Perform dropout. Args: input_tensor: float Tensor. dropout_prob: Python float. The probability of dropping out a value (NOT of *keepi

docs.

Precision, Recall and F1 from the confusion matrix Parameters ---------- cm : tf.Tensor of type tf.int32, of shape (num_classes, num_cl

Precision, Recall and F1 from the confusion matrix Parameters ---------- cm : tf.Tensor of type tf.int32, of shape (num_classes, num_cl

Precision, Recall and F1 from the confusion matrix Parameters ---------- cm : tf.Tensor of type tf.int32, of shape (num_classes, num_cl

Precision, Recall and F1 from the confusion matrix Parameters ---------- cm : tf.Tensor of type tf.int32, of shape (num_classes, num_cl

Precision, Recall and F1 from the confusion matrix Parameters ---------- cm : tf.Tensor of type tf.int32, of shape (num_classes, num_cl

Precision, Recall and F1 from the confusion matrix Parameters ---------- cm : tf.Tensor of type tf.int32, of shape (num_classes, num_cl

Safe division, return 0 if denominator is 0

Safe division, return 0 if denominator is 0

Safe division, return 0 if denominator is 0

Safe division, return 0 if denominator is 0

Safe division, return 0 if denominator is 0

Safe division, return 0 if denominator is 0

Performs a single optimization step. Arguments: closure (callable, optional): A closure that reevaluates the model

Adds a new item into `params`.

Constructs a `BertConfig` from a json file of parameters.

Constructs a `BertConfig` from a json file of parameters.

Constructs a `BertConfig` from a json file of parameters.

Constructs a `BertConfig` from a json file of parameters.

Constructs a `BertConfig` from a json file of parameters.

Returns: A tf initializer. Used to initialize variables in layers on top of XLNet.

Run layer normalization on the last dimension of the tensor.

Returns text encoded in a way suitable for print or `tf.logging`.

Prune a Conv1D layer (a model parameters) to keep only entries in index. A Conv1D work as a Linear layer (see e.g. BERT) but the weights are

Tokenizes a piece of text.

Tokenizes a piece of text.

Tokenizes a piece of text.

Tokenizes a piece of text.

Tokenizes a piece of text.

Calls the model_fn with required parameters.

Given something that might be a URL (or might be a local path), determine which. If it's a URL, download the file and cache it, and retur

Converts a sequence of [tokens|ids] using the vocab.

Converts a sequence of [tokens|ids] using the vocab.

Converts a sequence of [tokens|ids] using the vocab.

Converts a sequence of [tokens|ids] using the vocab.

Converts a sequence of [tokens|ids] using the vocab.

Converts a sequence of [tokens|ids] using the vocab.

Converts a sequence of [tokens|ids] using the vocab.

Loads a data file into a list of `InputBatch`s.

Converts a sequence of tokens into ids using the vocab.

Perform dropout. Args: input_tensor: float Tensor. dropout_prob: Python float. The probability of dropping out a value (NOT of *keepi

Perform dropout. Args: input_tensor: float Tensor. dropout_prob: Python float. The probability of dropping out a value (NOT of *keepi

Perform dropout. Args: input_tensor: float Tensor. dropout_prob: Python float. The probability of dropping out a value (NOT of *keepi

Perform dropout. Args: input_tensor: float Tensor. dropout_prob: Python float. The probability of dropping out a value (NOT of *keepi

Perform dropout. Args: input_tensor: float Tensor. dropout_prob: Python float. The probability of dropping out a value (NOT of *keepi

Perform dropout. Args: input_tensor: float Tensor. dropout_prob: Python float. The probability of dropping out a value (NOT of *keepi

Flattens the `features` and `labels` to a single tensor list.

Returns an `_Inputs` instance according to `input_fn` return value.

Constructs a `BertConfig` from a json file of parameters.

Gets final hidden layer of encoder. Returns: float Tensor of shape [batch_size, seq_length, hidden_size] corresponding to the final h

Gets final hidden layer of encoder. Returns: float Tensor of shape [batch_size, seq_length, hidden_size] corresponding to the final h

Gets final hidden layer of encoder. Returns: float Tensor of shape [batch_size, seq_length, hidden_size] corresponding to the final h

Gets final hidden layer of encoder. Returns: float Tensor of shape [batch_size, seq_length, hidden_size] corresponding to the final h

Gets final hidden layer of encoder. Returns: float Tensor of shape [batch_size, seq_length, hidden_size] corresponding to the final h

Lower text and remove punctuation, articles and extra whitespace.

Post-attention processing.

Core relative positional attention operations.

Core relative positional attention operations.

Detects whether scalar_stopping_signal indicates stopping.

Validates and records the structure of `features` and `labels`.

将sentence中的繁体字转为简体字 :param sentence: 待转换的句子 :return: 将句子中繁体字转换为简体字之后的句子