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!45623 [MS][OP]move to the right place 

Merge pull request !45623 from mengyuanli/export_init
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i-robot 2022-11-21 06:21:43 +00:00 committed by Gitee
parent 17d0bce3f5 aa4c4d6e43
commit e85693d49c
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8 changed files with 83 additions and 95 deletions
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2
mindspore/python/mindspore/ops/function/spectral_func.py
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@ -60,7 +60,7 @@ def blackman_window(window_length, periodic=True, *, dtype=None):
ValueError: If the dimension of `window_length` is not 0.
Supported Platforms:
``Ascend`` ``CPU`` ``GPU``
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> window_length = Tensor(10, mindspore.int32)

3
mindspore/python/mindspore/ops/operations/__init__.py
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@ -113,7 +113,7 @@ from .nn_ops import (LSTM, SGD, Adam, AdamWeightDecay, FusedSparseAdam, FusedSpa
PSROIPooling, Dilation2D, DataFormatVecPermute, DeformableOffsets, FractionalAvgPool,
FractionalMaxPool, FractionalMaxPool3DWithFixedKsize, FractionalMaxPoolWithFixedKsize,
GridSampler2D, TripletMarginLoss, UpsampleNearest3D, UpsampleTrilinear3D)
from .other_ops import (Assign, IOU, BartlettWindow, BlackmanWindow, BoundingBoxDecode, BoundingBoxEncode,
from .other_ops import (Assign, IOU, BoundingBoxDecode, BoundingBoxEncode,
ConfusionMatrix, UpdateState, Load, StopGradient,
CheckValid, Partial, Depend, identity, Push, Pull, PyFunc, _DynamicLossScale,
SampleDistortedBoundingBoxV2)
@ -123,6 +123,7 @@ from .random_ops import (RandomChoiceWithMask, StandardNormal, Gamma, RandomGamm
ParameterizedTruncatedNormal, RandomPoisson)
from .rl_ops import (BufferAppend, BufferGetItem, BufferSample)
from .sparse_ops import (SparseToDense, SparseTensorDenseMatmul, SparseTensorDenseAdd)
from .spectral_ops import (BartlettWindow, BlackmanWindow)
__all__ = [
'HSVToRGB',

2
mindspore/python/mindspore/ops/operations/nn_ops.py
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@ -7998,7 +7998,7 @@ class CTCLossV2(Primitive):
"""
@prim_attr_register
def __init__(self, blank, reduction="none", zero_infinity=False):
def __init__(self, blank=0, reduction="none", zero_infinity=False):
"""Initialize CTCLossV2"""
self.init_prim_io_names(inputs=["log_probs", "targets", "input_lengths", "target_lengths"],
outputs=["neg_log_likelihood", "log_alpha"])

88
mindspore/python/mindspore/ops/operations/other_ops.py
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@ -154,33 +154,6 @@ class BoundingBoxEncode(PrimitiveWithInfer):
validator.check_equal_int(len(stds), 4, "stds len", self.name)
class BartlettWindow(Primitive):
r"""
Bartlett window function.
Refer to :func:`mindspore.ops.bartlett_window` for more details.
Supported Platforms:
``GPU``
Examples:
>>> window_length = Tensor(5, mstype.int32)
>>> bartlett_window = ops.BartlettWindow(periodic=True, dtype=mstype.float32)
>>> output = bartlett_window(window_length)
>>> print(output)
[0. 0.4 0.8 0.8 0.4]
"""
@prim_attr_register
def __init__(self, periodic=True, dtype=mstype.float32):
"""Initialize BartlettWindow"""
self.add_prim_attr("max_length", 1000000)
validator.check_value_type("periodic", periodic, [bool], self.name)
validator.check_value_type("dtype", dtype, [mstype.Type], self.name)
valid_values = (mstype.float16, mstype.float32, mstype.float64)
validator.check_type_name("dtype", dtype, valid_values, self.name)
class BoundingBoxDecode(Primitive):
"""
Decodes bounding boxes locations.
@ -824,64 +797,3 @@ class PyFunc(PrimitiveWithInfer):
logger.warning("The function output are empty tuple. Add a placeholder instead. "
"Do not use it as it could be any uninitialized data.")
return (mstype.int32,)
class BlackmanWindow(Primitive):
r"""
Blackman window function.
The input "window_length" is a tensor that datatype must be a integer, which
controlling the returned window size. In particular, If "window_length" =1,
the returned window contains a single value 1.
Attr "periodic" determines whether the returned window trims off the last duplicate value
from the symmetric window and is ready to be used as a periodic window with functions.
Therefore, if attr "periodic" is true, the "N" in formula is in fact "window_length" + 1.
.. math::
w[n] = 0.42 - 0.5 cos(\frac{2\pi n}{N - 1}) + 0.08 cos(\frac{4\pi n}{N - 1})
\text{where : N is the full window size.}
Args:
periodic (bool): If True, returns a window to be used as periodic function.
If False, return a symmetric window. Default: True.
dtype (mindspore.dtype): the desired data type of returned tensor.
Only float16, float32 and float64 is allowed. Default: mindspore.float32.
Inputs:
- **window_length** (Tensor) - the size of returned window, with data type int32, int64.
The input data should be an integer with a value of [0, 1000000].
Outputs:
A 1-D tensor of size "window_length" containing the window. Its datatype is set by the attr 'dtype'.
Raises:
TypeError: If "window_length" is not a Tensor.
TypeError: If "periodic" is not a bool.
TypeError: If "dtype" is not one of: float16, float32, float64.
TypeError: If the type of "window_length" is not one of: int32, int64.
ValueError: If the value range of "window_length" is not [0,1000000].
ValueError: If the dimension of "window_length" is not 0.
Supported Platforms:
``Ascend`` ``CPU``
Examples:
>>> window_length = Tensor(10, mindspore.int32)
>>> blackman_window = ops.BlackmanWindow(periodic = True, dtype = mindspore.float32)
>>> output = blackman_window(window_length)
>>> print(output)
[-2.9802322e-08 4.0212840e-02 2.0077014e-01 5.0978714e-01
8.4922993e-01 1.0000000e+00 8.4922981e-01 5.0978690e-01
2.0077008e-01 4.0212870e-02]
"""
@prim_attr_register
def __init__(self, periodic=True, dtype=mstype.float32):
"""Initialize BlackmanWindow"""
self.add_prim_attr("max_length", 1000000)
validator.check_value_type("periodic", periodic, [bool], self.name)
validator.check_value_type("dtype", dtype, [mstype.Type], self.name)
valid_values = (mstype.float16, mstype.float32, mstype.float64)
validator.check_type_name("dtype", dtype, valid_values, self.name)

