at(0));
+ TYPE_ASSIGN_CHECK(*in_attrs, 1, out_attrs->at(0));
+ //check if it is float16, float32 or float64. If not, raise error
+ if(in_attrs->at(0) > 2){
+ // do not support int now.
+ std::ostringstream os;
+ os << "Do not support `int` as input.\n";
+ throw ::mxnet::op::InferTypeError(os.str(), 0);
+ }
+ return out_attrs->at(0) != -1;
+}
+
+NNVM_REGISTER_OP(_npi_arctan2)
+.set_num_inputs(2)
+.set_num_outputs(1)
+.set_attr("FListInputNames",
+ [](const NodeAttrs& attrs) {
+ return std::vector{"x1", "x2"};
+ })
+.set_attr("FInferShape", BinaryBroadcastShape)
+.set_attr("FInferType", Arctan2OpType)
+.set_attr("FCompute", BinaryBroadcastCompute)
+.set_attr("FGradient",
ElemwiseGradUseIn{"_backward_npi_arctan2"})
+.set_attr("FInplaceOption",
+ [](const NodeAttrs& attrs) {
+ return std::vector >{{0, 0}};
+ })
+.add_argument("x1", "NDArray-or-Symbol", "The input array")
+.add_argument("x2", "NDArray-or-Symbol", "The input array");
+
+NNVM_REGISTER_OP(_backward_npi_arctan2)
+.set_num_inputs(3)
+.set_num_outputs(2)
+.set_attr("TIsBackward", true)
+.set_attr("FResourceRequest",
+ [](const NodeAttrs& attrs) {
+ return std::vector{ResourceRequest::kTempSpace};
+ })
+.set_attr("FCompute",
BinaryBroadcastBackwardUseIn);
+
+MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_arctan2_scalar)
+.set_attr("FCompute", BinaryScalarOp::Compute)
+.set_attr("FGradient",
ElemwiseGradUseIn{"_backward_npi_arctan2_scalar"});
+
+MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_rarctan2_scalar)
+.set_attr("FCompute", BinaryScalarOp::Compute)
+.set_attr("FGradient",
ElemwiseGradUseIn{"_backward_npi_rarctan2_scalar"});
+
+MXNET_OPERATOR_REGISTER_BINARY(_backward_npi_arctan2_scalar)
+.add_argument("scalar", "float", "scalar value")
+.set_attr_parser([](NodeAttrs *attrs) { attrs->parsed =
std::stod(attrs->dict["scalar"]); })
+.set_attr("FCompute", BinaryScalarOp::Backward<
+ cpu, mshadow_op::arctan2_grad>);
Review comment:
Similar for the case below.
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[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new branch for pr.
haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new branch for pr. URL: https://github.com/apache/incubator-mxnet/pull/15519#discussion_r302928599 ## File path: tests/python/gpu/test_operator_gpu.py ## @@ -2300,6 +2300,81 @@ def test_math(): for op in ops: run_math(op, shape, dtype, check_value=check_value) +@with_seed() +@npx.use_np_shape +def test_np_arctan2(): +@npx.use_np_shape +class TestArctan2(HybridBlock): +def __init__(self): +super(TestArctan2, self).__init__() + +def hybrid_forward(self, F, x1, x2): +return F.np.arctan2(x1, x2) + +#Reduce dimension of src to dimention of des. +def dimReduce(src, des): +srcShape = src.shape +desShape = des.shape +if len(desShape) == 0: +return src.sum() +redu = [] +for i, j in zip(range(len(srcShape)-1, -1, -1), range(len(desShape)-1, -1, -1)): +if srcShape[i] != desShape[j] and desShape[j] == 1: +redu.append(i) +if j == 0: +for k in range(0, i): +redu.append(k) +break +if len(redu) > 0: +src = np.reshape(src.sum(axis=tuple(redu)), desShape) +return src + +types = ['float64', 'float32', 'float16'] +for hybridize in [True, False]: +for shape1, shape2 in [[(1,), (1,)], # single elements +[(4, 5), (4, 5)], # normal case +[(3, 2), (3, 2)], # tall matrices +[(), ()], # scalar only +[(3, 0, 2), (3, 0, 2)], # zero-dim +[(3, 4, 5), (4, 1)], # trailing dim broadcasting +[(3, 4, 5), ()], # scalar broadcasting +[(), (1, 2, 3)], # scalar broadcasting +[(4, 3), (4, 1)], # single broadcasting +[(3, 4, 5), (3, 1, 5)] # single broadcasting in the middle +]: Review comment: Align lines: ```python for shape1, shape2 in [[(1,), (1,)], # single elements [(4, 5), (4, 5)], # normal case [(3, 2), (3, 2)], # tall matrices [(), ()], # scalar only [(3, 0, 2), (3, 0, 2)], # zero-dim [(3, 4, 5), (4, 1)], # trailing dim broadcasting [(3, 4, 5), ()], # scalar broadcasting [(), (1, 2, 3)], # scalar broadcasting [(4, 3), (4, 1)], # single broadcasting [(3, 4, 5), (3, 1, 5)] # single broadcasting in the middle ]: ``` This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new branch for pr.
haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new
branch for pr.
URL: https://github.com/apache/incubator-mxnet/pull/15519#discussion_r302928820
##
File path: src/operator/numpy/np_elemwise_broadcast_op.cu
##
@@ -42,6 +42,12 @@ NNVM_REGISTER_OP(_npi_mod)
NNVM_REGISTER_OP(_npi_power)
.set_attr("FCompute", BinaryBroadcastCompute);
+NNVM_REGISTER_OP(_npi_arctan2)
+.set_attr("FCompute", BinaryBroadcastCompute);
+
+NNVM_REGISTER_OP(_backward_npi_arctan2)
+.set_attr("FCompute",
BinaryBroadcastBackwardUseIn);
Review comment:
one more blank line below.
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[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new branch for pr.
haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new branch for pr. URL: https://github.com/apache/incubator-mxnet/pull/15519#discussion_r302928682 ## File path: tests/python/gpu/test_operator_gpu.py ## @@ -2300,6 +2300,81 @@ def test_math(): for op in ops: run_math(op, shape, dtype, check_value=check_value) +@with_seed() +@npx.use_np_shape +def test_np_arctan2(): +@npx.use_np_shape +class TestArctan2(HybridBlock): +def __init__(self): +super(TestArctan2, self).__init__() + +def hybrid_forward(self, F, x1, x2): +return F.np.arctan2(x1, x2) + +#Reduce dimension of src to dimention of des. +def dimReduce(src, des): +srcShape = src.shape +desShape = des.shape +if len(desShape) == 0: +return src.sum() +redu = [] +for i, j in zip(range(len(srcShape)-1, -1, -1), range(len(desShape)-1, -1, -1)): +if srcShape[i] != desShape[j] and desShape[j] == 1: +redu.append(i) +if j == 0: +for k in range(0, i): +redu.append(k) +break +if len(redu) > 0: +src = np.reshape(src.sum(axis=tuple(redu)), desShape) +return src + +types = ['float64', 'float32', 'float16'] +for hybridize in [True, False]: +for shape1, shape2 in [[(1,), (1,)], # single elements +[(4, 5), (4, 5)], # normal case +[(3, 2), (3, 2)], # tall matrices +[(), ()], # scalar only +[(3, 0, 2), (3, 0, 2)], # zero-dim +[(3, 4, 5), (4, 1)], # trailing dim broadcasting +[(3, 4, 5), ()], # scalar broadcasting +[(), (1, 2, 3)], # scalar broadcasting +[(4, 3), (4, 1)], # single broadcasting +[(3, 4, 5), (3, 1, 5)] # single broadcasting in the middle +]: +for oneType in types: +if oneType == 'float16': +rtol=1e-2 +atol = 1e-2 +else: +rtol=1e-3 +atol = 1e-5 +test_arctan2 = TestArctan2() +if hybridize: +test_arctan2.hybridize() +x1 = rand_ndarray(shape1, dtype=oneType).as_np_ndarray() +x2 = rand_ndarray(shape2, dtype=oneType).as_np_ndarray() +x11 = x1.asnumpy() +x21 = x2.asnumpy() +x1.attach_grad() +x2.attach_grad() +np_out = np.arctan2(x1.asnumpy(), x2.asnumpy()) +with mx.autograd.record(): +mx_out = test_arctan2(x1, x2) +assert mx_out.shape == np_out.shape +assert_almost_equal(mx_out.asnumpy(), np_out, rtol=rtol, atol=atol) +mx_out.backward() +np_backward_1 = x21 / (x11 * x11 + x21 * x21) +np_backward_2 = -1 * x11 / (x11 * x11 + x21 * x21) +np_backward_1 = dimReduce(np_backward_1, x11) +np_backward_2 = dimReduce(np_backward_2, x21) +assert_almost_equal(x1.grad.asnumpy(), np_backward_1, rtol=rtol, atol=atol) +assert_almost_equal(x2.grad.asnumpy(), np_backward_2, rtol=rtol, atol=atol) + +mx_out = mx.np.arctan2(x1, x2) +np_out = np.arctan2(x1.asnumpy(), x2.asnumpy()) +assert_almost_equal(mx_out.asnumpy(), np_out, rtol=rtol, atol=atol) + Review comment: one more blank line below This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new branch for pr.
