forked from vllm-project/vllm
-
Notifications
You must be signed in to change notification settings - Fork 1
/
CMakeLists.txt
544 lines (473 loc) · 20.1 KB
/
CMakeLists.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
cmake_minimum_required(VERSION 3.26)
# When building directly using CMake, make sure you run the install step
# (it places the .so files in the correct location).
#
# Example:
# mkdir build && cd build
# cmake -G Ninja -DVLLM_PYTHON_EXECUTABLE=`which python3` -DCMAKE_INSTALL_PREFIX=.. ..
# cmake --build . --target install
#
# If you want to only build one target, make sure to install it manually:
# cmake --build . --target _C
# cmake --install . --component _C
project(vllm_extensions LANGUAGES CXX)
# CUDA by default, can be overridden by using -DVLLM_TARGET_DEVICE=... (used by setup.py)
set(VLLM_TARGET_DEVICE "cuda" CACHE STRING "Target device backend for vLLM")
message(STATUS "Build type: ${CMAKE_BUILD_TYPE}")
message(STATUS "Target device: ${VLLM_TARGET_DEVICE}")
include(${CMAKE_CURRENT_LIST_DIR}/cmake/utils.cmake)
# Suppress potential warnings about unused manually-specified variables
set(ignoreMe "${VLLM_PYTHON_PATH}")
# Prevent installation of dependencies (cutlass) by default.
install(CODE "set(CMAKE_INSTALL_LOCAL_ONLY TRUE)" ALL_COMPONENTS)
#
# Supported python versions. These versions will be searched in order, the
# first match will be selected. These should be kept in sync with setup.py.
#
set(PYTHON_SUPPORTED_VERSIONS "3.8" "3.9" "3.10" "3.11" "3.12")
# Supported NVIDIA architectures.
set(CUDA_SUPPORTED_ARCHS "7.0;7.5;8.0;8.6;8.9;9.0")
# Supported AMD GPU architectures.
set(HIP_SUPPORTED_ARCHS "gfx906;gfx908;gfx90a;gfx940;gfx941;gfx942;gfx1030;gfx1100")
#
# Supported/expected torch versions for CUDA/ROCm.
#
# Currently, having an incorrect pytorch version results in a warning
# rather than an error.
#
# Note: the CUDA torch version is derived from pyproject.toml and various
# requirements.txt files and should be kept consistent. The ROCm torch
# versions are derived from Dockerfile.rocm
#
set(TORCH_SUPPORTED_VERSION_CUDA "2.5.0")
set(TORCH_SUPPORTED_VERSION_ROCM "2.5.0")
#
# Try to find python package with an executable that exactly matches
# `VLLM_PYTHON_EXECUTABLE` and is one of the supported versions.
#
if (VLLM_PYTHON_EXECUTABLE)
find_python_from_executable(${VLLM_PYTHON_EXECUTABLE} "${PYTHON_SUPPORTED_VERSIONS}")
else()
message(FATAL_ERROR
"Please set VLLM_PYTHON_EXECUTABLE to the path of the desired python version"
" before running cmake configure.")
endif()
#
# Update cmake's `CMAKE_PREFIX_PATH` with torch location.
#
append_cmake_prefix_path("torch" "torch.utils.cmake_prefix_path")
# Ensure the 'nvcc' command is in the PATH
find_program(NVCC_EXECUTABLE nvcc)
if (CUDA_FOUND AND NOT NVCC_EXECUTABLE)
message(FATAL_ERROR "nvcc not found")
endif()
#
# Import torch cmake configuration.
# Torch also imports CUDA (and partially HIP) languages with some customizations,
# so there is no need to do this explicitly with check_language/enable_language,
# etc.
#
find_package(Torch REQUIRED)
#
# Forward the non-CUDA device extensions to external CMake scripts.
#
if (NOT VLLM_TARGET_DEVICE STREQUAL "cuda" AND
NOT VLLM_TARGET_DEVICE STREQUAL "rocm")
if (VLLM_TARGET_DEVICE STREQUAL "cpu")
include(${CMAKE_CURRENT_LIST_DIR}/cmake/cpu_extension.cmake)
else()
return()
endif()
return()
endif()
#
# Set up GPU language and check the torch version and warn if it isn't
# what is expected.
#
if (NOT HIP_FOUND AND CUDA_FOUND)
set(VLLM_GPU_LANG "CUDA")
if (NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_CUDA})
message(WARNING "Pytorch version ${TORCH_SUPPORTED_VERSION_CUDA} "
"expected for CUDA build, saw ${Torch_VERSION} instead.")
