change in TRT-LLM loading mechanism and exposing aot_joint_export in _compiler.py #3398
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -3,6 +3,9 @@ | |
| import functools | ||
| import logging | ||
| import os | ||
| import shutil | ||
| import subprocess | ||
| import sys | ||
| from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union, overload | ||
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| import numpy as np | ||
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@@ -12,6 +15,7 @@ | |
| from torch.fx.node import Argument, Target | ||
| from torch.fx.passes.shape_prop import TensorMetadata | ||
| from torch_tensorrt import _enums | ||
| from torch_tensorrt._enums import Platform | ||
| from torch_tensorrt.dynamo._settings import CompilationSettings | ||
| from torch_tensorrt.dynamo._SourceIR import SourceIR | ||
| from torch_tensorrt.dynamo.conversion._ConversionContext import ConversionContext | ||
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@@ -923,64 +927,151 @@ def args_bounds_check( | |
| return args[i] if len(args) > i and args[i] is not None else replacement | ||
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| def install_wget(platform: str) -> None: | ||
| if shutil.which("wget"): | ||
| _LOGGER.debug("wget is already installed") | ||
| return | ||
| if platform.startswith("linux"): | ||
| try: | ||
| # if its root | ||
| if os.geteuid() == 0: | ||
| subprocess.run(["apt-get", "update"], check=True) | ||
| subprocess.run(["apt-get", "install", "-y", "wget"], check=True) | ||
| else: | ||
| _LOGGER.debug("Please run with sudo permissions") | ||
| subprocess.run(["sudo", "apt-get", "update"], check=True) | ||
| subprocess.run(["sudo", "apt-get", "install", "-y", "wget"], check=True) | ||
| except subprocess.CalledProcessError as e: | ||
| _LOGGER.debug("Error installing wget:", e) | ||
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| def install_mpi(platform: str) -> None: | ||
| if platform.startswith("linux"): | ||
| try: | ||
| # if its root | ||
| if os.geteuid() == 0: | ||
| subprocess.run(["apt-get", "update"], check=True) | ||
| subprocess.run(["apt-get", "install", "-y", "libmpich-dev"], check=True) | ||
| subprocess.run( | ||
| ["apt-get", "install", "-y", "libopenmpi-dev"], check=True | ||
| ) | ||
| else: | ||
| _LOGGER.debug("Please run with sudo permissions") | ||
| subprocess.run(["sudo", "apt-get", "update"], check=True) | ||
| subprocess.run( | ||
| ["sudo", "apt-get", "install", "-y", "libmpich-dev"], check=True | ||
| ) | ||
| subprocess.run( | ||
| ["sudo", "apt-get", "install", "-y", "libopenmpi-dev"], check=True | ||
| ) | ||
| except subprocess.CalledProcessError as e: | ||
| _LOGGER.debug("Error installing mpi libs:", e) | ||
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| def download_plugin_lib_path(py_version: str, platform: str) -> str: | ||
| plugin_lib_path = None | ||
| if py_version not in ("cp310", "cp312"): | ||
| _LOGGER.warning( | ||
| "No available wheel for python versions other than py3.10 and py3.12" | ||
| ) | ||
| install_wget(platform) | ||
| base_url = "https://pypi.nvidia.com/tensorrt-llm/" | ||
| file_name = f"tensorrt_llm-0.17.0.post1-{py_version}-{py_version}-{platform}.whl" | ||
| download_url = base_url + file_name | ||
| cmd = ["wget", download_url] | ||
| try: | ||
| if not (os.path.exists(file_name)): | ||
| _LOGGER.info(f"Running command: {' '.join(cmd)}") | ||
| subprocess.run(cmd) | ||
| _LOGGER.info("Download complete of wheel") | ||
| if os.path.exists(file_name): | ||
| _LOGGER.info("filename now present") | ||
| if os.path.exists("./tensorrt_llm/libs/libnvinfer_plugin_tensorrt_llm.so"): | ||
| plugin_lib_path = ( | ||
| "./tensorrt_llm/libs/" + "libnvinfer_plugin_tensorrt_llm.so" | ||
| ) | ||
| else: | ||
| import zipfile | ||
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||
| with zipfile.ZipFile(file_name, "r") as zip_ref: | ||
