[incubator-mxnet] 09/42: Change np_compat to np_shape
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
commit fd0cb053e253cbf2d0cd498f79dec96ba30fe155
Author: reminisce
AuthorDate: Sun May 26 22:41:28 2019 -0700
Change np_compat to np_shape
---
python/mxnet/gluon/block.py | 2 +-
python/mxnet/gluon/parameter.py | 10 +-
python/mxnet/gluon/utils.py | 1 +
python/mxnet/ndarray/numpy/_op.py | 3 +--
python/mxnet/ndarray/register.py| 4 ++--
python/mxnet/numpy/__init__.py | 2 +-
python/mxnet/numpy/multiarray.py| 8 +++-
tests/python/unittest/test_numpy_gluon.py | 6 +++---
tests/python/unittest/test_numpy_ndarray.py | 20 ++--
tests/python/unittest/test_numpy_op.py | 16
10 files changed, 35 insertions(+), 37 deletions(-)
diff --git a/python/mxnet/gluon/block.py b/python/mxnet/gluon/block.py
index 807f160..1362891 100644
--- a/python/mxnet/gluon/block.py
+++ b/python/mxnet/gluon/block.py
@@ -551,7 +551,7 @@ class Block(object):
for hook in self._forward_hooks.values():
hook(self, args, out)
-if _mx_np.is_np_compat():
+if _mx_np.is_np_shape():
_check_all_np_ndarrays(_flatten(out, "output")[0])
return out
diff --git a/python/mxnet/gluon/parameter.py b/python/mxnet/gluon/parameter.py
index 307fb15..2d3e8c0 100644
--- a/python/mxnet/gluon/parameter.py
+++ b/python/mxnet/gluon/parameter.py
@@ -31,7 +31,7 @@ from .. import symbol, ndarray, initializer, context
from ..context import Context, cpu
from .. import autograd
from .utils import _indent, _brief_print_list, shape_is_known
-from .. import is_np_shape
+from ..util import is_np_shape
# pylint: disable= invalid-name
tensor_types = (symbol.Symbol, ndarray.NDArray)
@@ -188,7 +188,7 @@ class Parameter(object):
if self._shape is None:
self._shape = new_shape
return
-unknown_dim_size = -1 if is_np_compat() else 0
+unknown_dim_size = -1 if is_np_shape() else 0
assert len(self._shape) == len(new_shape) and \
all(j in (unknown_dim_size, i) for i, j in zip(new_shape,
self._shape)), \
"Expected shape %s is incompatible with given shape %s."%(
@@ -330,7 +330,7 @@ class Parameter(object):
initializer.create(default_init)(
initializer.InitDesc(self.name, {'__init__': init}), data)
# TODO(junwu): use np random operators when available
-if is_np_compat():
+if is_np_shape():
data = data.as_np_ndarray() # convert to np.ndarray
self._init_impl(data, ctx)
@@ -357,7 +357,7 @@ class Parameter(object):
self._grad = [ndarray.zeros(shape=i.shape, dtype=i.dtype,
ctx=i.context,
stype=self._grad_stype) for i in
self._data]
# TODO(junwu): use np.zeros
-if is_np_compat():
+if is_np_shape():
self._grad = [arr.as_np_ndarray() for arr in self._grad]
autograd.mark_variables(self._check_and_get(self._data, list),
@@ -606,7 +606,7 @@ class Parameter(object):
self._var = symbol.var(self.name, shape=self.shape,
dtype=self.dtype,
lr_mult=self.lr_mult, wd_mult=self.wd_mult,
init=self.init, stype=self._stype)
-if is_np_compat():
+if is_np_shape():
self._var = self._var.as_np_ndarray()
return self._var
diff --git a/python/mxnet/gluon/utils.py b/python/mxnet/gluon/utils.py
index acfcce2..b21e06d 100644
--- a/python/mxnet/gluon/utils.py
+++ b/python/mxnet/gluon/utils.py
@@ -40,6 +40,7 @@ import numpy as np
from .. import ndarray
from ..util import is_np_shape
+
def split_data(data, num_slice, batch_axis=0, even_split=True):
"""Splits an NDArray into `num_slice` slices along `batch_axis`.
