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[MM][Bugfix] Update hf_config to hf_text_config (#5319)

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### What this PR does / why we need it?

Following https://github.com/vllm-project/vllm-ascend/pull/5205, update
`hf_config` to `hf_text_config`.

Find more details at
https://github.com/vllm-project/vllm-ascend/pull/5205#issuecomment-3675417534
and
https://github.com/vllm-project/vllm-ascend/pull/5205#issuecomment-3677920872.

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: release/v0.13.0
- vLLM main:
5fbfa8d9ef

Signed-off-by: shen-shanshan <467638484@qq.com>
This commit is contained in:
Shanshan Shen
2026-01-06 16:41:39 +08:00
committed by GitHub
parent 293b2275df
commit b94d589769
23 changed files with 44 additions and 43 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
tests/ut/ops/test_rotary_embedding.py
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@@ -115,7 +115,7 @@ class TestAscendRotaryEmbedding(unittest.TestCase):
model_config = ModelConfig(MODEL,
tokenizer=MODEL,
max_model_len=MAX_NUM_BATCHED_TOKEND)
model_config.hf_config = PretrainedConfig()
model_config.hf_text_config = PretrainedConfig()
vllm_config.model_config = model_config
with set_ascend_forward_context(None, vllm_config):
result_q, result_k = self.layer.forward(self.positions, self.query,
@@ -141,7 +141,7 @@ class TestAscendRotaryEmbedding(unittest.TestCase):
model_config = ModelConfig(MODEL,
tokenizer=MODEL,
max_model_len=MAX_NUM_BATCHED_TOKEND)
model_config.hf_config = PretrainedConfig()
model_config.hf_text_config = PretrainedConfig()
vllm_config.model_config = model_config
with set_ascend_forward_context(None, vllm_config):
result_q, result_k = self.layer.forward(self.positions,
@@ -164,7 +164,7 @@ class TestAscendRotaryEmbedding(unittest.TestCase):
model_config = ModelConfig(MODEL,
tokenizer=MODEL,
max_model_len=MAX_NUM_BATCHED_TOKEND)
model_config.hf_config = PretrainedConfig()
model_config.hf_text_config = PretrainedConfig()
vllm_config.model_config = model_config
with set_ascend_forward_context(None, vllm_config):
self.layer.forward(self.positions, self.query, self.key,
@@ -184,7 +184,7 @@ class TestAscendRotaryEmbedding(unittest.TestCase):
model_config = ModelConfig(MODEL,
tokenizer=MODEL,
max_model_len=MAX_NUM_BATCHED_TOKEND)
model_config.hf_config = PretrainedConfig()
model_config.hf_text_config = PretrainedConfig()
vllm_config.model_config = model_config
with set_ascend_forward_context(None, vllm_config):
result_q, result_k = self.layer.forward(
@@ -213,7 +213,7 @@ class TestAscendRotaryEmbedding(unittest.TestCase):
model_config = ModelConfig(MODEL,
tokenizer=MODEL,
max_model_len=MAX_NUM_BATCHED_TOKEND)
model_config.hf_config = PretrainedConfig()
model_config.hf_text_config = PretrainedConfig()
vllm_config.model_config = model_config
with set_ascend_forward_context(None, vllm_config):
result_q, result_k = self.layer.forward(self.positions, self.query,
@@ -404,7 +404,7 @@ class TestAscendMRotaryEmbedding(unittest.TestCase):
model_config = ModelConfig(MODEL_VL,
tokenizer=MODEL_VL,
max_model_len=MAX_NUM_BATCHED_TOKEND)
model_config.hf_config = PretrainedConfig()
model_config.hf_text_config = PretrainedConfig()
vllm_config.model_config = model_config
return vllm_config