[GitHub] [incubator-mxnet] eric-haibin-lin commented on issue #14383: MXNET_BACKWARD_DO_MIRROR is broken
eric-haibin-lin commented on issue #14383: MXNET_BACKWARD_DO_MIRROR is broken URL: https://github.com/apache/incubator-mxnet/issues/14383#issuecomment-473622044 related PR https://github.com/apache/incubator-mxnet/pull/11472 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] eric-haibin-lin commented on issue #14383: MXNET_BACKWARD_DO_MIRROR is broken
eric-haibin-lin commented on issue #14383: MXNET_BACKWARD_DO_MIRROR is broken URL: https://github.com/apache/incubator-mxnet/issues/14383#issuecomment-473622011 Contribution is welcome! 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] eric-haibin-lin commented on issue #14434: could i set multi kv_store in distribute training program?
eric-haibin-lin commented on issue #14434: could i set multi kv_store in distribute training program? URL: https://github.com/apache/incubator-mxnet/issues/14434#issuecomment-473621985 Not currently supported. what is your use 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
[incubator-mxnet] branch master updated: Correct update count with Gluon trainer and update_on_kvstore=False (#14377)
This is an automated email from the ASF dual-hosted git repository.
haibin pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/master by this push:
new 63ed258 Correct update count with Gluon trainer and
update_on_kvstore=False (#14377)
63ed258 is described below
commit 63ed258063137421e6d4def30435014ab57fb468
Author: Przemyslaw Tredak
AuthorDate: Sat Mar 16 23:48:30 2019 -0700
Correct update count with Gluon trainer and update_on_kvstore=False (#14377)
* LRScheduler with update_on_kvstore=False
* Cleaning trainer.py
* Retrigger CI
* Fixes from review
---
python/mxnet/gluon/trainer.py | 4
python/mxnet/optimizer/optimizer.py | 17 -
tests/python/unittest/test_gluon_trainer.py | 21 -
3 files changed, 28 insertions(+), 14 deletions(-)
diff --git a/python/mxnet/gluon/trainer.py b/python/mxnet/gluon/trainer.py
index 8060f38..45a44d8 100644
--- a/python/mxnet/gluon/trainer.py
+++ b/python/mxnet/gluon/trainer.py
@@ -241,10 +241,6 @@ class Trainer(object):
kvstore.set_optimizer(self._optimizer)
self._kvstore = kvstore
self._update_on_kvstore = update_on_kvstore
-if self._optimizer.lr_scheduler and not self._update_on_kvstore:
-raise ValueError("update_on_kvstore=False does not support " \
- "optimizer with LRScheduler. Please " \
- "consider setting learning rate manually.")
else:
self._kvstore = None
self._update_on_kvstore = None
diff --git a/python/mxnet/optimizer/optimizer.py
b/python/mxnet/optimizer/optimizer.py
index def2c95..2e7fe86 100644
--- a/python/mxnet/optimizer/optimizer.py
+++ b/python/mxnet/optimizer/optimizer.py
@@ -106,7 +106,8 @@ class Optimizer(object):
self.wd_mult = {}
self.begin_num_update = begin_num_update
self.num_update = begin_num_update
-self._index_update_count = {}
+self._all_index_update_counts = {0 : {}}
+self._index_update_count = self._all_index_update_counts[0]
self.clip_gradient = clip_gradient
self.multi_precision = multi_precision
self.aggregate_num = 0
@@ -380,6 +381,18 @@ class Optimizer(object):
self.wd_mult[name] = float(attr[name]['__wd_mult__'])
self.wd_mult.update(args_wd_mult)
+def _set_current_context(self, device_id):
+"""Sets the number of the currently handled device.
+
+Parameters
+--
+device_id : int
+The number of current device.
+"""
+if device_id not in self._all_index_update_counts:
+self._all_index_update_counts[device_id] = {}
+self._index_update_count = self._all_index_update_counts[device_id]
+
def _update_count(self, index):
"""Updates num_update.
@@ -1623,6 +1636,8 @@ class Updater(object):
indices = index
grads = grad
weights = weight
+if weights:
+self.optimizer._set_current_context(weights[0].context.device_id)
for i, idx in enumerate(indices):
# convert ctypes.char_p.value back to python str if needed
if isinstance(idx, bytes):
diff --git a/tests/python/unittest/test_gluon_trainer.py
b/tests/python/unittest/test_gluon_trainer.py
index 9f190a0..2d5874a 100644
--- a/tests/python/unittest/test_gluon_trainer.py
+++ b/tests/python/unittest/test_gluon_trainer.py
@@ -272,19 +272,22 @@ def test_trainer_lr_sched():
lr *= factor
mx.nd.waitall()
-@with_seed()
-def test_trainer_invalid_lr_sched():
+# Update on kvstore = False
x = gluon.Parameter('x', shape=(10,))
x.initialize(ctx=[mx.cpu(0), mx.cpu(1)], init='zeros')
freq = 2
factor = 0.1
lr = 1
lr_sched = mx.lr_scheduler.FactorScheduler(freq, factor=factor, base_lr=lr)
-invalid_trainer = gluon.Trainer([x], 'sgd', {'learning_rate': lr,
'lr_scheduler': lr_sched},
-update_on_kvstore=False)
-with mx.autograd.record():
-for w in x.list_data():
-y = w + 1
-y.backward()
-assert_raises(ValueError, invalid_trainer.step, 1)
+trainer = gluon.Trainer([x], 'sgd', {'learning_rate': lr, 'lr_scheduler':
lr_sched},
+update_on_kvstore=False)
+for i in range(10):
+with mx.autograd.record():
+for w in x.list_data():
+y = w + 1
+y.backward()
+trainer.step(1)
+if i % freq == 0:
+assert trainer.learning_rate == lr, (lr, trainer.learning_rate, i)
+lr *= factor
mx.nd.waitall()
[GitHub] [incubator-mxnet] eric-haibin-lin closed issue #12713: distributed kvstore bug in MXNet
eric-haibin-lin closed issue #12713: distributed kvstore bug in MXNet URL: https://github.com/apache/incubator-mxnet/issues/12713 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] eric-haibin-lin closed issue #13752: Adam, AdaMax and FTML cannot be used with Trainer(update_on_kv=False)
eric-haibin-lin closed issue #13752: Adam, AdaMax and FTML cannot be used with Trainer(update_on_kv=False) URL: https://github.com/apache/incubator-mxnet/issues/13752 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] eric-haibin-lin merged pull request #14377: Correct update count with Gluon trainer and update_on_kvstore=False
eric-haibin-lin merged pull request #14377: Correct update count with Gluon trainer and update_on_kvstore=False URL: https://github.com/apache/incubator-mxnet/pull/14377 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 #14359: Speedup _contrib_index_copy
haojin2 commented on issue #14359: Speedup _contrib_index_copy URL: https://github.com/apache/incubator-mxnet/pull/14359#issuecomment-473620958 @szha @zheng-da Ready for merge I think. 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 #14361: [numpy] Add a global switch to turn on/off numpy compatibility
