tf.layers.Layer

Base layer class.

Inherits From: Layer

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.layers.Layer

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

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

Arguments
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).

Mutable properties:

• 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.

Attributes
graph	DEPRECATED FUNCTION Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Stop using this property because tf.layers layers no longer track their graph.
scope_name