75
mindspore/python/mindspore/ops/operations/spectral_ops.py Normal file
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@ -0,0 +1,75 @@
# 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.
# ============================================================================
"""Spectral operators."""
from mindspore._checkparam import Validator as validator
from mindspore.common import dtype as mstype
from mindspore.ops.primitive import Primitive, prim_attr_register
class BartlettWindow(Primitive):
r"""
Bartlett window function.
Refer to :func:`mindspore.ops.bartlett_window` for more details.
Supported Platforms:
``GPU``
Examples:
>>> window_length = Tensor(5, mstype.int32)
>>> bartlett_window = ops.BartlettWindow(periodic=True, dtype=mstype.float32)
>>> output = bartlett_window(window_length)
>>> print(output)
[0. 0.4 0.8 0.8 0.4]
"""
@prim_attr_register
def __init__(self, periodic=True, dtype=mstype.float32):
"""Initialize BartlettWindow"""
self.add_prim_attr("max_length", 1000000)
validator.check_value_type("periodic", periodic, [bool], self.name)
validator.check_value_type("dtype", dtype, [mstype.Type], self.name)
valid_values = (mstype.float16, mstype.float32, mstype.float64)
validator.check_type_name("dtype", dtype, valid_values, self.name)
class BlackmanWindow(Primitive):
r"""
Blackman window function.
Refer to :func:`mindspore.ops.blackman_window` for more details.
Supported Platforms:
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> window_length = Tensor(10, mindspore.int32)
>>> blackman_window = ops.BlackmanWindow(periodic = True, dtype = mindspore.float32)
>>> output = blackman_window(window_length)
>>> print(output)
[-2.9802322e-08 4.0212840e-02 2.0077014e-01 5.0978714e-01
8.4922993e-01 1.0000000e+00 8.4922981e-01 5.0978690e-01
2.0077008e-01 4.0212870e-02]
"""
@prim_attr_register
def __init__(self, periodic=True, dtype=mstype.float32):
"""Initialize BlackmanWindow"""
self.add_prim_attr("max_length", 1000000)
validator.check_value_type("periodic", periodic, [bool], self.name)
validator.check_value_type("dtype", dtype, [mstype.Type], self.name)
valid_values = (mstype.float16, mstype.float32, mstype.float64)
validator.check_type_name("dtype", dtype, valid_values, self.name)

2
tests/st/ops/gpu/test_bartlett_window_op.py
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@ -17,7 +17,7 @@ import torch
import pytest
import mindspore.context as context
import mindspore.nn as nn
import mindspore.ops.operations.other_ops as P
import mindspore.ops.operations.spectral_ops as P
from mindspore import Tensor
from mindspore.common import dtype as mstype
from mindspore.common.api import jit

2
tests/st/ops/gpu/test_blackman_window_op.py
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@ -18,7 +18,7 @@ import pytest
import mindspore.context as context
import mindspore.nn as nn
from mindspore.ops import functional as F
import mindspore.ops.operations.other_ops as P
import mindspore.ops.operations.spectral_ops as P
from mindspore import Tensor
from mindspore.common import dtype as mstype
from mindspore.common.api import jit

4
tests/ut/python/ops/test_ops.py
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@ -140,7 +140,7 @@ from mindspore.nn.loss.loss import MultiMarginLoss
from mindspore.nn.loss.loss import MultilabelMarginLoss
from mindspore.nn.loss.loss import TripletMarginLoss
from mindspore.ops.operations.array_ops import Mvlgamma
from mindspore.ops.operations.other_ops import BartlettWindow
from mindspore.ops.operations.spectral_ops import BartlettWindow
from mindspore.ops.operations.nn_ops import SparseSoftmaxCrossEntropyWithLogitsV2
from mindspore.ops.operations.nn_ops import NthElement
from mindspore.ops.operations.nn_ops import Pdist
@ -188,7 +188,7 @@ from mindspore.ops.operations.sparse_ops import SparseSegmentMeanWithNumSegments
from mindspore.ops.operations.sparse_ops import SparseSlice
from mindspore.ops.operations.sparse_ops import SparseFillEmptyRows
from mindspore.ops.operations._grad_ops import SparseSliceGrad
from mindspore.ops.operations.other_ops import BlackmanWindow
from mindspore.ops.operations.spectral_ops import BlackmanWindow
from mindspore.ops.operations.nn_ops import SparseApplyCenteredRMSProp
from mindspore.ops.operations.nn_ops import SparseApplyProximalGradientDescent
from mindspore.ops.operations.sparse_ops import SparseReshape