INNER CODE UNIT · Python

run_evaluation

microsoft/AzureML-BERT · finetune/run_classifier_azureml.py:59

def run_evaluation(processor, output_mode, set_type):
    examples = processor.get_dev_examples(args.data_dir) if set_type == "dev" else processor.get_test_examples(args.data_dir)
    features = convert_examples_to_features(
                    examples, processor.get_labels(), args.max_seq_length, tokenizer, output_mode)
    logger.info(f" Running Evaluation on {set_type}")
    logger.info("  Num examples = %d", len(examples))
    logger.info("  Batch size = %d", args.eval_batch_size)
    all_input_ids = torch.tensor(
        [f.input_ids for f in features], dtype=torch.long)
    all_input_mask = torch.tensor(
        [f.input_mask for f in features], dtype=torch.long)
    all_segment_ids = torch.tensor(
        [f.segment_ids for f in features], dtype=torch.long)

    all_label_ids = None
    if output_mode == "classification":
        all_label_ids = torch.tensor(
            [f.label_id for f in features], dtype=torch.long)

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