haojin2 commented on a change in pull request #15519: [Numpy] arctan2, a new branch for pr. URL: https://github.com/apache/incubator-mxnet/pull/15519#discussion_r302928767 ## File path: tests/python/gpu/test_operator_gpu.py ## @@ -2300,6 +2300,81 @@ def test_math(): for op in ops: run_math(op, shape, dtype, check_value=check_value) +@with_seed() Review comment: One more blank line above, 2 blank lines between functions. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] haojin2 commented on issue #15169: Softmax with length
haojin2 commented on issue #15169: Softmax with length URL: https://github.com/apache/incubator-mxnet/pull/15169#issuecomment-510842258 @apeforest Trust me or not, I've tried what you're suggesting to do on my end way before this PR was raised but found it not easily done without affecting the existing softmax's performance by much. I think I'll stick to this version for now. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15169: Softmax with length
haojin2 commented on a change in pull request #15169: Softmax with length
URL: https://github.com/apache/incubator-mxnet/pull/15169#discussion_r302931319
##
File path: src/operator/nn/softmax-inl.h
##
@@ -464,35 +755,56 @@ void SoftmaxGradCompute(const nnvm::NodeAttrs& attrs,
mxnet::TShape shape = AxisShapeCompact(inputs[0].shape_, &axis, true);
int out_idx = softmax_has_dtype_override(attrs) ? 2 : 1;
+ out_idx = softmax_use_length(attrs) ? 3 : out_idx;
bool safe_acc = dmlc::GetEnv("MXNET_SAFE_ACCUMULATION", false);
MXNET_REAL_ACC_TYPE_SWITCH(inputs[0].type_flag_, OType, AType, {
MSHADOW_REAL_TYPE_SWITCH(outputs[0].type_flag_, DType, {
MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
-if (safe_acc) {
- if (shape.ndim() == 2) {
-SoftmaxGrad(
-ctx.get_stream(), inputs[out_idx].dptr(),
-inputs[0].dptr(), outputs[0].dptr(),
-shape.get<2>(), axis, static_cast(temperature));
+if (!softmax_use_length(attrs)) {
+ if (safe_acc) {
+if (shape.ndim() == 2) {
+ SoftmaxGrad(
+ ctx.get_stream(), inputs[out_idx].dptr(),
+ inputs[0].dptr(), outputs[0].dptr(),
+ shape.get<2>(), axis, static_cast(temperature));
+} else {
+ SoftmaxGrad(
+ ctx.get_stream(), inputs[out_idx].dptr(),
+ inputs[0].dptr(), outputs[0].dptr(),
+ shape.get<3>(), axis, static_cast(temperature));
+}
} else {
-SoftmaxGrad(
-ctx.get_stream(), inputs[out_idx].dptr(),
-inputs[0].dptr(), outputs[0].dptr(),
-shape.get<3>(), axis, static_cast(temperature));
+if (shape.ndim() == 2) {
+ SoftmaxGrad(
+ ctx.get_stream(), inputs[out_idx].dptr(),
+ inputs[0].dptr(), outputs[0].dptr(),
+ shape.get<2>(), axis, static_cast(temperature));
+} else {
+ SoftmaxGrad(
+ ctx.get_stream(), inputs[out_idx].dptr(),
+ inputs[0].dptr(), outputs[0].dptr(),
+ shape.get<3>(), axis, static_cast(temperature));
+}
}
} else {
- if (shape.ndim() == 2) {
-SoftmaxGrad(
+ MXNET_INT_TYPE_SWITCH(inputs[2].type_flag_, IType, {
Review comment:
It may not necessarily be int64_t, and what do you mean by "cast the type to
int64_t"? Allocating a new buffer on the fly within the operator to hold the
casted `length` input? I would consider that a big performance bottleneck.
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[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15169: Softmax with length
haojin2 commented on a change in pull request #15169: Softmax with length URL: https://github.com/apache/incubator-mxnet/pull/15169#discussion_r302931406 ## File path: src/operator/nn/softmax-inl.h ## @@ -113,6 +113,60 @@ inline void Softmax(Stream *s, DType *in, OType *out, } } +template +inline void SoftmaxWithLength(Stream *s, DType *in, OType *out, IType *length, Review comment: Answered below. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15169: Softmax with length
haojin2 commented on a change in pull request #15169: Softmax with length URL: https://github.com/apache/incubator-mxnet/pull/15169#discussion_r302931553 ## File path: tests/python/unittest/test_operator.py ## @@ -7838,6 +7871,7 @@ def get_output_names_callback(name, arr): except mx.base.MXNetError: # skip errors since test is to check all names pass +print(output_names) Review comment: Done. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15169: Softmax with length
haojin2 commented on a change in pull request #15169: Softmax with length
URL: https://github.com/apache/incubator-mxnet/pull/15169#discussion_r302932168
##
File path: src/operator/nn/softmax-inl.h
##
@@ -464,35 +755,56 @@ void SoftmaxGradCompute(const nnvm::NodeAttrs& attrs,
mxnet::TShape shape = AxisShapeCompact(inputs[0].shape_, &axis, true);
int out_idx = softmax_has_dtype_override(attrs) ? 2 : 1;
+ out_idx = softmax_use_length(attrs) ? 3 : out_idx;
bool safe_acc = dmlc::GetEnv("MXNET_SAFE_ACCUMULATION", false);
MXNET_REAL_ACC_TYPE_SWITCH(inputs[0].type_flag_, OType, AType, {
MSHADOW_REAL_TYPE_SWITCH(outputs[0].type_flag_, DType, {
MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
-if (safe_acc) {
- if (shape.ndim() == 2) {
-SoftmaxGrad(
-ctx.get_stream(), inputs[out_idx].dptr(),
-inputs[0].dptr(), outputs[0].dptr(),
-shape.get<2>(), axis, static_cast(temperature));
+if (!softmax_use_length(attrs)) {
Review comment:
The `length` is a tensor, not a single value. Please read the test cases
carefully.
