Fix benchmark arg

Signed-off-by: aviator19941 <avinash.sharma@amd.com>

sharktank/sharktank/utils/export_artifacts.py

@@ -251,13 +251,13 @@ def iree_benchmark_vmfb(
             f"--module={vmfb_name}",
         ]
         if self.tensor_parallelism_size > 1:
-            base_irpa_path, _ = os.path.splitext(path)
+            base_irpa_path, _ = os.path.splitext(irpa_path)
             params = [
                 f"--parameters=model={base_irpa_path}.rank{i}.irpa"
                 for i in range(self.tensor_parallelism_size)
             ]
         else:
-            params = f"--parameters=model={irpa_path}"
+            params = [f"--parameters=model={irpa_path}"]
         benchmark_args += params
         benchmark_args += args
         cmd = subprocess.list2cmdline(benchmark_args)

sharktank/tests/models/llama/benchmark_amdgpu_test.py

@@ -56,10 +56,10 @@ class BenchmarkLlama3_1_8B(BaseBenchmarkTest):
     def setUp(self):
         super().setUp()
         # TODO: add numpy files to Azure and download from it
-        self.artifacts_dir = Path("/data/llama-3.1/weights/8b")
-        self.gguf_path = self.artifacts_dir / "fp16/llama3.1_8b_fp16.gguf"
-        self.irpa_path = self.artifacts_dir / "fp16/llama3.1_8b_fp16.irpa"
-        self.irpa_path_fp8 = self.artifacts_dir / "f8/llama8b_fp8.irpa"
+        self.artifacts_dir = Path("/data/extra/models/llama3.1_8B")
+        self.gguf_path = self.artifacts_dir / "llama8b_f16.gguf"
+        self.irpa_path = self.artifacts_dir / "llama8b_f16.irpa"
+        self.irpa_path_fp8 = self.artifacts_dir / "llama8b_fp8.irpa"
         self.tensor_parallelism_size = 1
         self.dir_path_8b = self.dir_path / "llama-8b"
         self.temp_dir_8b = Path(self.dir_path_8b)
@@ -711,7 +711,7 @@ def setUp(self):
         strict=True,
         raises=IreeCompileException,
     )
-    def testBenchmark405B_f16_Decomposed(self):
+    def testBenchmark405B_f16_TP8_Decomposed(self):
         output_file_name = self.dir_path_405b / "f16_decomposed"
         output_mlir = self.llama405b_f16_decomposed_artifacts.create_file(
             suffix=".mlir", prefix=output_file_name