tf.layers.DenseLayer module

tf.layers.DenseLayer module

class tf.layers.DenseLayer.DenseLayer(*args: Any, **kwargs: Any)

Bases: modelzoo.common.tf.layers.BaseLayer.BaseLayer

Wrapper around the Keras densely-connected layer. Provides support for "gelu" activation.

Parameters

  • units (int) – Number of units in the layer output.

  • activation (Optional[Union[str, Callable]]) – If not None, an activation function to be applied after the dense layer. The activation function can either be a callable string name of a Tensorflow built-in activation, or "gelu".

  • use_bias (bool) – Whether to use bias.

  • kernel_initializer (str) – Kernel intializer. Defaults to "glorot_uniform".

  • kernel_initializer – Bias intializer. Defaults to "zeros".

  • kernel_regularizer (Optional[Callable]) – Kernel regularizer. Defaults to None.

  • bias_regularizer (Optional[Callable]) – Bias regularizer. Defaults to None.

  • activity_regularizer (Optional[Callable]) – Activity (output activation) regularizer. Defaults to None.

  • kernel_constraint (Optional[Callable]) – Kernel constraint. Defaults to None.

  • bias_constraint (Optional[Callable]) – Bias constraint. Defaults to None.

  • boundary_casting (bool) – If True, outputs the values in half precision and casts the input values up to full precision.

  • tf_summary (bool) – If True, saves the activations with summary_layer.

call(inputs, **kwargs)

Apply the densely-connected layer.

Parameters

inputs (Tensor) – An N-D tensor with shape: (batch_size, ..., input_dim).

Returns

An N-D tensor with shape: (batch_size, ..., units).

Return type

Tensor

previous

tf.layers.CrossEntropyFromLogitsLayer module

next

tf.layers.DropoutLayer module