cerebras.modelzoo.data.nlp.gpt.InferenceDataProcessor.InferenceDataProcessorLL#

class cerebras.modelzoo.data.nlp.gpt.InferenceDataProcessor.InferenceDataProcessorLL[source]#

Bases: cerebras.modelzoo.data.nlp.gpt.InferenceDataProcessor.InferenceDataProcessor

Subclass for processing EEH loglikelihood requests.

Methods

create_dataloader

Classmethod to create the dataloader object.

from_request_type

gen_data_samples

Preprocess raw text requests as fetched from EEH script into data samples consumable by GPT2 model and dump these to numpy file.
__init__(params, samples_file_list, dataset_size)[source]#
__call__(*args: Any, **kwargs: Any) → Any#

Call self as a function.

static __new__(cls, *args: Any, **kwargs: Any) → Any#
create_dataloader()#

Classmethod to create the dataloader object.

static gen_data_samples(requests: List, batch_size: int, max_sequence_length: int, tokenizer: Union[tokenizers.Tokenizer, transformers.PreTrainedTokenizerBase], eos_token_id: int, samples_saver: cerebras.modelzoo.common.utils.input.utils.SamplesSaver, request_type: cerebras.modelzoo.data.nlp.gpt.InferenceDataProcessor.RequestType, inf_start_token: Optional[int] = None, max_gen_tokens: Optional[int] = None) → Tuple[List[str], int, Tuple[int, int]]#

Preprocess raw text requests as fetched from EEH script into data samples consumable by GPT2 model and dump these to numpy file.

Parameters

  • requests – List of EEH’s Instance dataclass objects holding raw text data

  • batch_size – The batch size

  • max_sequence_length – The maximum length of each sample

  • tokenizer – The tokenizer used to tokenize raw text data

  • eos_token_id – int representing the end-of-sentence token

  • samples_saver – SamplesSaver object to manage the saving of data samples to file.

  • request_type – The type of request for which the data sample is to be created

  • inf_start_token – (generative tasks-only) int representing the start token for generative inference

  • max_gen_tokens – (generative tasks-only) The max number of tokens to generate

Returns

(List[str], int, tuple) tuple of - list of file paths where the samples are dumped; - int representing the size of the dataset (total no. of samples; - tuple of request metadata needed for EEH postprocessing.

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