Usually used for data parallelism where each slices is sent
diff --git a/python/mxnet/ndarray/numpy/_op.py
b/python/mxnet/ndarray/numpy/_op.py
index 725fba4..72b890d 100644
--- a/python/mxnet/ndarray/numpy/_op.py
+++ b/python/mxnet/ndarray/numpy/_op.py
@@ -20,7 +20,7 @@
from __future__ import absolute_import
import numpy as _np
from ...base import numeric_types
-from ...util import _sanity_check_params, use_np_compat, set_module
+from ...util import _sanity_check_params, set_module
from ...context import current_context
from . import _internal as _npi
@@ -90,7 +90,6 @@ def ones(shape, dtype=None, **kwargs):
#pylint: disable= too-many-arguments, no-member, protected-access
-@use_np_compat
def _ufunc_helper(lhs, rhs, fn_array, fn_scalar, lfn_scalar, rfn_scalar=None,
out=None):
""" Helper function for element-wise operation.
The function will
[incubator-mxnet] 09/42: Change np_compat to np_shape
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
commit b888e4c40aaa3b618cef9393c18cb9de2516bb93
Author: reminisce
AuthorDate: Sun May 26 22:41:28 2019 -0700
Change np_compat to np_shape
---
python/mxnet/gluon/block.py | 2 +-
python/mxnet/gluon/parameter.py | 10 +-
python/mxnet/gluon/utils.py | 1 +
python/mxnet/ndarray/numpy/_op.py | 3 +--
python/mxnet/ndarray/register.py| 4 ++--
python/mxnet/numpy/__init__.py | 2 +-
python/mxnet/numpy/multiarray.py| 8 +++-
tests/python/unittest/test_numpy_gluon.py | 6 +++---
tests/python/unittest/test_numpy_ndarray.py | 20 ++--
tests/python/unittest/test_numpy_op.py | 16
10 files changed, 35 insertions(+), 37 deletions(-)
diff --git a/python/mxnet/gluon/block.py b/python/mxnet/gluon/block.py
index 807f160..1362891 100644
--- a/python/mxnet/gluon/block.py
+++ b/python/mxnet/gluon/block.py
@@ -551,7 +551,7 @@ class Block(object):
for hook in self._forward_hooks.values():
hook(self, args, out)
-if _mx_np.is_np_compat():
+if _mx_np.is_np_shape():
_check_all_np_ndarrays(_flatten(out, "output")[0])
return out
diff --git a/python/mxnet/gluon/parameter.py b/python/mxnet/gluon/parameter.py
index 307fb15..2d3e8c0 100644
--- a/python/mxnet/gluon/parameter.py
+++ b/python/mxnet/gluon/parameter.py
@@ -31,7 +31,7 @@ from .. import symbol, ndarray, initializer, context
from ..context import Context, cpu
from .. import autograd
from .utils import _indent, _brief_print_list, shape_is_known
-from .. import is_np_shape
+from ..util import is_np_shape
# pylint: disable= invalid-name
tensor_types = (symbol.Symbol, ndarray.NDArray)
@@ -188,7 +188,7 @@ class Parameter(object):
if self._shape is None:
self._shape = new_shape
return
-unknown_dim_size = -1 if is_np_compat() else 0
+unknown_dim_size = -1 if is_np_shape() else 0
assert len(self._shape) == len(new_shape) and \
all(j in (unknown_dim_size, i) for i, j in zip(new_shape,
self._shape)), \
"Expected shape %s is incompatible with given shape %s."%(
@@ -330,7 +330,7 @@ class Parameter(object):
initializer.create(default_init)(
initializer.InitDesc(self.name, {'__init__': init}), data)
# TODO(junwu): use np random operators when available
-if is_np_compat():
+if is_np_shape():
data = data.as_np_ndarray() # convert to np.ndarray
self._init_impl(data, ctx)
@@ -357,7 +357,7 @@ class Parameter(object):
self._grad = [ndarray.zeros(shape=i.shape, dtype=i.dtype,
ctx=i.context,
stype=self._grad_stype) for i in
self._data]
# TODO(junwu): use np.zeros
-if is_np_compat():
+if is_np_shape():
self._grad = [arr.as_np_ndarray() for arr in self._grad]
autograd.mark_variables(self._check_and_get(self._data, list),
@@ -606,7 +606,7 @@ class Parameter(object):
self._var = symbol.var(self.name, shape=self.shape,
dtype=self.dtype,
lr_mult=self.lr_mult, wd_mult=self.wd_mult,
init=self.init, stype=self._stype)
-if is_np_compat():
+if is_np_shape():
self._var = self._var.as_np_ndarray()
return self._var
diff --git a/python/mxnet/gluon/utils.py b/python/mxnet/gluon/utils.py
index acfcce2..b21e06d 100644
--- a/python/mxnet/gluon/utils.py
+++ b/python/mxnet/gluon/utils.py
@@ -40,6 +40,7 @@ import numpy as np
from .. import ndarray
from ..util import is_np_shape
+
def split_data(data, num_slice, batch_axis=0, even_split=True):
"""Splits an NDArray into `num_slice` slices along `batch_axis`.
