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add vms for binarycrossentropy and binarycrossentropygrad

This commit is contained in:
lihongkang 2020-05-20 20:28:56 +08:00
parent 979d2e23dc
commit cf543382aa
4 changed files with 100 additions and 0 deletions
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2
mindspore/ops/_op_impl/tbe/__init__.py
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@ -188,3 +188,5 @@ from .pack import _pack_tbe
from .unpack import _unpack_tbe
from .prelu import _prelu_tbe
from .prelu_grad import _prelu_grad_tbe
from .binary_cross_entropy import _binary_cross_entropy_tbe
from .binary_cross_entropy_grad import _binary_cross_entropy_grad_tbe

41
mindspore/ops/_op_impl/tbe/binary_cross_entropy.py Normal file
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@ -0,0 +1,41 @@
# Copyright 2020 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.
# ============================================================================
"""BinaryCrossEntropy op"""
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
binary_cross_entropy_op_info = TBERegOp("BinaryCrossEntropy") \
.fusion_type("OPAQUE") \
.async_flag(False) \
.binfile_name("binary_cross_entropy.so") \
.compute_cost(10) \
.kernel_name("binary_cross_entropy") \
.partial_flag(True) \
.attr("reduction", "optional", "str", "all") \
.input(0, "x", False, "required", "all") \
.input(1, "y", False, "required", "all") \
.input(2, "weight", False, "optional", "all") \
.output(0, "output", False, "required", "all") \
.dtype_format(DataType.F16_Default, DataType.F16_Default, DataType.F16_Default, DataType.F16_Default) \
.dtype_format(DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD) \
.dtype_format(DataType.F32_Default, DataType.F32_Default, DataType.F32_Default, DataType.F32_Default) \
.dtype_format(DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD) \
.get_op_info()
@op_info_register(binary_cross_entropy_op_info)
def _binary_cross_entropy_tbe():
"""BinaryCrossEntropy TBE register"""
return

44
mindspore/ops/_op_impl/tbe/binary_cross_entropy_grad.py Normal file
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@ -0,0 +1,44 @@
# Copyright 2020 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.
# ============================================================================
"""BinaryCrossEntropyGrad op"""
from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
binary_cross_entropy_grad_op_info = TBERegOp("BinaryCrossEntropyGrad") \
.fusion_type("OPAQUE") \
.async_flag(False) \
.binfile_name("binary_cross_entropy_grad.so") \
.compute_cost(10) \
.kernel_name("binary_cross_entropy_grad") \
.partial_flag(True) \
.attr("reduction", "optional", "str", "all") \
.input(0, "x", False, "required", "all") \
.input(1, "y", False, "required", "all") \
.input(2, "grad_output", False, "required", "all") \
.input(3, "weight", False, "optional", "all") \
.output(0, "output", False, "required", "all") \
.dtype_format(DataType.F16_Default, DataType.F16_Default, DataType.F16_Default, DataType.F16_Default,
DataType.F16_Default) \
.dtype_format(DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD) \
.dtype_format(DataType.F32_Default, DataType.F32_Default, DataType.F32_Default, DataType.F32_Default,
DataType.F32_Default) \
.dtype_format(DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD) \
.get_op_info()
@op_info_register(binary_cross_entropy_grad_op_info)
def _binary_cross_entropy_grad_tbe():
"""BinaryCrossEntropyGrad TBE register"""
return

13
tests/ut/python/ops/test_ops.py
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@ -972,6 +972,19 @@ test_case_nn_ops = [
'desc_inputs': [[3, 3], [3, 3], Tensor(0.001, mstype.float32), [3, 3], Tensor(0.1, mstype.float32), [3, 3]],
'desc_bprop': [3, 3],
'skip': ['backward']}),
('BinaryCrossEntropy', {
'block': P.BinaryCrossEntropy(),
'desc_inputs': [Tensor([[0.3, 0.8], [0.4, 0.3]], mstype.float16),
Tensor([[0.4, 1.2], [-0.4, -0.9]], mstype.float16),
Tensor([[-1.4, -0.7], [0.9, 0.7]], mstype.float16)],
'desc_bprop': []}),
('BinaryCrossEntropyGrad', {
'block': G.BinaryCrossEntropyGrad(),
'desc_inputs': [Tensor([[0.3, 0.8], [0.4, 0.3]], mstype.float16),
Tensor([[0.4, 1.2], [-0.4, -0.9]], mstype.float16), Tensor(0.85, mstype.float16),
Tensor([[-1.4, -0.7], [0.9, 0.7]], mstype.float16)],
'desc_bprop': [],
'skip': ['backward']}),
]
test_case_array_ops = [