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[GitHub] [incubator-mxnet] apeforest commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
apeforest commented on a change in pull request #15490: Utility to help
developers debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r302933381
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; i++) {
Review comment:
nit: use ++i for performance
This is
[GitHub] [incubator-mxnet] apeforest commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
apeforest commented on a change in pull request #15490: Utility to help
developers debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r302934098
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; i++) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info,
[GitHub] [incubator-mxnet] apeforest commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
apeforest commented on a change in pull request #15490: Utility to help
developers debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r302935550
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; i++) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info,
[GitHub] [incubator-mxnet] braindotai commented on issue #15496: Loaded pretrained model but train accuracy starts from zero,
braindotai commented on issue #15496: Loaded pretrained model but train
accuracy starts from zero,
URL:
https://github.com/apache/incubator-mxnet/issues/15496#issuecomment-510847042
Below code should work
```python
model.save_checkpoint('model', epoch = 0)
sym, arg_params, aux_params = mx.model.load_checkpoint('model', epoch = 0)
model = mx.mod.Module(sym, context = mx.gpu())
model.bind(data_shapes = train_data.provide_data, label_shapes =
train_data.provide_label)
model.set_params(arg_params, aux_params)
```
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[GitHub] [incubator-mxnet] apeforest commented on issue #15490: Utility to help developers debug operators: Tensor Inspector
apeforest commented on issue #15490: Utility to help developers debug operators: Tensor Inspector URL: https://github.com/apache/incubator-mxnet/pull/15490#issuecomment-510847250 @eric-haibin-lin This utility looks really useful for debugging mxnet backend. Please take a look if interested. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] marcoabreu commented on issue #15506: Improving error message
marcoabreu commented on issue #15506: Improving error message URL: https://github.com/apache/incubator-mxnet/issues/15506#issuecomment-510860930 I think that this error is a quite standard one. Considering that the compiler might write to a lot of locations due to optimizations, I don't think that we can safely tell which partition in particular is too small. To avoid giving false leads, I wouldn't improve the error message here. As long as the error is really related to disk or ram space, it should be straight forward to solve it. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] wkcn commented on issue #15499: Improve diagnose.py, adding build features info and binary library path.
wkcn commented on issue #15499: Improve diagnose.py, adding build features info and binary library path. URL: https://github.com/apache/incubator-mxnet/pull/15499#issuecomment-510861117 Thank you for the improvement! I have a suggestion : ) Could we only print the relative path? Some users don't like the printing of the absolute path with their privacy. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] wkcn edited a comment on issue #15499: Improve diagnose.py, adding build features info and binary library path.
wkcn edited a comment on issue #15499: Improve diagnose.py, adding build features info and binary library path. URL: https://github.com/apache/incubator-mxnet/pull/15499#issuecomment-510861117 Thank you for the improvement! LGTM. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] pengzhao-intel edited a comment on issue #13598: More fine-grained operator implementation dispatch & memory planning flow
pengzhao-intel edited a comment on issue #13598: More fine-grained operator implementation dispatch & memory planning flow URL: https://github.com/apache/incubator-mxnet/issues/13598#issuecomment-472725241 @danithaca Tao has answered the question in the forum :) thanks to raising the question. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] KhurramPirov commented on issue #15504: Saved model and then looked at the output of the same batch after loading, got different results!
KhurramPirov commented on issue #15504: Saved model and then looked at the
output of the same batch after loading, got different results!
URL:
https://github.com/apache/incubator-mxnet/issues/15504#issuecomment-510873701
It doesn't work inside batch_callback.
пт, 12 июл. 2019 г. в 13:03, Rishik Mourya :
> Make sure you are saving and loading the model from the same path. I've
> tested the code below and it is working fine.
>
> for batch in data_iter:
> model.forward(batch)
> out1 = model.get_outputs()[0]
> break
> model.save_checkpoint('model', epoch = 0)
> sym, arg_params, aux_params = mx.model.load_checkpoint('model', epoch = 0)
> model.set_params(arg_params, aux_params)
> model.forward(batch)
> out2 = model.get_outputs()[0]print(f'diff_output:{nd.abs(out1 - out2)}')
>
> Output is all zeros.
>
> —
> You are receiving this because you were mentioned.
> Reply to this email directly, view it on GitHub
>
,
> or mute the thread
>
> .
>
--
Khurram Pirov
skype: matrixrextended
mob: +7-916-439-53-76
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[GitHub] [incubator-mxnet] KhurramPirov commented on issue #15496: Loaded pretrained model but train accuracy starts from zero,
KhurramPirov commented on issue #15496: Loaded pretrained model but train
accuracy starts from zero,
URL:
https://github.com/apache/incubator-mxnet/issues/15496#issuecomment-510873847
It doesn't work inside batch_callback and model.fit.
пт, 12 июл. 2019 г. в 14:08, Rishik Mourya :
> Below code should work
>
> model.save_checkpoint('model', epoch = 0)
>
> sym, arg_params, aux_params = mx.model.load_checkpoint('model', epoch = 0)
>
> model = mx.mod.Module(sym, context = mx.gpu())
> model.bind(data_shapes = train_data.provide_data, label_shapes =
train_data.provide_label)
> model.set_params(arg_params, aux_params)
>
> —
> You are receiving this because you were mentioned.
> Reply to this email directly, view it on GitHub
>
,
> or mute the thread
>
> .
>
--
Khurram Pirov
skype: matrixrextended
mob: +7-916-439-53-76
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[GitHub] [incubator-mxnet] gxkevin opened a new issue #15520: most time cost in NDArray GetData() func
gxkevin opened a new issue #15520: most time cost in NDArray GetData() func
URL: https://github.com/apache/incubator-mxnet/issues/15520
My predict code is like this， I have 32 worker thread, each has 1 openmp
thread, the mxnet engine is NaiveEngine , using the openblas, disable the
mkldnn, running the code on the Skylatex machine, using the avx512, but it is
not faster than the avx2, I don't know why?
And what's more, the naiveEngine means that all the funcs are
sequential？(not asynchronous?)
In this condition, the WaitAll() func should removed?
what's more , I found that the most time is the NDArray.GetData(), about
17ms, and the Forward() cost 6ms, why GetData() cost so much time? How to
increase the proformance?
the Avx512 doesn't work.
dnn_model->model_data["data"].SyncCopyFromCPU(batch_data.data(),
batch_size * fea_num);
mxnet::cpp::NDArray::WaitAll();
dnn_model->exec->Forward(false);
mxnet::cpp::NDArray::WaitAll();
uint32_t output_num = dnn_model->exec->outputs.size();
for (uint32_t j = 0; j < b_num; j++) {
for (uint32_t q_idx = 0; q_idx < output_num; q_idx++) {
//cvm_q_t* item = result + ins_idx;
//item->q[q_idx] =
dnn_model->exec->outputs[q_idx].GetData()[j];
_result[ins_index][q_idx] =
dnn_model->exec->outputs[q_idx].GetData()[j];
CVM_DEBUG_LOG("ins_index:%u q_idx %u q:%f", ins_index,
q_idx, _result[ins_index][q_idx]);
}
ins_index += 1;
}
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[GitHub] [incubator-mxnet] mikemwx commented on issue #15302: [Numpy] Numpy hstack
mikemwx commented on issue #15302: [Numpy] Numpy hstack URL: https://github.com/apache/incubator-mxnet/pull/15302#issuecomment-510876247 > LGTM, remember to add examples to the doc and it will be good for merge Docs are added This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] smissan closed issue #15514: dmlc.lib is not generated
smissan closed issue #15514: dmlc.lib is not generated URL: https://github.com/apache/incubator-mxnet/issues/15514 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] braindotai commented on issue #12185: from_logits definition seems different from what is expected?
