[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 the SPDX site: - https://spdx.dev/learn/handling-license-info/ Signed-off-by: Russell Bryant <rbryant@redhat.com> commit 5a1cf1cb3b80759131c73f6a9dddebccac039dea Author: Russell Bryant <rbryant@redhat.com> Date: Fri Jan 31 14:36:32 2025 -0500 Check for SPDX headers using pre-commit Signed-off-by: Russell Bryant <rbryant@redhat.com> --------- Signed-off-by: Russell Bryant <rbryant@redhat.com>
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# SPDX-License-Identifier: Apache-2.0
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import os
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import os
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import sys
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import sys
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import zipfile
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import zipfile
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# SPDX-License-Identifier: Apache-2.0
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import argparse
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import argparse
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import os
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import os
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# SPDX-License-Identifier: Apache-2.0
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"""
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"""
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LM eval harness on model to compare vs HF baseline computed offline.
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LM eval harness on model to compare vs HF baseline computed offline.
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Configs are found in configs/$MODEL.yaml
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Configs are found in configs/$MODEL.yaml
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# SPDX-License-Identifier: Apache-2.0
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import json
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import json
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import os
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import os
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from pathlib import Path
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from pathlib import Path
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# SPDX-License-Identifier: Apache-2.0
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import argparse
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import argparse
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from transformers import AutoTokenizer
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from transformers import AutoTokenizer
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# SPDX-License-Identifier: Apache-2.0
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import argparse
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import argparse
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import json
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import json
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from pathlib import Path
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from pathlib import Path
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# SPDX-License-Identifier: Apache-2.0
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from lmdeploy.serve.openai.api_client import APIClient
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from lmdeploy.serve.openai.api_client import APIClient
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api_client = APIClient("http://localhost:8000")
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api_client = APIClient("http://localhost:8000")
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# SPDX-License-Identifier: Apache-2.0
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import datetime
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import datetime
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import json
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import json
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import os
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import os
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language: system
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language: system
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verbose: true
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verbose: true
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stages: [commit-msg]
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stages: [commit-msg]
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- id: check-spdx-header
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name: Check SPDX headers
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entry: python tools/check_spdx_header.py
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language: python
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types: [python]
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- id: suggestion
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- id: suggestion
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name: Suggestion
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name: Suggestion
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entry: bash -c 'echo "To bypass pre-commit hooks, add --no-verify to git commit."'
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entry: bash -c 'echo "To bypass pre-commit hooks, add --no-verify to git commit."'
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language: system
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language: system
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verbose: true
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verbose: true
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pass_filenames: false
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pass_filenames: false
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# SPDX-License-Identifier: Apache-2.0
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import json
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import json
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import os
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import os
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import sys
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import sys
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# SPDX-License-Identifier: Apache-2.0
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"""Benchmark guided decoding throughput."""
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"""Benchmark guided decoding throughput."""
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import argparse
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import argparse
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import dataclasses
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import dataclasses
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# SPDX-License-Identifier: Apache-2.0
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"""Benchmark the latency of processing a single batch of requests."""
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"""Benchmark the latency of processing a single batch of requests."""
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import argparse
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import argparse
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import dataclasses
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import dataclasses
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# SPDX-License-Identifier: Apache-2.0
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"""
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"""
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Offline benchmark to test the long document QA throughput.
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Offline benchmark to test the long document QA throughput.
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# SPDX-License-Identifier: Apache-2.0
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"""
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"""
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Benchmark the efficiency of prefix caching.
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Benchmark the efficiency of prefix caching.
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# SPDX-License-Identifier: Apache-2.0
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"""Benchmark offline prioritization."""
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"""Benchmark offline prioritization."""
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import argparse
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import argparse
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import dataclasses
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import dataclasses
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# SPDX-License-Identifier: Apache-2.0
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r"""Benchmark online serving throughput.
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r"""Benchmark online serving throughput.
