p60975123
/
mindspore
forked from mindspore-Ecosystem/mindspore
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

tensor_sum_to_size_master

This commit is contained in:
yide12 2022-12-08 19:49:46 +08:00
parent d7a19bf0fe
commit 06de9234d3
15 changed files with 202 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

1
docs/api/api_python/mindspore.ops.rst
View File

@ -263,6 +263,7 @@ mindspore.ops
mindspore.ops.square
mindspore.ops.sub
mindspore.ops.subtract
mindspore.ops.sum_to_size
mindspore.ops.svd
mindspore.ops.tan
mindspore.ops.true_divide

6
docs/api/api_python/mindspore/Tensor/mindspore.Tensor.sum_to_size.rst Normal file
View File

@ -0,0 +1,6 @@
mindspore.Tensor.sum_to_size
============================
.. py:method:: mindspore.Tensor.sum_to_size(*size)
详情请参考 :func:`mindspore.ops.sum_to_size`。

1
docs/api/api_python/mindspore/mindspore.Tensor.rst
View File

@ -248,6 +248,7 @@ mindspore.Tensor
mindspore.Tensor.sub
mindspore.Tensor.subtract
mindspore.Tensor.sum
mindspore.Tensor.sum_to_size
mindspore.Tensor.svd
mindspore.Tensor.swapaxes
mindspore.Tensor.T

16
docs/api/api_python/ops/mindspore.ops.func_sum_to_size.rst Normal file
View File

@ -0,0 +1,16 @@
mindspore.ops.sum_to_size
=========================
.. py:function:: mindspore.ops.sum_to_size(x, *size)
将Tensor `x` 加和成 `size`。`size` 必须可以扩展到Tensor的大小。
参数：
- **x** (Tensor) - 求和的Tensor。
- **size** (Union[tuple(int), int]) - 期望输出Tensor的shape。
返回：
Tensor，根据 `size` 对 `x` 进行求和的结果。
异常：
- **ValueError** - `size` 不能扩展成 `x` 的大小。

1
docs/api/api_python_en/Tensor_list.rst
View File

@ -254,6 +254,7 @@
mindspore.Tensor.sub
mindspore.Tensor.subtract
mindspore.Tensor.sum
mindspore.Tensor.sum_to_size
mindspore.Tensor.svd
mindspore.Tensor.swapaxes
mindspore.Tensor.T

1
docs/api/api_python_en/mindspore.ops.rst
View File

@ -263,6 +263,7 @@ Element-by-Element Operations
mindspore.ops.square
mindspore.ops.sub
mindspore.ops.subtract
mindspore.ops.sum_to_size
mindspore.ops.svd
mindspore.ops.tan
mindspore.ops.true_divide

1
mindspore/ccsrc/pipeline/jit/resource.cc
View File

@ -328,6 +328,7 @@ BuiltInTypeMap &GetMethodMap() {
{"true_divide", std::string("true_divide")}, // true_divide()
{"triu", std::string("triu")}, // triu()
{"subtract", std::string("subtract")}, // true_divide()
{"sum_to_size", std::string("sum_to_size")}, // sum_to_size()
{"exp", std::string("exp")}, // P.Exp()
{"repeat", std::string("repeat")}, // C.repeat_elements
{"bernoulli", prim::kPrimBernoulli}, // P.Bernoulli()

9
mindspore/python/mindspore/_extends/parse/standard_method.py
View File

@ -1205,8 +1205,8 @@ def permute(x, *dims):
"""
if dims is None:
raise ValueError(f"For Tensor.permute, the dims must not be none.")
if len(dims) == 1:
return F.permute(x, *dims)
if len(dims) == 1 and isinstance(dims[0], tuple):
return F.permute(x, dims[0])
return F.permute(x, dims)
@ -1989,6 +1989,11 @@ def sum(x, axis=None, dtype=None, keepdims=False, initial=None): # pylint: disa
return res.astype(dtype)
def sum_to_size(x, *size):
"""For details, please refer to :func:`mindspore.ops.sum_to_size`."""
return F.sum_to_size(x, *size)
def repeat(x, repeats, axis=None):
"""
Repeat elements of an array.

9
mindspore/python/mindspore/common/tensor.py
View File

@ -1819,8 +1819,8 @@ class Tensor(Tensor_):
self._init_check()
if not dims:
raise ValueError(f"For Tensor.permute, the dims must not be none.")
if len(dims) == 1:
return tensor_operator_registry.get("permute")(self, *dims)
if len(dims) == 1 and isinstance(dims[0], tuple):
return tensor_operator_registry.get("permute")(self, dims[0])
return tensor_operator_registry.get("permute")(self, dims)
def positive(self):
@ -3037,6 +3037,11 @@ class Tensor(Tensor_):
res += initial
return res.astype(dtype)
def sum_to_size(self, *size):
"""For details, please refer to :func:`mindspore.ops.sum_to_size`."""
self._init_check()
return tensor_operator_registry.get("sum_to_size")(self, *size)
def repeat(self, repeats, axis=None):
"""
Repeat elements of a tensor.

