def default_params(): params = BasicSeq2Seq.default_params().copy() params.update({ "attention.class": "AttentionLayerBahdanau", "attention.params": {"num_units": 150}, "bridge.class": "seq2seq.models.bridges.ZeroBridge", "encoder.class": "seq2seq.encoders.BidirectionalRNNEncoder", "encoder.params": {"rnn_cell": {"cell_class": "LSTMCell", "cell_params": {"num_units": 150}, "dropout_input_keep_prob": 0.5, "dropout_output_keep_prob": 0.5, "num_layers": 1}}, "decoder.class": "seq2seq.decoders.AttentionDecoder", "decoder.params": {"max_decode_length": 250, "rnn_cell": {"cell_class": "LSTMCell", "cell_params": {"num_units": 150}, "dropout_input_keep_prob": 0.5, "dropout_output_keep_prob": 0.5, "num_layers": 1}}, "optimizer.name": "Adam", "optimizer.params": {"epsilon": 0.0000008}, "optimizer.learning_rate": 0.0005, "source.max_seq_len": 50, "source.reverse": False, "target.max_seq_len": 250, }) return params
def default_params(): params = BasicSeq2Seq.default_params().copy() params.update({ "attention.dim": 128, "attention.score_type": "dot", "bridge_spec": { "class": "ZeroBridge", }, }) return params
def default_params(): params = BasicSeq2Seq.default_params().copy() params.update({ "attention.class": "AttentionLayerBahdanau", "attention.params": {}, # Arbitrary attention layer parameters "bridge.class": "seq2seq.models.bridges.ZeroBridge", "encoder.class": "seq2seq.encoders.BidirectionalRNNEncoder", "encoder.params": {}, # Arbitrary parameters for the encoder "decoder.class": "seq2seq.decoders.AttentionDecoder", "decoder.params": {} # Arbitrary parameters for the decoder }) return params
def default_params(): params = BasicSeq2Seq.default_params().copy() params.update({ "bridge.class": "seq2seq.models.bridges.InitialStateBridge", "bridge.params": {}, "encoder.class": "seq2seq.encoders.UnidirectionalRNNEncoder", "encoder.params": {}, # Arbitrary parameters for the encoder "decoder.class": "seq2seq.decoders.BasicDecoder", "decoder.params": {}, # Arbitrary parameters for the decoder "source_candidate.max_seq_len": 20, "source_candidate.reverse": True, "vocab_source_candidate": None }) return params