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On the server side, run one of the following commands:
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On the server side, run one of the following commands:
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# SPDX-License-Identifier: Apache-2.0
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r"""Benchmark online serving throughput with guided decoding.
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r"""Benchmark online serving throughput with guided decoding.
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On the server side, run one of the following commands:
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On the server side, run one of the following commands:
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# SPDX-License-Identifier: Apache-2.0
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"""Benchmark offline inference throughput."""
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"""Benchmark offline inference throughput."""
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import argparse
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import argparse
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import dataclasses
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import dataclasses
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# SPDX-License-Identifier: Apache-2.0
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import argparse
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import argparse
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import copy
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import copy
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import itertools
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import itertools
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# SPDX-License-Identifier: Apache-2.0
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# Cutlass bench utils
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# Cutlass bench utils
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from typing import Iterable, Tuple
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from typing import Iterable, Tuple
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# SPDX-License-Identifier: Apache-2.0
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import argparse
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import argparse
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import copy
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import copy
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import itertools
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import itertools
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# SPDX-License-Identifier: Apache-2.0
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# Weight Shapes are in the format
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# Weight Shapes are in the format
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# ([K, N], TP_SPLIT_DIM)
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# ([K, N], TP_SPLIT_DIM)
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# Example:
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# Example:
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# SPDX-License-Identifier: Apache-2.0
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import os
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import os
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import aiohttp
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import aiohttp
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# SPDX-License-Identifier: Apache-2.0
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import asyncio
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import asyncio
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import itertools
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import itertools
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# SPDX-License-Identifier: Apache-2.0
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import json
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import json
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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# SPDX-License-Identifier: Apache-2.0
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import pickle as pkl
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import pickle as pkl
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import time
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import time
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from dataclasses import dataclass
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from dataclasses import dataclass
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# SPDX-License-Identifier: Apache-2.0
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import os
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import os
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import sys
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import sys
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from typing import Optional
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from typing import Optional
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# SPDX-License-Identifier: Apache-2.0
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import time
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import time
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import torch
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import torch
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# SPDX-License-Identifier: Apache-2.0
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import argparse
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import argparse
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import copy
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import copy
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import json
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import json
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# SPDX-License-Identifier: Apache-2.0
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import argparse
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import argparse
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import copy
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import copy
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import itertools
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import itertools
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# SPDX-License-Identifier: Apache-2.0
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from typing import List
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from typing import List
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import torch
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import torch
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# SPDX-License-Identifier: Apache-2.0
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import argparse
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import argparse
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import time
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import time
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from datetime import datetime
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from datetime import datetime
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# SPDX-License-Identifier: Apache-2.0
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import random
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import random
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import time
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import time
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from typing import List, Optional
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from typing import List, Optional
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# SPDX-License-Identifier: Apache-2.0
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import time
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import time
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import torch
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import torch
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# SPDX-License-Identifier: Apache-2.0
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import itertools
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import itertools
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from typing import Optional, Tuple, Union
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from typing import Optional, Tuple, Union
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# SPDX-License-Identifier: Apache-2.0
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from itertools import accumulate
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from itertools import accumulate
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from typing import List, Optional
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from typing import List, Optional
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# SPDX-License-Identifier: Apache-2.0
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WEIGHT_SHAPES = {
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WEIGHT_SHAPES = {
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"ideal": [[4 * 256 * 32, 256 * 32]],
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"ideal": [[4 * 256 * 32, 256 * 32]],
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"mistralai/Mistral-7B-v0.1/TP1": [
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"mistralai/Mistral-7B-v0.1/TP1": [
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# SPDX-License-Identifier: Apache-2.0
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import math
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import math
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import pickle
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import pickle
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import re
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import re
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# SPDX-License-Identifier: Apache-2.0
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import dataclasses
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import dataclasses
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from typing import Any, Callable, Iterable, Optional
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from typing import Any, Callable, Iterable, Optional
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# SPDX-License-Identifier: Apache-2.0
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# Weight Shapes are in the format
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# Weight Shapes are in the format
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# ([K, N], TP_SPLIT_DIM)
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# ([K, N], TP_SPLIT_DIM)
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# Example:
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# Example:
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# SPDX-License-Identifier: Apache-2.0
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import cProfile
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import cProfile
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import pstats
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import pstats
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# SPDX-License-Identifier: Apache-2.0
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#!/usr/bin/env python3
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#!/usr/bin/env python3
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#
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#
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# SPDX-License-Identifier: Apache-2.0
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# ruff: noqa
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# ruff: noqa
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# code borrowed from https://github.com/pytorch/pytorch/blob/main/torch/utils/collect_env.py
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# code borrowed from https://github.com/pytorch/pytorch/blob/main/torch/utils/collect_env.py
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# SPDX-License-Identifier: Apache-2.0
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import enum
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import enum
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from typing import Dict, Union
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from typing import Dict, Union
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# SPDX-License-Identifier: Apache-2.0
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import itertools
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import itertools
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import math
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import math
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import os
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import os
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# SPDX-License-Identifier: Apache-2.0
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# Configuration file for the Sphinx documentation builder.
