Call this method to monkey patch optimizer step function so that masks can be applied to gradients and weights during training. You mu

Utility function to print customMatmulPerf_t structure

Computes the accuracy over the k top predictions for the specified values of k

calculate min/max values from collector if :func:`MaxCollector <quantization.MaxCollector>` is used, kwargs should be None. if :func:`Hist

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

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

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

Serializes this instance to a JSON string.

Run the bert transformer layer by FasterTransformer. Args: inputs: A tf.Tensor with shape [batch_size, seq_len, hidden_dimension].

Gets the list of labels for this data set.

Run layer normalization on the last dimension of the tensor.

Get the n-best logits from a list.