wkcn edited a comment on issue #14361: [numpy] Add a global switch to turn on/off numpy compatibility URL: https://github.com/apache/incubator-mxnet/pull/14361#issuecomment-473616124 when set_numpy_comp(True) is called, the output of some reduction operators Is always a scalar, which break the construct of computational graph, and not benefit for deployment. Example: ```python x = mx.nd.arange(6) x [0. 1. 2. 3. 4. 5.] x[1] [1.] float(x[1]) 1.0 # 1-dim NDArray mx.nd.sum(x) [15.] # 0-dim NDArray mx.numpy.sum(x) 15.0 # built-in float float(mx.numpy.sum(x)) 15.0 ``` 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 #14361: [numpy] Add a global switch to turn on/off numpy compatibility
wkcn edited a comment on issue #14361: [numpy] Add a global switch to turn on/off numpy compatibility URL: https://github.com/apache/incubator-mxnet/pull/14361#issuecomment-473616124 when set_numpy_comp(True) is called, the output of some reduction operators Is always a scalar, which break the construct of computational graph, and not benefit for deployment. Example: ```python x = mx.nd.arange(6) x [0. 1. 2. 3. 4. 5.] x[1] [1.] # 1-dim NDArray mx.nd.sum(x) [15.] # 0-dim NDArray mx.numpy.sum(x) 15.0 # built-in float float(mx.numpy.sum(x)) 15.0 ``` 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 #14361: [numpy] Add a global switch to turn on/off numpy compatibility
wkcn edited a comment on issue #14361: [numpy] Add a global switch to turn on/off numpy compatibility URL: https://github.com/apache/incubator-mxnet/pull/14361#issuecomment-473616124 when set_numpy_comp(True) is called, the output of some reduction operators Is always a scalar, which break the construct of computational graph, and not benefit for deployment. I will write an example. ```python x = mx.nd.arange(6) x [0. 1. 2. 3. 4. 5.] x[1] [1.] # 1-dim NDArray mx.nd.sum(x) [15.] # 0-dim NDArray mx.numpy.sum(x) 15.0 ``` 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 #14361: [numpy] Add a global switch to turn on/off numpy compatibility
wkcn edited a comment on issue #14361: [numpy] Add a global switch to turn on/off numpy compatibility URL: https://github.com/apache/incubator-mxnet/pull/14361#issuecomment-473616124 when set_numpy_comp(True) is called, the output of some reduction operators Is always a scalar, which break the construct of computational graph, and not benefit for deployment. Example: ```python x = mx.nd.arange(6) x [0. 1. 2. 3. 4. 5.] x[1] [1.] # 1-dim NDArray mx.nd.sum(x) [15.] # 0-dim NDArray mx.numpy.sum(x) 15.0 ``` 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 #14361: [numpy] Add a global switch to turn on/off numpy compatibility
wkcn commented on issue #14361: [numpy] Add a global switch to turn on/off numpy compatibility URL: https://github.com/apache/incubator-mxnet/pull/14361#issuecomment-473616124 when set_numpy_comp(True) is called, the output of some reduction operators Is always a scalar, which break the construct of computational graph, and not benefit for deployment. I will write an example. 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 #14361: [numpy] Add a global switch to turn on/off numpy compatibility
wkcn commented on issue #14361: [numpy] Add a global switch to turn on/off numpy compatibility URL: https://github.com/apache/incubator-mxnet/pull/14361#issuecomment-473616035 Sorry that I clicked by mistake. 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] reminisce opened a new pull request #14361: [numpy] Add a global switch to turn on/off numpy compatibility
reminisce opened a new pull request #14361: [numpy] Add a global switch to turn on/off numpy compatibility URL: https://github.com/apache/incubator-mxnet/pull/14361 This PR is implemented based upon the discussion with @eric-haibin-lin. It provides two APIs and NumPy-compatible NDArray indexing behavior, i.e. `y = x[i]`. 1. `set_numpy_comp(enable)` This is a thread-safe utility function for users to enable or disable NumPy-compatible behaviors in MXNet. This will generally affect the behavior of the following two operations: 1. NDArray indexing. When `enable=False`, NDArray indexing always returns a tensor with `ndim >= 1`, which is the default behavior of MXNet kept for backward compatibility. When `enable=True`, NDArray indexing will return a tensor with `ndim >= 0`, which is consistent with NumPy's indexing behavior. The result tensor with `ndim = 0` is actually a scalar whose shape is `()`. For example: >>> from mxnet.base import set_numpy_comp >>> x = mx.nd.arange(6) >>> x [0. 1. 2. 3. 4. 5.] >>> x[1] [1.] >>> set_numpy_comp(enable=True) >>> x[1] 1.0 >>> set_numpy_comp(enable=False) >>> x[1] [1.] 2. NDArray's convenience fluent methods. When `enable=True`, the convenience fluent methods will dispatch the calls to NumPy operators if implemented in MXNet. For example, given an NDArray `data`, `data.sum()` will call `mxnet.ndarray.sum(data)` when `enable=False` (default behavior), and mxnet.numpy.sum(data)` when `enable=True`. 2. `_is_numpy_comp()` This is a thread-safe utility function for checking whether NumPy-compatibility has been enabled or disabled. This is implemented for developers to use. Users are not expected to call this function. @junrushao1994 @eric-haibin-lin @szha @zheng-da @yzhliu 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 closed pull request #14361: [numpy] Add a global switch to turn on/off numpy compatibility
wkcn closed pull request #14361: [numpy] Add a global switch to turn on/off numpy compatibility URL: https://github.com/apache/incubator-mxnet/pull/14361 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 #14361: [numpy] Add a global switch to turn on/off numpy compatibility
wkcn commented on issue #14361: [numpy] Add a global switch to turn on/off numpy compatibility URL: https://github.com/apache/incubator-mxnet/pull/14361#issuecomment-473615972 when set_numpy_comp(true), the output of some reduction operators is always a scalsr, breaking the construct of static graph and the deployment. 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] arcadiaphy edited a comment on issue #14451: fix custom operation in fork
arcadiaphy edited a comment on issue #14451: fix custom operation in fork
URL: https://github.com/apache/incubator-mxnet/pull/14451#issuecomment-473611263
@wkcn For the two questions:
1. Yes, each process has its independent threads. Fork only duplicates the
caller thread, so we need to make sure all locking primitives are in valid
states and re-create the threads in child process. The easiest way is to
restart CustomOperator when fork happens just like Engine does.
