Fix some more Transformers nightly tests (#29872)
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
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@@ -89,6 +89,7 @@ _CONFIG_REGISTRY: dict[str, type[PretrainedConfig]] = LazyConfigDict(
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step3_text="Step3TextConfig",
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qwen3_next="Qwen3NextConfig",
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lfm2_moe="Lfm2MoeConfig",
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tarsier2="Tarsier2Config",
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)
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_CONFIG_ATTRS_MAPPING: dict[str, str] = {
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@@ -127,6 +128,9 @@ class HFConfigParser(ConfigParserBase):
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if config_dict.get("speculators_config") is not None
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else model_type
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)
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# Allow hf_overrides to override model_type before checking _CONFIG_REGISTRY
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if (hf_overrides := kwargs.pop("hf_overrides", None)) is not None:
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model_type = hf_overrides.get("model_type", model_type)
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if model_type in _CONFIG_REGISTRY:
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config_class = _CONFIG_REGISTRY[model_type]
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@@ -310,7 +314,7 @@ def patch_rope_parameters(config: PretrainedConfig) -> None:
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config.rope_parameters["rope_theta"] = rope_theta
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# No RoPE parameters to patch
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if not hasattr(config, "rope_parameters"):
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if getattr(config, "rope_parameters", None) is None:
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return
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# Add original_max_position_embeddings if present
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@@ -351,7 +355,10 @@ def patch_rope_parameters_dict(rope_parameters: dict[str, Any]) -> None:
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rope_parameters["rope_type"] = "longrope"
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logger.warning("Replacing legacy rope_type 'su' with 'longrope'")
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elif rope_parameters["rope_type"] == "mrope":
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assert "mrope_section" in rope_parameters
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if "mrope_section" not in rope_parameters:
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raise ValueError(
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"Legacy rope_type 'mrope' requires 'mrope_section' in rope_parameters"
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)
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rope_parameters["rope_type"] = "default"
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logger.warning("Replacing legacy rope_type 'mrope' with 'default'")
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@@ -584,6 +591,7 @@ def get_config(
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trust_remote_code=trust_remote_code,
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revision=revision,
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code_revision=code_revision,
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hf_overrides=hf_overrides_kw,
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**kwargs,
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)
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# Special architecture mapping check for GGUF models
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@@ -915,11 +923,13 @@ def get_hf_text_config(config: PretrainedConfig):
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"""
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text_config = config.get_text_config()
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if text_config is not config:
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# The code operates under the assumption that text_config should have
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# `num_attention_heads` (among others). Assert here to fail early
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# if transformers config doesn't align with this assumption.
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assert hasattr(text_config, "num_attention_heads")
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if text_config is not config and not hasattr(text_config, "num_attention_heads"):
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raise ValueError(
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"The text_config extracted from the model config does not have "
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"`num_attention_heads` attribute. This indicates a mismatch "
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"between the model config and vLLM's expectations. Please "
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"ensure that the model config is compatible with vLLM."
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)
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return text_config
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