layer_dot: Layer that computes a dot product between samples in two...

In keras: R Interface to 'Keras'

Layer that computes a dot product between samples in two tensors.

Description

Layer that computes a dot product between samples in two tensors.

Usage

layer_dot(inputs, ..., axes, normalize = FALSE)

Arguments

inputs	A input tensor, or list of input tensors. Can be missing.
...	Unnamed args are treated as additional inputs. Named arguments are passed on as standard layer arguments.
axes	Integer or list of integers, axis or axes along which to take the dot product.
normalize	Whether to L2-normalize samples along the dot product axis before taking the dot product. If set to TRUE, then the output of the dot product is the cosine proximity between the two samples.

Value

If inputs is supplied: A tensor, the dot product of the samples from the inputs. If inputs is missing, a keras layer instance is returned.

See Also

• https://www.tensorflow.org/api_docs/python/tf/keras/layers/dot

• https://keras.io/api/layers/merging_layers/dot/

Other merge layers: layer_average(), layer_concatenate(), layer_maximum(), layer_minimum(), layer_multiply(), layer_subtract()

keras documentation built on May 29, 2024, 3:20 a.m.