tf.keras.backend.local_conv1d

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Apply 1D conv with un-shared weights.

Aliases:

tf.keras.backend.local_conv1d(
    inputs,
    kernel,
    kernel_size,
    strides,
    data_format=None
)

Arguments:

  • inputs: 3D tensor with shape: (batch_size, steps, input_dim) if data_format is "channels_last" or (batch_size, input_dim, steps) if data_format is "channels_first".
  • kernel: the unshared weight for convolution, with shape (output_length, feature_dim, filters).
  • kernel_size: a tuple of a single integer, specifying the length of the 1D convolution window.
  • strides: a tuple of a single integer, specifying the stride length of the convolution.
  • data_format: the data format, channels_first or channels_last.

Returns:

A 3d tensor with shape: (batch_size, output_length, filters) if data_format='channels_first' or 3D tensor with shape: (batch_size, filters, output_length) if data_format='channels_last'.