braindotai commented on issue #12185: from_logits definition seems different from what is expected? URL: https://github.com/apache/incubator-mxnet/issues/12185#issuecomment-510939653 [Check this out](https://www.tensorflow.org/api_docs/python/tf/nn/softmax_cross_entropy_with_logits) Here it says "logits: Per-label activations, typically a linear output", which means `nd.dot(x, w) + b` in terms of MXNet. There are actually two versions of logits, first is simply the linear layer(as mentions in the above link), and second is the unscaled log probabilities. That is the reason Tensorflow provided 2 versions of "softmax_cross_entropy_with_logits". In MXNet mx.gluon.loss.SoftmaxCrossEntropyLoss accepts the linear output(`nd.dot(x, w) + b`) as output in the argument. You can check [here](https://gluon.mxnet.io/chapter02_supervised-learning/softmax-regression-gluon.html), the layer definition is `net = gluon.nn.Dense(num_outputs)`, defining the loss as `gluon.loss.SoftmaxCrossEntropyLoss()` and then calculating loss as ```python output = net(data) loss = softmax_cross_entropy(output, label) ``` This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] frankfliu commented on issue #15520: most time cost in NDArray GetData() func
frankfliu commented on issue #15520: most time cost in NDArray GetData() func URL: https://github.com/apache/incubator-mxnet/issues/15520#issuecomment-510943143 @mxnet-label-bot add [question, performance] This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] TaoLv opened a new pull request #15521: Avoid memory copy for dropout inference
TaoLv opened a new pull request #15521: Avoid memory copy for dropout inference URL: https://github.com/apache/incubator-mxnet/pull/15521 ## Description ## Fix the first item in #14198. ## Checklist ## ### Essentials ### Please feel free to remove inapplicable items for your PR. - [ ] The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to the relevant [JIRA issue](https://issues.apache.org/jira/projects/MXNET/issues) created (except PRs with tiny changes) - [ ] Changes are complete (i.e. I finished coding on this PR) - [ ] All changes have test coverage: - Unit tests are added for small changes to verify correctness (e.g. adding a new operator) - Nightly tests are added for complicated/long-running ones (e.g. changing distributed kvstore) - Build tests will be added for build configuration changes (e.g. adding a new build option with NCCL) - [ ] Code is well-documented: - For user-facing API changes, API doc string has been updated. - For new C++ functions in header files, their functionalities and arguments are documented. - For new examples, README.md is added to explain the what the example does, the source of the dataset, expected performance on test set and reference to the original paper if applicable - Check the API doc at http://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html - [ ] To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change ### Changes ### - [ ] Feature1, tests, (and when applicable, API doc) - [ ] Feature2, tests, (and when applicable, API doc) ## Comments ## - If this change is a backward incompatible change, why must this change be made. - Interesting edge cases to note here This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] TaoLv commented on issue #15521: Avoid memory copy for dropout inference
TaoLv commented on issue #15521: Avoid memory copy for dropout inference URL: https://github.com/apache/incubator-mxnet/pull/15521#issuecomment-510944094 @eric-haibin-lin please help to review. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] ChaiBapchya commented on issue #15506: Improving error message
ChaiBapchya commented on issue #15506: Improving error message URL: https://github.com/apache/incubator-mxnet/issues/15506#issuecomment-510944105 Alright. If it is tough to safely tell the location, can't it be renamed to ``` fatal error : No space left on device compilation terminated. ``` Might sound like a nitpick and in that case I don't mind closing this issue. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] KellenSunderland commented on a change in pull request #15449: cuda/cuDNN lib version checking. Force cuDNN v7 usage.
KellenSunderland commented on a change in pull request #15449: cuda/cuDNN lib
version checking. Force cuDNN v7 usage.
URL: https://github.com/apache/incubator-mxnet/pull/15449#discussion_r303065500
##
File path: src/common/cuda_utils.cc
##
@@ -0,0 +1,108 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file cuda_utils.cc
+ * \brief CUDA debugging utilities.
+ */
+
+#include
+#include "cuda_utils.h"
+
+#if MXNET_USE_CUDA == 1
+
+namespace mxnet {
+namespace common {
+namespace cuda {
+
+// The oldest version of cuda used in upstream MXNet CI testing, both for unix
and windows.
+// Users that have rebuilt MXNet against older versions will we advised with a
warning to upgrade
+// their systems to match the CI level. Minimally, users should rerun the CI
locally.
+#if defined(_MSC_VER)
+#define MXNET_CI_OLDEST_CUDA_VERSION 9020
+#else
+#define MXNET_CI_OLDEST_CUDA_VERSION 1
+#endif
+
+// Dynamic init here will emit a warning if runtime and compile-time cuda lib
versions mismatch.
+// Also if the user has recompiled their source to a version no longer tested
by upstream CI.
+bool cuda_version_check_performed = []() {
+ // Don't bother with checks if there are no GPUs visible (e.g. with
CUDA_VISIBLE_DEVICES="")
+ if (dmlc::GetEnv("MXNET_CUDA_VERSION_CHECKING", true) &&
Context::GetGPUCount() > 0) {
+int linkedAgainstCudaVersion = 0;
+CUDA_CALL(cudaRuntimeGetVersion(&linkedAgainstCudaVersion));
+if (linkedAgainstCudaVersion != CUDA_VERSION)
+ LOG(WARNING) << "cuda library mismatch: linked-against version " <<
linkedAgainstCudaVersion
Review comment:
Thanks for the updates and clarification Dick.
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[GitHub] [incubator-mxnet] KellenSunderland merged pull request #15449: cuda/cuDNN lib version checking. Force cuDNN v7 usage.
KellenSunderland merged pull request #15449: cuda/cuDNN lib version checking. Force cuDNN v7 usage. URL: https://github.com/apache/incubator-mxnet/pull/15449 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[incubator-mxnet] branch master updated (554b196 -> 6a564be)
This is an automated email from the ASF dual-hosted git repository. kellen pushed a change to branch master in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 554b196 Rebase #13757 to master (#15189) add 6a564be cuda/cuDNN lib version checking. Force cuDNN v7 usage. (#15449) No new revisions were added by this update. Summary of changes: docs/faq/env_var.md | 10 + include/mxnet/resource.h | 8 ++-- src/common/cuda_utils.cc | 105 +++ src/common/cuda_utils.h | 27 src/resource.cc | 22 +- 5 files changed, 158 insertions(+), 14 deletions(-) create mode 100644 src/common/cuda_utils.cc
[incubator-mxnet] branch numpy updated: [Numpy] Numpy hstack (#15302)
This is an automated email from the ASF dual-hosted git repository.
