INNER CODE UNIT · Python

max_ix

HendrikStrobelt/detecting-fake-text · backend/api.py:222

            max_ix = min(min_ix + batch_size, len(y_toks) - 1)
            cur_input_batch = []
            cur_target_batch = []
            # Construct each batch
            for running_ix in range(max_ix - min_ix):
                tokens_tensor = y.clone()
                mask_index = min_ix + running_ix
                tokens_tensor[0, mask_index + 1] = self.mask_tok

                # Reduce computational complexity by subsetting
                min_index = max(0, mask_index - max_context)
                max_index = min(tokens_tensor.shape[1] - 1,
                                mask_index + max_context + 1)

                tokens_tensor = tokens_tensor[:, min_index:max_index]
                # Add padding
                needed_padding = max_context * 2 + 1 - tokens_tensor.shape[1]
                if min_index == 0 and max_index == y.shape[1] - 1:

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