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ptrendx pushed a commit to branch v1.6.x
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/v1.6.x by this push:
new 00f169f port shape op to 1.6.x (#16912)
00f169f is described below
commit 00f169f7519e1e416592b68c3dc8ac92362d6d07
Author: Hao Jin <[email protected]>
AuthorDate: Tue Nov 26 09:07:49 2019 -0800
port shape op to 1.6.x (#16912)
---
python/mxnet/ndarray/numpy/_op.py | 40 +++++++++++--
python/mxnet/numpy/multiarray.py | 68 +++++++++++++++++-----
python/mxnet/numpy_dispatch_protocol.py | 1 +
.../python/unittest/test_numpy_interoperability.py | 15 +++--
tests/python/unittest/test_numpy_op.py | 19 ++++++
5 files changed, 119 insertions(+), 24 deletions(-)
diff --git a/python/mxnet/ndarray/numpy/_op.py
b/python/mxnet/ndarray/numpy/_op.py
index ed3d9d8..4ce675a 100644
--- a/python/mxnet/ndarray/numpy/_op.py
+++ b/python/mxnet/ndarray/numpy/_op.py
@@ -28,7 +28,7 @@ from ...context import current_context
from . import _internal as _npi
from ..ndarray import NDArray
-__all__ = ['zeros', 'ones', 'full', 'add', 'subtract', 'multiply', 'divide',
'mod', 'remainder', 'power',
+__all__ = ['shape', 'zeros', 'ones', 'full', 'add', 'subtract', 'multiply',
'divide', 'mod', 'remainder', 'power',
'arctan2', 'sin', 'cos', 'tan', 'sinh', 'cosh', 'tanh', 'log10',
'sqrt', 'cbrt', 'abs',
'absolute', 'exp', 'expm1', 'arcsin', 'arccos', 'arctan', 'sign',
'log', 'degrees', 'log2',
'log1p', 'rint', 'radians', 'reciprocal', 'square', 'negative',
'fix', 'ceil', 'floor',
@@ -41,7 +41,37 @@ __all__ = ['zeros', 'ones', 'full', 'add', 'subtract',
'multiply', 'divide', 'mo
'hsplit', 'rot90', 'einsum', 'true_divide', 'nonzero',
'shares_memory', 'may_share_memory', 'diff']
@set_module('mxnet.ndarray.numpy')
-def zeros(shape, dtype=_np.float32, order='C', ctx=None):
+def shape(a):
+ """
+ Return the shape of an array.
+ Parameters
+ ----------
+ a : array_like
+ Input array.
+ Returns
+ -------
+ shape : tuple of ints
+ The elements of the shape tuple give the lengths of the
+ corresponding array dimensions.
+ See Also
+ --------
+ ndarray.shape : Equivalent array method.
+ Examples
+ --------
+ >>> np.shape(np.eye(3))
+ (3, 3)
+ >>> np.shape([[1, 2]])
+ (1, 2)
+ >>> np.shape([0])
+ (1,)
+ >>> np.shape(0)
+ ()
+ """
+ return a.shape
+
+
+@set_module('mxnet.ndarray.numpy')
+def zeros(shape, dtype=_np.float32, order='C', ctx=None): # pylint:
disable=redefined-outer-name
"""Return a new array of given shape and type, filled with zeros.
This function currently only supports storing multi-dimensional data
in row-major (C-style).
@@ -75,7 +105,7 @@ def zeros(shape, dtype=_np.float32, order='C', ctx=None):
@set_module('mxnet.ndarray.numpy')
-def ones(shape, dtype=_np.float32, order='C', ctx=None):
+def ones(shape, dtype=_np.float32, order='C', ctx=None): # pylint:
disable=redefined-outer-name
"""Return a new array of given shape and type, filled with ones.
This function currently only supports storing multi-dimensional data
in row-major (C-style).
@@ -108,8 +138,9 @@ def ones(shape, dtype=_np.float32, order='C', ctx=None):
return _npi.ones(shape=shape, ctx=ctx, dtype=dtype)
+# pylint: disable=too-many-arguments, redefined-outer-name
@set_module('mxnet.ndarray.numpy')
-def full(shape, fill_value, dtype=None, order='C', ctx=None, out=None): #
pylint: disable=too-many-arguments
+def full(shape, fill_value, dtype=None, order='C', ctx=None, out=None):
"""
Return a new array of given shape and type, filled with `fill_value`.
