Zero-padding layer for 3D data (spatial or spatio-temporal).
Zero-padding layer for 3D data (spatial or spatio-temporal).
layer_zero_padding_3d( object, padding = c(1L, 1L, 1L), data_format = NULL, batch_size = NULL, name = NULL, trainable = NULL, weights = NULL )
object |
Model or layer object |
padding |
int, or list of 3 ints, or list of 3 lists of 2 ints.
|
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. |
5D tensor with shape:
If data_format
is "channels_last"
: (batch, first_axis_to_pad, second_axis_to_pad, third_axis_to_pad, depth)
If data_format
is "channels_first"
: (batch, depth, first_axis_to_pad, second_axis_to_pad, third_axis_to_pad)
5D tensor with shape:
If data_format
is "channels_last"
: (batch, first_padded_axis, second_padded_axis, third_axis_to_pad, depth)
If data_format
is "channels_first"
: (batch, depth, first_padded_axis, second_padded_axis, third_axis_to_pad)
Other convolutional layers:
layer_conv_1d_transpose()
,
layer_conv_1d()
,
layer_conv_2d_transpose()
,
layer_conv_2d()
,
layer_conv_3d_transpose()
,
layer_conv_3d()
,
layer_conv_lstm_2d()
,
layer_cropping_1d()
,
layer_cropping_2d()
,
layer_cropping_3d()
,
layer_depthwise_conv_2d()
,
layer_separable_conv_1d()
,
layer_separable_conv_2d()
,
layer_upsampling_1d()
,
layer_upsampling_2d()
,
layer_upsampling_3d()
,
layer_zero_padding_1d()
,
layer_zero_padding_2d()
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