Usually used for data parallelism where each slices is sent
diff --git a/python/mxnet/ndarray/numpy/_op.py
b/python/mxnet/ndarray/numpy/_op.py
index 725fba4..72b890d 100644
--- a/python/mxnet/ndarray/numpy/_op.py
+++ b/python/mxnet/ndarray/numpy/_op.py
@@ -20,7 +20,7 @@
from __future__ import absolute_import
import numpy as _np
from ...base import numeric_types
-from ...util import _sanity_check_params, use_np_compat, set_module
+from ...util import _sanity_check_params, set_module
from ...context import current_context
from . import _internal as _npi
@@ -90,7 +90,6 @@ def ones(shape, dtype=None, **kwargs):
#pylint: disable= too-many-arguments, no-member, protected-access
-@use_np_compat
def _ufunc_helper(lhs, rhs, fn_array, fn_scalar, lfn_scalar, rfn_scalar=None,
out=None):
""" Helper function for element-wise operation.
The function will
[incubator-mxnet] 09/42: Change np_compat to np_shape
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
commit d8b075adaa9ed8da4f0ffce1b066e14dc9feeae9
Author: reminisce
AuthorDate: Sun May 26 22:41:28 2019 -0700
Change np_compat to np_shape
---
python/mxnet/gluon/block.py | 2 +-
python/mxnet/gluon/parameter.py | 10 +-
python/mxnet/gluon/utils.py | 1 +
python/mxnet/ndarray/numpy/_op.py | 3 +--
python/mxnet/ndarray/register.py| 4 ++--
python/mxnet/numpy/__init__.py | 2 +-
python/mxnet/numpy/multiarray.py| 8 +++-
tests/python/unittest/test_numpy_gluon.py | 6 +++---
tests/python/unittest/test_numpy_ndarray.py | 20 ++--
tests/python/unittest/test_numpy_op.py | 16
10 files changed, 35 insertions(+), 37 deletions(-)
diff --git a/python/mxnet/gluon/block.py b/python/mxnet/gluon/block.py
index 807f160..1362891 100644
--- a/python/mxnet/gluon/block.py
+++ b/python/mxnet/gluon/block.py
@@ -551,7 +551,7 @@ class Block(object):
for hook in self._forward_hooks.values():
hook(self, args, out)
-if _mx_np.is_np_compat():
+if _mx_np.is_np_shape():
_check_all_np_ndarrays(_flatten(out, "output")[0])
return out
diff --git a/python/mxnet/gluon/parameter.py b/python/mxnet/gluon/parameter.py
index 307fb15..2d3e8c0 100644
--- a/python/mxnet/gluon/parameter.py
+++ b/python/mxnet/gluon/parameter.py
@@ -31,7 +31,7 @@ from .. import symbol, ndarray, initializer, context
from ..context import Context, cpu
from .. import autograd
from .utils import _indent, _brief_print_list, shape_is_known
-from .. import is_np_shape
+from ..util import is_np_shape
# pylint: disable= invalid-name
tensor_types = (symbol.Symbol, ndarray.NDArray)
@@ -188,7 +188,7 @@ class Parameter(object):
if self._shape is None:
self._shape = new_shape
return
-unknown_dim_size = -1 if is_np_compat() else 0
+unknown_dim_size = -1 if is_np_shape() else 0
assert len(self._shape) == len(new_shape) and \
all(j in (unknown_dim_size, i) for i, j in zip(new_shape,
self._shape)), \
"Expected shape %s is incompatible with given shape %s."%(
@@ -330,7 +330,7 @@ class Parameter(object):
initializer.create(default_init)(
initializer.InitDesc(self.name, {'__init__': init}), data)
# TODO(junwu): use np random operators when available
-if is_np_compat():
