tf.keras.backend.local_conv1d

View source on GitHub

Apply 1D conv with un-shared weights.

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'.