endif()
elseif(HIP_FOUND)
set(VLLM_GPU_LANG "HIP")
# Importing torch recognizes and sets up some HIP/ROCm configuration but does
# not let cmake recognize .hip files. In order to get cmake to understand the
# .hip extension automatically, HIP must be enabled explicitly.
enable_language(HIP)
# ROCm 5.X and 6.X
if (ROCM_VERSION_DEV_MAJOR GREATER_EQUAL 5 AND
NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_ROCM})
message(WARNING "Pytorch version >= ${TORCH_SUPPORTED_VERSION_ROCM} "
"expected for ROCm build, saw ${Torch_VERSION} instead.")
endif()
else()
message(FATAL_ERROR "Can't find CUDA or HIP installation.")
endif()
if(VLLM_GPU_LANG STREQUAL "CUDA")
#
# For cuda we want to be able to control which architectures we compile for on
# a per-file basis in order to cut down on compile time. So here we extract
# the set of architectures we want to compile for and remove the from the
# CMAKE_CUDA_FLAGS so that they are not applied globally.
#
clear_cuda_arches(CUDA_ARCH_FLAGS)
extract_unique_cuda_archs_ascending(CUDA_ARCHS "${CUDA_ARCH_FLAGS}")
message(STATUS "CUDA target architectures: ${CUDA_ARCHS}")
# Filter the target architectures by the supported supported archs
# since for some files we will build for all CUDA_ARCHS.
cuda_archs_loose_intersection(CUDA_ARCHS
"${CUDA_SUPPORTED_ARCHS}" "${CUDA_ARCHS}")
message(STATUS "CUDA supported target architectures: ${CUDA_ARCHS}")
else()
#
# For other GPU targets override the GPU architectures detected by cmake/torch
# and filter them by the supported versions for the current language.
# The final set of arches is stored in `VLLM_GPU_ARCHES`.
#
override_gpu_arches(VLLM_GPU_ARCHES
${VLLM_GPU_LANG}
"${${VLLM_GPU_LANG}_SUPPORTED_ARCHS}")
endif()
#
# Query torch for additional GPU compilation flags for the given
# `VLLM_GPU_LANG`.
# The final set of arches is stored in `VLLM_GPU_FLAGS`.
#
get_torch_gpu_compiler_flags(VLLM_GPU_FLAGS ${VLLM_GPU_LANG})
#
# Set nvcc parallelism.
#
if(NVCC_THREADS AND VLLM_GPU_LANG STREQUAL "CUDA")
list(APPEND VLLM_GPU_FLAGS "--threads=${NVCC_THREADS}")
endif()
#
# Use FetchContent for C++ dependencies that are compiled as part of vLLM's build process.
# setup.py will override FETCHCONTENT_BASE_DIR to play nicely with sccache.
# Each dependency that produces build artifacts should override its BINARY_DIR to avoid
# conflicts between build types. It should instead be set to ${CMAKE_BINARY_DIR}/<dependency>.
#
include(FetchContent)
file(MAKE_DIRECTORY ${FETCHCONTENT_BASE_DIR}) # Ensure the directory exists
message(STATUS "FetchContent base directory: ${FETCHCONTENT_BASE_DIR}")
#
# Define other extension targets
#
#
# _C extension
#
set(VLLM_EXT_SRC
"csrc/cache_kernels.cu"
"csrc/attention/attention_kernels.cu"
"csrc/pos_encoding_kernels.cu"
"csrc/activation_kernels.cu"
"csrc/layernorm_kernels.cu"
"csrc/quantization/gptq/q_gemm.cu"
"csrc/quantization/compressed_tensors/int8_quant_kernels.cu"
"csrc/quantization/fp8/common.cu"
"csrc/cuda_utils_kernels.cu"
"csrc/prepare_inputs/advance_step.cu"
"csrc/torch_bindings.cpp")
if(VLLM_GPU_LANG STREQUAL "CUDA")
SET(CUTLASS_ENABLE_HEADERS_ONLY ON CACHE BOOL "Enable only the header library")
# Set CUTLASS_REVISION manually -- its revision detection doesn't work in this case.
set(CUTLASS_REVISION "v3.5.1" CACHE STRING "CUTLASS revision to use")
