tf.compat.v1.layers.Layer

Base layer class.

Inherits From: Layer, Module

tf.compat.v1.layers.Layer(
    trainable=True, name=None, dtype=None, **kwargs
)

It is considered legacy, and we recommend the use of tf.keras.layers.Layer instead.

trainable Boolean, whether the layer's variables should be trainable.
name String name of the layer.
dtype Default dtype of the layer's weights (default of None means use the type of the first input).

Read-only properties: name: The name of the layer (string). dtype: Default dtype of the layer's weights (default of None means use the type of the first input). trainable_variables: List of trainable variables. non_trainable_variables: List of non-trainable variables. variables: List of all variables of this layer, trainable and non-trainable. updates: List of update ops of this layer. losses: List of losses added by this layer. trainable_weights: List of variables to be included in backprop. non_trainable_weights: List of variables that should not be included in backprop. weights: The concatenation of the lists trainable_weights and non_trainable_weights (in this order).

trainable Whether the layer should be trained (boolean).
input_spec Optional (list of) InputSpec object(s) specifying the constraints on inputs that can be accepted by the layer.

graph

scope_name

Methods

apply

View source

apply(
    *args, **kwargs
)

get_losses_for

View source

get_losses_for(
    inputs
)

Retrieves losses relevant to a specific set of inputs.

Args
inputs Input tensor or list/tuple of input tensors.

Returns
List of loss tensors of the layer that depend on inputs.

get_updates_for

View source

get_updates_for(
    inputs
)

Retrieves updates relevant to a specific set of inputs.

Args
inputs Input tensor or list/tuple of input tensors.

Returns
List of update ops of the layer that depend on inputs.