haoj pushed a commit to branch numpy
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/numpy by this push:
new a26b201 [Numpy] Numpy hstack (#15302)
a26b201 is described below
commit a26b2010183c5ad167c53d1c8e57d950959a3ac3
Author: Mike
AuthorDate: Sat Jul 13 01:08:11 2019 +0800
[Numpy] Numpy hstack (#15302)
* Add numpy compatible hstack that currently pass CPU tests
Regsiter hstack in GPU
Rgister backward function to GPU
Add some comments
Fix the issues pointed out in code review
Minor syntax fix according to comments
Add docs
* Minor syntax fix
---
python/mxnet/ndarray/numpy/_op.py | 42 +++-
python/mxnet/numpy/multiarray.py | 42 +++-
python/mxnet/symbol/numpy/_symbol.py | 42 +++-
src/operator/nn/concat-inl.h | 44
src/operator/numpy/np_matrix_op.cc | 91 ++
src/operator/numpy/np_matrix_op.cu | 6 +++
tests/python/unittest/test_numpy_op.py | 65
7 files changed, 329 insertions(+), 3 deletions(-)
diff --git a/python/mxnet/ndarray/numpy/_op.py
b/python/mxnet/ndarray/numpy/_op.py
index ff0e8c8..76ed88c 100644
--- a/python/mxnet/ndarray/numpy/_op.py
+++ b/python/mxnet/ndarray/numpy/_op.py
@@ -33,7 +33,7 @@ __all__ = ['zeros', 'ones', 'maximum', 'minimum', 'stack',
'arange', 'argmax',
'clip', 'split', 'swapaxes', 'expand_dims', 'tile', 'linspace',
'eye',
'sin', 'cos', 'sinh', 'cosh', 'log10', 'sqrt', 'abs', 'exp',
'arctan', 'sign', 'log',
'degrees', 'log2', 'rint', 'radians', 'mean', 'reciprocal',
'square', 'arcsin',
- 'argsort']
+ 'argsort', 'hstack']
@set_module('mxnet.ndarray.numpy')
@@ -511,6 +511,46 @@ def concatenate(seq, axis=0, out=None):
@set_module('mxnet.ndarray.numpy')
+def hstack(arrays):
+"""
+Stack arrays in sequence horizontally (column wise).
+This is equivalent to concatenation along the second axis,
+except for 1-D arrays where it concatenates along the first axis.
+Rebuilds arrays divided by hsplit.
+This function makes most sense for arrays with up to 3 dimensions.
+For instance, for pixel-data with a height (first axis), width (second
axis),
+and r/g/b channels (third axis). The functions concatenate,
+stack and block provide more general stacking and concatenation operations.
+
+Parameters
+--
+tup : sequence of ndarrays
+The arrays must have the same shape along all but the second axis,
except 1-D arrays which can be any length.
+
+Returns
+---
+stacked : ndarray
+The array formed by stacking the given arrays.
+
+Examples
+
+>>> from mxnet import np,npx
+>>> a = np.array((1,2,3))
+>>> b = np.array((2,3,4))
+>>> np.hstack((a,b))
+array([1., 2., 3., 2., 3., 4.])
+
+>>> a = np.array([[1],[2],[3]])
+>>> b = np.array([[2],[3],[4]])
+>>> np.hstack((a,b))
+array([[1., 2.],
+ [2., 3.],
+ [3., 4.]])
+"""
+return _npi.hstack(*arrays)
+
+
+@set_module('mxnet.ndarray.numpy')
def add(x1, x2, out=None):
"""Add arguments element-wise.
diff --git a/python/mxnet/numpy/multiarray.py b/python/mxnet/numpy/multiarray.py
index 83fcfc1..d20db96 100644
--- a/python/mxnet/numpy/multiarray.py
+++ b/python/mxnet/numpy/multiarray.py
@@ -48,7 +48,7 @@ __all__ = ['ndarray', 'empty', 'array', 'zeros', 'ones',
'maximum', 'minimum', '
'clip', 'split', 'swapaxes', 'expand_dims', 'tile', 'linspace',
'eye', 'sin', 'cos',
'sin', 'cos', 'sinh', 'cosh', 'log10', 'sqrt', 'abs', 'exp',
'arctan', 'sign', 'log',
'degrees', 'log2', 'rint', 'radians', 'mean', 'reciprocal',
'square', 'arcsin',
- 'argsort']
+ 'argsort', 'hstack']
# This function is copied from ndarray.py since pylint
@@ -1566,6 +1566,46 @@ def stack(arrays, axis=0, out=None):
@set_module('mxnet.numpy')
+def hstack(arrays):
+"""
+Stack arrays in sequence horizontally (column wise).
+This is equivalent to concatenation along the second axis,
+except for 1-D arrays where it concatenates along the first axis.
+Rebuilds arrays divided by hsplit.
+This function makes most sense for arrays with up to 3 dimensions.
+For instance, for pixel-data with a height (first axis), width (second
axis),
+and r/g/b channels (third axis). The functions concatenate,
+stack and block provide more general stacking and concatenation operations.
+
+Parameters
+--
+tup : sequence of ndarrays
+The arrays must have the same shape along all but the second axis,
except 1-D arrays which can be any length.
+
+Returns
+---
+stacked : ndarray
[GitHub] [incubator-mxnet] haojin2 merged pull request #15302: [Numpy] Numpy hstack
haojin2 merged pull request #15302: [Numpy] Numpy hstack URL: https://github.com/apache/incubator-mxnet/pull/15302 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] Zha0q1 commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
Zha0q1 commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303073483
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; i++) {
Review comment:
I remember compiler will optimize this to ++i? Anyways, I will make the
change myself
-
[GitHub] [incubator-mxnet] Zha0q1 commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
Zha0q1 commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303081013
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; i++) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] Zha0q1 commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
Zha0q1 commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303081013
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; i++) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] Zha0q1 commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
Zha0q1 commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303082695
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; i++) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] Zha0q1 commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
Zha0q1 commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303082645
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; i++) {
Review comment:
fixed
This is an automated message from
[GitHub] [incubator-mxnet] ChaiBapchya opened a new pull request #15522: Add optimizer update operator benchmarks to opperf
ChaiBapchya opened a new pull request #15522: Add optimizer update operator benchmarks to opperf URL: https://github.com/apache/incubator-mxnet/pull/15522 ## Description ## Added neural network optimizer (Adam, sgd, etc) update operators to the existing set of opperf benchmarks ## Checklist ## ### Essentials ### Please feel free to remove inapplicable items for your PR. - [X] Changes are complete (i.e. I finished coding on this PR) - [X] All changes have test coverage: - [X] Code is well-documented: - [X] To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change ### Changes ### - [ ] Added optimizer update ops to opperf @sandeep-krishnamurthy @apeforest This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] aaronmarkham opened a new pull request #15523: add julia env settings
aaronmarkham opened a new pull request #15523: add julia env settings URL: https://github.com/apache/incubator-mxnet/pull/15523 ## Description ## I missed this env var requirement in the Julia docs PR, #15454. ## Comment We should probably add some CI test for the website publish routine so this kind of thing doesn't get overlooked until after a merge. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] marcoabreu commented on issue #15426: Add -R option to ci/build.py to avoid rebuilding containers
marcoabreu commented on issue #15426: Add -R option to ci/build.py to avoid rebuilding containers URL: https://github.com/apache/incubator-mxnet/pull/15426#issuecomment-510979685 Ye it's probably user id - for whatever reason docker cares about that... This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] marcoabreu merged pull request #15426: Add -R option to ci/build.py to avoid rebuilding containers
marcoabreu merged pull request #15426: Add -R option to ci/build.py to avoid rebuilding containers URL: https://github.com/apache/incubator-mxnet/pull/15426 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[incubator-mxnet] branch master updated (6a564be -> 9ff6c46)
This is an automated email from the ASF dual-hosted git repository. marcoabreu pushed a change to branch master in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from 6a564be cuda/cuDNN lib version checking. Force cuDNN v7 usage. (#15449) add 9ff6c46 Add -R option to ci/build.py to avoid rebuilding containers (#15426) No new revisions were added by this update. Summary of changes: ci/build.py | 10 +- 1 file changed, 9 insertions(+), 1 deletion(-)
