def __init__(self, params, train):
"""Initialize layers to build Transformer model.
Args:
params: hyperparameter object defining layer sizes, dropout values, etc.
train: boolean indicating whether the model is in training mode. Used to
determine if dropout layers should be added.
"""
self.train = train
self.params = params
self.embedding_softmax_layer = embedding_layer.EmbeddingSharedWeights(
params["vocab_size"],
params["hidden_size"],
method="matmul" if params["tpu"] else "gather")
self.src_encoder_input_layer = EncoderInputLayer(params, train)
self.src_encoder_stack = EncoderStack(params,
train) # encode source sentence
self.src_sent_emb_layer = SentenceEmbeddingLayer(
params, train) # embed source sentence
# debug
if self.train:
self.tgt_encoder_input_layer = EncoderInputLayer(params, train)
self.tgt_encoder_stack = EncoderStack(
params, train) # encode target sentence
self.tgt_sent_emb_layer = SentenceEmbeddingLayer(
params, train) # embed target sentence
self.latent_variable_layer = LatentVariableLayer(
params, train) # generate latent variable
#self.encoder_output_layer = EncoderOutputLayer(params, train) # generate encoder output
self.decoder_stack = DecoderStack(params, train) # decode
def __init__(self, params, train):
"""Initialize layers to build Transformer model.
Args:
params: hyperparameter object defining layer sizes, dropout values, etc.
train: boolean indicating whether the model is in training mode. Used to
determine if dropout layers should be added.
"""
self.train = train
self.params = params
self.embedding_softmax_layer = embedding_layer.EmbeddingSharedWeights(
params.vocab_size, params.hidden_size)
self.encoder_stack = EncoderStack(params, train)
self.decoder_stack = DecoderStack(params, train)
def __init__(self, params, train):
"""Initialize layers to build Transformer model.
Args:
params: hyperparameter object defining layer sizes, dropout values, etc.
train: boolean indicating whether the model is in training mode. Used to
determine if dropout layers should be added.
"""
self.train = train # 这个train是一个标志，指示是什么模式
self.params = params
self.embedding_softmax_layer = embedding_layer.EmbeddingSharedWeights( # 不知道干了啥
params["vocab_size"],
params["hidden_size"],
method="matmul" if params["tpu"] else "gather")
self.encoder_stack = EncoderStack(params, train)
self.decoder_stack = DecoderStack(params, train)
def __init__(self, params, train):
"""Initialize layers to build Transformer model.
Args:参数：
params: hyperparameter object defining layer sizes, dropout values, etc. 超参们
train: boolean indicating whether the model is in training mode. Used to 那些bool们
determine if dropout layers should be added.
"""
self.train = train
self.params = params
# 定义embedding层词库大小、向量维度（为什么名字还带个softmax呢？？？）
self.embedding_softmax_layer = embedding_layer.EmbeddingSharedWeights(
params["vocab_size"],
params["hidden_size"],
method="matmul" if params["tpu"] else "gather")
# 定义encoder和decoder层（主要定义层数、向量尺寸、dropout）
self.encoder_stack = EncoderStack(params, train)
self.decoder_stack = DecoderStack(params, train)
