d3rlpy.encoders.VectorEncoderFactory¶

class d3rlpy.encoders.VectorEncoderFactory(hidden_units=None, activation='relu', use_batch_norm=False, use_dense=False)[source]¶

Vector encoder factory class.

This is the default encoder factory for vector observation.

Parameters:	hidden_units (list) – list of hidden unit sizes. If `None`, the standard architecture with `[256, 256]` is used. activation (str) – activation function name. use_batch_norm (bool) – flag to insert batch normalization layers. use_dense (bool) – flag to use DenseNet architecture.

hidden_units¶

list of hidden unit sizes.

Type:	list

activation¶

activation function name.

Type:	str

use_batch_norm¶

flag to insert batch normalization layers.

Type:	bool

use_dense¶

flag to use DenseNet architecture.

Type:	bool

Methods

create(observation_shape, action_size=None, discrete_action=False)[source]¶

Returns PyTorch’s enocder module.

Parameters:	observation_shape (tuple) – observation shape. action_size (int) – action size. If None, the encoder does not take action as input. discrete_action (bool) – flag if action-space is discrete.
Returns:	an enocder object.
Return type:	torch.nn.Module

get_params(deep=False)[source]¶

Returns encoder parameters.

Parameters:	deep (bool) – flag to deeply copy the parameters.
Returns:	encoder parameters.
Return type:	dict

get_type()¶

Returns encoder type.

Returns:	encoder type.
Return type:	str

Attributes