layer_embedding
Turns positive integers (indexes) into dense vectors of fixed size.
Description
For example, 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.
Usage
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
) Arguments
| Arguments | Description |
|---|---|
| object | What to compose the new Layer instance with. Typically a Sequential model or a Tensor (e.g., as returned by layer_input()). The return value depends on object. If object is: - missing or NULL, the Layer instance is returned. - a Sequential model, the model with an additional layer is returned. - a Tensor, the output tensor from layer_instance(object) is returned. |
| input_dim | int > 0. Size of the vocabulary, i.e. maximum integer index + 1. |
| output_dim | int >= 0. Dimension of the dense embedding. |
| embeddings_initializer | Initializer for the embeddings matrix. |
| embeddings_regularizer | Regularizer function applied to the embeddings matrix. |
| activity_regularizer | activity_regularizer |
| embeddings_constraint | Constraint function applied to the embeddings matrix. |
| mask_zero | 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 TRUE then all subsequent layers in the model need to support masking or an exception will be raised. If mask_zero is set to TRUE, as a consequence, index 0 cannot be used in the vocabulary (input_dim should equal size of vocabulary + 1). |
| input_length | Length of input sequences, when it is constant. This argument is required if you are going to connect Flatten then Dense layers upstream (without it, the shape of the dense outputs cannot be computed). |
| batch_size | Fixed batch size for layer |
| name | 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. |
| trainable | Whether the layer weights will be updated during training. |
| weights | Initial weights for layer. |
Section
Input shape
2D tensor with shape: (batch_size, sequence_length).
Output shape
3D tensor with shape: (batch_size, sequence_length, output_dim).