layer_upsampling_3d
Upsampling layer for 3D inputs.
Description
Repeats the 1st, 2nd and 3rd dimensions of the data by size[[0]]
, size[[1]]
and size[[2]]
respectively.
Usage
layer_upsampling_3d(
object, size = c(2L, 2L, 2L),
data_format = NULL,
batch_size = NULL,
name = NULL,
trainable = NULL,
weights = NULL
)
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. |
size | int, or list of 3 integers. The upsampling factors for dim1, dim2 and dim3. |
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”. |
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. |
Section
Input shape
5D tensor with shape:
If
data_format
is"channels_last"
:(batch, dim1, dim2, dim3, channels)
If
data_format
is"channels_first"
:(batch, channels, dim1, dim2, dim3)
Output shape
5D tensor with shape:
If
data_format
is"channels_last"
:(batch, upsampled_dim1, upsampled_dim2, upsampled_dim3, channels)
If
data_format
is"channels_first"
:(batch, channels, upsampled_dim1, upsampled_dim2, upsampled_dim3)
See Also
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_1d()
, layer_depthwise_conv_2d()
, layer_separable_conv_1d()
, layer_separable_conv_2d()
, layer_upsampling_1d()
, layer_upsampling_2d()
, layer_zero_padding_1d()
, layer_zero_padding_2d()
, layer_zero_padding_3d()