[GitHub] [incubator-mxnet] aaronmarkham opened a new pull request #15524: refine Nano setup directions
aaronmarkham opened a new pull request #15524: refine Nano setup directions URL: https://github.com/apache/incubator-mxnet/pull/15524 ## Description ## After another run-through on a fresh Nano, plus trying out these new pip wheels, we found some refinements that should make the setup go a little more cleanly. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15349: Numpy Tensordot Operator
haojin2 commented on a change in pull request #15349: Numpy Tensordot Operator URL: https://github.com/apache/incubator-mxnet/pull/15349#discussion_r303094358 ## File path: tests/python/unittest/test_numpy_op.py ## @@ -26,6 +26,151 @@ from mxnet.test_utils import check_numeric_gradient from common import assertRaises, with_seed import random +import collections + Review comment: one more blank line. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15349: Numpy Tensordot Operator
haojin2 commented on a change in pull request #15349: Numpy Tensordot Operator
URL: https://github.com/apache/incubator-mxnet/pull/15349#discussion_r303094273
##
File path: src/operator/numpy/np_tensordot_op.cc
##
@@ -0,0 +1,222 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * \file np_tensordot_op.cc
+ * \brief CPU Implementation of numpy-compatible tensordot
+ */
+
+#include
+#include "np_tensordot_op-inl.h"
+
+namespace mxnet {
+namespace op {
+
+bool TensordotOpShape(const nnvm::NodeAttrs& attrs,
+ mxnet::ShapeVector *in_attrs,
+ mxnet::ShapeVector *out_attrs) {
+ CHECK_EQ(in_attrs->size(), 2U);
+ CHECK_EQ(out_attrs->size(), 1U);
+
+ const mxnet::TShape& a_shape = in_attrs->at(0);
+ const mxnet::TShape& b_shape = in_attrs->at(1);
+
+ if (!ndim_is_known(a_shape) || !ndim_is_known(b_shape)) {
+return false;
+ }
+
+ if ((a_shape.ndim() < 1) || (b_shape.ndim() < 1)) {
+return false;
+ }
+
+ const TensordotParam& param = nnvm::get(attrs.parsed);
+ const Tuple& a_axes_summed = param.a_axes_summed;
+ const Tuple& b_axes_summed = param.b_axes_summed;
+
+ Tuple a_axes_remained;
+ Tuple b_axes_remained;
+ Tuple a_axes;
+ Tuple b_axes;
+ GetReorderedAxes(a_axes_summed, &a_axes_remained, &a_axes, b_axes_summed,
&b_axes_remained,
+ &b_axes, a_shape, b_shape);
+
+ CHECK_EQ(a_axes_summed.ndim(), b_axes_summed.ndim());
+
+ mxnet::TShape out_shape(a_axes_remained.ndim() + b_axes_remained.ndim(), -1);
+ for (int i = 0; i < a_axes_remained.ndim(); i++) {
+out_shape[i] = a_shape[a_axes_remained[i]];
+ }
+ for (int i = 0; i < b_axes_remained.ndim(); i++) {
+out_shape[a_axes_remained.ndim() + i] = b_shape[b_axes_remained[i]];
+ }
+ SHAPE_ASSIGN_CHECK(*out_attrs, 0, out_shape);
+
+ mxnet::TShape tem_shape1(a_axes.ndim(), -1);
+ for (int i = 0; i < a_axes_remained.ndim(); i++) {
+tem_shape1[a_axes_remained[i]] = out_shape[i];
+ }
+ for (int i = 0; i < a_axes_summed.ndim(); i++) {
+tem_shape1[a_axes_summed[i]] = b_shape[b_axes_summed[i]];
+ }
+ SHAPE_ASSIGN_CHECK(*in_attrs, 0, tem_shape1);
+
+ mxnet::TShape tem_shape2(b_axes.ndim(), -1);
+ for (int i = 0; i < b_axes_remained.ndim(); i++) {
+tem_shape2[b_axes_remained[i]] = out_shape[a_axes_remained.ndim() + i];
+ }
+ for (int i = 0; i < b_axes_summed.ndim(); i++) {
+tem_shape2[b_axes_summed[i]] = a_shape[a_axes_summed[i]];
+ }
+ SHAPE_ASSIGN_CHECK(*in_attrs, 1, tem_shape2);
+
+ return shape_is_known(*in_attrs) && shape_is_known(*out_attrs);
+}
+
+DMLC_REGISTER_PARAMETER(TensordotParam);
+
+NNVM_REGISTER_OP(_npi_tensordot)
+.set_attr_parser(mxnet::op::ParamParser)
+.set_num_inputs(2)
+.set_num_outputs(1)
+.set_attr("FListInputNames",
+ [](const NodeAttrs& attrs) {
+return std::vector{"a", "b"};
+ })
+.set_attr("FInferShape", TensordotOpShape)
+.set_attr("FInferType", mxnet::op::ElemwiseType<2, 1>)
+.set_attr("FResourceRequest",
+ [](const NodeAttrs& attrs) {
+return std::vector{ResourceRequest::kTempSpace};
+ })
+.set_attr("FCompute", TensordotOpForward)
+.set_attr("FGradient",
mxnet::op::ElemwiseGradUseIn{"_backward_npi_tensordot"})
+.add_argument("a", "NDArray-or-Symbol", "First input")
+.add_argument("b", "NDArray-or-Symbol", "Second input")
+.add_arguments(TensordotParam::__FIELDS__());
+
+NNVM_REGISTER_OP(_backward_npi_tensordot)
+.set_attr_parser(mxnet::op::ParamParser)
+.set_num_inputs(3)
+.set_num_outputs(2)
+.set_attr("TIsBackward", true)
+.set_attr("FResourceRequest",
+ [](const NodeAttrs& attrs) {
+return std::vector{ResourceRequest::kTempSpace};
+ })
+.set_attr("FCompute", TensordotOpBackward);
+
+bool TensordotIntAxesOpShape(const nnvm::NodeAttrs& attrs,
+ mxnet::ShapeVector *in_attrs,
+ mxnet::ShapeVector *out_attrs) {
+ CHECK_EQ(in_attrs->size(), 2U);
+ CHECK_EQ(out_attrs->size(), 1U);
+
+ const mxnet::TShape& a_shape = in_attrs->at(0);
+ const mxnet::TShape& b_shape = in_attrs->at(1);
+
+ if (!ndim_is_known(a_shape) || !ndim_is_known(b_shape)) {
+return false;
+ }
+
+ if ((a_shape.ndim() < 1) || (b_shape.ndim() < 1)) {
+return false;
+ }
+
+ c
[GitHub] [incubator-mxnet] sandeep-krishnamurthy opened a new issue #15525: Nightly tests / integration tests in PRs are not tested before merging
sandeep-krishnamurthy opened a new issue #15525: Nightly tests / integration tests in PRs are not tested before merging URL: https://github.com/apache/incubator-mxnet/issues/15525 We do not test nightly/integration tests added in a PR at PR CI stage. This leads to a PR with failing integration test to get merged and all our nightly CI jobs starts failing. We need to make sure everything in the PR is tested before merge. For this particular problem, one suggested solution could be - If there are nightly tests in the PR, it needs to be executed as part of PR validation. Suggestions? @roywei @marcoabreu @lanking520 This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] mxnet-label-bot commented on issue #15525: Nightly tests / integration tests in PRs are not tested before merging
mxnet-label-bot commented on issue #15525: Nightly tests / integration tests in PRs are not tested before merging URL: https://github.com/apache/incubator-mxnet/issues/15525#issuecomment-510983068 Hey, this is the MXNet Label Bot. Thank you for submitting the issue! I will try and suggest some labels so that the appropriate MXNet community members can help resolve it. Here are my recommended labels: Test This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] Zha0q1 commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
Zha0q1 commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303081013
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; i++) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] marcoabreu commented on issue #15525: Nightly tests / integration tests in PRs are not tested before merging
marcoabreu commented on issue #15525: Nightly tests / integration tests in PRs are not tested before merging URL: https://github.com/apache/incubator-mxnet/issues/15525#issuecomment-510985789 I'd love to have context sensitive validations. Unfortunately, this feature doesn't exist out of the box. In general I think that we consider master bleeding edge. Thus, it's okay to have less coverage for the sake of speed and costs. If a PR breaks something, we usually revert it and get back to the original author. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] roywei commented on issue #15525: Nightly tests / integration tests in PRs are not tested before merging
roywei commented on issue #15525: Nightly tests / integration tests in PRs are not tested before merging URL: https://github.com/apache/incubator-mxnet/issues/15525#issuecomment-510993342 - Nightly tests are supposed to fail and we can revert whichever PR caused it, other wise it's too costly to run even for PR validation, imagine each commit will trigger a big job. - Most of the time, when contributors are changing nightly test configurations and adding nightly tests, they test it anyway, it's not likely to fail. - Test tuorials is a special case as many people are contributing to tutorials. But most of them don't know they have to add any dependency in CI and warnings are considered as failure. That's most of the reasons for CI failure. To start with, without any new features been added, maybe some way to enforce contributors to test tutorials locally before merging PR. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] roywei edited a comment on issue #15525: Nightly tests / integration tests in PRs are not tested before merging
