Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.8/site-packages/tensorflow/python/data/util/random_seed.py: 44%

1# Copyright 2018 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"""Utilities for generating Tensor-valued random seeds.""" 

16 

17from tensorflow.python.framework import constant_op 

18from tensorflow.python.framework import dtypes 

19from tensorflow.python.framework import ops 

20from tensorflow.python.framework import random_seed 

21from tensorflow.python.ops import array_ops 

22from tensorflow.python.ops import math_ops 

23 

24 

25def get_seed(seed): 

26 """Returns the local seeds an operation should use given an op-specific seed. 

27 

28 See `random_seed.get_seed` for more details. This wrapper adds support for 

29 the case where `seed` may be a tensor. 

30 

31 Args: 

32 seed: An integer or a `tf.int64` scalar tensor. 

33 

34 Returns: 

35 A tuple of two `tf.int64` scalar tensors that should be used for the local 

36 seed of the calling dataset. 

37 """ 

38 seed, seed2 = random_seed.get_seed(seed) 

39 if seed is None: 

40 seed = constant_op.constant(0, dtype=dtypes.int64, name="seed") 

41 else: 

42 seed = ops.convert_to_tensor(seed, dtype=dtypes.int64, name="seed") 

43 if seed2 is None: 

44 seed2 = constant_op.constant(0, dtype=dtypes.int64, name="seed2") 

45 else: 

46 with ops.name_scope("seed2") as scope: 

47 seed2 = ops.convert_to_tensor(seed2, dtype=dtypes.int64) 

48 seed2 = array_ops.where_v2( 

49 math_ops.logical_and( 

50 math_ops.equal(seed, 0), math_ops.equal(seed2, 0)), 

51 constant_op.constant(2**31 - 1, dtype=dtypes.int64), 

52 seed2, 

53 name=scope) 

54 return seed, seed2