Parameters
@@ -161,6 +192,7 @@ def full(shape, fill_value, dtype=None, order='C',
ctx=None, out=None): # pylin
ctx = current_context()
dtype = _np.float32 if dtype is None else dtype
return _npi.full(shape=shape, value=fill_value, ctx=ctx, dtype=dtype,
out=out)
+# pylint: enable=too-many-arguments, redefined-outer-name
@set_module('mxnet.ndarray.numpy')
diff --git a/python/mxnet/numpy/multiarray.py b/python/mxnet/numpy/multiarray.py
index ad5fb54..35a549e 100644
--- a/python/mxnet/numpy/multiarray.py
+++ b/python/mxnet/numpy/multiarray.py
@@ -45,7 +45,7 @@ from ..context import current_context
from ..ndarray import numpy as _mx_nd_np
from ..ndarray.numpy import _internal as _npi
-__all__ = ['ndarray', 'empty', 'array', 'zeros', 'ones', 'full', 'add',
'subtract', 'multiply', 'divide',
+__all__ = ['ndarray', 'empty', 'array', 'shape', 'zeros', 'ones', 'full',
'add', 'subtract', 'multiply', 'divide',
'mod', 'remainder', 'power', 'arctan2', 'sin', 'cos', 'tan',
'sinh', 'cosh', 'tanh', 'log10',
'sqrt', 'cbrt', 'abs', 'absolute', 'exp', 'expm1', 'arcsin',
'arccos', 'arctan', 'sign', 'log',
'degrees', 'log2', 'log1p', 'rint', 'radians', 'reciprocal',
'square', 'negative',
@@ -66,7 +66,7 @@ _NDARRAY_ADVANCED_INDEXING = 1
# This function is copied from ndarray.py since pylint
# keeps giving false alarm error of undefined-all-variable
-def _new_alloc_handle(shape, ctx, delay_alloc, dtype=mx_real_t):
+def _new_alloc_handle(shape, ctx, delay_alloc, dtype=mx_real_t): # pylint:
disable=redefined-outer-name
"""Return a new handle with specified shape and context.
Empty handle is only used to hold results.
@@ -88,7 +88,7 @@ def _new_alloc_handle(shape, ctx, delay_alloc,
dtype=mx_real_t):
return hdl
-def _reshape_view(a, *shape):
+def _reshape_view(a, *shape): # pylint: disable=redefined-outer-name
"""Returns a **view** of this array with a new shape without altering any
data.
Parameters
@@ -459,7 +459,7 @@ class ndarray(NDArray):
"""
# handling possible boolean indexing first
ndim = self.ndim
- shape = self.shape
+ shape = self.shape # pylint: disable=redefined-outer-name
if isinstance(key, list):
try:
@@ -801,7 +801,7 @@ class ndarray(NDArray):
def __len__(self):
"""Number of elements along the first axis."""
- shape = self.shape
+ shape = self.shape # pylint: disable=redefined-outer-name
if len(shape) == 0:
raise TypeError('len() of unsized object')
return self.shape[0]
@@ -1161,7 +1161,7 @@ class ndarray(NDArray):
"""
raise AttributeError('mxnet.numpy.ndarray object has no attribute
reshape_like')
- def reshape_view(self, *shape, **kwargs):
+ def reshape_view(self, *shape, **kwargs): # pylint:
disable=redefined-outer-name
"""Returns a **view** of this array with a new shape without altering
any data.
Inheritated from NDArray.reshape.
"""
@@ -1515,13 +1515,15 @@ class ndarray(NDArray):
"""Returns the average of the array elements along given axis."""
return mean(self, axis=axis, dtype=dtype, out=out, keepdims=keepdims)
- def std(self, axis=None, dtype=None, out=None, ddof=0, keepdims=False): #
pylint: disable=arguments-differ
+ # pylint: disable=too-many-arguments, arguments-differ
+ def std(self, axis=None, dtype=None, out=None, ddof=0, keepdims=False):
"""Returns the standard deviation of the array elements along given
axis."""
return std(self, axis=axis, dtype=dtype, ddof=ddof, keepdims=keepdims,
out=out)
- def var(self, axis=None, dtype=None, out=None, ddof=0, keepdims=False): #
pylint: disable=arguments-differ
+ def var(self, axis=None, dtype=None, out=None, ddof=0, keepdims=False):
"""Returns the variance of the array elements, along given axis."""
return var(self, axis=axis, dtype=dtype, out=out, ddof=ddof,
keepdims=keepdims)
+ # pylint: enable=too-many-arguments, arguments-differ
def cumsum(self, axis=None, dtype=None, out=None):
"""Return the cumulative sum of the elements along the given axis."""
