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@@ -208,7 +208,8 @@ class CifPredictorV2(nn.Module):
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mask_2 = torch.cat([ones_t, mask], dim=1)
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mask = mask_2 - mask_1
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tail_threshold = mask * tail_threshold
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- alphas = torch.cat([alphas, tail_threshold], dim=1)
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+ alphas = torch.cat([alphas, zeros_t], dim=1)
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+ alphas = torch.add(alphas, tail_threshold)
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else:
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tail_threshold = torch.tensor([tail_threshold], dtype=alphas.dtype).to(alphas.device)
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tail_threshold = torch.reshape(tail_threshold, (1, 1))
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@@ -654,4 +655,4 @@ class CifPredictorV3(nn.Module):
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predictor_alignments = index_div_bool_zeros_count_tile_out
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predictor_alignments_length = predictor_alignments.sum(-1).type(encoder_sequence_length.dtype)
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- return predictor_alignments.detach(), predictor_alignments_length.detach()
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+ return predictor_alignments.detach(), predictor_alignments_length.detach()
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