FetchContent_Declare(
cutlass
GIT_REPOSITORY https://github.com/nvidia/cutlass.git
GIT_TAG v3.5.1
GIT_PROGRESS TRUE
# Speed up CUTLASS download by retrieving only the specified GIT_TAG instead of the history.
# Important: If GIT_SHALLOW is enabled then GIT_TAG works only with branch names and tags.
# So if the GIT_TAG above is updated to a commit hash, GIT_SHALLOW must be set to FALSE
GIT_SHALLOW TRUE
)
FetchContent_MakeAvailable(cutlass)
list(APPEND VLLM_EXT_SRC
"csrc/mamba/mamba_ssm/selective_scan_fwd.cu"
"csrc/mamba/causal_conv1d/causal_conv1d.cu"
"csrc/quantization/aqlm/gemm_kernels.cu"
"csrc/quantization/awq/gemm_kernels.cu"
"csrc/quantization/gguf/gguf_kernel.cu"
"csrc/custom_all_reduce.cu"
"csrc/permute_cols.cu"
"csrc/quantization/cutlass_w8a8/scaled_mm_entry.cu")
set_gencode_flags_for_srcs(
SRCS "${VLLM_EXT_SRC}"
CUDA_ARCHS "${CUDA_ARCHS}")
# Only build Marlin kernels if we are building for at least some compatible archs.
# Keep building Marlin for 9.0 as there are some group sizes and shapes that
# are not supported by Machete yet.
cuda_archs_loose_intersection(MARLIN_ARCHS "8.0;8.6;8.9;9.0" ${CUDA_ARCHS})
if (MARLIN_ARCHS)
set(MARLIN_SRCS
"csrc/quantization/fp8/fp8_marlin.cu"
"csrc/quantization/marlin/dense/marlin_cuda_kernel.cu"
"csrc/quantization/marlin/sparse/marlin_24_cuda_kernel.cu"
"csrc/quantization/marlin/qqq/marlin_qqq_gemm_kernel.cu"
"csrc/quantization/gptq_marlin/gptq_marlin.cu"
"csrc/quantization/gptq_marlin/gptq_marlin_repack.cu"
"csrc/quantization/gptq_marlin/awq_marlin_repack.cu")
set_gencode_flags_for_srcs(
SRCS "${MARLIN_SRCS}"
CUDA_ARCHS "${MARLIN_ARCHS}")
list(APPEND VLLM_EXT_SRC "${MARLIN_SRCS}")
message(STATUS "Building Marlin kernels for archs: ${MARLIN_ARCHS}")
else()
message(STATUS "Not building Marlin kernels as no compatible archs found"
" in CUDA target architectures")
endif()
#
# The cutlass_scaled_mm kernels for Hopper (c3x, i.e. CUTLASS 3.x) require
# CUDA 12.0 or later (and only work on Hopper, 9.0/9.0a for now).
cuda_archs_loose_intersection(SCALED_MM_3X_ARCHS "9.0;9.0a" "${CUDA_ARCHS}")
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND SCALED_MM_3X_ARCHS)
set(SRCS "csrc/quantization/cutlass_w8a8/scaled_mm_c3x.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${SCALED_MM_3X_ARCHS}")
list(APPEND VLLM_EXT_SRC "${SRCS}")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_SCALED_MM_C3X=1")
message(STATUS "Building scaled_mm_c3x for archs: ${SCALED_MM_3X_ARCHS}")
else()
if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND SCALED_MM_3X_ARCHS)
message(STATUS "Not building scaled_mm_c3x as CUDA Compiler version is "
"not >= 12.0, we recommend upgrading to CUDA 12.0 or "
"later if you intend on running FP8 quantized models on "
"Hopper.")
else()
message(STATUS "Not building scaled_mm_c3x as no compatible archs found "
"in CUDA target architectures")
endif()
# clear SCALED_MM_3X_ARCHS so the scaled_mm_c2x kernels know we didn't
# build any 3x kernels
set(SCALED_MM_3X_ARCHS)
endif()
#
# For the cutlass_scaled_mm kernels we want to build the c2x (CUTLASS 2.x)
# kernels for the remaining archs that are not already built for 3x.
cuda_archs_loose_intersection(SCALED_MM_2X_ARCHS
"7.5;8.0;8.6;8.9;9.0" "${CUDA_ARCHS}")
# subtract out the archs that are already built for 3x
list(REMOVE_ITEM SCALED_MM_2X_ARCHS ${SCALED_MM_3X_ARCHS})
if (SCALED_MM_2X_ARCHS)
set(SRCS "csrc/quantization/cutlass_w8a8/scaled_mm_c2x.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${SCALED_MM_2X_ARCHS}")
list(APPEND VLLM_EXT_SRC "${SRCS}")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_SCALED_MM_C2X=1")
message(STATUS "Building scaled_mm_c2x for archs: ${SCALED_MM_2X_ARCHS}")
else()
if (SCALED_MM_3X_ARCHS)
message(STATUS "Not building scaled_mm_c2x as all archs are already built"
" for and covered by scaled_mm_c3x")
else()
message(STATUS "Not building scaled_mm_c2x as no compatible archs found "
"in CUDA target architectures")
endif()
endif()