@@ -1850,7 +1852,7 @@ class ndarray(NDArray):
"""Remove single-dimensional entries from the shape of a."""
return _mx_np_op.squeeze(self, axis=axis)
- def broadcast_to(self, shape):
+ def broadcast_to(self, shape): # pylint: disable=redefined-outer-name
return _mx_np_op.broadcast_to(self, shape)
def broadcast_like(self, other):
@@ -1912,7 +1914,7 @@ class ndarray(NDArray):
@set_module('mxnet.numpy')
-def empty(shape, dtype=_np.float32, order='C', ctx=None):
+def empty(shape, dtype=_np.float32, order='C', ctx=None): # pylint:
disable=redefined-outer-name
"""Return a new array of given shape and type, without initializing
entries.
Parameters
@@ -2016,7 +2018,37 @@ def array(object, dtype=None, ctx=None):
@set_module('mxnet.numpy')
-def zeros(shape, dtype=_np.float32, order='C', ctx=None):
+def shape(a):
+ """
+ Return the shape of an array.
+ Parameters
+ ----------
+ a : array_like
+ Input array.
+ Returns
+ -------
+ shape : tuple of ints
+ The elements of the shape tuple give the lengths of the
+ corresponding array dimensions.
+ See Also
+ --------
+ ndarray.shape : Equivalent array method.
+ Examples
+ --------
+ >>> np.shape(np.eye(3))
+ (3, 3)
+ >>> np.shape([[1, 2]])
+ (1, 2)
+ >>> np.shape([0])
+ (1,)
+ >>> np.shape(0)
+ ()
+ """
+ return _mx_nd_np.shape(a)
+
+
+@set_module('mxnet.numpy')
+def zeros(shape, dtype=_np.float32, order='C', ctx=None): # pylint:
disable=redefined-outer-name
"""Return a new array of given shape and type, filled with zeros.
This function currently only supports storing multi-dimensional data
in row-major (C-style).
@@ -2057,7 +2089,7 @@ def zeros(shape, dtype=_np.float32, order='C', ctx=None):
@set_module('mxnet.numpy')
-def ones(shape, dtype=_np.float32, order='C', ctx=None):
+def ones(shape, dtype=_np.float32, order='C', ctx=None): # pylint:
disable=redefined-outer-name
"""Return a new array of given shape and type, filled with ones.
This function currently only supports storing multi-dimensional data
in row-major (C-style).
@@ -2102,8 +2134,9 @@ def ones(shape, dtype=_np.float32, order='C', ctx=None):
return _mx_nd_np.ones(shape, dtype, order, ctx)
+# pylint: disable=too-many-arguments, redefined-outer-name
@set_module('mxnet.numpy')
-def full(shape, fill_value, dtype=None, order='C', ctx=None, out=None): #
pylint: disable=too-many-arguments
+def full(shape, fill_value, dtype=None, order='C', ctx=None, out=None):
"""
Return a new array of given shape and type, filled with `fill_value`.
@@ -2156,6 +2189,7 @@ def full(shape, fill_value, dtype=None, order='C',
ctx=None, out=None): # pylin
[2, 2]], dtype=int32)
"""
return _mx_nd_np.full(shape, fill_value, order=order, ctx=ctx,
dtype=dtype, out=out)
+# pylint: enable=too-many-arguments, redefined-outer-name
@set_module('mxnet.numpy')
@@ -4220,7 +4254,7 @@ def tensordot(a, b, axes=2):
@set_module('mxnet.numpy')
-def histogram(a, bins=10, range=None, normed=None, weights=None,
density=None): # pylint-disable=too-many-arguments
+def histogram(a, bins=10, range=None, normed=None, weights=None,
density=None): # pylint: disable=too-many-arguments
"""
Compute the histogram of a set of data.
@@ -4379,6 +4413,7 @@ def linspace(start, stop, num=50, endpoint=True,
retstep=False, dtype=None, axis
return _mx_nd_np.linspace(start, stop, num, endpoint, retstep, dtype,
axis, ctx)
+# pylint: disable=too-many-arguments
@set_module('mxnet.numpy')
def logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None,
axis=0, ctx=None):
r"""Return numbers spaced evenly on a log scale.
@@ -4453,6 +4488,7 @@ def logspace(start, stop, num=50, endpoint=True,
base=10.0, dtype=None, axis=0,
array([ 100. , 215.44347, 464.15887, 1000. ], ctx=gpu(0))
"""
return _mx_nd_np.logspace(start, stop, num, endpoint, base, dtype, axis,
ctx=ctx)
+# pylint: enable=too-many-arguments
@set_module('mxnet.numpy')
@@ -5418,7 +5454,7 @@ def mean(a, axis=None, dtype=None, out=None,
keepdims=False): # pylint: disable
@set_module('mxnet.numpy')
-def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False):
+def std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): #
pylint: disable=too-many-arguments
"""
Compute the standard deviation along the specified axis.
