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tf.keras.layers.UpSampling3D

TensorFlow 1 version View source on GitHub

Class UpSampling3D

Upsampling layer for 3D inputs.

Inherits From: Layer

Aliases:

Repeats the 1st, 2nd and 3rd dimensions of the data by size[0], size[1] and size[2] respectively.

Arguments:

  • size: Int, or tuple 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".

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)

__init__

View source

__init__(
    size=(2, 2, 2),
    data_format=None,
    **kwargs
)