2. There is no fork on windows, so python use spawn method to create new
process. I have no windows machine so I can only test on linux and mac
with:`import multiprocessing as mp; mp.set_start_method('spawn')` It seems like
python re-import mxnet in child process when spawning, so the bug doesn't exist
at all.
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[GitHub] [incubator-mxnet] arcadiaphy edited a comment on issue #14451: fix custom operation in fork
arcadiaphy edited a comment on issue #14451: fix custom operation in fork
URL: https://github.com/apache/incubator-mxnet/pull/14451#issuecomment-473611263
@wkcn For the two questions:
1. Yes, each process has its independent threads. Fork only duplicates the
caller thread, so we need to make sure all locking primitives are in valid
states and re-create the threads in child process. The easiest way is to
restart CustomOperator when fork happens just like Engine does.
2. There is no fork on windows, so python use spawn method to create new
process. I have no windows machine so I can only test on unix with:`import
multiprocessing as mp; mp.set_start_method('spawn')` It seems like python
re-import mxnet in child process when spawning, so the bug doesn't exist at all.
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[GitHub] [incubator-mxnet] arcadiaphy edited a comment on issue #14451: fix custom operation in fork
arcadiaphy edited a comment on issue #14451: fix custom operation in fork
URL: https://github.com/apache/incubator-mxnet/pull/14451#issuecomment-473611263
@wkcn For the two questions:
1. Yes, each process has its independent threads. Fork only duplicates the
caller thread, so we need to make sure all locking primitives are in valid
states and restart the threads in child process. The easiest way is to restart
CustomOperator when fork happens just like Engine does.
2. There is no fork on windows, so python use spawn method to create new
process. I have no windows machine so I can only test on unix with:`import
multiprocessing as mp; mp.set_start_method('spawn')` It seems like python
re-import mxnet in child process when spawning, so the bug doesn't exist at all.
This is an automated message from the Apache Git Service.
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[GitHub] [incubator-mxnet] arcadiaphy edited a comment on issue #14451: fix custom operation in fork
arcadiaphy edited a comment on issue #14451: fix custom operation in fork
URL: https://github.com/apache/incubator-mxnet/pull/14451#issuecomment-473611263
@wkcn For the two questions:
1. Yes, each process has its independent threads. Fork only duplicates the
caller thread, so we need to make sure all locking primitives are in valid
states and restart the threads in child process. The easiest way is to restart
CustomOperator when fork happens just like Engine does.
2. There is no fork on windows, so python use spawn method to create new
process. I have no windows machine so I can only test on unix with:`import
multiprocessing as mp; mp.set_start_method('spawn')` It seems like python
re-import mxnet in child process when spawning, so the bug doesn't exist even
without the fix.
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[GitHub] [incubator-mxnet] arcadiaphy commented on issue #14451: fix custom operation in fork
arcadiaphy commented on issue #14451: fix custom operation in fork
URL: https://github.com/apache/incubator-mxnet/pull/14451#issuecomment-473611263
@wkcn For the two questions:
1. Yes, each process has its independent threads. Fork only duplicates the
caller thread, so we need to make sure all locking primitives are in valid
states and restart the threads in child process. The easiest way is to restart
CustomOperator when fork happens just like Engine does.
2. There is no fork on windows, so python use spawn method to create new
process. I have no windows machine so I can only test on unix with:
```
import multiprocessing as mp
mp.set_start_method('spawn')
```
It seems like python re-import mxnet in child process when spawning, so the
bug doesn't exist even without the fix.
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[incubator-mxnet-site] branch asf-site updated: Bump the publish timestamp.
This is an automated email from the ASF dual-hosted git repository. zhasheng pushed a commit to branch asf-site in repository https://gitbox.apache.org/repos/asf/incubator-mxnet-site.git The following commit(s) were added to refs/heads/asf-site by this push: new 938b971 Bump the publish timestamp. 938b971 is described below commit 938b971611f04fed67bd855376e999595b29ba2b Author: mxnet-ci AuthorDate: Sun Mar 17 01:17:32 2019 + Bump the publish timestamp. --- date.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/date.txt b/date.txt new file mode 100644 index 000..7bc7d4f --- /dev/null +++ b/date.txt @@ -0,0 +1 @@ +Sun Mar 17 01:17:32 UTC 2019
[GitHub] [incubator-mxnet] szha merged pull request #14444: fix OOM error during resource allocation
szha merged pull request #1: fix OOM error during resource allocation URL: https://github.com/apache/incubator-mxnet/pull/1 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: fix OOM error during resource allocation (#14444)
This is an automated email from the ASF dual-hosted git repository. zhasheng pushed a commit to branch master in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git The following commit(s) were added to refs/heads/master by this push: new f602b0d fix OOM error during resource allocation (#1) f602b0d is described below commit f602b0de310fbdad40b26a87e51c6820790858b3 Author: Sheng Zha AuthorDate: Sat Mar 16 14:24:14 2019 -0700 fix OOM error during resource allocation (#1) --- src/resource.cc | 3 +++ 1 file changed, 3 insertions(+) diff --git a/src/resource.cc b/src/resource.cc index 80a5c0e..0317ff3 100644 --- a/src/resource.cc +++ b/src/resource.cc @@ -432,6 +432,9 @@ void Resource::get_cudnn_dropout_desc( // not initialized yet. size_t dropout_state_size; CUDNN_CALL(cudnnDropoutGetStatesSize(stream->dnn_handle_, &dropout_state_size)); +// reserve GPU space +Storage::Get()->DirectFree( + Storage::Get()->Alloc(dropout_state_size, state_space->ctx)); CUDNN_CALL(cudnnSetDropoutDescriptor(*dropout_desc, stream->dnn_handle_, dropout, state_space->GetSpace(dropout_state_size),
[incubator-mxnet-site] branch asf-site updated: Bump the publish timestamp.
