forked from huawei/mindspore2022
69 lines
1.9 KiB
Python
69 lines
1.9 KiB
Python
# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""Generate bprop for debug ops"""
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from .. import operations as P
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from ..composite.multitype_ops.zeros_like_impl import zeros_like
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from .grad_base import bprop_getters
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# Unused parameters are placeholders.
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@bprop_getters.register(P.ScalarSummary)
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def get_bprop_scalar_summary(self):
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"""Generate bprop for ScalarSummary"""
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def bprop(tag, x, out, dout):
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return tag, zeros_like(x)
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return bprop
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@bprop_getters.register(P.TensorSummary)
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def get_bprop_tensor_summary(self):
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"""Generate bprop for TensorSummary"""
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def bprop(tag, x, out, dout):
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return tag, zeros_like(x)
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return bprop
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@bprop_getters.register(P.ImageSummary)
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def get_bprop_image_summary(self):
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"""Generate bprop for ImageSummary"""
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def bprop(tag, x, out, dout):
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return tag, zeros_like(x)
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return bprop
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@bprop_getters.register(P.HistogramSummary)
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def get_bprop_histogram_summary(self):
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"""Generate bprop for HistogramSummary"""
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def bprop(tag, x, out, dout):
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return tag, zeros_like(x)
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return bprop
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@bprop_getters.register(P.InsertGradientOf)
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def get_bprop_insert_gradient_of(self):
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"""Generate bprop for InsertGradientOf"""
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f = self.f
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def bprop(x, out, dout):
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return (f(dout),)
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return bprop
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