Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.8/site-packages/keras/src/layers/pooling/global_max_pooling2d.py: 73%

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"""Global max pooling 2D layer.""" 

16 

17 

18from keras.src import backend 

19from keras.src.layers.pooling.base_global_pooling2d import GlobalPooling2D 

20 

21# isort: off 

22from tensorflow.python.util.tf_export import keras_export 

23 

24 

25@keras_export("keras.layers.GlobalMaxPooling2D", "keras.layers.GlobalMaxPool2D") 

26class GlobalMaxPooling2D(GlobalPooling2D): 

27 """Global max pooling operation for spatial data. 

28 

29 Examples: 

30 

31 >>> input_shape = (2, 4, 5, 3) 

32 >>> x = tf.random.normal(input_shape) 

33 >>> y = tf.keras.layers.GlobalMaxPooling2D()(x) 

34 >>> print(y.shape) 

35 (2, 3) 

36 

37 Args: 

38 data_format: A string, 

39 one of `channels_last` (default) or `channels_first`. 

40 The ordering of the dimensions in the inputs. 

41 `channels_last` corresponds to inputs with shape 

42 `(batch, height, width, channels)` while `channels_first` 

43 corresponds to inputs with shape 

44 `(batch, channels, height, width)`. 

45 It defaults to the `image_data_format` value found in your 

46 Keras config file at `~/.keras/keras.json`. 

47 If you never set it, then it will be "channels_last". 

48 keepdims: A boolean, whether to keep the spatial dimensions or not. 

49 If `keepdims` is `False` (default), the rank of the tensor is reduced 

50 for spatial dimensions. 

51 If `keepdims` is `True`, the spatial dimensions are retained with 

52 length 1. 

53 The behavior is the same as for `tf.reduce_max` or `np.max`. 

54 

55 Input shape: 

56 - If `data_format='channels_last'`: 

57 4D tensor with shape `(batch_size, rows, cols, channels)`. 

58 - If `data_format='channels_first'`: 

59 4D tensor with shape `(batch_size, channels, rows, cols)`. 

60 

61 Output shape: 

62 - If `keepdims`=False: 

63 2D tensor with shape `(batch_size, channels)`. 

64 - If `keepdims`=True: 

65 - If `data_format='channels_last'`: 

66 4D tensor with shape `(batch_size, 1, 1, channels)` 

67 - If `data_format='channels_first'`: 

68 4D tensor with shape `(batch_size, channels, 1, 1)` 

69 """ 

70 

71 def call(self, inputs): 

72 if self.data_format == "channels_last": 

73 return backend.max(inputs, axis=[1, 2], keepdims=self.keepdims) 

74 else: 

75 return backend.max(inputs, axis=[2, 3], keepdims=self.keepdims) 

76 

77 

78# Alias 

79 

80GlobalMaxPool2D = GlobalMaxPooling2D 

81