Fix random_sample test for new framework API.

test/infinicore/ops/random_sample.py

@@ -129,9 +129,9 @@ class OpTest(BaseOperatorTest):
     def get_test_cases(self):
         return parse_test_cases()
 
-    def prepare_inputs_and_kwargs(self, test_case, device):
+    def prepare_pytorch_inputs_and_kwargs(self, test_case, device):
         """Prepare inputs and kwargs, replacing TensorSpec objects with actual tensors"""
-        inputs, kwargs = super().prepare_inputs_and_kwargs(test_case, device)
+        inputs, kwargs = super().prepare_pytorch_inputs_and_kwargs(test_case, device)
 
         # If we already have stored logits (from a previous call), reuse them
         # to ensure consistency across multiple calls for the same test case
@@ -209,26 +209,27 @@ class OpTest(BaseOperatorTest):
 
         try:
             # Try the standard comparison first
-            # This will call prepare_inputs_and_kwargs which will set self._current_logits
+            # This will call prepare_pytorch_inputs_and_kwargs which will set self._current_logits
             return super().run_test(device, test_case, config)
         except AssertionError as original_error:
             # If standard comparison fails, check if this is a valid case where
             # indices differ but logits values are equal
 
-            # Only handle if we have stored logits (from prepare_inputs_and_kwargs)
+            # Only handle if we have stored logits (from prepare_pytorch_inputs_and_kwargs)
             if self._current_logits is None:
                 raise
 
             logits_tensor = self._current_logits
 
             # Re-run operations with the same logits to get results for comparison
-            # prepare_inputs_and_kwargs will reuse self._current_logits if it exists
+            # prepare_pytorch_inputs_and_kwargs will reuse self._current_logits if it exists
+            from framework.base import TestResult
             from framework.utils import (
-                infinicore_tensor_from_torch,
                 convert_infinicore_to_torch,
+                infinicore_tensor_from_torch,
             )
 
-            inputs, kwargs = self.prepare_inputs_and_kwargs(test_case, device)
+            inputs, kwargs = self.prepare_pytorch_inputs_and_kwargs(test_case, device)
 
             # Prepare infinicore inputs
             infini_inputs = []
@@ -268,7 +269,13 @@ class OpTest(BaseOperatorTest):
 
             # Check if indices are equal (standard case)
             if ic_idx == ref_idx:
-                return True, "passed"
+                # Return a successful TestResult object
+                return TestResult(
+                    success=True,
+                    return_code=0,
+                    test_case=test_case,
+                    device=device,
+                )
 
             # Special case: indices differ but logits values are equal
             # This is valid for random_sample when multiple indices have the same logits value
@@ -277,7 +284,13 @@ class OpTest(BaseOperatorTest):
                 logits_ic = logits_tensor[ic_idx].item()
                 if logits_ic == logits_ref:
                     # Valid: different indices but same logits value
-                    return True, "passed"
+                    # Return a successful TestResult object
+                    return TestResult(
+                        success=True,
+                        return_code=0,
+                        test_case=test_case,
+                        device=device,
+                    )
             except (IndexError, RuntimeError):
                 # If we can't access the logits, fall through to raise the original error
                 pass