5
mindspore/python/mindspore/nn/loss/loss.py
View File

@ -2386,9 +2386,8 @@ class CTCLoss(LossBase):
def construct(self, log_probs, targets, input_lengths, target_lengths):
if len(log_probs.shape) == 2:
n, c = log_probs.shape
log_probs = log_probs.reshape((n, 1, c))
targets = targets.reshape(1, targets.shape[0])
log_probs = log_probs.expand_dims(-2)
targets = targets.expand_dims(0)
if isinstance(input_lengths, int):
input_lengths = Tensor([input_lengths], mstype.int32)
else:

1
mindspore/python/mindspore/ops/function/__init__.py
View File

@ -172,6 +172,7 @@ from .math_func import (
real,
sub,
subtract,
sum_to_size,
sqrt,
square,
tensor_mul,

43
mindspore/python/mindspore/ops/function/math_func.py
View File

@ -809,6 +809,48 @@ def subtract(x, other, *, alpha=1):
return tensor_sub(x, alpha * other)
def sum_to_size(x, *size):
"""
Sum `x` Tensor to the `size`. `size` must be expandable to the Tensor size.
Args:
x (Tensor): The Tensor to be summed.
size (Union[tuple(int), int]): The expected shape of output Tensor.
Returns:
Tensor, the sum result of `x` according to the `size`.
Raises:
ValueError: If `size` is not expandable to the size of `x`.
Supported Platforms:
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> x = Tensor(np.random.randn(3, 3, 3, 3, 3, 3), mindspore.float32)
>>> output = ops.sum_to_size(x, (1, 3, 1, 3))
>>> print(output.shape)
(1, 3, 1, 3)
"""
if len(size) == 1 and isinstance(size[0], tuple):
size = size[0]
shape_x = x.shape
if len(size) > x.ndim:
raise ValueError(f"For sum_to_size, size {size} is not expandable to the tensor size {shape_x}.")
if len(size) < x.ndim:
pre_axis = tuple([axis for axis in range(x.ndim - len(size))])
x = x.sum(pre_axis)
axes = []
for i, element in enumerate(size):
if element != x.shape[i] and element == 1:
axes.append(i)
elif element != x.shape[i]:
raise ValueError(f"For sum_to_size, size {size} is not expandable to the tensor size {shape_x}.")
if axes:
return x.sum(tuple(axes), keepdims=True)
return x
def true_divide(dividend, divisor):
r"""
Alias for Tensor.div() with :math:`rounding\_mode=None`.
@ -9217,6 +9259,7 @@ __all__ = [
'tensor_sub',
'sub',
'subtract',
'sum_to_size',
'tensor_mul',
'mul',
'multiply',

1
mindspore/python/mindspore/ops/functional.py
View File

@ -140,6 +140,7 @@ tensor_operator_registry.register('bincount', bincount)
tensor_operator_registry.register('sqrt', sqrt)
tensor_operator_registry.register('square', square)
tensor_operator_registry.register('sub', sub)
tensor_operator_registry.register('sum_to_size', sum_to_size)
tensor_operator_registry.register('triu', Triu)
tensor_operator_registry.register('tan', P.Tan)
tensor_operator_registry.register('acos', acos)

57
tests/st/ops/test_func_sum_to_size.py Normal file
View File

@ -0,0 +1,57 @@
# Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed 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.
# ============================================================================
import numpy as np
import pytest
import mindspore as ms
import mindspore.nn as nn
from mindspore import Tensor, ops
class Net(nn.Cell):
def construct(self, x):
return ops.sum_to_size(x, (3, 1, 3))
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.platform_arm_cpu
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
def test_ops_sum_to_size(mode):
"""
Feature: ops.sum_to_size
Description: Verify the result of sum_to_size
Expectation: success
"""
ms.set_context(mode=mode)
x = Tensor([[[24, 20, 39],
[79, 67, 43],
[62, 0, 95]],
[[74, 5, 33],
[0, 35, 78],
[67, 0, 29]],
[[45, 42, 77],
[70, 61, 72],
[23, 82, 47]]], ms.float32)
net = Net()
output = net(x)
expect_output = [[[165, 87, 177]],
[[141, 40, 140]],
[[138, 185, 196]]]
assert np.allclose(output.asnumpy(), expect_output)

57
tests/st/tensor/test_sum_to_size.py Normal file
View File

@ -0,0 +1,57 @@
# Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed 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.
# ============================================================================
import numpy as np
import pytest
import mindspore as ms
import mindspore.nn as nn
from mindspore import Tensor
class Net(nn.Cell):
def construct(self, x):
return x.sum_to_size((3, 1, 3))
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.platform_arm_cpu
@pytest.mark.platform_x86_gpu_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.platform_x86_ascend_training
@pytest.mark.env_onecard
@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
def test_tensor_sum_to_size(mode):
"""
Feature: Tensor.sum_to_size
Description: Verify the result of sum_to_size
Expectation: success
"""
ms.set_context(mode=mode)
x = Tensor([[[24, 20, 39],
[79, 67, 43],
[62, 0, 95]],
[[74, 5, 33],
[0, 35, 78],
[67, 0, 29]],
[[45, 42, 77],
[70, 61, 72],
[23, 82, 47]]], ms.float32)
net = Net()
output = net(x)
expect_output = [[[165, 87, 177]],
[[141, 40, 140]],
[[138, 185, 196]]]
assert np.allclose(output.asnumpy(), expect_output)