neuralmonkey.encoders.facebook_conv module¶
From the paper Convolutional Sequence to Sequence Learning.
http://arxiv.org/abs/1705.03122
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class
neuralmonkey.encoders.facebook_conv.
SentenceEncoder
(name: str, input_sequence: neuralmonkey.model.sequence.EmbeddedSequence, conv_features: int, encoder_layers: int, kernel_width: int = 5, dropout_keep_prob: float = 1.0, reuse: neuralmonkey.model.model_part.ModelPart = None, save_checkpoint: str = None, load_checkpoint: str = None, initializers: List[Tuple[str, Callable]] = None) → None¶ Bases:
neuralmonkey.model.model_part.ModelPart
,neuralmonkey.model.stateful.TemporalStatefulWithOutput
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__init__
(name: str, input_sequence: neuralmonkey.model.sequence.EmbeddedSequence, conv_features: int, encoder_layers: int, kernel_width: int = 5, dropout_keep_prob: float = 1.0, reuse: neuralmonkey.model.model_part.ModelPart = None, save_checkpoint: str = None, load_checkpoint: str = None, initializers: List[Tuple[str, Callable]] = None) → None¶ Construct a new parameterized object.
Parameters: - name – The name for the model part. Will be used in the variable and name scopes.
- reuse – Optional parameterized part with which to share parameters.
- save_checkpoint – Optional path to a checkpoint file which will store the parameters of this object.
- load_checkpoint – Optional path to a checkpoint file from which to load initial variables for this object.
- initializers – An InitializerSpecs instance with specification of the initializers.
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order_embeddings
¶
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ordered_embedded_inputs
¶
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output
¶ Return the object output.
A 2D Tensor of shape (batch, state_size) which contains the resulting state of the object.
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temporal_mask
¶ Return mask for the temporal_states.
A 2D Tensor of shape (batch, time) of type float32 which masks the temporal states so each sequence can have a different length. It should only contain ones or zeros.
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temporal_states
¶ Return object states in time.
A 3D Tensor of shape (batch, time, state_size) which contains the states of the object in time (e.g. hidden states of a recurrent encoder.
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