[Misc] Add SPDX-License-Identifier headers to python source files (#12628)

- **Add SPDX license headers to python source files**
- **Check for SPDX headers using pre-commit**

commit 9d7ef44c3cfb72ca4c32e1c677d99259d10d4745
Author: Russell Bryant <rbryant@redhat.com>
Date:   Fri Jan 31 14:18:24 2025 -0500

    Add SPDX license headers to python source files
    
This commit adds SPDX license headers to python source files as
recommended to
the project by the Linux Foundation. These headers provide a concise way
that is
both human and machine readable for communicating license information
for each
source file. It helps avoid any ambiguity about the license of the code
and can
    also be easily used by tools to help manage license compliance.
    
The Linux Foundation runs license scans against the codebase to help
ensure
    we are in compliance with the licenses of the code we use, including
dependencies. Having these headers in place helps that tool do its job.
    
    More information can be found on ...

benchmarks/cutlass_benchmarks/w8a8_benchmarks.py

+# SPDX-License-Identifier: Apache-2.0
+
 import argparse
 import copy
 import itertools

benchmarks/cutlass_benchmarks/weight_shapes.py

+# SPDX-License-Identifier: Apache-2.0
+
 # Weight Shapes are in the format
 # ([K, N], TP_SPLIT_DIM)
 # Example:

benchmarks/disagg_benchmarks/disagg_prefill_proxy_server.py

+# SPDX-License-Identifier: Apache-2.0
+
 import os
 
 import aiohttp

benchmarks/disagg_benchmarks/round_robin_proxy.py

+# SPDX-License-Identifier: Apache-2.0
+
 import asyncio
 import itertools
 

benchmarks/disagg_benchmarks/visualize_benchmark_results.py

+# SPDX-License-Identifier: Apache-2.0
+
 import json
 
 import matplotlib.pyplot as plt

benchmarks/fused_kernels/layernorm_rms_benchmarks.py

+# SPDX-License-Identifier: Apache-2.0
+
 import pickle as pkl
 import time
 from dataclasses import dataclass

benchmarks/kernels/benchmark_aqlm.py

+# SPDX-License-Identifier: Apache-2.0
+
 import os
 import sys
 from typing import Optional

benchmarks/kernels/benchmark_layernorm.py

+# SPDX-License-Identifier: Apache-2.0
+
 import time
 
 import torch

benchmarks/kernels/benchmark_lora.py

+# SPDX-License-Identifier: Apache-2.0
+
 import argparse
 import copy
 import json

benchmarks/kernels/benchmark_machete.py

+# SPDX-License-Identifier: Apache-2.0
+
 import argparse
 import copy
 import itertools

benchmarks/kernels/benchmark_marlin.py

+# SPDX-License-Identifier: Apache-2.0
+
 from typing import List
 
 import torch

benchmarks/kernels/benchmark_moe.py

+# SPDX-License-Identifier: Apache-2.0
+
 import argparse
 import time
 from datetime import datetime

benchmarks/kernels/benchmark_paged_attention.py

+# SPDX-License-Identifier: Apache-2.0
+
 import random
 import time
 from typing import List, Optional

benchmarks/kernels/benchmark_quant.py

+# SPDX-License-Identifier: Apache-2.0
+
 import time
 
 import torch

benchmarks/kernels/benchmark_rmsnorm.py

+# SPDX-License-Identifier: Apache-2.0
+
 import itertools
 from typing import Optional, Tuple, Union
 

benchmarks/kernels/benchmark_rope.py

+# SPDX-License-Identifier: Apache-2.0
+
 from itertools import accumulate
 from typing import List, Optional
 

benchmarks/kernels/benchmark_shapes.py

+# SPDX-License-Identifier: Apache-2.0
+
 WEIGHT_SHAPES = {
     "ideal": [[4 * 256 * 32, 256 * 32]],
     "mistralai/Mistral-7B-v0.1/TP1": [

benchmarks/kernels/graph_machete_bench.py

+# SPDX-License-Identifier: Apache-2.0
+
 import math
 import pickle
 import re

benchmarks/kernels/utils.py

+# SPDX-License-Identifier: Apache-2.0
+
 import dataclasses
 from typing import Any, Callable, Iterable, Optional
 

benchmarks/kernels/weight_shapes.py

+# SPDX-License-Identifier: Apache-2.0
+
 # Weight Shapes are in the format
 # ([K, N], TP_SPLIT_DIM)
 # Example: