Conv2DTranspose¶

__init__¶

Conv2DTranspose.__init__(
  filters,
  kernel_size,
  strides=(1, 1),
  padding='valid',
  output_padding=None,
  data_format=None,
  dilation_rate=(1, 1),
  activation=None,
  use_bias=True,
  kernel_initializer='glorot_uniform',
  bias_initializer='zeros',
  kernel_regularizer=None,
  bias_regularizer=None,
  **kwargs
)[source]¶

Create a Conv2DTranspose Layer.

Parameters:

• filters (int) – The number of output filters.
• kernel_size (Sequence[int]) – The shape of convolution kernel.
• strides (Sequence[int], optional) – The stride(s) of sliding window.
• padding (Union[{'valid', 'same'}, Sequence[int]], optional) – The padding algorithm or padding sizes.
• output_padding (Sequence[int], optional) – The sizes of padded to the output.
• data_format ({'channels_first', 'channels_last'}, optional) – The optional data format.
• dilation_rate (Sequence[int], optional) – The rate(s) of dilated kernel.
• activation (Union[callable, str], optional) – The optional activation function.
• use_bias (bool, optional, default=True) – True to apply a bias.
• kernel_initializer (Union[callable, str], optional) – The initializer for kernel.
• bias_initializer (Union[callable, str], optional) – The initializer for bias.
• kernel_regularizer (Union[callable, str], optional) – The regularizer for kernel.
• bias_regularizer (Union[callable, str], optional) – The regularizer for bias.