function dense(args) {
	  return new Dense(args);
	}
Creates a dense (fully connected) layer.

This layer implements the operation:
  `output = activation(dot(input, kernel) + bias)`

`activation` is the element-wise activation function
  passed as the `activation` argument.

`kernel` is a weights matrix created by the layer.

`bias` is a bias vector created by the layer (only applicable if `useBias`
is `true`).

**Input shape:**

  nD `tf.Tensor` with shape: `(batchSize, ..., inputDim)`.

  The most common situation would be
  a 2D input with shape `(batchSize, inputDim)`.

**Output shape:**

  nD tensor with shape: `(batchSize, ..., units)`.

  For instance, for a 2D input with shape `(batchSize, inputDim)`,
  the output would have shape `(batchSize, units)`.

Note: if the input to the layer has a rank greater than 2, then it is
flattened prior to the initial dot product with the kernel.

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