def __init__(self, params, mode, name): GraphModule.__init__(self, name) Configurable.__init__(self, params, mode) self.params["rnn_cell"] = _toggle_dropout(self.params["rnn_cell"], mode) self.cell = training_utils.get_rnn_cell(**self.params["rnn_cell"]) # Not initialized yet self.initial_state = None self.helper = None
def __init__(self, params, mode, name): GraphModule.__init__(self, name) Configurable.__init__(self, params, mode) self.params["rnn_cell"] = _toggle_dropout(self.params["rnn_cell"], mode) self.cell = training_utils.get_rnn_cell(**self.params["rnn_cell"]) # Not initialized yet self.initial_state = None self.helper = None
def __init__(self,
params,
mode,
vocab_size,
config,
target_embedding,
pos_embedding,
start_tokens,
name="conv_decoder_fairseq"):
GraphModule.__init__(self, name)
Configurable.__init__(self, params, mode)
self.vocab_size = vocab_size
self.config=config
self.target_embedding=target_embedding
self.start_tokens=start_tokens
self._combiner_fn = locate(self.params["position_embeddings.combiner_fn"])
self.pos_embed = pos_embedding
self.current_inputs = None
self.initial_state = None
def __init__(self,
params,
mode,
vocab_size,
config,
target_embedding,
pos_embedding,
start_tokens,
name="conv_decoder_fairseq"):
GraphModule.__init__(self, name)
Configurable.__init__(self, params, mode)
self.vocab_size = vocab_size
self.config = config
self.target_embedding = target_embedding
self.start_tokens = start_tokens
self._combiner_fn = locate(
self.params["position_embeddings.combiner_fn"])
self.pos_embed = pos_embedding
self.current_inputs = None
self.initial_state = None
def __init__(self, params, mode, name):
GraphModule.__init__(self, name)
Configurable.__init__(self, params, mode)
self.params["rnn_cell"] = _toggle_dropout(
self.params["rnn_cell"],
["dropout_input_keep_prob", "dropout_output_keep_prob"], mode)
self.params["dropout_decoder"] = _toggle_dropout(
self.params["dropout_decoder"], ["dropout_deep_output_layer"],
mode)
with tf.variable_scope("rec1"):
self.cell_rec1 = training_utils.get_rnn_cell(
**self.params["rnn_cell"])
with tf.variable_scope("rec2"):
self.cell_rec2 = training_utils.get_rnn_cell(
**self.params["rnn_cell"])
# Not initialized yet
self.initial_state = None
self.helper = None
def __init__(self):
GraphModule.__init__(self, name)
Configurable.__init__(self, params, mode)
def __init__(self, params, mode, name="attention"):
GraphModule.__init__(self, name)
Configurable.__init__(self, params, mode)
def __init__(self, params, mode, name="attention"): GraphModule.__init__(self, name) Configurable.__init__(self, params, mode)
def __init__(self, params, mode, vocab_size, name="inception_deocder"):
GraphModule.__init__(self, name)
Configurable.__init__(self, params, mode)
self.vocab_size = vocab_size
