Constructor for BertModel. Args: config: `BertConfig` instance. is_training: bool. true for training model, false for eval model. Con

Constructs a InputExample. Args: guid: Unique id for the example. text_a: string. The untokenized text of the first sequence. For sin

init all hyperparameter here

:param d_model: :param d_k: :param d_v: :param sequence_length: :param h: :param batch_size:

:param x: shape should be:[batch,sequence_length,d_model] :param layer_index: index of layer :return: shape:[sequence_len

init all hyperparameter here

init all hyperparameter here

:param d_model: :param d_k: :param d_v: :param sequence_length: :param h: :param batch_size:

:param d_model: :param d_k: :param d_v: :param sequence_length: :param h: :param batch_size:

:param d_model: :param d_k: :param d_v: :param sequence_length: :param h: :param batch_size:

init all hyperparameter here

init all hyperparameter here

init all hyperparameter here

init all hyperparameter here

init all hyperparameter here

init all hyperparameter here

init all hyperparameter here

init all hyperparameter here

init all hyperparameter here

init all hyperparameter here

init all hyperparameter here

init all hyperparameter here

Reads a tab separated value file.

compoute f1_score. :param logits: [batch_size,label_size] :param evalY: [batch_size,label_size] :return:

compoute f1_score. :param logits: [batch_size,label_size] :param evalY: [batch_size,label_size] :return:

compute weights for labels in current batch, and update weights_label(a dict) :param weights_label:a dict :param logit: [None,Vocabula

Convert a set of `InputExample`s to a list of `InputFeatures`.

Creates a classification model.

Creates an optimizer training op.

create vocabulary :param training_data_path: :param vocab_size: :param name_scope: :return:

Get a loop_function that extracts the previous symbol and embeds it. Used by decoder. :param embedding: embedding tensor for symbol :para

Gaussian Error Linear Unit. This is a smoother version of the RELU. Original paper: https://arxiv.org/abs/1606.08415 Args: input_tensor: f

Compute the union of the current variables and checkpoint variables.

Gets a collection of `InputExample`s for the dev set.

See base class.

See base class.

See base class.

See base class.

See base class.

See base class.

Gets output of the embedding lookup (i.e., input to the transformer). Returns: float Tensor of shape [batch_size, seq_length, hidden_size]