list(4L, 20L) -> list(c(0.25, 0.1), c(0.6, -0.2)) This layer
can only be used as the first layer in a model.
layer_embedding( object, input_dim, output_dim, embeddings_initializer = "uniform", embeddings_regularizer = NULL, activity_regularizer = NULL, embeddings_constraint = NULL, mask_zero = FALSE, input_length = NULL, batch_size = NULL, name = NULL, trainable = NULL, weights = NULL )
What to compose the new
int > 0. Size of the vocabulary, i.e. maximum integer index + 1.
int >= 0. Dimension of the dense embedding.
Initializer for the
Regularizer function applied to the
Constraint function applied to the
Whether or not the input value 0 is a special "padding"
value that should be masked out. This is useful when using recurrent
layers, which may take variable length inputs. If this is
Length of input sequences, when it is constant. This
argument is required if you are going to connect
Fixed batch size for layer
An optional name string for the layer. Should be unique in a model (do not reuse the same name twice). It will be autogenerated if it isn't provided.
Whether the layer weights will be updated during training.
Initial weights for layer.
2D tensor with shape:
3D tensor with shape:
(batch_size, sequence_length, output_dim).