[Misc] rename torch_dtype to dtype (#26695)

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>

tests/conftest.py

@@ -334,7 +334,7 @@ class HfRunner:
             trust_remote_code=trust_remote_code,
         )
         self.device = self.get_default_device()
-        self.dtype = torch_dtype = _get_and_verify_dtype(
+        self.dtype = dtype = _get_and_verify_dtype(
             self.model_name,
             self.config,
             dtype=dtype,
@@ -342,7 +342,7 @@ class HfRunner:
         )
 
         model_kwargs = model_kwargs if model_kwargs is not None else {}
-        model_kwargs.setdefault("torch_dtype", torch_dtype)
+        model_kwargs.setdefault("dtype", dtype)
 
         if is_sentence_transformer:
             # Lazy init required for AMD CI
@@ -388,7 +388,7 @@ class HfRunner:
         if not skip_tokenizer_init:
             self.tokenizer = AutoTokenizer.from_pretrained(
                 model_name,
-                torch_dtype=torch_dtype,
+                dtype=dtype,
                 trust_remote_code=trust_remote_code,
             )
 
@@ -398,7 +398,7 @@ class HfRunner:
 
         self.processor = AutoProcessor.from_pretrained(
             model_name,
-            torch_dtype=torch_dtype,
+            dtype=dtype,
             trust_remote_code=trust_remote_code,
         )
         if skip_tokenizer_init:

tests/models/multimodal/pooling/test_intern_vit.py

@@ -38,7 +38,7 @@ def run_intern_vit_test(
         config.norm_type = "rms_norm"
 
     hf_model = AutoModel.from_pretrained(
-        model, torch_dtype=torch_dtype, trust_remote_code=True
+        model, dtype=torch_dtype, trust_remote_code=True
     ).to("cuda")
     hf_outputs_per_image = [
         hf_model(pixel_value.to("cuda")).last_hidden_state

tests/models/multimodal/pooling/test_radio.py

@@ -45,7 +45,7 @@ def run_radio_test(
     hf_model = AutoModel.from_pretrained(
         model_id,
         config=config,
-        torch_dtype=torch_dtype,
+        dtype=torch_dtype,
         trust_remote_code=True,
     ).to("cuda")
     hf_model.eval()