+if is_np_shape():
data = data.as_np_ndarray() # convert to np.ndarray
self._init_impl(data, ctx)
@@ -357,7 +357,7 @@ class Parameter(object):
self._grad = [ndarray.zeros(shape=i.shape, dtype=i.dtype,
ctx=i.context,
stype=self._grad_stype) for i in
self._data]
# TODO(junwu): use np.zeros
-if is_np_compat():
+if is_np_shape():
self._grad = [arr.as_np_ndarray() for arr in self._grad]
autograd.mark_variables(self._check_and_get(self._data, list),
@@ -606,7 +606,7 @@ class Parameter(object):
self._var = symbol.var(self.name, shape=self.shape,
dtype=self.dtype,
lr_mult=self.lr_mult, wd_mult=self.wd_mult,
init=self.init, stype=self._stype)
-if is_np_compat():
+if is_np_shape():
self._var = self._var.as_np_ndarray()
return self._var
diff --git a/python/mxnet/gluon/utils.py b/python/mxnet/gluon/utils.py
index acfcce2..b21e06d 100644
--- a/python/mxnet/gluon/utils.py
+++ b/python/mxnet/gluon/utils.py
@@ -40,6 +40,7 @@ import numpy as np
from .. import ndarray
from ..util import is_np_shape
+
def split_data(data, num_slice, batch_axis=0, even_split=True):
"""Splits an NDArray into `num_slice` slices along `batch_axis`.
Usually used for data parallelism where each slices is sent
diff --git a/python/mxnet/ndarray/numpy/_op.py
b/python/mxnet/ndarray/numpy/_op.py
index 725fba4..72b890d 100644
--- a/python/mxnet/ndarray/numpy/_op.py
+++ b/python/mxnet/ndarray/numpy/_op.py
@@ -20,7 +20,7 @@
from __future__ import absolute_import
import numpy as _np
from ...base import numeric_types
-from ...util import _sanity_check_params, use_np_compat, set_module
+from ...util import _sanity_check_params, set_module
from ...context import current_context
from . import _internal as _npi
@@ -90,7 +90,6 @@ def ones(shape, dtype=None, **kwargs):
#pylint: disable= too-many-arguments, no-member, protected-access
-@use_np_compat
def _ufunc_helper(lhs, rhs, fn_array, fn_scalar, lfn_scalar, rfn_scalar=None,
out=None):
""" Helper function for element-wise operation.
The function will
[incubator-mxnet] 09/42: Change np_compat to np_shape
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
commit 8b1a03103b66dcf9e4f0198ef410680333cf28e5
Author: reminisce
AuthorDate: Sun May 26 22:41:28 2019 -0700
Change np_compat to np_shape
---
python/mxnet/gluon/block.py | 2 +-
python/mxnet/gluon/parameter.py | 10 +-
python/mxnet/gluon/utils.py | 1 +
python/mxnet/ndarray/numpy/_op.py | 3 +--
python/mxnet/ndarray/register.py| 4 ++--
python/mxnet/numpy/__init__.py | 2 +-
python/mxnet/numpy/multiarray.py| 8 +++-
tests/python/unittest/test_numpy_gluon.py | 6 +++---
tests/python/unittest/test_numpy_ndarray.py | 20 ++--
tests/python/unittest/test_numpy_op.py | 16
10 files changed, 35 insertions(+), 37 deletions(-)
diff --git a/python/mxnet/gluon/block.py b/python/mxnet/gluon/block.py
index 2f07950..2877d3b 100644
--- a/python/mxnet/gluon/block.py
+++ b/python/mxnet/gluon/block.py
@@ -551,7 +551,7 @@ class Block(object):
for hook in self._forward_hooks.values():
hook(self, args, out)
-if _mx_np.is_np_compat():
+if _mx_np.is_np_shape():
_check_all_np_ndarrays(_flatten(out, "output")[0])
