Conv1DTranspose

class ivy.neural_net_stateful.layers.Conv1DTranspose(input_channels, output_channels, filter_size, strides, padding, output_shape=None, data_format='NWC', dilations=1, dev_str='cpu', v=None)[source]

Bases: ivy.neural_net_stateful.module.Module

__init__(input_channels, output_channels, filter_size, strides, padding, output_shape=None, data_format='NWC', dilations=1, dev_str='cpu', v=None)[source]

1D transpose convolutional layer.

Parameters
  • input_channels (int) – Number of input channels for the layer.

  • output_channels (int) – Number of output channels for the layer.

  • filter_size (int) – Size of the convolutional filter.

  • strides (int or sequence of ints) – The stride of the sliding window for each dimension of input.

  • padding (string or sequence of ints) – “SAME” or “VALID” indicating the algorithm, or list indicating the per-dimension paddings.

  • output_shape (sequence of ints, needed for TensorFlow) – Shape of the output

  • data_format (string) – “NWC” or “NCW”. Defaults to “NWC”.

  • dilations (int or sequence of ints) – The dilation factor for each dimension of input.

  • dev_str (str, optional) – device on which to create the layer’s variables ‘cuda:0’, ‘cuda:1’, ‘cpu’ etc. Default is cpu.

  • v (ivy container of variables, optional) – the variables for each of the linear layer, as a container, constructed internally by default.


Supported Frameworks:

empty jax_logo empty tf_logo empty pytorch_logo empty mxnet_logo empty numpy_logo empty