[build] enable existing pytorch (for GH200, aarch64, nightly) (vllm-p…

…roject#8713)

Signed-off-by: Alvant <alvasian@yandex.ru>

docs/source/getting_started/installation.rst

@@ -72,6 +72,29 @@ You can also build and install vLLM from source:
     $ cd vllm
     $ pip install -e .  # This may take 5-10 minutes.
 
+.. note::
+
+    This will uninstall existing PyTorch, and install the version required by vLLM. If you want to use an existing PyTorch installation, there need to be some changes:
+
+    .. code-block:: console
+
+        $ git clone https://github.com/vllm-project/vllm.git
+        $ cd vllm
+        $ python use_existing_torch.py
+        $ pip install -r requirements-build.txt
+        $ pip install -e . --no-build-isolation
+
+    The differences are:
+
+    - ``python use_existing_torch.py``: This script will remove all the PyTorch versions in the requirements files, so that the existing PyTorch installation will be used.
+    - ``pip install -r requirements-build.txt``: You need to manually install the requirements for building vLLM.
+    - ``pip install -e . --no-build-isolation``: You need to disable build isolation, so that the build system can use the existing PyTorch installation.
+
+    This is especially useful when the PyTorch dependency cannot be easily installed via pip, e.g.:
+
+    - build vLLM with PyTorch nightly or a custom PyTorch build.
+    - build vLLM with aarch64 and cuda (GH200), where the PyTorch wheels are not available on PyPI. Currently, only PyTorch nightly has wheels for aarch64 with CUDA. You can run ``pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu124`` to install PyTorch nightly, and then build vLLM on top of it.
+
 .. note::
 
     vLLM can fully run only on Linux, but you can still build it on other systems (for example, macOS). This build is only for development purposes, allowing for imports and a more convenient dev environment. The binaries will not be compiled and not work on non-Linux systems. You can create such a build with the following commands:

requirements-common.txt

@@ -18,7 +18,7 @@ prometheus_client >= 0.18.0
 prometheus-fastapi-instrumentator >= 7.0.0
 tiktoken >= 0.6.0  # Required for DBRX tokenizer
 lm-format-enforcer == 0.10.6
-outlines >= 0.0.43, < 0.1 # Requires torch >= 2.1.0
+outlines >= 0.0.43, < 0.1
 typing_extensions >= 4.10
 filelock >= 3.10.4 # filelock starts to support `mode` argument from 3.10.4
 partial-json-parser # used for parsing partial JSON outputs

use_existing_torch.py

@@ -0,0 +1,18 @@
+import glob
+
+requires_files = glob.glob('requirements*.txt')
+requires_files += ["pyproject.toml"]
+for file in requires_files:
+    print(f">>> cleaning {file}")
+    with open(file, 'r') as f:
+        lines = f.readlines()
+    if "torch" in "".join(lines).lower():
+        print("removed:")
+        with open(file, 'w') as f:
+            for line in lines:
+                if 'torch' not in line.lower():
+                    f.write(line)
+                else:
+                    print(line.strip())
+    print(f"<<< done cleaning {file}")
+    print()