1# Copyright 2017 The TensorFlow Authors. All Rights Reserved. 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================== 15"""Miscellaneous utilities that don't fit anywhere else.""" 16 17from tensorflow.python.framework import ops 18from tensorflow.python.ops import array_ops 19from tensorflow.python.ops import gen_math_ops 20from tensorflow.python.ops import math_ops 21 22 23def alias_tensors(*args): 24 """Wraps any Tensor arguments with an identity op. 25 26 Any other argument, including Variables, is returned unchanged. 27 28 Args: 29 *args: Any arguments. Must contain at least one element. 30 31 Returns: 32 Same as *args, with Tensor instances replaced as described. 33 34 Raises: 35 ValueError: If args doesn't meet the requirements. 36 """ 37 38 def alias_if_tensor(a): 39 return array_ops.identity(a) if isinstance(a, ops.Tensor) else a 40 41 # TODO(mdan): Recurse into containers? 42 # TODO(mdan): Anything we can do about variables? Fake a scope reuse? 43 if len(args) > 1: 44 return (alias_if_tensor(a) for a in args) 45 elif len(args) == 1: 46 return alias_if_tensor(args[0]) 47 48 raise ValueError('at least one argument required') 49 50 51def get_range_len(start, limit, delta): 52 dist = ops.convert_to_tensor(limit - start) 53 unadjusted_len = dist // delta 54 adjustment = math_ops.cast( 55 gen_math_ops.not_equal(dist % delta, 56 array_ops.zeros_like(unadjusted_len)), dist.dtype) 57 final_len = unadjusted_len + adjustment 58 return gen_math_ops.maximum(final_len, array_ops.zeros_like(final_len)) 59