wehub-resource-sync
56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. 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,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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# pylint: disable=invalid-name
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"""Sequence mask in python"""
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import numpy as np
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def sequence_mask(data, valid_length, mask_value, axis):
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"""batch_matmul operator implemented in numpy.
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Parameters
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----------
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data : numpy.ndarray
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N-D with shape [batch_size, MAX_LENGTH, ...] or [MAX_LENGTH, batch_size, ...]
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valid_length : numpy.ndarray
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1-D with shape [batch_size,]
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mask_value : float
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Masking value
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axis : int
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The axis of the length dimension
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Returns
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-------
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out : numpy.ndarray
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N-D with shape same as data
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"""
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in_shape = data.shape
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max_length = data.shape[axis]
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val_len_expand_shape = [1 for _ in range(len(in_shape))]
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val_len_expand_shape[1 - axis] = in_shape[1 - axis]
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seq_len_expand_shape = [1 for _ in range(len(in_shape))]
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seq_len_expand_shape[axis] = in_shape[axis]
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mask = np.broadcast_to(
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np.arange(max_length).reshape(seq_len_expand_shape), in_shape
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) >= valid_length.reshape(val_len_expand_shape)
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out = data * (1 - mask) + mask_value * mask
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return out
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