return out
diff --git a/python/mxnet/gluon/parameter.py b/python/mxnet/gluon/parameter.py
index 307fb15..2d3e8c0 100644
--- a/python/mxnet/gluon/parameter.py
+++ b/python/mxnet/gluon/parameter.py
@@ -31,7 +31,7 @@ from .. import symbol, ndarray, initializer, context
from ..context import Context, cpu
from .. import autograd
from .utils import _indent, _brief_print_list, shape_is_known
-from .. import is_np_shape
+from ..util import is_np_shape
# pylint: disable= invalid-name
tensor_types = (symbol.Symbol, ndarray.NDArray)
@@ -188,7 +188,7 @@ class Parameter(object):
if self._shape is None:
self._shape = new_shape
return
-unknown_dim_size = -1 if is_np_compat() else 0
+unknown_dim_size = -1 if is_np_shape() else 0
assert len(self._shape) == len(new_shape) and \
all(j in (unknown_dim_size, i) for i, j in zip(new_shape,
self._shape)), \
"Expected shape %s is incompatible with given shape %s."%(
@@ -330,7 +330,7 @@ class Parameter(object):
initializer.create(default_init)(
initializer.InitDesc(self.name, {'__init__': init}), data)
# TODO(junwu): use np random operators when available
-if is_np_compat():
+if is_np_shape():
data = data.as_np_ndarray() # convert to np.ndarray
self._init_impl(data, ctx)
@@ -357,7 +357,7 @@ class Parameter(object):
self._grad = [ndarray.zeros(shape=i.shape, dtype=i.dtype,
ctx=i.context,
stype=self._grad_stype) for i in
self._data]
# TODO(junwu): use np.zeros
-if is_np_compat():
+if is_np_shape():
self._grad = [arr.as_np_ndarray() for arr in self._grad]
autograd.mark_variables(self._check_and_get(self._data, list),
@@ -606,7 +606,7 @@ class Parameter(object):
self._var = symbol.var(self.name, shape=self.shape,
dtype=self.dtype,
lr_mult=self.lr_mult, wd_mult=self.wd_mult,
init=self.init, stype=self._stype)
-if is_np_compat():
+if is_np_shape():
self._var = self._var.as_np_ndarray()
return self._var
diff --git a/python/mxnet/gluon/utils.py b/python/mxnet/gluon/utils.py
index a1c1e5b..ea5d242 100644
--- a/python/mxnet/gluon/utils.py
+++ b/python/mxnet/gluon/utils.py
@@ -40,6 +40,7 @@ import numpy as np
from .. import ndarray
from ..util import is_np_shape
+
def split_data(data, num_slice, batch_axis=0, even_split=True):
"""Splits an NDArray into `num_slice` slices along `batch_axis`.
Usually used for data parallelism where each slices is sent
diff --git a/python/mxnet/ndarray/numpy/_op.py
b/python/mxnet/ndarray/numpy/_op.py
index 725fba4..72b890d 100644
--- a/python/mxnet/ndarray/numpy/_op.py
+++ b/python/mxnet/ndarray/numpy/_op.py
@@ -20,7 +20,7 @@
from __future__ import absolute_import
import numpy as _np
from ...base import numeric_types
-from ...util import _sanity_check_params, use_np_compat, set_module
+from ...util import _sanity_check_params, set_module
from ...context import current_context
from . import _internal as _npi
@@ -90,7 +90,6 @@ def ones(shape, dtype=None, **kwargs):
#pylint: disable= too-many-arguments, no-member, protected-access
-@use_np_compat
def _ufunc_helper(lhs, rhs, fn_array, fn_scalar, lfn_scalar, rfn_scalar=None,
out=None):
""" Helper function for element-wise operation.
