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Merge 7bd999ba02 into bc1fca39f3
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commit
920fa8663d
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@ -218,6 +218,8 @@ class Engine:
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ids = torch.tensor([tokens], dtype=torch.long, device=device)
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ids = torch.tensor([tokens], dtype=torch.long, device=device)
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logits = self.model.forward(ids, kv_cache=kv_cache_prefill)
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logits = self.model.forward(ids, kv_cache=kv_cache_prefill)
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logits = logits[:, -1, :]
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logits = logits[:, -1, :]
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# expand the logits to be of size (num_samples, vocab_size)
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logits = logits.expand(num_samples, -1)
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next_ids = sample_next_token(logits, rng, temperature, top_k) # (B, 1)
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next_ids = sample_next_token(logits, rng, temperature, top_k) # (B, 1)
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sampled_tokens = next_ids[:, 0].tolist()
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sampled_tokens = next_ids[:, 0].tolist()
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@ -248,8 +250,6 @@ class Engine:
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# Get sampled tokens - either from prefill or from forward pass
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# Get sampled tokens - either from prefill or from forward pass
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if first_iteration:
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if first_iteration:
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# Use the tokens we already sampled from prefill
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# Use the tokens we already sampled from prefill
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sampled_tokens = [sampled_tokens[0]] * num_samples # Broadcast first token to all rows
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# TODO: we should sample a token for each row instead of broadcasting
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first_iteration = False
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first_iteration = False
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else:
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else:
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# Forward the model and get the next token for each row
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# Forward the model and get the next token for each row
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