Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.8/site-packages/tensorboard/util/encoder.py: 53%

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"""TensorBoard encoder helper module. 

16 

17Encoder depends on TensorFlow. 

18""" 

19 

20 

21import numpy as np 

22 

23from tensorboard.util import op_evaluator 

24 

25 

26class _TensorFlowPngEncoder(op_evaluator.PersistentOpEvaluator): 

27 """Encode an image to PNG. 

28 

29 This function is thread-safe, and has high performance when run in 

30 parallel. See `encode_png_benchmark.py` for details. 

31 

32 Arguments: 

33 image: A numpy array of shape `[height, width, channels]`, where 

34 `channels` is 1, 3, or 4, and of dtype uint8. 

35 

36 Returns: 

37 A bytestring with PNG-encoded data. 

38 """ 

39 

40 def __init__(self): 

41 super().__init__() 

42 self._image_placeholder = None 

43 self._encode_op = None 

44 

45 def initialize_graph(self): 

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

47 import tensorflow.compat.v1 as tf 

48 

49 self._image_placeholder = tf.placeholder( 

50 dtype=tf.uint8, name="image_to_encode" 

51 ) 

52 self._encode_op = tf.image.encode_png(self._image_placeholder) 

53 

54 def run(self, image): # pylint: disable=arguments-differ 

55 if not isinstance(image, np.ndarray): 

56 raise ValueError("'image' must be a numpy array: %r" % image) 

57 if image.dtype != np.uint8: 

58 raise ValueError( 

59 "'image' dtype must be uint8, but is %r" % image.dtype 

60 ) 

61 return self._encode_op.eval(feed_dict={self._image_placeholder: image}) 

62 

63 

64encode_png = _TensorFlowPngEncoder() 

65 

66 

67class _TensorFlowWavEncoder(op_evaluator.PersistentOpEvaluator): 

68 """Encode an audio clip to WAV. 

69 

70 This function is thread-safe and exhibits good parallel performance. 

71 

72 Arguments: 

73 audio: A numpy array of shape `[samples, channels]`. 

74 samples_per_second: A positive `int`, in Hz. 

75 

76 Returns: 

77 A bytestring with WAV-encoded data. 

78 """ 

79 

80 def __init__(self): 

81 super().__init__() 

82 self._audio_placeholder = None 

83 self._samples_per_second_placeholder = None 

84 self._encode_op = None 

85 

86 def initialize_graph(self): 

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

88 import tensorflow.compat.v1 as tf 

89 

90 self._audio_placeholder = tf.placeholder( 

91 dtype=tf.float32, name="image_to_encode" 

92 ) 

93 self._samples_per_second_placeholder = tf.placeholder( 

94 dtype=tf.int32, name="samples_per_second" 

95 ) 

96 self._encode_op = tf.audio.encode_wav( 

97 self._audio_placeholder, 

98 sample_rate=self._samples_per_second_placeholder, 

99 ) 

100 

101 def run( 

102 self, audio, samples_per_second 

103 ): # pylint: disable=arguments-differ 

104 if not isinstance(audio, np.ndarray): 

105 raise ValueError("'audio' must be a numpy array: %r" % audio) 

106 if not isinstance(samples_per_second, int): 

107 raise ValueError( 

108 "'samples_per_second' must be an int: %r" % samples_per_second 

109 ) 

110 feed_dict = { 

111 self._audio_placeholder: audio, 

112 self._samples_per_second_placeholder: samples_per_second, 

113 } 

114 return self._encode_op.eval(feed_dict=feed_dict) 

115 

116 

117encode_wav = _TensorFlowWavEncoder()