Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.8/site-packages/tensorflow/python/autograph/utils/misc.py: 37%

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))