This is an automated email from the ASF dual-hosted git repository. zhasheng pushed a commit to branch asf-site in repository https://gitbox.apache.org/repos/asf/incubator-mxnet-site.git The following commit(s) were added to refs/heads/asf-site by this push: new ba2b31e Bump the publish timestamp. ba2b31e is described below commit ba2b31e91ee95b5bf73ea0ecca766a6e99ef9b4c Author: mxnet-ci AuthorDate: Sat Mar 16 20:52:04 2019 + Bump the publish timestamp. --- date.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/date.txt b/date.txt new file mode 100644 index 000..100533c --- /dev/null +++ b/date.txt @@ -0,0 +1 @@ +Sat Mar 16 20:52:04 UTC 2019
[GitHub] [incubator-mxnet] reminisce commented on issue #14361: [numpy] Add a global switch to turn on/off numpy compatibility
reminisce commented on issue #14361: [numpy] Add a global switch to turn on/off numpy compatibility URL: https://github.com/apache/incubator-mxnet/pull/14361#issuecomment-473591126 @wkcn Can you elaborate why we cannot use a switch to guarantee backward compatibility and allow users to opt in new numpy compatible behavior? 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] arcadiaphy edited a comment on issue #14396: mx.nd.Custom not working in subprocess
arcadiaphy edited a comment on issue #14396: mx.nd.Custom not working in
subprocess
URL:
https://github.com/apache/incubator-mxnet/issues/14396#issuecomment-473577236
After #14363, the threads is created when running custom operator, so
custom operator needs also to be executed in main process to reproduce the bug:
```
from concurrent import futures
import mxnet as mx
import sys
class AdditionOP(mx.operator.CustomOp):
def __init__(self):
super(AdditionOP, self).__init__()
def forward(self, is_train, req, in_data, out_data, aux):
out_data[0][:] = in_data[0] + in_data[1]
def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
in_grad[0][:] = out_grad[0]
in_grad[1][:] = out_grad[0]
@mx.operator.register("AdditionOP")
class AdditionOPProp(mx.operator.CustomOpProp):
def __init__(self):
super(AdditionOPProp, self).__init__()
def list_arguments(self):
return ['a', 'b']
def list_outputs(self):
return ['output']
def infer_shape(self, in_shape):
return in_shape, [in_shape[0]]
def create_operator(self, ctx, shapes, dtypes):
return AdditionOP()
def foo():
a = mx.nd.array([1, 2, 3])
b = mx.nd.array([4, 5, 6])
a.attach_grad()
b.attach_grad()
print("REC")
with mx.autograd.record():
c = mx.nd.Custom(a, b, op_type='AdditionOP')
dc = mx.nd.array([7, 8, 9])
c.backward(dc)
print('Okay :-)')
print('a + b = c \n {} + {} = {}'.format(a.asnumpy(), b.asnumpy(),
c.asnumpy()))
def main():
foo() # ensure custom threads created in main process
ex = futures.ProcessPoolExecutor(1)
r = ex.submit(foo)
r.result()
if __name__ == '__main__':
main()
```
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[GitHub] [incubator-mxnet] arcadiaphy edited a comment on issue #14396: mx.nd.Custom not working in subprocess
arcadiaphy edited a comment on issue #14396: mx.nd.Custom not working in
subprocess
URL:
https://github.com/apache/incubator-mxnet/issues/14396#issuecomment-473577236
After #14363, the threads in custom is created when running custom
operator, so custom operator needs also to be executed in main process to
reproduce the bug:
```
from concurrent import futures
import mxnet as mx
import sys
class AdditionOP(mx.operator.CustomOp):
def __init__(self):
super(AdditionOP, self).__init__()
def forward(self, is_train, req, in_data, out_data, aux):
out_data[0][:] = in_data[0] + in_data[1]
def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
in_grad[0][:] = out_grad[0]
in_grad[1][:] = out_grad[0]
@mx.operator.register("AdditionOP")
class AdditionOPProp(mx.operator.CustomOpProp):
def __init__(self):
super(AdditionOPProp, self).__init__()
def list_arguments(self):
return ['a', 'b']
def list_outputs(self):
return ['output']
def infer_shape(self, in_shape):
return in_shape, [in_shape[0]]
def create_operator(self, ctx, shapes, dtypes):
return AdditionOP()
def foo():
a = mx.nd.array([1, 2, 3])
b = mx.nd.array([4, 5, 6])
a.attach_grad()
b.attach_grad()
print("REC")
with mx.autograd.record():
c = mx.nd.Custom(a, b, op_type='AdditionOP')
dc = mx.nd.array([7, 8, 9])
c.backward(dc)
print('Okay :-)')
print('a + b = c \n {} + {} = {}'.format(a.asnumpy(), b.asnumpy(),
c.asnumpy()))
def main():
foo() # ensure custom threads created in main process
ex = futures.ProcessPoolExecutor(1)
r = ex.submit(foo)
r.result()
if __name__ == '__main__':
main()
```
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[GitHub] [incubator-mxnet] arcadiaphy edited a comment on issue #14396: mx.nd.Custom not working in subprocess
arcadiaphy edited a comment on issue #14396: mx.nd.Custom not working in
subprocess
URL:
https://github.com/apache/incubator-mxnet/issues/14396#issuecomment-473577236
After #14363, the threads in custom is created after running first custom
operator, so custom operator needs also to be executed in main process to
reproduce the bug:
```
from concurrent import futures
import mxnet as mx
import sys
class AdditionOP(mx.operator.CustomOp):
def __init__(self):
super(AdditionOP, self).__init__()
def forward(self, is_train, req, in_data, out_data, aux):
out_data[0][:] = in_data[0] + in_data[1]
def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
in_grad[0][:] = out_grad[0]
in_grad[1][:] = out_grad[0]
@mx.operator.register("AdditionOP")
class AdditionOPProp(mx.operator.CustomOpProp):
def __init__(self):
super(AdditionOPProp, self).__init__()
def list_arguments(self):
return ['a', 'b']
def list_outputs(self):
return ['output']
def infer_shape(self, in_shape):
return in_shape, [in_shape[0]]
