Save this instance to a json file.

Get the index of the word corresponding (i.e. comprising) to an encoded token in a sequence of the batch. Can be called as:

Tokenizes a piece of text.

Recursively unwraps a model from potential containers (as used in distributed training). Args: model (`torch.nn.Module`): The model

Computes random mask spans for a given shape. Used to implement [SpecAugment: A Simple Data Augmentation Method for ASR](https://arxiv.org/ab

Computes random mask spans for a given shape. Used to implement [SpecAugment: A Simple Data Augmentation Method for ASR](https://arxiv.org/ab

Gather value of `tensors` (tensor or list/tuple of nested tensors) and convert them to numpy before concatenating them to `gathered`

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

Split an input array into blocks of a given `block_len` along the given `axis`. If the dimension length is not a multiple of `block_len`, it will

Split an input tensor into blocks of a given `block_len` along the given `dim`. If the dimension length is not a multiple of `block_len`, it will

Add a key to _index (MinHashLSH) the min_hash is used to query closest matches based on the jaccard_threshold. The new key is either a

Computes the transition scores of sequences given the generation scores (and beam indices, if beam search was used). This is a conven

Converts an image to RGB format. Only converts if the image is of type PIL.Image.Image, otherwise returns the image as is. Args:

Convert the inner content to tensors. Args: tensor_type (`str` or [`~utils.TensorType`], *optional*): Th

Converts bounding boxes from corners format to center format. corners format: contains the coodinates for the top-left and bottom-right corn

Create and fill numpy array of size len_of_validation_data * max_length_of_output_tensor Args: start_or_end_logits(:obj:

This method forwards all its arguments to TrOCRTokenizer's [`~PreTrainedTokenizer.decode`]. Please refer to the docstring of this met

Downloads a given url in a temporary file. This function is not safe to use in multiple processes. Its only use is for deprecated behavior al

Framework-agnostic version of `numpy.expand_dims` that will work on torch/TensorFlow/Jax tensors as well as NumPy arrays.

Export a Pytorch or TensorFlow model to an ONNX Intermediate Representation (IR) Args: preprocessor: ([`PreTrainedTokenizer`], [`Fea

Creates a random float32 tensor

Calling this function will disable the gradient computation for the feature encoder so that its parameter will not be updated during

Set requires_grad=False for each of model.parameters()

r""" Example: ```python >>> from transformers import EncoderDecoderModel >>> model = EncoderDecoderModel.from_pretra

Extracts a class from a module file, present in the local folder or repository of a model. <Tip warning={true}> Calling this function w

Returns a list of dictionaries, containing titles and text of the retrieved documents. Args: doc_ids (`np.ndarray` of sh

Returns the underlying rotation as a rotation matrix tensor. Returns: The rotation as a rotation matrix tensor

If there are enough hypotheses and that none of the hypotheses being generated can become better than the worst one in the heap, then

list(map(f, x))

Normalize an image. image = (image - image_mean) / image_std. Args: image (`np.ndarray`): Image to norma

Normalize an image. image = (image - image_mean) / image_std. Args: image (`np.ndarray`): Image to norma

location will always be cpu for np tensors

location will always be cpu for np tensors