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# Copyright (c) 2020 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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import numpy as np
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import paddle
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def shuffle_dim(x, axis, perm=None):
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"""Permute input tensor along aixs given the permutation or randomly.
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Args:
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x (Tensor):
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The input tensor.
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axis (int):
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The axis to shuffle.
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perm (List[int], ndarray, optional):
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The order to reorder the tensor along the ``axis``-th dimension.
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It is a permutation of ``[0, d)``, where d is the size of the
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``axis``-th dimension of the input tensor. If not provided,
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a random permutation is used. Defaults to None.
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Returns:
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Tensor: The shuffled tensor, which has the same shape as x does.
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"""
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size = x.shape[axis]
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if perm is not None and len(perm) != size:
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raise ValueError("length of permutation should equals the input "
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"tensor's axis-th dimension's size")
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if perm is not None:
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perm = np.array(perm)
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else:
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perm = np.random.permutation(size)
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perm = paddle.to_tensor(perm)
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out = paddle.gather(x, perm, axis)
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return out
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