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# Configuration file for the Sphinx documentation builder.
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#
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#
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# This file only contains a selection of the most common options. For a full
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# This file only contains a selection of the most common options. For a full
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# SPDX-License-Identifier: Apache-2.0
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import itertools
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import itertools
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import re
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import re
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from dataclasses import dataclass, field
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from dataclasses import dataclass, field
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# SPDX-License-Identifier: Apache-2.0
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from vllm import LLM, SamplingParams
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from vllm import LLM, SamplingParams
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from vllm.utils import FlexibleArgumentParser
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from vllm.utils import FlexibleArgumentParser
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# SPDX-License-Identifier: Apache-2.0
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from vllm import LLM, SamplingParams
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from vllm import LLM, SamplingParams
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# Sample prompts.
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# Sample prompts.
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# SPDX-License-Identifier: Apache-2.0
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"""
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"""
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This example shows how to use vLLM for running offline inference
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This example shows how to use vLLM for running offline inference
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with the correct prompt format on audio language models.
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with the correct prompt format on audio language models.
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# SPDX-License-Identifier: Apache-2.0
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from vllm import LLM, SamplingParams
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from vllm import LLM, SamplingParams
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# Sample prompts.
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# Sample prompts.
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# SPDX-License-Identifier: Apache-2.0
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from vllm import LLM
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from vllm import LLM
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# Sample prompts.
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# Sample prompts.
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# SPDX-License-Identifier: Apache-2.0
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from vllm import LLM, SamplingParams
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from vllm import LLM, SamplingParams
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llm = LLM(model="meta-llama/Meta-Llama-3-8B-Instruct")
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llm = LLM(model="meta-llama/Meta-Llama-3-8B-Instruct")
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# SPDX-License-Identifier: Apache-2.0
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# ruff: noqa
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# ruff: noqa
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import json
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import json
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import random
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import random
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# SPDX-License-Identifier: Apache-2.0
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from vllm import LLM
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from vllm import LLM
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# Sample prompts.
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# Sample prompts.
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# SPDX-License-Identifier: Apache-2.0
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from dataclasses import asdict
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from dataclasses import asdict
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from vllm import LLM, SamplingParams
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from vllm import LLM, SamplingParams
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# SPDX-License-Identifier: Apache-2.0
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from vllm import LLM, SamplingParams
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from vllm import LLM, SamplingParams
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# Sample prompts.
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# Sample prompts.
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# SPDX-License-Identifier: Apache-2.0
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"""
|
"""
|
||||||
This example shows how to use Ray Data for running offline batch inference
|
This example shows how to use Ray Data for running offline batch inference
|
||||||
distributively on a multi-nodes cluster.
|
distributively on a multi-nodes cluster.
