layer_average_pooling_2d {keras} | R Documentation

## Average pooling operation for spatial data.

### Description

Average pooling operation for spatial data.

### Usage

    layer_average_pooling_2d(object, pool_size = c(2L, 2L), strides = NULL,
      padding = "valid", data_format = NULL, batch_size = NULL,
      name = NULL, trainable = NULL, weights = NULL)

### Arguments

`object` | Model or layer object
`pool_size` | integer or list of 2 integers, factors by which to downscale (vertical, horizontal). (2, 2) will halve the input in both spatial dimension. If only one integer is specified, the same window length will be used for both dimensions.
`strides` | Integer, list of 2 integers, or NULL. Strides values. If NULL, it will default to `pool_size`.
`padding` | One of `"valid"` or `"same"` (case-insensitive).
`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

- If `data_format='channels_last'`: 4D tensor with shape: `(batch_size, pooled_rows, pooled_cols, channels)`

- If `data_format='channels_first'`: 4D tensor with shape: `(batch_size, channels, pooled_rows, pooled_cols)`

### See Also

Other pooling layers: `layer_average_pooling_1d`, `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_2d`, `layer_global_max_pooling_3d`, `layer_max_pooling_1d`, `layer_max_pooling_2d`, `layer_max_pooling_3d`

[Package keras version 2.2.4 Index]