def __init__(self, params):
super(PGN, self).__init__()
self.params = params
self.encoder = Encoder(params["vocab_size"], params["embed_size"],
params["enc_units"], params["batch_size"])
self.attention = LuongAttention(params["attn_units"])
self.decoder = Decoder(params["vocab_size"], params["embed_size"],
params["dec_units"], params["batch_size"])
self.pointer = Pointer()
def __init__(self, params, embeddings_matrix):
super(PGN, self).__init__()
self.params = params
self.encoder = Encoder(params["vocab_size"], params["embed_size"],
params["enc_units"], params["batch_size"],
embeddings_matrix)
self.attention = BahdanauAttention(params["attn_units"])
self.decoder = Decoder(params["vocab_size"], params["embed_size"],
params["dec_units"], params["batch_size"],
embeddings_matrix)
self.pointer = Pointer()
def __init__(self, params):
super(PGN, self).__init__()
self.params = params
self.encoder = Encoder(params["vocab_size"], params["embed_size"],
params["enc_units"], params["batch_size"])
self.attention = BahdanauAttention(params["attn_units"])
if params["coverage"]:
self.coverage = Coverage(params["attn_units"])
self.decoder = Decoder(params["vocab_size"], params["embed_size"],
params["dec_units"], params["batch_size"],
params["use_stats"])
self.pointer = Pointer()
def __init__(self, params):
super(PGN, self).__init__()
word_model_path = os.path.join(os.path.abspath('../'), 'data',
'w2v.model')
vocab_path = os.path.join(os.path.abspath('../'), 'data',
'words_frequences.txt')
self.params = params
self.matrix = get_embedding(vocab_path, word_model_path, params)
self.encoder = Encoder(params["vocab_size"], params["embed_size"],
self.matrix, params["enc_units"],
params["batch_size"])
self.attention = BahdanauAttention(params["attn_units"])
self.decoder = Decoder(params["vocab_size"], params["embed_size"],
self.matrix, params["dec_units"],
params["batch_size"])
self.pointer = Pointer()