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trl/experimental/async_grpo/async_grpo_trainer.py

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@@ -1266,8 +1266,6 @@ def _log_step_metrics(self) -> None:
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## `_wall_clock` divides by `perf/step_s`: the whole step, rollout waits included and says what fraction of the allocation actually became training.
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if self._step_forward_tokens > 0:
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mean_seq_len = self._step_seq_len_weighted / self._step_forward_tokens
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# `get_text_config()` returns the config itself for text-only models; for a VLM it returns the text
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# config, which is the one that carries `hidden_size`, `vocab_size`, ... (composite configs do not).
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flops_per_token = compute_flops_per_token(self.model.config.get_text_config(), int(mean_seq_len))
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world_size = self.accelerator.num_processes
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metrics["perf/forwarded_tok_s_fwd_bwd"].append((self._step_forward_tokens, fwd_bwd_s))

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