The function will
[incubator-mxnet] 09/42: Change np_compat to np_shape
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
commit 3712ba04cd5c0974f2c9839451d9852ee88b88a6
Author: reminisce
AuthorDate: Sun May 26 22:41:28 2019 -0700
Change np_compat to np_shape
---
python/mxnet/gluon/block.py | 2 +-
python/mxnet/gluon/parameter.py | 10 +-
python/mxnet/gluon/utils.py | 1 +
python/mxnet/ndarray/numpy/_op.py | 3 +--
python/mxnet/ndarray/register.py| 4 ++--
python/mxnet/numpy/__init__.py | 2 +-
python/mxnet/numpy/multiarray.py| 8 +++-
tests/python/unittest/test_numpy_gluon.py | 6 +++---
tests/python/unittest/test_numpy_ndarray.py | 20 ++--
tests/python/unittest/test_numpy_op.py | 16
10 files changed, 35 insertions(+), 37 deletions(-)
diff --git a/python/mxnet/gluon/block.py b/python/mxnet/gluon/block.py
index 2f07950..2877d3b 100644
--- a/python/mxnet/gluon/block.py
+++ b/python/mxnet/gluon/block.py
@@ -551,7 +551,7 @@ class Block(object):
for hook in self._forward_hooks.values():
hook(self, args, out)
-if _mx_np.is_np_compat():
+if _mx_np.is_np_shape():
_check_all_np_ndarrays(_flatten(out, "output")[0])
return out
diff --git a/python/mxnet/gluon/parameter.py b/python/mxnet/gluon/parameter.py
index 307fb15..2d3e8c0 100644
--- a/python/mxnet/gluon/parameter.py
+++ b/python/mxnet/gluon/parameter.py
@@ -31,7 +31,7 @@ from .. import symbol, ndarray, initializer, context
from ..context import Context, cpu
from .. import autograd
from .utils import _indent, _brief_print_list, shape_is_known
-from .. import is_np_shape
+from ..util import is_np_shape
# pylint: disable= invalid-name
tensor_types = (symbol.Symbol, ndarray.NDArray)
@@ -188,7 +188,7 @@ class Parameter(object):
if self._shape is None:
self._shape = new_shape
return
-unknown_dim_size = -1 if is_np_compat() else 0
+unknown_dim_size = -1 if is_np_shape() else 0
assert len(self._shape) == len(new_shape) and \
all(j in (unknown_dim_size, i) for i, j in zip(new_shape,
self._shape)), \
"Expected shape %s is incompatible with given shape %s."%(
@@ -330,7 +330,7 @@ class Parameter(object):
initializer.create(default_init)(
initializer.InitDesc(self.name, {'__init__': init}), data)
# TODO(junwu): use np random operators when available
-if is_np_compat():
+if is_np_shape():
data = data.as_np_ndarray() # convert to np.ndarray
self._init_impl(data, ctx)
@@ -357,7 +357,7 @@ class Parameter(object):
self._grad = [ndarray.zeros(shape=i.shape, dtype=i.dtype,
ctx=i.context,
stype=self._grad_stype) for i in
self._data]
# TODO(junwu): use np.zeros
-if is_np_compat():
+if is_np_shape():
self._grad = [arr.as_np_ndarray() for arr in self._grad]
autograd.mark_variables(self._check_and_get(self._data, list),
@@ -606,7 +606,7 @@ class Parameter(object):
self._var = symbol.var(self.name, shape=self.shape,
dtype=self.dtype,
lr_mult=self.lr_mult, wd_mult=self.wd_mult,
init=self.init, stype=self._stype)
-if is_np_compat():
+if is_np_shape():
self._var = self._var.as_np_ndarray()
return self._var
diff --git a/python/mxnet/gluon/utils.py b/python/mxnet/gluon/utils.py
index a1c1e5b..ea5d242 100644
--- a/python/mxnet/gluon/utils.py
+++ b/python/mxnet/gluon/utils.py
@@ -40,6 +40,7 @@ import numpy as np
from .. import ndarray
from ..util import is_np_shape
+
def split_data(data, num_slice, batch_axis=0, even_split=True):
"""Splits an NDArray into `num_slice` slices along `batch_axis`.
Usually used for data parallelism where each slices is sent
diff --git a/python/mxnet/ndarray/numpy/_op.py
b/python/mxnet/ndarray/numpy/_op.py
index 725fba4..72b890d 100644
--- a/python/mxnet/ndarray/numpy/_op.py
+++ b/python/mxnet/ndarray/numpy/_op.py
@@ -20,7 +20,7 @@
from __future__ import absolute_import
import numpy as _np
from ...base import numeric_types
-from ...util import _sanity_check_params, use_np_compat, set_module
+from ...util import _sanity_check_params, set_module
from ...context import current_context
from . import _internal as _npi
@@ -90,7 +90,6 @@ def ones(shape, dtype=None, **kwargs):
#pylint: disable= too-many-arguments, no-member, protected-access
-@use_np_compat
def _ufunc_helper(lhs, rhs, fn_array, fn_scalar, lfn_scalar, rfn_scalar=None,
out=None):
""" Helper function for element-wise operation.
The function will
