layer_global_max_pooling_2d: Global max pooling operation for spatial data.

In dfalbel/keras: R Interface to 'Keras'

Description

Global max pooling operation for spatial data.

Usage

layer_global_max_pooling_2d(
  object,
  data_format = NULL,
  batch_size = NULL,
  name = NULL,
  trainable = NULL,
  weights = NULL
)

Arguments

object	Model or layer object
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".
batch_size	Fixed batch size for layer
name	An optional name string for the layer. Should be unique in a model (do not reuse the same name twice). It will be autogenerated if it isn't provided.
trainable	Whether the layer weights will be updated during training.
weights	Initial weights for layer.

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)

See Also

Other pooling layers: layer_average_pooling_1d(), layer_average_pooling_2d(), layer_average_pooling_3d(), layer_global_average_pooling_1d(), layer_global_average_pooling_2d(), layer_global_average_pooling_3d(), layer_global_max_pooling_1d(), layer_global_max_pooling_3d(), layer_max_pooling_1d(), layer_max_pooling_2d(), layer_max_pooling_3d()

dfalbel/keras documentation built on Nov. 27, 2019, 8:16 p.m.