zhoujie2104231
2757a4d0d2
添加了Stock-Prediction-Models项目的多个文件，包括数据集、模型代码、README文档和CSS样式文件。这些文件用于股票预测模型的训练和展示，涵盖了LSTM、GRU等深度学习模型的应用。
46 lines
1.6 KiB
Python
46 lines
1.6 KiB
Python
# Copyright 2017 Google Inc.
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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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"""DNC util ops and modules."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import numpy as np
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import tensorflow as tf
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def batch_invert_permutation(permutations):
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"""Returns batched `tf.invert_permutation` for every row in `permutations`."""
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with tf.name_scope('batch_invert_permutation', values=[permutations]):
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unpacked = tf.unstack(permutations)
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inverses = [tf.invert_permutation(permutation) for permutation in unpacked]
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return tf.stack(inverses)
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def batch_gather(values, indices):
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"""Returns batched `tf.gather` for every row in the input."""
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with tf.name_scope('batch_gather', values=[values, indices]):
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unpacked = zip(tf.unstack(values), tf.unstack(indices))
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result = [tf.gather(value, index) for value, index in unpacked]
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return tf.stack(result)
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def one_hot(length, index):
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"""Return an nd array of given `length` filled with 0s and a 1 at `index`."""
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result = np.zeros(length)
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result[index] = 1
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return result
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