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
from vllm import LLM
|
from vllm import LLM
|
||||||
|
|
||||||
# Sample prompts.
|
# Sample prompts.
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
'''
|
'''
|
||||||
Demonstrate prompting of text-to-text
|
Demonstrate prompting of text-to-text
|
||||||
encoder/decoder models, specifically BART
|
encoder/decoder models, specifically BART
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
'''
|
'''
|
||||||
Demonstrate prompting of text-to-text
|
Demonstrate prompting of text-to-text
|
||||||
encoder/decoder models, specifically Florence-2
|
encoder/decoder models, specifically Florence-2
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
from huggingface_hub import hf_hub_download
|
from huggingface_hub import hf_hub_download
|
||||||
|
|
||||||
from vllm import LLM, SamplingParams
|
from vllm import LLM, SamplingParams
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
import argparse
|
import argparse
|
||||||
from typing import List, Tuple
|
from typing import List, Tuple
|
||||||
|
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
This example shows how to use LoRA with different quantization techniques
|
This example shows how to use LoRA with different quantization techniques
|
||||||
for offline inference.
|
for offline inference.
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
import gc
|
import gc
|
||||||
import time
|
import time
|
||||||
from typing import List
|
from typing import List
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
This example shows how to use the multi-LoRA functionality
|
This example shows how to use the multi-LoRA functionality
|
||||||
for offline inference.
|
for offline inference.
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
from vllm import LLM, SamplingParams
|
from vllm import LLM, SamplingParams
|
||||||
|
|
||||||
# Sample prompts.
|
# Sample prompts.
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
import os
|
import os
|
||||||
|
|
||||||
from vllm import LLM, SamplingParams
|
from vllm import LLM, SamplingParams
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
# ruff: noqa
|
# ruff: noqa
|
||||||
import argparse
|
import argparse
|
||||||
|
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
from vllm import LLM, SamplingParams
|
from vllm import LLM, SamplingParams
|
||||||
from vllm.distributed import cleanup_dist_env_and_memory
|
from vllm.distributed import cleanup_dist_env_and_memory
|
||||||
|
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
import inspect
|
import inspect
|
||||||
import json
|
import json
|
||||||
import os
|
import os
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
import argparse
|
import argparse
|
||||||
import dataclasses
|
import dataclasses
|
||||||
import os
|
import os
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
a simple demonstration of RLHF with vLLM, inspired by
|
a simple demonstration of RLHF with vLLM, inspired by
|
||||||
the OpenRLHF framework https://github.com/OpenRLHF/OpenRLHF .
|
the OpenRLHF framework https://github.com/OpenRLHF/OpenRLHF .
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
Saves each worker's model state dict directly to a checkpoint, which enables a
|
Saves each worker's model state dict directly to a checkpoint, which enables a
|
||||||
fast load path for large tensor-parallel models where each worker only needs to
|
fast load path for large tensor-parallel models where each worker only needs to
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
from vllm import LLM
|
from vllm import LLM
|
||||||
|
|
||||||
# Sample prompts.
|
# Sample prompts.
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
import os
|
import os
|
||||||
import time
|
import time
|
||||||
|
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
from enum import Enum
|
from enum import Enum
|
||||||
|
|
||||||
from pydantic import BaseModel
|
from pydantic import BaseModel
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
experimental support for tensor-parallel inference with torchrun,
|
experimental support for tensor-parallel inference with torchrun,
|
||||||
see https://github.com/vllm-project/vllm/issues/11400 for
|
see https://github.com/vllm-project/vllm/issues/11400 for
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
from vllm import LLM, SamplingParams
|
from vllm import LLM, SamplingParams
|
||||||
|
|
||||||
prompts = [
|
prompts = [
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
This example shows how to use vLLM for running offline inference with
|
This example shows how to use vLLM for running offline inference with
|
||||||
the correct prompt format on vision language models for text generation.
|
the correct prompt format on vision language models for text generation.
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
This example shows how to use vLLM for running offline inference with
|
This example shows how to use vLLM for running offline inference with
|
||||||
the correct prompt format on vision language models for multimodal embedding.
|
the correct prompt format on vision language models for multimodal embedding.