def create_operator(self, ctx, shapes, dtypes):
return AdditionOP()
def foo():
a = mx.nd.array([1, 2, 3])
b = mx.nd.array([4, 5, 6])
a.attach_grad()
b.attach_grad()
print("REC")
with mx.autograd.record():
c = mx.nd.Custom(a, b, op_type='AdditionOP')
dc = mx.nd.array([7, 8, 9])
c.backward(dc)
print('Okay :-)')
print('a + b = c \n {} + {} = {}'.format(a.asnumpy(), b.asnumpy(),
c.asnumpy()))
def main():
# ensure custom threads created in main process
foo()
ex = futures.ProcessPoolExecutor(1)
r = ex.submit(foo)
r.result()
if __name__ == '__main__':
main()
```
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[GitHub] [incubator-mxnet] arcadiaphy edited a comment on issue #14396: mx.nd.Custom not working in subprocess
arcadiaphy edited a comment on issue #14396: mx.nd.Custom not working in
subprocess
URL:
https://github.com/apache/incubator-mxnet/issues/14396#issuecomment-473577236
After #14363, the threads in custom is created after running first custom
operator, so custom operator needs also to be executed in main process to
reproduce the bug:
```
from concurrent import futures
import mxnet as mx
import sys
class AdditionOP(mx.operator.CustomOp):
def __init__(self):
super(AdditionOP, self).__init__()
def forward(self, is_train, req, in_data, out_data, aux):
out_data[0][:] = in_data[0] + in_data[1]
def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
in_grad[0][:] = out_grad[0]
in_grad[1][:] = out_grad[0]
@mx.operator.register("AdditionOP")
class AdditionOPProp(mx.operator.CustomOpProp):
def __init__(self):
super(AdditionOPProp, self).__init__()
def list_arguments(self):
return ['a', 'b']
def list_outputs(self):
return ['output']
def infer_shape(self, in_shape):
return in_shape, [in_shape[0]]
def create_operator(self, ctx, shapes, dtypes):
return AdditionOP()
def foo():
a = mx.nd.array([1, 2, 3])
b = mx.nd.array([4, 5, 6])
a.attach_grad()
b.attach_grad()
print("REC")
with mx.autograd.record():
c = mx.nd.Custom(a, b, op_type='AdditionOP')
dc = mx.nd.array([7, 8, 9])
c.backward(dc)
print('Okay :-)')
print('a + b = c \n {} + {} = {}'.format(a.asnumpy(), b.asnumpy(),
c.asnumpy()))
def main():
foo() # ensure custom threads created in main process
ex = futures.ProcessPoolExecutor(1)
r = ex.submit(foo)
r.result()
if __name__ == '__main__':
main()
```
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[GitHub] [incubator-mxnet] arcadiaphy opened a new pull request #14451: fix custom operation in fork
arcadiaphy opened a new pull request #14451: fix custom operation in fork URL: https://github.com/apache/incubator-mxnet/pull/14451 ## Description ## Fix #14396. Update pthread_atfork function to properly setup fork in custom operator. ## 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] arcadiaphy edited a comment on issue #14396: mx.nd.Custom not working in subprocess
arcadiaphy edited a comment on issue #14396: mx.nd.Custom not working in
subprocess
URL:
https://github.com/apache/incubator-mxnet/issues/14396#issuecomment-473577236
After #14363, the threads in custom is created after running first custom
operator, the new script to reproduce the bug:
```
from concurrent import futures
import mxnet as mx
import sys
class AdditionOP(mx.operator.CustomOp):
def __init__(self):
super(AdditionOP, self).__init__()
def forward(self, is_train, req, in_data, out_data, aux):
out_data[0][:] = in_data[0] + in_data[1]
def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
in_grad[0][:] = out_grad[0]
in_grad[1][:] = out_grad[0]
@mx.operator.register("AdditionOP")
class AdditionOPProp(mx.operator.CustomOpProp):
def __init__(self):
super(AdditionOPProp, self).__init__()
def list_arguments(self):
return ['a', 'b']
def list_outputs(self):
return ['output']
def infer_shape(self, in_shape):
return in_shape, [in_shape[0]]
def create_operator(self, ctx, shapes, dtypes):
return AdditionOP()
def foo():
a = mx.nd.array([1, 2, 3])
b = mx.nd.array([4, 5, 6])
a.attach_grad()
b.attach_grad()
print("REC")
with mx.autograd.record():
c = mx.nd.Custom(a, b, op_type='AdditionOP')
dc = mx.nd.array([7, 8, 9])
c.backward(dc)
print('Okay :-)')
print('a + b = c \n {} + {} = {}'.format(a.asnumpy(), b.asnumpy(),
c.asnumpy()))
def main():
foo() # ensure threads created in custom
ex = futures.ProcessPoolExecutor(1)
r = ex.submit(foo)
r.result()
if __name__ == '__main__':
main()
```
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[GitHub] [incubator-mxnet] arcadiaphy edited a comment on issue #14396: mx.nd.Custom not working in subprocess
arcadiaphy edited a comment on issue #14396: mx.nd.Custom not working in
subprocess
URL:
https://github.com/apache/incubator-mxnet/issues/14396#issuecomment-473577236
After #14363, the threads in custom is created after running first custom
operator, the new script to reproduce the bug:
```
from concurrent import futures
import mxnet as mx
import sys
class AdditionOP(mx.operator.CustomOp):
def __init__(self):
super(AdditionOP, self).__init__()
def forward(self, is_train, req, in_data, out_data, aux):
out_data[0][:] = in_data[0] + in_data[1]
def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
in_grad[0][:] = out_grad[0]
in_grad[1][:] = out_grad[0]
@mx.operator.register("AdditionOP")
class AdditionOPProp(mx.operator.CustomOpProp):
def __init__(self):
super(AdditionOPProp, self).__init__()
def list_arguments(self):
return ['a', 'b']
def list_outputs(self):
return ['output']
def infer_shape(self, in_shape):
return in_shape, [in_shape[0]]
def create_operator(self, ctx, shapes, dtypes):
return AdditionOP()
def foo():
a = mx.nd.array([1, 2, 3])
b = mx.nd.array([4, 5, 6])
a.attach_grad()
b.attach_grad()
print("REC")
with mx.autograd.record():
