[ROCm][CI] fix test_common.py (#48676)
Signed-off-by: charlifu <charlifu@amd.com> Co-authored-by: Andreas Karatzas <akaratza@amd.com>
Charlie Fu committed
Jul 15, 2026 at 01:42 UTC
adce0681181e8e258e2028f1b78ad24718f5c169
2 files changed
+10
-4
tests/conftest.py
+9
-3
@@ -642,10 +642,12 @@ class HfRunner:
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outputs: list[tuple[list[list[int]], list[str]]] = []
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for inputs in all_inputs:
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+ generate_kwargs = dict(kwargs)
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+ generate_kwargs.setdefault("tokenizer", self.tokenizer)
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output_ids: torch.Tensor = self.model.generate(
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**self.wrap_device(inputs),
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use_cache=True,
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- **kwargs,
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+ **generate_kwargs,
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)
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if self.processor is None:
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raise RuntimeError(
@@ -724,6 +726,8 @@ class HfRunner:
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all_logprobs: list[list[torch.Tensor]] = []
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for inputs in all_inputs:
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+ generate_kwargs = dict(kwargs)
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+ generate_kwargs.setdefault("tokenizer", self.tokenizer)
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output: "GenerateOutput" = self.model.generate(
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**self.wrap_device(inputs),
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use_cache=True,
@@ -731,7 +735,7 @@ class HfRunner:
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max_new_tokens=max_tokens,
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output_hidden_states=True,
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return_dict_in_generate=True,
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- **kwargs,
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+ **generate_kwargs,
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)
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seq_logprobs = self._hidden_states_to_seq_logprobs(output.hidden_states)
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all_logprobs.append(seq_logprobs)
@@ -812,6 +816,8 @@ class HfRunner:
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all_output_strs: list[str] = []
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for inputs in all_inputs:
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+ generate_kwargs = dict(kwargs)
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+ generate_kwargs.setdefault("tokenizer", self.tokenizer)
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output: "GenerateOutput" = self.model.generate(
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**self.wrap_device(inputs),
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use_cache=use_cache,
@@ -819,7 +825,7 @@ class HfRunner:
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max_new_tokens=max_tokens,
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output_hidden_states=True,
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return_dict_in_generate=True,
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- **kwargs,
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+ **generate_kwargs,
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)
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# Encoder-decoder models return decoder_hidden_states instead of
vllm/model_executor/models/hyperclovax.py
+1
-1
@@ -459,7 +459,7 @@ class HyperCLOVAXForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
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input_ids: torch.Tensor | None,
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positions: torch.Tensor,
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*,
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- intermediate_tensors: IntermediateTensors | None,
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+ intermediate_tensors: IntermediateTensors | None = None,
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inputs_embeds: torch.Tensor | None = None,
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) -> torch.Tensor | IntermediateTensors:
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model_output = self.model(