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research/efficient-hrl/context/gin_utils.py
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ofirnachum
add training code
05 дек 2018, 17:10
05 дек 2018, 17:10
052361d
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# Copyright 2018 The TensorFlow Authors All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Gin configurable utility functions. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import numpy as np import gin.tf @gin.configurable def gin_sparse_array(size, values, indices, fill_value=0): arr = np.zeros(size) arr.fill(fill_value) arr[indices] = values return arr @gin.configurable def gin_sum(values): result = values[0] for value in values[1:]: result += value return result @gin.configurable def gin_range(n): return range(n)