Dense, linear transformation layer.
tfm.nlp.layers.LinearTransformLayer(
kernel_initializer: _Initializer = default_kernel_initializer,
name: str = 'linear_transform',
**kwargs
)
Applies matrix multiplications over sequence and hidden dimensions.
Args |
kernel_initializer
|
Initialization scheme for kernel.
|
name
|
Name for layer.
|
**kwargs
|
Keyword arguments.
|
Methods
call
View source
call(
query: tf.Tensor, value: tf.Tensor, **kwargs
) -> tf.Tensor
Applies layer to query
.
Args |
query
|
Batch of input embeddings, typically of shape [batch_size,
max_seq_length, hidden_dim].
|
value
|
Unused. Included to match attention layer API.
|
**kwargs
|
Optional arguments to catch unused attention keyword arguments.
|
Returns |
Linearly transformed query inputs with shape
[batch_size, max_seq_length, hidden_dim].
|