Creates examples for the training and dev sets.

Creates examples for the training and dev sets.

Creates examples for the training and dev sets.

shift every row 1 step right, converting columns into diagonals. Example:: chunked_hidden_states: [ 0.4983, 2.6918, -

pads rows and then flips rows and columns

Prepare masks that ignore padding tokens in the decoder and a causal mask for the decoder if none are provided. This mimics the default behav

Prepare masks that ignore padding tokens in the decoder and a causal mask for the decoder if none are provided. This mimics the default behav

Prepare :obj:`inputs` before feeding them to the model, converting them to tensors if they are not already and handling potential sta

Build relative position according to the query and key We assume the absolute position of query :math:`P_q` is range from (0, query_size) an

Utility to convert a number of bytes (int) into a number of mega bytes (int)

Checks whether to bail out if output_dir already exists and has more than expected_items in it `args`: needs to have the following attribute

XLNet write prediction logic (more complex than Bert's). Write final predictions to the json file and log-odds of null if needed. Requir

Write final predictions to the json file and log-odds of null if needed.

Loads a data file into a list of `InputFeatures`

Loads a data file into a list of `InputFeatures` `cls_token_at_end` define the location of the CLS token: - False (Default, BERT/X

Converts a sequence of tokens (string) in a single string.

Delete token. Do not fail if token does not exist.

The device used by this process.

Ensure input are presented in the correct order, without any Non Args: model: The model used to forward the input data token

Calculate entropy of a pre-softmax logit Tensor

Format `t` (in seconds) to (h):mm:ss

Append a string-identifier at the end (before the extension, if any) to the provided filepath Args: filename: pathlib.Path The actua

Returns the model's input embeddings. Returns: :obj:`nn.Module`: A torch module mapping vocabulary to hidden states.

Get the model modules inside the transformers library.

Get the objects in module that are models.

Returns the the linear layer that produces question answering logits. Returns: :obj:`nn.Module`: A torch module mapping

Returns the the linear layer that produces question answering logits Returns: :obj:`nn.Module`: A torch module mapping t

Loads a data file into a list of ``InputFeatures`` Args: examples: List of ``InputExamples`` or ``tf.data.Dataset`` containing the e

The accumulated gradients on the current replica.

r""" Generates sequences for models with a language modeling head using greedy decoding. Parameters: input_ids (:obj:`to

Find and group together the adjacent tokens with the same entity predicted. Args: entities (:obj:`dict`): The entities p

Attempt to infer the static vs dynamic axes for each input and output tensors for a specific model Args: nlp: The pipeline object ho

From fairseq

Log :obj:`logs` on the various objects watching training. Subclass and override this method to inject custom behavior. Args

Remove a callback from the current list of :class:`~transformer.TrainerCallback` and returns it. If the callback is not found, retur

Post-attention processing.