Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.8/site-packages/keras/src/layers/merging/average.py: 62%

1# Copyright 2015 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"""Layer that averages several inputs.""" 

16 

17 

18from keras.src.layers.merging.base_merge import _Merge 

19 

20# isort: off 

21from tensorflow.python.util.tf_export import keras_export 

22 

23 

24@keras_export("keras.layers.Average") 

25class Average(_Merge): 

26 """Layer that averages a list of inputs element-wise. 

27 

28 It takes as input a list of tensors, all of the same shape, and returns 

29 a single tensor (also of the same shape). 

30 

31 Example: 

32 

33 >>> x1 = np.ones((2, 2)) 

34 >>> x2 = np.zeros((2, 2)) 

35 >>> y = tf.keras.layers.Average()([x1, x2]) 

36 >>> y.numpy().tolist() 

37 [[0.5, 0.5], [0.5, 0.5]] 

38 

39 Usage in a functional model: 

40 

41 >>> input1 = tf.keras.layers.Input(shape=(16,)) 

42 >>> x1 = tf.keras.layers.Dense(8, activation='relu')(input1) 

43 >>> input2 = tf.keras.layers.Input(shape=(32,)) 

44 >>> x2 = tf.keras.layers.Dense(8, activation='relu')(input2) 

45 >>> avg = tf.keras.layers.Average()([x1, x2]) 

46 >>> out = tf.keras.layers.Dense(4)(avg) 

47 >>> model = tf.keras.models.Model(inputs=[input1, input2], outputs=out) 

48 

49 Raises: 

50 ValueError: If there is a shape mismatch between the inputs and the shapes 

51 cannot be broadcasted to match. 

52 """ 

53 

54 def _merge_function(self, inputs): 

55 output = inputs[0] 

56 for i in range(1, len(inputs)): 

57 output += inputs[i] 

58 return output / len(inputs) 

59 

60 

61@keras_export("keras.layers.average") 

62def average(inputs, **kwargs): 

63 """Functional interface to the `tf.keras.layers.Average` layer. 

64 

65 Example: 

66 

67 >>> x1 = np.ones((2, 2)) 

68 >>> x2 = np.zeros((2, 2)) 

69 >>> y = tf.keras.layers.Average()([x1, x2]) 

70 >>> y.numpy().tolist() 

71 [[0.5, 0.5], [0.5, 0.5]] 

72 

73 Usage in a functional model: 

74 

75 >>> input1 = tf.keras.layers.Input(shape=(16,)) 

76 >>> x1 = tf.keras.layers.Dense(8, activation='relu')(input1) 

77 >>> input2 = tf.keras.layers.Input(shape=(32,)) 

78 >>> x2 = tf.keras.layers.Dense(8, activation='relu')(input2) 

79 >>> avg = tf.keras.layers.Average()([x1, x2]) 

80 >>> out = tf.keras.layers.Dense(4)(avg) 

81 >>> model = tf.keras.models.Model(inputs=[input1, input2], outputs=out) 

82 

83 Args: 

84 inputs: A list of input tensors. 

85 **kwargs: Standard layer keyword arguments. 

86 

87 Returns: 

88 A tensor, the average of the inputs. 

89 

90 Raises: 

91 ValueError: If there is a shape mismatch between the inputs and the shapes 

92 cannot be broadcasted to match. 

93 """ 

94 return Average(**kwargs)(inputs) 

95