c = mx.nd.Custom(a, b, op_type='AdditionOP')
dc = mx.nd.array([7, 8, 9])
c.backward(dc)
print('Okay :-)')
print('a + b = c \n {} + {} = {}'.format(a.asnumpy(), b.asnumpy(),
c.asnumpy()))
def main():
foo() # ensure custom threads created in main process
ex = futures.ProcessPoolExecutor(1)
r = ex.submit(foo)
r.result()
if __name__ == '__main__':
main()
```
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[GitHub] [incubator-mxnet] arcadiaphy commented on issue #14396: mx.nd.Custom not working in subprocess
arcadiaphy commented on issue #14396: mx.nd.Custom not working in subprocess
URL:
https://github.com/apache/incubator-mxnet/issues/14396#issuecomment-473577236
After #14363, the threads in custom is created after running first custom
operator, the new script to reproduce the bug:
```
from concurrent import futures
import mxnet as mx
import sys
class AdditionOP(mx.operator.CustomOp):
def __init__(self):
super(AdditionOP, self).__init__()
def forward(self, is_train, req, in_data, out_data, aux):
out_data[0][:] = in_data[0] + in_data[1]
def backward(self, req, out_grad, in_data, out_data, in_grad, aux):
in_grad[0][:] = out_grad[0]
in_grad[1][:] = out_grad[0]
@mx.operator.register("AdditionOP")
class AdditionOPProp(mx.operator.CustomOpProp):
def __init__(self):
super(AdditionOPProp, self).__init__()
def list_arguments(self):
return ['a', 'b']
def list_outputs(self):
return ['output']
def infer_shape(self, in_shape):
return in_shape, [in_shape[0]]
def create_operator(self, ctx, shapes, dtypes):
return AdditionOP()
def foo():
a = mx.nd.array([1, 2, 3])
b = mx.nd.array([4, 5, 6])
a.attach_grad()
b.attach_grad()
print("REC")
with mx.autograd.record():
c = mx.nd.Custom(a, b, op_type='AdditionOP')
dc = mx.nd.array([7, 8, 9])
c.backward(dc)
print('Okay :-)')
print('a + b = c \n {} + {} = {}'.format(a.asnumpy(), b.asnumpy(),
c.asnumpy()))
def main():
foo()
ex = futures.ProcessPoolExecutor(1)
r = ex.submit(foo)
r.result()
if __name__ == '__main__':
main()
```
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[incubator-mxnet-site] branch asf-site updated: Bump the publish timestamp.
This is an automated email from the ASF dual-hosted git repository. zhasheng pushed a commit to branch asf-site in repository https://gitbox.apache.org/repos/asf/incubator-mxnet-site.git The following commit(s) were added to refs/heads/asf-site by this push: new 37f583f Bump the publish timestamp. 37f583f is described below commit 37f583ffce1afadb5366a445170f633ac301ea22 Author: mxnet-ci AuthorDate: Sat Mar 16 19:17:17 2019 + Bump the publish timestamp. --- date.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/date.txt b/date.txt new file mode 100644 index 000..d9d3993 --- /dev/null +++ b/date.txt @@ -0,0 +1 @@ +Sat Mar 16 19:17:17 UTC 2019
[GitHub] [incubator-mxnet] vandanavk commented on issue #14035: Fix documentation for bilinear upsampling and add unit test
vandanavk commented on issue #14035: Fix documentation for bilinear upsampling and add unit test URL: https://github.com/apache/incubator-mxnet/pull/14035#issuecomment-473574788 @mxnet-label-bot update [Operator, pr-awaiting-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] seujung commented on a change in pull request #13735: update wavenet codes
seujung commented on a change in pull request #13735: update wavenet codes
URL: https://github.com/apache/incubator-mxnet/pull/13735#discussion_r265847269
##
File path: example/gluon/wavenet/models.py
##
@@ -0,0 +1,118 @@
+
+# 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.
+
+"""
+Module: WaveNet network modulep
+"""
+from mxnet import nd
+from mxnet.gluon import nn
+import mxnet.ndarray as F
+# pylint: disable=invalid-name, too-many-arguments, arguments-differ,
attribute-defined-outside-init, too-many-instance-attributes,
invalid-sequence-index, no-self-use
+class One_Hot(nn.Block):
+"""
+Description : generate one hot result
+"""
+def __init__(self, depth):
+super(One_Hot, self).__init__()
+self.depth = depth
+
+def forward(self, X_in):
+with X_in.context:
+X_in = X_in
+self.ones = nd.one_hot(nd.arange(self.depth), self.depth)
+return self.ones[X_in, :]
+
+def __repr__(self):
+return self.__class__.__name__ + "({})".format(self.depth)
+
+class WaveNet(nn.Block):
Review comment:
update hybrid module for wavenet model
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[GitHub] [incubator-mxnet] seujung commented on a change in pull request #13735: update wavenet codes
seujung commented on a change in pull request #13735: update wavenet codes
URL: https://github.com/apache/incubator-mxnet/pull/13735#discussion_r265847269
##
File path: example/gluon/wavenet/models.py
##
@@ -0,0 +1,118 @@
+
+# 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.
+
+"""
+Module: WaveNet network modulep
+"""
+from mxnet import nd
+from mxnet.gluon import nn
+import mxnet.ndarray as F
+# pylint: disable=invalid-name, too-many-arguments, arguments-differ,
attribute-defined-outside-init, too-many-instance-attributes,
invalid-sequence-index, no-self-use
+class One_Hot(nn.Block):
+"""
+Description : generate one hot result
+"""
+def __init__(self, depth):
+super(One_Hot, self).__init__()
+self.depth = depth
+
+def forward(self, X_in):
+with X_in.context:
+X_in = X_in
+self.ones = nd.one_hot(nd.arange(self.depth), self.depth)
+return self.ones[X_in, :]
+
+def __repr__(self):
+return self.__class__.__name__ + "({})".format(self.depth)
+
+class WaveNet(nn.Block):
Review comment:
I try to change hybridBlock. But this code occurs error.
code : output = F.multiply(F.sigmond(output_sigmoid), F.tanh(output_tanh))
error : Argument data must have NDArray type, but got Symbol
Is there any way to solve this problem?
