W3cubDocs

/TensorFlow 2.3

tf.keras.layers.GlobalMaxPool2D

View source on GitHub

Global max pooling operation for spatial data.

Examples:

input_shape = (2, 4, 5, 3)
x = tf.random.normal(input_shape)
y = tf.keras.layers.GlobalMaxPool2D()(x)
print(y.shape)
(2, 3)
Arguments
data_format A string, one of channels_last (default) or channels_first. The ordering of the dimensions in the inputs. channels_last corresponds to inputs with shape (batch, height, width, channels) while channels_first corresponds to inputs with shape (batch, channels, height, width). It defaults to the image_data_format value found in your Keras config file at ~/.keras/keras.json. If you never set it, then it will be "channels_last".

Input shape:

  • If data_format='channels_last': 4D tensor with shape (batch_size, rows, cols, channels).
  • If data_format='channels_first': 4D tensor with shape (batch_size, channels, rows, cols).

Output shape:

2D tensor with shape (batch_size, channels).

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/keras/layers/GlobalMaxPool2D