layer_max_pooling_3d.Rd
Max pooling operation for 3D data (spatial or spatio-temporal).
layer_max_pooling_3d(object, pool_size = c(2L, 2L, 2L), strides = NULL, padding = "valid", data_format = NULL, batch_size = NULL, name = NULL, trainable = NULL, weights = NULL)
object | Model or layer object |
---|---|
pool_size | list of 3 integers, factors by which to downscale (dim1, dim2, dim3). (2, 2, 2) will halve the size of the 3D input in each dimension. |
strides | list of 3 integers, or NULL. Strides values. |
padding | One of |
data_format | A string, one of |
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. |
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)
If data_format='channels_last'
: 5D tensor with shape: (batch_size, pooled_dim1, pooled_dim2, pooled_dim3, channels)
If data_format='channels_first'
: 5D tensor with shape: (batch_size, channels, pooled_dim1, pooled_dim2, pooled_dim3)
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_2d
,
layer_global_max_pooling_3d
,
layer_max_pooling_1d
,
layer_max_pooling_2d