chore: import upstream snapshot with attribution

python/sglang/srt/distributed/device_communicators/cuda_wrapper.py

@@ -0,0 +1,189 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+# Adapted from https://github.com/vllm-project/vllm/blob/v0.6.4.post1/vllm/distributed/device_communicators/cuda_wrapper.py
+
+"""This file is a pure Python wrapper for the cudart library.
+It avoids the need to compile a separate shared library, and is
+convenient for use when we just need to call a few functions.
+"""
+
+import ctypes
+import logging
+from dataclasses import dataclass
+from typing import Any, Dict, List, Optional
+
+# this line makes it possible to directly load `libcudart.so` using `ctypes`
+import torch  # noqa
+
+from sglang.srt.utils import is_musa
+
+_is_musa = is_musa()
+
+logger = logging.getLogger(__name__)
+
+# === export types and functions from cudart to Python ===
+# for the original cudart definition, please check
+# https://docs.nvidia.com/cuda/cuda-runtime-api/index.html
+
+cudaError_t = ctypes.c_int
+cudaMemcpyKind = ctypes.c_int
+
+
+class cudaIpcMemHandle_t(ctypes.Structure):
+    _fields_ = [("internal", ctypes.c_byte * 128)]
+
+
+@dataclass
+class Function:
+    name: str
+    restype: Any
+    argtypes: List[Any]
+
+
+def find_loaded_library(lib_name) -> Optional[str]:
+    """
+    According to according to https://man7.org/linux/man-pages/man5/proc_pid_maps.5.html,
+    the file `/proc/self/maps` contains the memory maps of the process, which includes the
+    shared libraries loaded by the process. We can use this file to find the path of the
+    a loaded library.
+    """  # noqa
+    found = False
+    with open("/proc/self/maps") as f:
+        for line in f:
+            if lib_name in line:
+                found = True
+                break
+    if not found:
+        # the library is not loaded in the current process
+        return None
+    # if lib_name is libcudart, we need to match a line with:
+    # address /path/to/libcudart-hash.so.11.0
+    start = line.index("/")
+    path = line[start:].strip()
+    filename = path.split("/")[-1]
+    assert filename.rpartition(".so")[0].startswith(
+        lib_name
+    ), f"Unexpected filename: {filename} for library {lib_name}"
+    return path
+
+
+class CudaRTLibrary:
+    exported_functions = [
+        # ​cudaError_t cudaSetDevice ( int  device )
+        Function("cudaSetDevice", cudaError_t, [ctypes.c_int]),
+        # cudaError_t 	cudaDeviceSynchronize ( void )
+        Function("cudaDeviceSynchronize", cudaError_t, []),
+        # ​cudaError_t cudaDeviceReset ( void )
+        Function("cudaDeviceReset", cudaError_t, []),
+        # const char* 	cudaGetErrorString ( cudaError_t error )
+        Function("cudaGetErrorString", ctypes.c_char_p, [cudaError_t]),
+        # ​cudaError_t 	cudaMalloc ( void** devPtr, size_t size )
+        Function(
+            "cudaMalloc",
+            cudaError_t,
+            [ctypes.POINTER(ctypes.c_void_p), ctypes.c_size_t],
+        ),
+        # ​cudaError_t 	cudaFree ( void* devPtr )
+        Function("cudaFree", cudaError_t, [ctypes.c_void_p]),
+        # ​cudaError_t cudaMemset ( void* devPtr, int  value, size_t count )
+        Function(
+            "cudaMemset", cudaError_t, [ctypes.c_void_p, ctypes.c_int, ctypes.c_size_t]
+        ),
+        # ​cudaError_t cudaMemcpy ( void* dst, const void* src, size_t count, cudaMemcpyKind kind ) # noqa
+        Function(
+            "cudaMemcpy",
+            cudaError_t,
+            [ctypes.c_void_p, ctypes.c_void_p, ctypes.c_size_t, cudaMemcpyKind],
+        ),
+        # cudaError_t cudaIpcGetMemHandle ( cudaIpcMemHandle_t* handle, void* devPtr ) # noqa
+        Function(
+            "cudaIpcGetMemHandle",
