layer_global_average_pooling_3d
Global Average pooling operation for 3D data.
Description
Global Average pooling operation for 3D data.
Usage
layer_global_average_pooling_3d(
object, data_format = NULL,
keepdims = FALSE,
... )
Arguments
Arguments | Description |
---|---|
object | What to compose the new Layer instance with. Typically a Sequential model or a Tensor (e.g., as returned by layer_input() ). The return value depends on object . If object is: - missing or NULL , the Layer instance is returned. - a Sequential model, the model with an additional layer is returned. - a Tensor, the output tensor from layer_instance(object) is returned. |
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, spatial_dim1, spatial_dim2, spatial_dim3, channels) while channels_first corresponds to inputs with shape (batch, channels, spatial_dim1, spatial_dim2, spatial_dim3) . 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”. |
keepdims | A boolean, whether to keep the spatial dimensions or not. If keepdims is FALSE (default), the rank of the tensor is reduced for spatial dimensions. If keepdims is TRUE , the spatial dimensions are retained with length 1. The behavior is the same as for tf.reduce_mean or np.mean . |
… | standard layer arguments. |
Section
Input shape
If
data_format='channels_last'
: 5D tensor with shape:(batch_size, spatial_dim1, spatial_dim2, spatial_dim3, channels)
If
data_format='channels_first'
: 5D tensor with shape:(batch_size, channels, spatial_dim1, spatial_dim2, spatial_dim3)
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_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()