roywei edited a comment on issue #15525: Nightly tests / integration tests in PRs are not tested before merging URL: https://github.com/apache/incubator-mxnet/issues/15525#issuecomment-510993342 - Nightly tests are supposed to fail and we can revert whichever PR caused it, other wise it's too costly to run even selected jobs only for PR validation, imagine each commit will trigger a big job. - Most of the time, when contributors are changing nightly test configurations and adding nightly tests, they test it anyway, it's not likely to fail. - Test tuorials is a special case as many people are contributing to tutorials. But most of them don't know they have to add any dependency in CI and warnings are considered as failure. That's most of the reasons for CI failure. To start with, without any new features been added, maybe some way to enforce contributors to test tutorials locally before merging PR. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] roywei edited a comment on issue #15525: Nightly tests / integration tests in PRs are not tested before merging
roywei edited a comment on issue #15525: Nightly tests / integration tests in PRs are not tested before merging URL: https://github.com/apache/incubator-mxnet/issues/15525#issuecomment-510993342 - Nightly tests are supposed to fail and we can revert whichever PR caused it, other wise it's too costly to run even selected jobs only for PR validation, imagine each commit will trigger a big job. - Most of the time, when contributors are changing nightly test configurations and adding nightly tests, they test it anyway, it's not likely to fail. - Test tuorials is a special case as many people are contributing to tutorials. But most of them don't know they have to add any dependency package used in tutorial in CI docker file and warnings are considered as failure. That's most of the reasons for CI failure. To start with, without any new features been added, maybe some way to enforce contributors to test tutorials locally before merging PR. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] roywei edited a comment on issue #15525: Nightly tests / integration tests in PRs are not tested before merging
roywei edited a comment on issue #15525: Nightly tests / integration tests in PRs are not tested before merging URL: https://github.com/apache/incubator-mxnet/issues/15525#issuecomment-510993342 - Nightly tests are supposed to fail and we can revert whichever PR caused it, other wise it's too costly to run even selected jobs only for PR validation, imagine each commit will trigger a big job. - Most of the time, when contributors are changing nightly test configurations and adding nightly tests, they test it anyway, it's not likely to fail. - Test tuorials is a special case as many people are contributing to tutorials. But most of them don't know they have to add any dependency package used in tutorial in CI docker file and warnings generated are considered as failure. That's most of the reasons for CI failure. To start with, without any new features been added, maybe some way to enforce contributors to test tutorials locally before merging PR. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] roywei edited a comment on issue #15525: Nightly tests / integration tests in PRs are not tested before merging
roywei edited a comment on issue #15525: Nightly tests / integration tests in PRs are not tested before merging URL: https://github.com/apache/incubator-mxnet/issues/15525#issuecomment-510993342 - Nightly tests are supposed to fail and we can revert whichever PR caused it, other wise it's too costly to run even selected jobs only for PR validation, imagine each commit will trigger a big job. - Most of the time, when contributors are changing nightly test configurations and adding nightly tests, they test it anyway, it's not likely to fail. - Test tuorials is a special case as many people are contributing to tutorials. But most of them don't know they have to add any dependency package used in tutorial in CI docker file and warnings generated are considered as failure. That's most of the reasons for CI failure. To start with, without any new features been added, maybe some way to enforce contributors to test locally before merging PR. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] roywei edited a comment on issue #15525: Nightly tests / integration tests in PRs are not tested before merging
roywei edited a comment on issue #15525: Nightly tests / integration tests in PRs are not tested before merging URL: https://github.com/apache/incubator-mxnet/issues/15525#issuecomment-510993342 - Nightly tests are supposed to fail and we can revert whichever PR caused it, other wise it's too costly to run even selected jobs only for PR validation, imagine each commit will trigger a big job. - Most of the time, when contributors are changing nightly test configurations and adding nightly tests, they test it anyway, it's not likely to fail. - Test tuorials is a special case as many people are contributing to tutorials. But most of them don't know they have to add any dependency package used in tutorial in CI docker file and warnings generated are considered as failure. That's most of the reasons for CI failure. To start with, without any new features been added, maybe some way to enforce contributors to test locally before merging PR. (Having label bot to leave a message if nightly test change detected?) This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] roywei edited a comment on issue #15525: Nightly tests / integration tests in PRs are not tested before merging
roywei edited a comment on issue #15525: Nightly tests / integration tests in PRs are not tested before merging URL: https://github.com/apache/incubator-mxnet/issues/15525#issuecomment-510993342 - Nightly tests are supposed to fail and we can revert whichever PR caused it, other wise it's too costly to run even selected jobs only for PR validation, imagine each commit will trigger a big job. - Most of the time, when contributors are changing nightly test configurations and adding nightly tests, they test it anyway, it's not likely to fail. - Test tuorials is a special case as many people are contributing to tutorials. But most of them don't know they have to add any dependency package used in tutorial in CI docker file and warnings generated are considered as failure. That's most of the reasons for CI failure. To start with, without any new features been added to CI, maybe some way to enforce contributors to test locally before merging PR. (Having label bot to leave a message if nightly test change detected?) This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] anirudh2290 commented on a change in pull request #15245: FP16 Support for C Predict API
anirudh2290 commented on a change in pull request #15245: FP16 Support for C
Predict API
URL: https://github.com/apache/incubator-mxnet/pull/15245#discussion_r303110259
##
File path: amalgamation/python/mxnet_predict.py
##
@@ -160,10 +249,18 @@ def forward(self, **kwargs):
>>> predictor.forward(data=mydata)
>>> out = predictor.get_output(0)
"""
+if self.type_dict and len(self.type_dict) != len(kwargs.items()):
+raise ValueError("number of kwargs should be same as len of
type_dict" \
+ "Please check your forward pass inputs" \
+ "or type_dict passed to Predictor instantiation")
+
for k, v in kwargs.items():
if not isinstance(v, np.ndarray):
raise ValueError("Expect numpy ndarray as input")
-v = np.asarray(v, dtype=np.float32, order='C')
+if self.type_dict and k in self.type_dict:
+v = np.asarray(v, dtype=self.type_dict[k], order='C')
+else:
+v = np.asarray(v, dtype=np.float32, order='C')
Review comment:
we use the lookup table to map the dtype int, which comes from mxnet backend
to numpy dtype. For cases, we are not determining it from backend dtype I think
it is better to use np.float32 rather than _DTYPE_MX_TO_NP[0].
