Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.8/site-packages/keras/src/layers/reshaping/up_sampling1d.py: 52%

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"""Keras upsampling layer for 1D inputs.""" 

16 

17 

18import tensorflow.compat.v2 as tf 

19 

20from keras.src import backend 

21from keras.src.engine.base_layer import Layer 

22from keras.src.engine.input_spec import InputSpec 

23 

24# isort: off 

25from tensorflow.python.util.tf_export import keras_export 

26 

27 

28@keras_export("keras.layers.UpSampling1D") 

29class UpSampling1D(Layer): 

30 """Upsampling layer for 1D inputs. 

31 

32 Repeats each temporal step `size` times along the time axis. 

33 

34 Examples: 

35 

36 >>> input_shape = (2, 2, 3) 

37 >>> x = np.arange(np.prod(input_shape)).reshape(input_shape) 

38 >>> print(x) 

39 [[[ 0 1 2] 

40 [ 3 4 5]] 

41 [[ 6 7 8] 

42 [ 9 10 11]]] 

43 >>> y = tf.keras.layers.UpSampling1D(size=2)(x) 

44 >>> print(y) 

45 tf.Tensor( 

46 [[[ 0 1 2] 

47 [ 0 1 2] 

48 [ 3 4 5] 

49 [ 3 4 5]] 

50 [[ 6 7 8] 

51 [ 6 7 8] 

52 [ 9 10 11] 

53 [ 9 10 11]]], shape=(2, 4, 3), dtype=int64) 

54 

55 Args: 

56 size: Integer. Upsampling factor. 

57 

58 Input shape: 

59 3D tensor with shape: `(batch_size, steps, features)`. 

60 

61 Output shape: 

62 3D tensor with shape: `(batch_size, upsampled_steps, features)`. 

63 """ 

64 

65 def __init__(self, size=2, **kwargs): 

66 super().__init__(**kwargs) 

67 self.size = int(size) 

68 self.input_spec = InputSpec(ndim=3) 

69 

70 def compute_output_shape(self, input_shape): 

71 input_shape = tf.TensorShape(input_shape).as_list() 

72 size = ( 

73 self.size * input_shape[1] if input_shape[1] is not None else None 

74 ) 

75 return tf.TensorShape([input_shape[0], size, input_shape[2]]) 

76 

77 def call(self, inputs): 

78 output = backend.repeat_elements(inputs, self.size, axis=1) 

79 return output 

80 

81 def get_config(self): 

82 config = {"size": self.size} 

83 base_config = super().get_config() 

84 return dict(list(base_config.items()) + list(config.items())) 

85