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
This example shows how to use vLLM for running offline inference with
|
This example shows how to use vLLM for running offline inference with
|
||||||
multi-image input on vision language models for text generation,
|
multi-image input on vision language models for text generation,
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
import time
|
import time
|
||||||
|
|
||||||
from vllm import LLM, SamplingParams
|
from vllm import LLM, SamplingParams
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""Example Python client for `vllm.entrypoints.api_server`
|
"""Example Python client for `vllm.entrypoints.api_server`
|
||||||
NOTE: The API server is used only for demonstration and simple performance
|
NOTE: The API server is used only for demonstration and simple performance
|
||||||
benchmarks. It is not intended for production use.
|
benchmarks. It is not intended for production use.
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
Example of using the OpenAI entrypoint's rerank API which is compatible with
|
Example of using the OpenAI entrypoint's rerank API which is compatible with
|
||||||
the Cohere SDK: https://github.com/cohere-ai/cohere-python
|
the Cohere SDK: https://github.com/cohere-ai/cohere-python
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
import argparse
|
import argparse
|
||||||
|
|
||||||
import gradio as gr
|
import gradio as gr
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
import argparse
|
import argparse
|
||||||
import json
|
import json
|
||||||
|
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
Example of using the OpenAI entrypoint's rerank API which is compatible with
|
Example of using the OpenAI entrypoint's rerank API which is compatible with
|
||||||
Jina and Cohere https://jina.ai/reranker
|
Jina and Cohere https://jina.ai/reranker
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
from openai import OpenAI
|
from openai import OpenAI
|
||||||
|
|
||||||
# Modify OpenAI's API key and API base to use vLLM's API server.
|
# Modify OpenAI's API key and API base to use vLLM's API server.
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""An example showing how to use vLLM to serve multimodal models
|
"""An example showing how to use vLLM to serve multimodal models
|
||||||
and run online serving with OpenAI client.
|
and run online serving with OpenAI client.
|
||||||
|
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
Set up this example by starting a vLLM OpenAI-compatible server with tool call
|
Set up this example by starting a vLLM OpenAI-compatible server with tool call
|
||||||
options enabled. For example:
|
options enabled. For example:
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
from enum import Enum
|
from enum import Enum
|
||||||
|
|
||||||
from openai import OpenAI
|
from openai import OpenAI
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
An example shows how to generate chat completions from reasoning models
|
An example shows how to generate chat completions from reasoning models
|
||||||
like DeepSeekR1.
|
like DeepSeekR1.
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
An example shows how to generate chat completions from reasoning models
|
An example shows how to generate chat completions from reasoning models
|
||||||
like DeepSeekR1.
|
like DeepSeekR1.
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
import argparse
|
import argparse
|
||||||
import base64
|
import base64
|
||||||
import io
|
import io
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
from openai import OpenAI
|
from openai import OpenAI
|
||||||
|
|
||||||
# Modify OpenAI's API key and API base to use vLLM's API server.
|
# Modify OpenAI's API key and API base to use vLLM's API server.
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
Example online usage of Score API.
|
Example online usage of Score API.
|
||||||
|
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
from openai import OpenAI
|
from openai import OpenAI
|
||||||
|
|
||||||
# Modify OpenAI's API key and API base to use vLLM's API server.
|
# Modify OpenAI's API key and API base to use vLLM's API server.
|
||||||
|
@ -1,3 +1,4 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
"""
|
"""
|
||||||
Example online usage of Pooling API.
|
Example online usage of Pooling API.
|
||||||
|
|
||||||
|
@ -1,3 +1,5 @@
|
|||||||
|
# SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
import requests
|
import requests
|
||||||
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import (
|
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import (
|
||||||
OTLPSpanExporter)
|
OTLPSpanExporter)
|
||||||
|
Some files were not shown because too many files have changed in this diff Show More
Loading…
x
Reference in New Issue
Block a user