@docstring_util.expand_docstring(args=doc_args)<EOL><INDENT>def __init__(<EOL>self,<EOL>filters,<EOL>kernel_size,<EOL>strides=<NUM_LIT:1>,<EOL>padding='<STR_LIT>',<EOL>data_format='<STR_LIT>',<EOL>dilation_rate=<NUM_LIT:1>,<EOL>activation=None,<EOL>activity_regularizer=None,<EOL>kernel_posterior_fn=tfp_layers_util.default_mean_field_normal_fn(),<EOL>kernel_posterior_tensor_fn=lambda d: d.sample(),<EOL>kernel_prior_fn=tfp_layers_util.default_multivariate_normal_fn,<EOL>kernel_divergence_fn=lambda q, p, ignore: tfd.kl_divergence(q, p),<EOL>bias_posterior_fn=tfp_layers_util.default_mean_field_normal_fn(is_singular=True),  <EOL>bias_posterior_tensor_fn=lambda d: d.sample(),<EOL>bias_prior_fn=None,<EOL>bias_divergence_fn=lambda q, p, ignore: tfd.kl_divergence(q, p),<EOL>seed=None,<EOL>**kwargs):<EOL><DEDENT>
<EOL>super(Conv1DFlipout, self).__init__(<EOL>rank=<NUM_LIT:1>,<EOL>filters=filters,<EOL>kernel_size=kernel_size,<EOL>strides=strides,<EOL>padding=padding,<EOL>data_format=data_format,<EOL>dilation_rate=dilation_rate,<EOL>activation=tf.keras.activations.get(activation),<EOL>activity_regularizer=activity_regularizer,<EOL>kernel_posterior_fn=kernel_posterior_fn,<EOL>kernel_posterior_tensor_fn=kernel_posterior_tensor_fn,<EOL>kernel_prior_fn=kernel_prior_fn,<EOL>kernel_divergence_fn=kernel_divergence_fn,<EOL>bias_posterior_fn=bias_posterior_fn,<EOL>bias_posterior_tensor_fn=bias_posterior_tensor_fn,<EOL>bias_prior_fn=bias_prior_fn,<EOL>bias_divergence_fn=bias_divergence_fn,<EOL>seed=seed,<EOL>**kwargs)<EOL>
Construct layer.

        Args:
          filters: Integer, the dimensionality of the output space (i.e. the number
            of filters in the convolution).
          kernel_size: An integer or tuple/list of a single integer, specifying the
            length of the 1D convolution window.
          strides: An integer or tuple/list of a single integer,
            specifying the stride length of the convolution.
            Specifying any stride value != 1 is incompatible with specifying
            any `dilation_rate` value != 1.
          padding: One of `"valid"` or `"same"` (case-insensitive).
          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, length,
            channels)` while `channels_first` corresponds to inputs with shape
            `(batch, channels, length)`.
          dilation_rate: An integer or tuple/list of a single integer, specifying
            the dilation rate to use for dilated convolution.
            Currently, specifying any `dilation_rate` value != 1 is
            incompatible with specifying any `strides` value != 1.
          ${args}
          seed: Python scalar `int` which initializes the random number
            generator. Default value: `None` (i.e., use global seed).