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[GitHub] [incubator-mxnet] larroy commented on issue #15426: Add -R option to ci/build.py to avoid rebuilding containers
larroy commented on issue #15426: Add -R option to ci/build.py to avoid rebuilding containers URL: https://github.com/apache/incubator-mxnet/pull/15426#issuecomment-510997277 Danke fuer die merge. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] larroy edited a comment on issue #15426: Add -R option to ci/build.py to avoid rebuilding containers
larroy edited a comment on issue #15426: Add -R option to ci/build.py to avoid rebuilding containers URL: https://github.com/apache/incubator-mxnet/pull/15426#issuecomment-510997277 Danke für die merge. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] larroy commented on issue #15270: Fix warnings in CLang.
larroy commented on issue #15270: Fix warnings in CLang. URL: https://github.com/apache/incubator-mxnet/pull/15270#issuecomment-510997782 Done, could we get those small PRs that fix warnings merged? This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] marcoabreu commented on issue #15525: Nightly tests / integration tests in PRs are not tested before merging
marcoabreu commented on issue #15525: Nightly tests / integration tests in PRs are not tested before merging URL: https://github.com/apache/incubator-mxnet/issues/15525#issuecomment-510999095 I'm certainly in favour of a context sensitive bot that gives certain comments if certain types of changes are detected. But enforcing directly isn't possible besides adding actual checks. For example, we asked people in the past to run make lint locally. I could give you statistics about how often linting fails in ci, but trust me that something that simple isn't even followed most of the time. So basically we can't request anything from people unless we enforce it, which I'm opposed to in this particular case This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] larroy commented on issue #15465: [RFC] Integrate TVM into Apache MXNet
larroy commented on issue #15465: [RFC] Integrate TVM into Apache MXNet URL: https://github.com/apache/incubator-mxnet/issues/15465#issuecomment-510999368 Could we add more information on how will it impact the build systems and dependencies? While integrating TVM is exciting, I think is fair to gauge the increase of complexity, build and release implications. Would it be possible to load operators compiled with TVM dynamically? This would open a path to modularize MXNet and reduce the library size / target inference only version in a more streamlined way than with amalgamation hacks. This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] larroy commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
larroy commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303115908
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; ++i) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] larroy commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
larroy commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303119170
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; ++i) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] larroy commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
larroy commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303117010
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; ++i) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] larroy commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
larroy commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303118403
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; ++i) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] larroy commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
larroy commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303113524
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
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[GitHub] [incubator-mxnet] larroy commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
larroy commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303113874
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; ++i) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] larroy commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
larroy commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303118876
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; ++i) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] larroy commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
larroy commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303119928
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; ++i) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] larroy commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
larroy commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303118036
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; ++i) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] larroy commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
larroy commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303119597
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; ++i) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] larroy commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
larroy commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303113816
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; ++i) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
[GitHub] [incubator-mxnet] Zha0q1 commented on issue #15490: Utility to help developers debug operators: Tensor Inspector
Zha0q1 commented on issue #15490: Utility to help developers debug operators: Tensor Inspector URL: https://github.com/apache/incubator-mxnet/pull/15490#issuecomment-511013592 > Nice work, just a few comments, looks good. Thank you for the detailed advices! This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-mxnet] Zha0q1 commented on a change in pull request #15490: Utility to help developers debug operators: Tensor Inspector
Zha0q1 commented on a change in pull request #15490: Utility to help developers
debug operators: Tensor Inspector
URL: https://github.com/apache/incubator-mxnet/pull/15490#discussion_r303129096
##
File path: src/common/tensor_inspector.h
##
@@ -0,0 +1,733 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * Copyright (c) 2019 by Contributors
+ * \file tensor_inspector.h
+ * \brief utility to inspect tensor objects
+ * \author Zhaoqi Zhu
+ */
+
+#ifndef MXNET_COMMON_TENSOR_INSPECTOR_H_
+#define MXNET_COMMON_TENSOR_INSPECTOR_H_
+
+#include
+#include
+#include
+#include
+#include
+#include "../../3rdparty/mshadow/mshadow/base.h"
+#include "../../tests/cpp/include/test_util.h"
+
+namespace mxnet {
+
+/*!
+ * \brief this singleton struct mediates individual TensorInspector objects
+ * so that we can control the global behavior from each of them
+ */
+struct InspectorManager {
+ static InspectorManager* get() {
+static std::mutex mtx;
+static std::unique_ptr im = nullptr;
+if (!im) {
+ std::unique_lock lk(mtx);
+ if (!im)
+im = std::make_unique();
+}
+return im.get();
+ }
+ /* !\brief mutex used to lock interactive_print() and check_value() */
+ std::mutex mutex_;
+ /* !\brief skip all interactive prints */
+ bool interactive_print_skip_all_ = false;
+ /* !\brief skip all value checks */
+ bool check_value_skip_all_ = false;
+ /* !\brief visit count for interactive print tags */
+ std::unordered_map interactive_print_tag_counter_;
+ /* !\brief visit count for check value tags */
+ std::unordered_map check_value_tag_counter_;
+ /* !\brief visit count for dump value tags */
+ std::unordered_map dump_value_tag_counter_;
+};
+
+/*!
+ * \brief Enum for building value checkers for TensorInspector::check_value()
+ */
+enum CheckerType {
+ NegativeChecker, // check if is negative
+ PositiveChecker, // check if is positive
+ ZeroChecker, // check if is zero
+ NaNChecker, // check if is NaN, will always return false if DType is not a
float type
+ InfChecker, // check if is infinity, will always return false if DType is
not a float type
+ PositiveInfChecker, // check if is positive infinity,
+ // will always return false if DType is not a float type
+ NegativeInfChecker, // check if is nagative infinity,
+ // will always return false if DType is not a float type
+ FiniteChecker, // check if is finite, will always return false if DType is
not a float type
+ NormalChecker, // check if is neither infinity nor NaN
+ AbnormalChecker, // chekck if is infinity or nan
+};
+
+/**
+ * ___ _ _
+ * |__ __||_ _| | |
+ *| | ___ _ __ ___ ___ _ __| | _ __ ___ _ __ ___ ___| |_ ___ _ __
+ *| |/ _ \ '_ \/ __|/ _ \| '__| | | '_ \/ __| '_ \ / _ \/ __| __/ _ \| '__|
+ *| | __/ | | \__ \ (_) | | _| |_| | | \__ \ |_) | __/ (__| || (_) | |
+ *|_|\___|_| |_|___/\___/|_||_|_| |_|___/ .__/ \___|\___|\__\___/|_|
+ * | |
+ * |_|
+ */
+
+/*!
+ * \brief This class provides a unified interface to inspect the value of all
data types
+ * including Tensor, TBlob, and NDArray. If the tensor resides on GPU, then it
will be
+ * copied from GPU memory back to CPU memory to be operated on. Internally,
all data types
+ * are stored as a TBlob object tb_.
+ */
+class TensorInspector {
+ private:
+ /*!
+ * \brief generate the tensor info, including data type and shape
+ * \tparam DType the data type
+ * \tparam StreamType the type of the stream object
+ * \param os stream object to output to
+ */
+ template
+ inline void tensor_info_to_string(StreamType* os) {
+int dimension = tb_.ndim();
+*os << "<" << typeid(tb_.dptr()[0]).name() << " Tensor ";
+*os << tb_.shape_[0];
+for (int i = 1; i < dimension; ++i) {
+ *os << 'x' << tb_.shape_[i];
+}
+*os << ">" << std::endl;
+ }
+
+ /*!
+ * \brief output the tensor info, inc
