r""" Instantiates one of the base model classes of the library from a pre-trained model configuration. The model class to instantiate

labels: [b1, b2] Return true_log_probs: [b1, b2] samp_log_probs: [n_sample] neg_samples: [n_s

Creates a random int32 tensor of the shape within the vocab size.

Deal with dynamic shape in tensorflow cleanly.

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

Creates a `tf.initializers.truncated_normal` with the given range. Args: initializer_range: float, initializer range for stddev. Retur

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

Create a schedule with a learning rate that decreases linearly after linearly increasing during a warmup period.

Converts a string in a sequence of ids (integer), using the tokenizer and vocabulary. Same as doing ``self.convert_tokens_to_ids(sel

Basic Tokenization of a piece of text. Split on "white spaces" only, for sub-word tokenization, see WordPieceTokenizer. Args:

Initialize and prunes weights if needed.

Create a schedule with a constant learning rate.

Converts a sequence of ids (integer) in a string, using the tokenizer and vocabulary with options to remove special tokens and clean

Train model on train set and evaluate on train and valid set. Returns: state dict of the best model with highest valid f1 score

Converts a single token, or a sequence of tokens, (str/unicode) in a single integer id (resp. a sequence of ids), using the vocabulary.

调用执行函数 :param _image: 待处理图像 :return: 执行后的Image对象

Reads a tab separated value file.

r""" Instantiates one of the base model classes of the library from a pre-trained model configuration. The model class to instantiate

Get labels on the last column from file. Args: filename: file name Returns: List[str]: label list

Calculate accuracy and f1 score. Args: golds: answers predicts: predictions given by model Returns: accuracy, f1 sco

convert text-label into text-index. input: text: text labels of each image. [batch_size] output: text: concate

Evaluate model on data loader in device. Args: model: model to be evaluate data_loader: torch.utils.data.DataLoader devic

Prune a linear layer (a model parameters) to keep only entries in index. Return the pruned layer as a new layer with requires_grad=True.

Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and adding special tokens

Find the most likely tag sequence using Viterbi algorithm. Args: emissions (`~torch.Tensor`): Emission score tensor of size

将图像统一转换为PIL格式 :param image: 图像 :return: Image格式的图像

Build vocab.txt for SMP-CAIL2020-Argmine.

Returns a dictionary containing the encoded sequence or sequence pair and additional informations: the mask for sequence classificati

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

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

Save a model and its configuration file to a directory, so that it can be re-loaded using the `:func:`~transformers.PreTrainedModel.from_

Cut words for a sentence. Args: sentence: sentence Returns: words list

Cut words for a sentence. Args: sentence: sentence Returns: words list

Cut words for a sentence. Args: sentence: sentence Returns: words list

Cut words for a sentence. Args: sentence: sentence Returns: words list

Cut words for a sentence. Args: sentence: sentence Returns: words list

Cut words for a sentence. Args: sentence: sentence Returns: words list

Cut words for a sentence. Args: sentence: sentence Returns: words list

Cut words for a sentence. Args: sentence: sentence Returns: words list

Cut words for a sentence. Args: sentence: sentence Returns: words list

Cut words for a sentence. Args: sentence: sentence Returns: words list