Returns the standard deviation, a measure of the spread of a distribution,
@@ -5485,7 +5521,7 @@ def std(a, axis=None, dtype=None, out=None, ddof=0,
keepdims=False):
@set_module('mxnet.numpy')
-def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False):
+def var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False): #
pylint: disable=too-many-arguments
"""
Compute the variance along the specified axis.
Returns the variance of the array elements, a measure of the spread of a
diff --git a/python/mxnet/numpy_dispatch_protocol.py
b/python/mxnet/numpy_dispatch_protocol.py
index 8a4a90c..9e68d36 100644
--- a/python/mxnet/numpy_dispatch_protocol.py
+++ b/python/mxnet/numpy_dispatch_protocol.py
@@ -125,6 +125,7 @@ _NUMPY_ARRAY_FUNCTION_LIST = [
'column_stack',
'zeros_like',
'linalg.norm',
+ 'shape',
'trace',
'tril',
'meshgrid',
diff --git a/tests/python/unittest/test_numpy_interoperability.py
b/tests/python/unittest/test_numpy_interoperability.py
index 5b6cea7..da3c17c 100644
--- a/tests/python/unittest/test_numpy_interoperability.py
+++ b/tests/python/unittest/test_numpy_interoperability.py
@@ -1122,6 +1122,12 @@ def _add_workload_nonzero():
OpArgMngr.add_workload('nonzero', np.array([True, False, False],
dtype=np.bool_))
+def _add_workload_shape():
+ OpArgMngr.add_workload('shape', np.random.uniform(size=()))
+ OpArgMngr.add_workload('shape', np.random.uniform(size=(0, 1)))
+ OpArgMngr.add_workload('shape', np.random.uniform(size=(2, 3)))
+
+
def _add_workload_diff():
x = np.array([1, 4, 6, 7, 12])
OpArgMngr.add_workload('diff', x)
@@ -1253,6 +1259,7 @@ def _prepare_workloads():
_add_workload_greater_equal(array_pool)
_add_workload_less(array_pool)
_add_workload_less_equal(array_pool)
+ _add_workload_shape()
_add_workload_diff()
@@ -1284,11 +1291,11 @@ def _check_interoperability_helper(op_name, *args,
**kwargs):
expected_out = _get_numpy_op_output(onp_op, *args, **kwargs)
if isinstance(out, (tuple, list)):
assert type(out) == type(expected_out)
- for arr in out:
- assert isinstance(arr, np.ndarray)
for arr, expected_arr in zip(out, expected_out):
- assert isinstance(arr, np.ndarray)
- assert_almost_equal(arr.asnumpy(), expected_arr, rtol=1e-3,
atol=1e-4, use_broadcast=False, equal_nan=True)
+ if isinstance(arr, np.ndarray):
+ assert_almost_equal(arr.asnumpy(), expected_arr, rtol=1e-3,
atol=1e-4, use_broadcast=False, equal_nan=True)
+ else:
+ _np.testing.assert_equal(arr, expected_arr)
else:
assert isinstance(out, np.ndarray)
assert_almost_equal(out.asnumpy(), expected_out, rtol=1e-3, atol=1e-4,
use_broadcast=False, equal_nan=True)
diff --git a/tests/python/unittest/test_numpy_op.py
b/tests/python/unittest/test_numpy_op.py
index 3aef5ca..5ec9944 100644
--- a/tests/python/unittest/test_numpy_op.py
+++ b/tests/python/unittest/test_numpy_op.py
@@ -756,6 +756,25 @@ def test_np_moment():
np_out = getattr(_np, name)(x.asnumpy(),
axis=axis, dtype=acc_type[itype], keepdims=keepdims, ddof=ddof).astype(dtype)
assert_almost_equal(mx_out.asnumpy(), np_out,
rtol=rtol, atol=atol, use_broadcast=False, equal_nan=True)
+@with_seed()
+@use_np
+def test_np_shape():
+ shapes = [
+ (),
+ (0, 1),
+ (2, 3),
+ (2, 3, 4),
+ ]
+
+ for shape in shapes:
+ mx_a = np.random.uniform(size=shape)
+ np_a = _np.random.uniform(size=shape)
+
+ mx_shape = np.shape(mx_a)
+ np_shape = _np.shape(np_a)
+
+ assert mx_shape == np_shape
+
@with_seed()
@use_np
