Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.8/site-packages/tensorboard/plugins/scalar/summary.py: 28%

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"""Scalar summaries and TensorFlow operations to create them. 

16 

17A scalar summary stores a single floating-point value, as a rank-0 

18tensor. 

19""" 

20 

21 

22import numpy as np 

23 

24from tensorboard.plugins.scalar import metadata 

25from tensorboard.plugins.scalar import summary_v2 

26 

27 

28# Export V2 versions. 

29scalar = summary_v2.scalar 

30scalar_pb = summary_v2.scalar_pb 

31 

32 

33def op(name, data, display_name=None, description=None, collections=None): 

34 """Create a legacy scalar summary op. 

35 

36 Arguments: 

37 name: A unique name for the generated summary node. 

38 data: A real numeric rank-0 `Tensor`. Must have `dtype` castable 

39 to `float32`. 

40 display_name: Optional name for this summary in TensorBoard, as a 

41 constant `str`. Defaults to `name`. 

42 description: Optional long-form description for this summary, as a 

43 constant `str`. Markdown is supported. Defaults to empty. 

44 collections: Optional list of graph collections keys. The new 

45 summary op is added to these collections. Defaults to 

46 `[Graph Keys.SUMMARIES]`. 

47 

48 Returns: 

49 A TensorFlow summary op. 

50 """ 

51 # TODO(nickfelt): remove on-demand imports once dep situation is fixed. 

52 import tensorflow.compat.v1 as tf 

53 

54 if display_name is None: 

55 display_name = name 

56 summary_metadata = metadata.create_summary_metadata( 

57 display_name=display_name, description=description 

58 ) 

59 with tf.name_scope(name): 

60 with tf.control_dependencies([tf.assert_scalar(data)]): 

61 return tf.summary.tensor_summary( 

62 name="scalar_summary", 

63 tensor=tf.cast(data, tf.float32), 

64 collections=collections, 

65 summary_metadata=summary_metadata, 

66 ) 

67 

68 

69def pb(name, data, display_name=None, description=None): 

70 """Create a legacy scalar summary protobuf. 

71 

72 Arguments: 

73 name: A unique name for the generated summary, including any desired 

74 name scopes. 

75 data: A rank-0 `np.array` or array-like form (so raw `int`s and 

76 `float`s are fine, too). 

77 display_name: Optional name for this summary in TensorBoard, as a 

78 `str`. Defaults to `name`. 

79 description: Optional long-form description for this summary, as a 

80 `str`. Markdown is supported. Defaults to empty. 

81 

82 Returns: 

83 A `tf.Summary` protobuf object. 

84 """ 

85 # TODO(nickfelt): remove on-demand imports once dep situation is fixed. 

86 import tensorflow.compat.v1 as tf 

87 

88 data = np.array(data) 

89 if data.shape != (): 

90 raise ValueError( 

91 "Expected scalar shape for data, saw shape: %s." % data.shape 

92 ) 

93 if data.dtype.kind not in ("b", "i", "u", "f"): # bool, int, uint, float 

94 raise ValueError("Cast %s to float is not supported" % data.dtype.name) 

95 tensor = tf.make_tensor_proto(data.astype(np.float32)) 

96 

97 if display_name is None: 

98 display_name = name 

99 summary_metadata = metadata.create_summary_metadata( 

100 display_name=display_name, description=description 

101 ) 

102 tf_summary_metadata = tf.SummaryMetadata.FromString( 

103 summary_metadata.SerializeToString() 

104 ) 

105 summary = tf.Summary() 

106 summary.value.add( 

107 tag="%s/scalar_summary" % name, 

108 metadata=tf_summary_metadata, 

109 tensor=tensor, 

110 ) 

111 return summary