mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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115 lines
4.7 KiB
Python
115 lines
4.7 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2022-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Shared utilities for local LLM model paths and HuggingFace download mocking."""
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import os
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from functools import wraps
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from pathlib import Path
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from typing import Optional
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from unittest.mock import patch
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# Mapping from HuggingFace Hub ID to local subdirectory under LLM_MODELS_ROOT.
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# NOTE: hf_id_to_llm_models_subdir below will fall back to checking if the model name exists
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# in LLM_MODELS_ROOT if not present here, so it's not required to list models that already
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# exist as a top-level directory in LLM_MODELS_ROOT.
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HF_ID_TO_LLM_MODELS_SUBDIR = {
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"meta-llama/Meta-Llama-3.1-8B-Instruct": "llama-3.1-model/Llama-3.1-8B-Instruct",
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"meta-llama/Llama-3.1-8B-Instruct": "llama-3.1-model/Llama-3.1-8B-Instruct",
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"meta-llama/Llama-3.1-8B": "llama-3.1-model/Meta-Llama-3.1-8B",
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"TinyLlama/TinyLlama-1.1B-Chat-v1.0": "llama-models-v2/TinyLlama-1.1B-Chat-v1.0",
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"meta-llama/Llama-4-Scout-17B-16E-Instruct": "llama4-models/Llama-4-Scout-17B-16E-Instruct",
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"mistralai/Mixtral-8x7B-Instruct-v0.1": "Mixtral-8x7B-Instruct-v0.1",
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"mistralai/Mistral-Small-3.1-24B-Instruct-2503": "Mistral-Small-3.1-24B-Instruct-2503",
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"Qwen/Qwen3-30B-A3B": "Qwen3/Qwen3-30B-A3B",
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"Qwen/Qwen2.5-3B-Instruct": "Qwen2.5-3B-Instruct",
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"microsoft/Phi-3-mini-4k-instruct": "Phi-3/Phi-3-mini-4k-instruct",
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"deepseek-ai/DeepSeek-V3": "DeepSeek-V3",
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"deepseek-ai/DeepSeek-R1": "DeepSeek-R1/DeepSeek-R1",
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"ibm-ai-platform/Bamba-9B-v2": "Bamba-9B-v2",
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"nvidia/NVIDIA-Nemotron-Nano-12B-v2": "NVIDIA-Nemotron-Nano-12B-v2",
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"nvidia/NVIDIA-Nemotron-Nano-31B-A3-v3": "NVIDIA-Nemotron-Nano-31B-A3-v3",
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"nvidia/Nemotron-Nano-3-30B-A3.5B-dev-1024": "Nemotron-Nano-3-30B-A3.5B-dev-1024",
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"yuhuili/EAGLE3-LLaMA3.1-Instruct-8B": "EAGLE3-LLaMA3.1-Instruct-8B",
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}
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def llm_models_root(check: bool = False) -> Optional[Path]:
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root = Path("/home/scratch.trt_llm_data/llm-models/")
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if "LLM_MODELS_ROOT" in os.environ:
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root = Path(os.environ.get("LLM_MODELS_ROOT"))
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if not root.exists():
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root = Path("/scratch.trt_llm_data/llm-models/")
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if check:
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assert root.exists(), (
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"You must set LLM_MODELS_ROOT env or be able to access /home/scratch.trt_llm_data to run this test"
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)
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return root if root.exists() else None
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def llm_datasets_root() -> str:
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return os.path.join(llm_models_root(check=True), "datasets")
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def hf_id_to_local_model_dir(hf_hub_id: str) -> str | None:
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"""Return the local model directory under LLM_MODELS_ROOT for a given HuggingFace Hub ID.
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Raises ValueError if the model is not found in LLM_MODELS_ROOT. This is meant to ensure that tests do not download
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models from HuggingFace.
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"""
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root = llm_models_root()
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if root is None:
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return None
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if hf_hub_id in HF_ID_TO_LLM_MODELS_SUBDIR:
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return str(root / HF_ID_TO_LLM_MODELS_SUBDIR[hf_hub_id])
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# Fall back to checking if the model name exists as a top-level directory in LLM_MODELS_ROOT
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model_name = hf_hub_id.split("/")[-1]
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if os.path.isdir(root / model_name):
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return str(root / model_name)
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raise ValueError(f"HuggingFace model '{hf_hub_id}' not found in LLM_MODELS_ROOT")
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def mock_snapshot_download(repo_id: str, **kwargs) -> str:
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"""Mock huggingface_hub.snapshot_download that returns an existing local model directory.
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NOTE: This function does not currently handle the revision / allow_patterns / ignore_patterns parameters.
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"""
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local_path = hf_id_to_local_model_dir(repo_id)
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if local_path is None:
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raise ValueError(f"Model '{repo_id}' not found in LLM_MODELS_ROOT")
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return local_path
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def with_mocked_hf_download(func):
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"""Decorator to mock huggingface_hub.snapshot_download for tests.
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When applied, any calls to snapshot_download will be redirected to use
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local model paths from LLM_MODELS_ROOT instead of downloading from HuggingFace.
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"""
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@wraps(func)
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def wrapper(*args, **kwargs):
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with patch("huggingface_hub.snapshot_download", side_effect=mock_snapshot_download):
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return func(*args, **kwargs)
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return wrapper
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