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48 lines
1.5 KiB
48 lines
1.5 KiB
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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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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from typing import Union
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import paddle
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def is_broadcastable(shp1, shp2):
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for a, b in zip(shp1[::-1], shp2[::-1]):
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if a == 1 or b == 1 or a == b:
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pass
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else:
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return False
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return True
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# assume that len(shp1) == len(shp2)
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def broadcast_shape(shp1, shp2):
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result = []
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for a, b in zip(shp1[::-1], shp2[::-1]):
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result.append(max(a, b))
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return result[::-1]
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def masked_fill(xs: paddle.Tensor,
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mask: paddle.Tensor,
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value: Union[float, int]):
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# comment following line for converting dygraph to static graph.
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# assert is_broadcastable(xs.shape, mask.shape) is True
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bshape = broadcast_shape(xs.shape, mask.shape)
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mask.stop_gradient = True
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mask = mask.broadcast_to(bshape)
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trues = paddle.ones_like(xs) * value
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mask = mask.cast(dtype=paddle.bool)
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xs = paddle.where(mask, trues, xs)
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return xs
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