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[GitHub] [incubator-mxnet] seujung commented on a change in pull request #13735: update wavenet codes
seujung commented on a change in pull request #13735: update wavenet codes
URL: https://github.com/apache/incubator-mxnet/pull/13735#discussion_r265847269
##
File path: example/gluon/wavenet/models.py
##
@@ -0,0 +1,118 @@
+
+# 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.
+
+"""
+Module: WaveNet network modulep
+"""
+from mxnet import nd
+from mxnet.gluon import nn
+import mxnet.ndarray as F
+# pylint: disable=invalid-name, too-many-arguments, arguments-differ,
attribute-defined-outside-init, too-many-instance-attributes,
invalid-sequence-index, no-self-use
+class One_Hot(nn.Block):
+"""
+Description : generate one hot result
+"""
+def __init__(self, depth):
+super(One_Hot, self).__init__()
+self.depth = depth
+
+def forward(self, X_in):
+with X_in.context:
+X_in = X_in
+self.ones = nd.one_hot(nd.arange(self.depth), self.depth)
+return self.ones[X_in, :]
+
+def __repr__(self):
+return self.__class__.__name__ + "({})".format(self.depth)
+
+class WaveNet(nn.Block):
Review comment:
I try to change hybridBlock. #764fa84241344c0ea2721f14a2d81e878150b46e. But
this code occurs error.
code : output = F.multiply(F.sigmond(output_sigmoid), F.tanh(output_tanh))
error : Argument data must have NDArray type, but got Symbol
Is there any way to solve this problem?
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[GitHub] [incubator-mxnet] seujung commented on a change in pull request #13735: update wavenet codes
seujung commented on a change in pull request #13735: update wavenet codes
URL: https://github.com/apache/incubator-mxnet/pull/13735#discussion_r265847269
##
File path: example/gluon/wavenet/models.py
##
@@ -0,0 +1,118 @@
+
+# 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.
+
+"""
+Module: WaveNet network modulep
+"""
+from mxnet import nd
+from mxnet.gluon import nn
+import mxnet.ndarray as F
+# pylint: disable=invalid-name, too-many-arguments, arguments-differ,
attribute-defined-outside-init, too-many-instance-attributes,
invalid-sequence-index, no-self-use
+class One_Hot(nn.Block):
+"""
+Description : generate one hot result
+"""
+def __init__(self, depth):
+super(One_Hot, self).__init__()
+self.depth = depth
+
+def forward(self, X_in):
+with X_in.context:
+X_in = X_in
+self.ones = nd.one_hot(nd.arange(self.depth), self.depth)
+return self.ones[X_in, :]
+
+def __repr__(self):
+return self.__class__.__name__ + "({})".format(self.depth)
+
+class WaveNet(nn.Block):
Review comment:
I try to change hybridBlock. ##13735. But this code occurs error.
code : output = F.multiply(F.sigmond(output_sigmoid), F.tanh(output_tanh))
error : Argument data must have NDArray type, but got Symbol
Is there any way to solve this problem?
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[GitHub] [incubator-mxnet] Bleach665 commented on issue #14378: Win10 build error: gtest, no 'object' file generated
Bleach665 commented on issue #14378: Win10 build error: gtest, no 'object' file generated URL: https://github.com/apache/incubator-mxnet/issues/14378#issuecomment-473545561 I did not make any changes to the code. As for Cmake, I do not remember exactly what changes I made to the configuration, but for sure nothing is critically important. Probably all of these issues were already fixed below or it was depend on VS version (my 2017, you as I understand 2015). 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] stereomatchingkiss commented on issue #14378: Win10 build error: gtest, no 'object' file generated
stereomatchingkiss commented on issue #14378: Win10 build error: gtest, no 'object' file generated URL: https://github.com/apache/incubator-mxnet/issues/14378#issuecomment-473538922 > but I successfully build mxnet with [ed83071](https://github.com/apache/incubator-mxnet/commit/ed8307121ecb7d7f0717ccd080848f5b16dcf191) It is a good news if you can build it on windows. How do you solve the issues of #13958 and #14343? I can build mxnet with mkl too, problems is it always throw exception at runtime if you do the inference task by cpu. ed83071 is a bit newer than 1.4.0, wonder if they fix the build issues on windows already?I am still waiting next stable release. 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] stereomatchingkiss edited a comment on issue #14378: Win10 build error: gtest, no 'object' file generated
stereomatchingkiss edited a comment on issue #14378: Win10 build error: gtest, no 'object' file generated URL: https://github.com/apache/incubator-mxnet/issues/14378#issuecomment-473538922 > but I successfully build mxnet with [ed83071](https://github.com/apache/incubator-mxnet/commit/ed8307121ecb7d7f0717ccd080848f5b16dcf191) It is a good news if you can build it on windows. How do you solve the issues of #13958 and #14343? I can build mxnet(1.3.1) with mkl too, problems is it always throw exception at runtime if you do the inference task by cpu(by gpu is fine). ed83071 is a bit newer than 1.4.0, wonder if they fix the build issues on windows already?I am still waiting next stable release. 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] stereomatchingkiss edited a comment on issue #14378: Win10 build error: gtest, no 'object' file generated
stereomatchingkiss edited a comment on issue #14378: Win10 build error: gtest, no 'object' file generated URL: https://github.com/apache/incubator-mxnet/issues/14378#issuecomment-473538922 > but I successfully build mxnet with [ed83071](https://github.com/apache/incubator-mxnet/commit/ed8307121ecb7d7f0717ccd080848f5b16dcf191) It is a good news if you can build it on windows. How do you solve the issues of #13958 and #14343? I can build mxnet with mkl too, problems is it always throw exception at runtime if you do the inference task by cpu(by gpu is fine). ed83071 is a bit newer than 1.4.0, wonder if they fix the build issues on windows already?I am still waiting next stable release. 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] Bleach665 edited a comment on issue #14378: Win10 build error: gtest, no 'object' file generated
Bleach665 edited a comment on issue #14378: Win10 build error: gtest, no 'object' file generated URL: https://github.com/apache/incubator-mxnet/issues/14378#issuecomment-473535906 @stereomatchingkiss , but I successfully build mxnet with ed8307121ecb7d7f0717ccd080848f5b16dcf191 rev. With mkl, mkl blas, cuda, cudnn, opencv... However, I have not used it yet. Is it possible that the bugs will appear when it will be used? And thanks for the great guide. PS. Gtest I skip during the build. 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] Bleach665 commented on issue #14378: Win10 build error: gtest, no 'object' file generated
Bleach665 commented on issue #14378: Win10 build error: gtest, no 'object' file generated URL: https://github.com/apache/incubator-mxnet/issues/14378#issuecomment-473535906 @stereomatchingkiss , but I successfully build mxnet with ed8307121ecb7d7f0717ccd080848f5b16dcf191 rev. With mkl, mkl blas, cuda, cudnn, opencv... However, I have not used it yet. Is it possible that the bugs will appear when it will be used? And thanks for the great guide. 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] stereomatchingkiss commented on issue #14378: Win10 build error: gtest, no 'object' file generated
stereomatchingkiss commented on issue #14378: Win10 build error: gtest, no 'object' file generated URL: https://github.com/apache/incubator-mxnet/issues/14378#issuecomment-473531466 > > > Yes, --recursive flag was used. > And just now I did reproduce this bug on another computer with same software. Don't try to build mxnet1.4.0, it is broken, I suggest you build mxnet1.3.1, it is still broken on windows 10, but unless with a lot of efforts, you can build it. Please check this [blog ](http://qtandopencv.blogspot.com/2019/03/build-mxnet-131-on-windows.html)if you want to know how to build mxnet1.3.1 on windows. 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-site] branch asf-site updated: Bump the publish timestamp.
