60 lines
2.1 KiB
Python
60 lines
2.1 KiB
Python
# Copyright 2017 The TensorFlow 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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# ==============================================================================
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"""Miscellaneous utilities that don't fit anywhere else."""
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from tensorflow.python.framework import ops
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from tensorflow.python.framework import tensor
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from tensorflow.python.ops import array_ops
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from tensorflow.python.ops import gen_math_ops
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from tensorflow.python.ops import math_ops
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def alias_tensors(*args):
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"""Wraps any Tensor arguments with an identity op.
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Any other argument, including Variables, is returned unchanged.
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Args:
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*args: Any arguments. Must contain at least one element.
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Returns:
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Same as *args, with Tensor instances replaced as described.
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Raises:
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ValueError: If args doesn't meet the requirements.
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"""
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def alias_if_tensor(a):
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return array_ops.identity(a) if isinstance(a, tensor.Tensor) else a
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# TODO(mdan): Recurse into containers?
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# TODO(mdan): Anything we can do about variables? Fake a scope reuse?
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if len(args) > 1:
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return (alias_if_tensor(a) for a in args)
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elif len(args) == 1:
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return alias_if_tensor(args[0])
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raise ValueError('at least one argument required')
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def get_range_len(start, limit, delta):
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dist = ops.convert_to_tensor(limit - start)
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unadjusted_len = dist // delta
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adjustment = math_ops.cast(
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gen_math_ops.not_equal(dist % delta,
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array_ops.zeros_like(unadjusted_len)), dist.dtype)
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final_len = unadjusted_len + adjustment
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return gen_math_ops.maximum(final_len, array_ops.zeros_like(final_len))
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