function conv1d$2(args) {
	  return new Conv1D(args);
	}
1D convolution layer (e.g., temporal convolution).

This layer creates a convolution kernel that is convolved
with the layer input over a single spatial (or temporal) dimension
to produce a tensor of outputs.

If `use_bias` is True, a bias vector is created and added to the outputs.

If `activation` is not `null`, it is applied to the outputs as well.

When using this layer as the first layer in a model, provide an
`inputShape` argument `Array` or `null`.

For example, `inputShape` would be:
- `[10, 128]` for sequences of 10 vectors of 128-dimensional vectors
- `[null, 128]` for variable-length sequences of 128-dimensional vectors.

@doc {heading: 'Layers', subheading: 'Convolutional',  namespace: 'layers'}