This is an automated email from the ASF dual-hosted git repository. zhasheng pushed a commit to branch asf-site in repository https://gitbox.apache.org/repos/asf/incubator-mxnet-site.git The following commit(s) were added to refs/heads/asf-site by this push: new e3f0727 Bump the publish timestamp. e3f0727 is described below commit e3f07274a70452573e245d7fa0392382bcdcfdc4 Author: mxnet-ci AuthorDate: Sat Mar 16 13:18:04 2019 + Bump the publish timestamp. --- date.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/date.txt b/date.txt new file mode 100644 index 000..77537c8 --- /dev/null +++ b/date.txt @@ -0,0 +1 @@ +Sat Mar 16 13:18:04 UTC 2019
[GitHub] [incubator-mxnet] pengzhao-intel commented on issue #13668: Update MKL-DNN to v0.18 release (was: fix the Dense layer issue)
pengzhao-intel commented on issue #13668: Update MKL-DNN to v0.18 release (was: fix the Dense layer issue) URL: https://github.com/apache/incubator-mxnet/pull/13668#issuecomment-473521118 It's great that all CI passed. @wkcn @szha please help confirm all concerns are resolved. We will merge the PR in 24 hours in case there's no further concern. 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] chinakook commented on issue #14443: Mxnet allclose
chinakook commented on issue #14443: Mxnet allclose URL: https://github.com/apache/incubator-mxnet/pull/14443#issuecomment-473520075 It this op only support float32? 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] ZhennanQin commented on a change in pull request #14277: Enhance PartitionGraph
ZhennanQin commented on a change in pull request #14277: Enhance PartitionGraph URL: https://github.com/apache/incubator-mxnet/pull/14277#discussion_r266196192 ## File path: src/operator/subgraph/subgraph_property.h ## @@ -200,7 +197,7 @@ typedef dmlc::ThreadLocalStore__REGISTER_OR_GET__(#Name, &SubgraphPropertyType::Create) +SubgraphPropertyRegistry::Get()->__REGISTER__(#Name, &SubgraphPropertyType::Create) Review comment: @anirudh2290 Putting MXNET_REGISTER_SUBGRAPH_PROPERTY in header file is not a good usecase. If developer include that header twice, then I think he just wants to register that properties twice for same backend. I admited this may cause misleading if developer doesn't know the details behind MXNET_REGISTER_SUBGRAPH_PROPERTY . But I have no idea how to avoid this. Do you have any good suggestion? Please consider the requirement I listed in previous comment. 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 #14361: [numpy] Add a global switch to turn on/off numpy compatibility
wkcn edited a comment on issue #14361: [numpy] Add a global switch to turn on/off numpy compatibility URL: https://github.com/apache/incubator-mxnet/pull/14361#issuecomment-473513487 In my opinion, we can not use the switch. Instead, We can add a typecast from an 1-size NDArray to a scalar. 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 #14361: [numpy] Add a global switch to turn on/off numpy compatibility
wkcn commented on issue #14361: [numpy] Add a global switch to turn on/off numpy compatibility URL: https://github.com/apache/incubator-mxnet/pull/14361#issuecomment-473513487 In my opinion, we can not use the switch. Instead, We can add a typecast from 0-shape NDArray to a scalar. 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] wuxun-zhang commented on issue #14286: Add examples of running MXNet with Horovod
wuxun-zhang commented on issue #14286: Add examples of running MXNet with Horovod URL: https://github.com/apache/incubator-mxnet/pull/14286#issuecomment-473513431 @apeforest There are no problem when building Horovod from source. Just want to verify if Horovod PyPi package can also work well. @yuxihu I have tried the lastest MXNet with this [commit](https://github.com/apache/incubator-mxnet/commit/226212b40b5b1a43a3d91d3a810541887beaae8c). When I `import horovod.mxnet as hvd`, still got the error `undefined symbol`. Did you run this example successfully on CPU? If so, can you tell me what's your building command for MXNet without mkldnn? Thanks in advance. 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-site] branch asf-site updated: Bump the publish timestamp.
This is an automated email from the ASF dual-hosted git repository. zhasheng pushed a commit to branch asf-site in repository https://gitbox.apache.org/repos/asf/incubator-mxnet-site.git The following commit(s) were added to refs/heads/asf-site by this push: new aaa0c9e Bump the publish timestamp. aaa0c9e is described below commit aaa0c9e2eaf945afaef9ba097792d27d8252c852 Author: mxnet-ci AuthorDate: Sat Mar 16 07:22:33 2019 + Bump the publish timestamp. --- date.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/date.txt b/date.txt new file mode 100644 index 000..059b908 --- /dev/null +++ b/date.txt @@ -0,0 +1 @@ +Sat Mar 16 07:22:33 UTC 2019