| zip_ref.extractall(".") # Extract to a folder named 'tensorrt_llm' | ||
| plugin_lib_path = ( | ||
| "./tensorrt_llm/libs/" + "libnvinfer_plugin_tensorrt_llm.so" | ||
| ) | ||
| except subprocess.CalledProcessError as e: | ||
| _LOGGER.debug(f"Error occurred while trying to download: {e}") | ||
| except Exception as e: | ||
| _LOGGER.debug(f"An unexpected error occurred: {e}") | ||
| return plugin_lib_path | ||
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| def load_tensorrt_llm() -> bool: | ||
| """ | ||
| Attempts to load the TensorRT-LLM plugin and initialize it. | ||
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| Returns: | ||
| bool: True if the plugin was successfully loaded and initialized, False otherwise. | ||
| """ | ||
| plugin_lib_path = os.environ.get("TRTLLM_PLUGINS_PATH") | ||
| if not plugin_lib_path: | ||
| _LOGGER.warning( | ||
| "Please set the TRTLLM_PLUGINS_PATH to the directory containing libnvinfer_plugin_tensorrt_llm.so to use converters for torch.distributed ops or else set the USE_TRTLLM_PLUGINS variable to download the shared library", | ||
| ) | ||
| for key, value in os.environ.items(): | ||
| print(f"{key}: {value}") | ||
| use_trtllm_plugin = os.environ.get("USE_TRTLLM_PLUGINS", "0").lower() in ( | ||
| "1", | ||
| "true", | ||
| "yes", | ||
| "on", | ||
| ) | ||
| if not use_trtllm_plugin: | ||
| _LOGGER.warning( | ||
| "Neither TRTLLM_PLUGIN_PATH is set nor is it directed to download the shared library" | ||
| ) | ||
| return False | ||
| else: | ||
| py_version = f"cp{sys.version_info.major}{sys.version_info.minor}" | ||
|
There was a problem hiding this comment. Why do we restrict to cp310 and cp312, It shouldnt matter if we are pulling the whl and unzipping ourselves There was a problem hiding this comment. https://pypi.nvidia.com/tensorrt-llm/ In this since I see the tags for only cp310 and cp312 I added the check |
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| platform = Platform.current_platform() | ||
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| platform = str(platform).lower() | ||
| plugin_lib_path = download_plugin_lib_path(py_version, platform) | ||
| try: | ||
| # Load the shared | ||
| install_mpi(platform) | ||
| handle = ctypes.CDLL(plugin_lib_path) | ||
| _LOGGER.info(f"Successfully loaded plugin library: {plugin_lib_path}") | ||
| except OSError as e_os_error: | ||
| _LOGGER.error( | ||
| f"Failed to load libnvinfer_plugin_tensorrt_llm.so from {plugin_lib_path}" | ||
| f"Ensure the path is correct and the library is compatible", | ||
| exc_info=e_os_error, | ||
| ) | ||
| return False | ||
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| try: | ||
| # Configure plugin initialization arguments | ||
| handle.initTrtLlmPlugins.argtypes = [ctypes.c_void_p, ctypes.c_char_p] | ||
| handle.initTrtLlmPlugins.restype = ctypes.c_bool | ||
| except AttributeError as e_plugin_unavailable: | ||
| _LOGGER.warning( | ||
| "Unable to initialize the TensorRT-LLM plugin library", | ||
| exc_info=e_plugin_unavailable, | ||
| ) | ||
| return False | ||
|
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||
| try: | ||
| # Initialize the plugin | ||
| TRT_LLM_PLUGIN_NAMESPACE = "tensorrt_llm" | ||
| if handle.initTrtLlmPlugins(None, TRT_LLM_PLUGIN_NAMESPACE.encode("utf-8")): | ||
| _LOGGER.info("TensorRT-LLM plugin successfully initialized") | ||
| return True | ||
| else: | ||
| _LOGGER.warning("TensorRT-LLM plugin library failed in initialization") | ||
| return False | ||
| except Exception as e_initialization_error: | ||
| _LOGGER.warning( | ||
| "Exception occurred during TensorRT-LLM plugin library initialization", | ||
| exc_info=e_initialization_error, | ||
| ) | ||
| return False | ||
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Lets put this utility in some place that is more user accessible like torch_tensorrt.utils