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({
"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