+            cudaError_t,
+            [ctypes.POINTER(cudaIpcMemHandle_t), ctypes.c_void_p],
+        ),
+        # ​cudaError_t cudaIpcOpenMemHandle ( void** devPtr, cudaIpcMemHandle_t handle, unsigned int  flags ) # noqa
+        Function(
+            "cudaIpcOpenMemHandle",
+            cudaError_t,
+            [ctypes.POINTER(ctypes.c_void_p), cudaIpcMemHandle_t, ctypes.c_uint],
+        ),
+    ]
+
+    # class attribute to store the mapping from the path to the library
+    # to avoid loading the same library multiple times
+    path_to_library_cache: Dict[str, Any] = {}
+
+    # class attribute to store the mapping from library path
+    #  to the corresponding dictionary
+    path_to_dict_mapping: Dict[str, Dict[str, Any]] = {}
+
+    def __init__(self, so_file: Optional[str] = None):
+        if so_file is None:
+            so_file = find_loaded_library("libcudart" if not _is_musa else "libmusart")
+            assert so_file is not None, "libcudart is not loaded in the current process"
+        if so_file not in CudaRTLibrary.path_to_library_cache:
+            lib = ctypes.CDLL(so_file)
+            CudaRTLibrary.path_to_library_cache[so_file] = lib
+        self.lib = CudaRTLibrary.path_to_library_cache[so_file]
+
+        if so_file not in CudaRTLibrary.path_to_dict_mapping:
+            _funcs = {}
+            for func in CudaRTLibrary.exported_functions:
+                f = getattr(self.lib, func.name)
+                f.restype = func.restype
+                f.argtypes = func.argtypes
+                _funcs[func.name] = f
+            CudaRTLibrary.path_to_dict_mapping[so_file] = _funcs
+        self.funcs = CudaRTLibrary.path_to_dict_mapping[so_file]
+
+    def CUDART_CHECK(self, result: cudaError_t) -> None:
+        if result != 0:
+            error_str = self.cudaGetErrorString(result)
+            raise RuntimeError(f"CUDART error: {error_str}")
+
+    def cudaGetErrorString(self, error: cudaError_t) -> str:
+        return self.funcs["cudaGetErrorString"](error).decode("utf-8")
+
+    def cudaSetDevice(self, device: int) -> None:
+        self.CUDART_CHECK(self.funcs["cudaSetDevice"](device))
+
+    def cudaDeviceSynchronize(self) -> None:
+        self.CUDART_CHECK(self.funcs["cudaDeviceSynchronize"]())
+
+    def cudaDeviceReset(self) -> None:
+        self.CUDART_CHECK(self.funcs["cudaDeviceReset"]())
+
+    def cudaMalloc(self, size: int) -> ctypes.c_void_p:
+        devPtr = ctypes.c_void_p()
+        self.CUDART_CHECK(self.funcs["cudaMalloc"](ctypes.byref(devPtr), size))
+        return devPtr
+
+    def cudaFree(self, devPtr: ctypes.c_void_p) -> None:
+        self.CUDART_CHECK(self.funcs["cudaFree"](devPtr))
+
+    def cudaMemset(self, devPtr: ctypes.c_void_p, value: int, count: int) -> None:
+        self.CUDART_CHECK(self.funcs["cudaMemset"](devPtr, value, count))
+
+    def cudaMemcpy(
+        self, dst: ctypes.c_void_p, src: ctypes.c_void_p, count: int
+    ) -> None:
+        cudaMemcpyDefault = 4
+        kind = cudaMemcpyDefault
+        self.CUDART_CHECK(self.funcs["cudaMemcpy"](dst, src, count, kind))
+
+    def cudaIpcGetMemHandle(self, devPtr: ctypes.c_void_p) -> cudaIpcMemHandle_t:
+        handle = cudaIpcMemHandle_t()
+        self.CUDART_CHECK(
+            self.funcs["cudaIpcGetMemHandle"](ctypes.byref(handle), devPtr)
+        )
+        return handle
+
+    def cudaIpcOpenMemHandle(self, handle: cudaIpcMemHandle_t) -> ctypes.c_void_p:
+        cudaIpcMemLazyEnablePeerAccess = 1
+        devPtr = ctypes.c_void_p()
+        self.CUDART_CHECK(
+            self.funcs["cudaIpcOpenMemHandle"](
+                ctypes.byref(devPtr), handle, cudaIpcMemLazyEnablePeerAccess
+            )
+        )
+        return devPtr