Dump SPIRV kernel in benchmark_driver.py

benchmarks/triton_kernels_benchmark/benchmark_driver.py

@@ -399,19 +399,77 @@ def format_of(ty):
     return src
 
 
+def serialize_kernel_metadata(arg, args_dict):
+    args_dict["num_warps"] = arg.num_warps
+    args_dict["threads_per_warp"] = arg.threads_per_warp
+    args_dict["shared_memory"] = arg.shared
+    args_dict["kernel_name"] = arg.name
+    args_dict["spv_name"] = f"{arg.name}.spv"
+
+
+def serialize_args(args, constants, signature):
+    import numbers
+    dir_path = os.getenv("TRITON_XPU_DUMP_SPIRV_KERNEL_ARGS")
+    if not os.path.exists(dir_path):
+        os.makedirs(dir_path)
+        print(f"Path to directory consisting of SPIR-V Runner data: {dir_path}")
+
+    cnt = 0
+    args_dict = {"gridX": args[cnt], "gridY": args[cnt + 1], "gridZ": args[cnt + 2]}
+    args_dict["argument_list"] = []
+    counts = {"tensors": 0, "scalars": 0, "karg_cnt": 0}
+    cnt = 4
+    for arg in args[cnt:]:
+        if type(arg).__name__ == "KernelMetadata":
+            serialize_kernel_metadata(arg, args_dict)
+
+        if isinstance(arg, torch.Tensor):
+            cpu_tensor = arg.cpu()
+            tensor_path = os.path.join(dir_path, f"tensor_{counts['tensors']}.pt")
+            with open(tensor_path, "wb") as f:
+                torch.save(cpu_tensor, f)
+            new_arg = {
+                "name": f"tensor_{counts['tensors']}", "type": "tensor", "dtype": str(arg.dtype), "ctype":
+                signature[counts["karg_cnt"]]
+            }
+            args_dict["argument_list"].append(new_arg)
+            counts["karg_cnt"] += 1
+            counts["tensors"] += 1
+
+        if isinstance(arg, numbers.Number):
+            if counts["karg_cnt"] not in constants:
+                new_arg = {
+                    "name": f"scalarArg_{counts['scalars']}", "type": "scalar", "value": args[cnt], "ctype":
+                    signature[counts["karg_cnt"]]
+                }
+                args_dict["argument_list"].append(new_arg)
+            counts["karg_cnt"] += 1
+            counts["scalars"] += 1
+        cnt += 1
+    # Dump argument info as a JSON file
+    json_path = os.path.join(dir_path, "args_data.json")
+    with open(json_path, "w", encoding="utf-8") as json_file:
+        import json
+        json.dump(args_dict, json_file, indent=4)
+
+
 class XPULauncher:
 
     def __init__(self, src, metadata):  # pylint: disable=unused-argument
         ids = {"ids_of_const_exprs": src.fn.constexprs if hasattr(src, "fn") else tuple()}
         constants = src.constants if hasattr(src, "constants") else {}
         cst_key = lambda i: src.fn.arg_names.index(i) if isinstance(i, str) else i
-        constants = {cst_key(key): value for key, value in constants.items()}
-        signature = {cst_key(key): value for key, value in src.signature.items()}
-        src = make_launcher(constants, signature, ids)
+        self.constants = {cst_key(key): value for key, value in constants.items()}
+        self.signature = {cst_key(key): value for key, value in src.signature.items()}
+        src = make_launcher(self.constants, self.signature, ids)
         mod = compile_module_from_src(src, "__triton_launcher")
         self.launch = mod.launch
 
     def __call__(self, *args, **kwargs):
+        # Serialize KernelArguments for SPIR-V Runner
+        serialize_kernel_args = os.getenv("TRITON_XPU_DUMP_SPIRV_KERNEL_ARGS", None)
+        if serialize_kernel_args:
+            serialize_args(args, self.constants, self.signature)
         self.launch(*args, **kwargs)