fix

Author: xadupre

_doc/examples/plot_export_with_modelbuilder.py

@@ -65,7 +65,7 @@ def generate_text(
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
 if not os.path.exists(filename):
     print(f"-- creating... on {device} into {filename!r}")
-    model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype=torch.bfloat16)
+    model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, dtype=torch.bfloat16)
     model = model.to(device)
     config = model.config
 else:

_doc/technical/plot_generate.py

@@ -47,7 +47,7 @@
     tokenizer = AutoTokenizer.from_pretrained(model_id)
 else:
     model_id = "microsoft/phi-1_5"
-    model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto")
+    model = AutoModelForCausalLM.from_pretrained(model_id, dtype="auto")
     tokenizer = AutoTokenizer.from_pretrained(model_id)
     config = get_pretrained_config(model_id)
     task = task = task_from_id(model_id)

_unittests/ut_tasks/try_tasks.py

@@ -263,7 +263,7 @@ def test_text_generation_phi4_moe(self):
         model = AutoModelForCausalLM.from_pretrained(
             model_path,
             device_map="cuda",
-            torch_dtype="auto",
+            dtype="auto",
             trust_remote_code=True,
             # if you do not use Ampere or later GPUs, change attention to "eager"
             # _attn_implementation='flash_attention_2',
@@ -352,7 +352,7 @@ def test_imagetext2text_generation_idefics(self):
         mid = "HuggingFaceM4/tiny-random-idefics"
         processor = AutoProcessor.from_pretrained(mid)
         model = IdeficsForVisionText2Text.from_pretrained(
-            mid, torch_dtype=torch.bfloat16, device_map="auto"
+            mid, dtype=torch.bfloat16, device_map="auto"
         )
 
         prompt = [
@@ -699,7 +699,7 @@ def test_falcon_mamba_dev(self):
             "text-generation",
             model=model,
             tokenizer=tokenizer,
-            torch_dtype=torch.bfloat16,
+            dtype=torch.bfloat16,
             trust_remote_code=True,
             device_map="auto",
         )
@@ -736,7 +736,7 @@ def test_falcon_mamba_7b(self):
             "text-generation",
             model=model,
             tokenizer=tokenizer,
-            torch_dtype=torch.bfloat16,
+            dtype=torch.bfloat16,
             trust_remote_code=True,
             device_map="auto",
         )
@@ -802,7 +802,7 @@ def test_text_to_image(self):
         from diffusers import StableDiffusionPipeline
 
         model_id = "diffusers/tiny-torch-full-checker"  # "stabilityai/stable-diffusion-2"
-        pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to(
+        pipe = StableDiffusionPipeline.from_pretrained(model_id, dtype=torch.float16).to(
             "cuda"
         )
 

_unittests/ut_xrun_doc/test_documentation_examples.py

@@ -85,6 +85,9 @@ def add_test_methods(cls):
 
             # transformers
 
+            if not reason and not has_dot and name in {"plot_export_with_modelbuilder.py"}:
+                reason = "downloading"
+
             if (
                 not reason
                 and name in {"plot_export_tiny_llm.py", "plot_export_tiny_llm_patched.py"}

onnx_diagnostic/ci_models/export_phi4_mm.py

@@ -794,7 +794,7 @@ def main(
             model_id,
             config=config,
             trust_remote_code=True,
-            torch_dtype=torch_dtype,
+            dtype=torch_dtype,
             device_map=device,
             attn_implementation="sdpa",
         ).eval()

onnx_diagnostic/investigate/input_observer.py

@@ -851,7 +851,11 @@ def remove_inputs(self, input_names: Sequence[str | int]):
             self._best_candidate.remove_inputs(input_names)
 
         for name_or_pos in sorted(input_names, reverse=True):
-            if self.default_values and name_or_pos in self.default_values:
+            if (
+                isinstance(name_or_pos, str)
+                and self.default_values
+                and name_or_pos in self.default_values
+            ):
                 del self.default_values[name_or_pos]
             if self.value_if_missing and name_or_pos in self.value_if_missing:
                 del self.value_if_missing[name_or_pos]
@@ -862,7 +866,7 @@ def remove_inputs(self, input_names: Sequence[str | int]):
             not self.args_name_and_position
         ), f"Not implemented when {self.args_name_and_position=}"
         input_names_str = {
-            (self.signature_name[i] if isinstance(i, int) else i) for i in input_names
+            (self.signature_names[i] if isinstance(i, int) else i) for i in input_names
         }
         self.signature_names = [
             name for name in self.signature_names if name not in input_names_str
@@ -1269,4 +1273,6 @@ def check_discrepancies(
 
     def remove_inputs(self, input_names: Sequence[str | int]):
         """Lets the users drops inputs."""
+        if self.info is None:
+            raise RuntimeError("No input was captured.")
         self.info.remove_inputs(input_names)