#
# Machete kernels
# The machete kernels only work on hopper and require CUDA 12.0 or later.
# Only build Machete kernels if we are building for something compatible with sm90a
cuda_archs_loose_intersection(MACHETE_ARCHS "9.0a" "${CUDA_ARCHS}")
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND MACHETE_ARCHS)
#
# For the Machete kernels we automatically generate sources for various
# preselected input type pairs and schedules.
# Generate sources:
set(MACHETE_GEN_SCRIPT
${CMAKE_CURRENT_SOURCE_DIR}/csrc/quantization/machete/generate.py)
file(MD5 ${MACHETE_GEN_SCRIPT} MACHETE_GEN_SCRIPT_HASH)
message(STATUS "Machete generation script hash: ${MACHETE_GEN_SCRIPT_HASH}")
message(STATUS "Last run machete generate script hash: $CACHE{MACHETE_GEN_SCRIPT_HASH}")
if (NOT DEFINED CACHE{MACHETE_GEN_SCRIPT_HASH}
OR NOT $CACHE{MACHETE_GEN_SCRIPT_HASH} STREQUAL ${MACHETE_GEN_SCRIPT_HASH})
execute_process(
COMMAND ${CMAKE_COMMAND} -E env
PYTHONPATH=${CMAKE_CURRENT_SOURCE_DIR}/csrc/cutlass_extensions/:${CUTLASS_DIR}/python/:${VLLM_PYTHON_PATH}:$PYTHONPATH
${Python_EXECUTABLE} ${MACHETE_GEN_SCRIPT}
RESULT_VARIABLE machete_generation_result
OUTPUT_VARIABLE machete_generation_output
OUTPUT_FILE ${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log
ERROR_FILE ${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log
)
if (NOT machete_generation_result EQUAL 0)
message(FATAL_ERROR "Machete generation failed."
" Result: \"${machete_generation_result}\""
"\nCheck the log for details: "
"${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log")
else()
set(MACHETE_GEN_SCRIPT_HASH ${MACHETE_GEN_SCRIPT_HASH}
CACHE STRING "Last run machete generate script hash" FORCE)
message(STATUS "Machete generation completed successfully.")
endif()
else()
message(STATUS "Machete generation script has not changed, skipping generation.")
endif()
# Add machete generated sources
file(GLOB MACHETE_GEN_SOURCES "csrc/quantization/machete/generated/*.cu")
list(APPEND VLLM_EXT_SRC ${MACHETE_GEN_SOURCES})
# forward compatible
set_gencode_flags_for_srcs(
SRCS "${MACHETE_GEN_SOURCES}"
CUDA_ARCHS "${MACHETE_ARCHS}")
list(APPEND VLLM_EXT_SRC
csrc/quantization/machete/machete_pytorch.cu)
message(STATUS "Building Machete kernels for archs: ${MACHETE_ARCHS}")
else()
if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0
AND MACHETE_ARCHS)
message(STATUS "Not building Machete kernels as CUDA Compiler version is "
"not >= 12.0, we recommend upgrading to CUDA 12.0 or "
"later if you intend on running w4a16 quantized models on "
"Hopper.")
else()
message(STATUS "Not building Machete kernels as no compatible archs "
"found in CUDA target architectures")
endif()
endif()
# if CUDA endif
endif()
message(STATUS "Enabling C extension.")
define_gpu_extension_target(
_C
DESTINATION vllm
LANGUAGE ${VLLM_GPU_LANG}
SOURCES ${VLLM_EXT_SRC}
COMPILE_FLAGS ${VLLM_GPU_FLAGS}
ARCHITECTURES ${VLLM_GPU_ARCHES}
INCLUDE_DIRECTORIES ${CUTLASS_INCLUDE_DIR}
USE_SABI 3
WITH_SOABI)
# If CUTLASS is compiled on NVCC >= 12.5, it by default uses
# cudaGetDriverEntryPointByVersion as a wrapper to avoid directly calling the
# driver API. This causes problems when linking with earlier versions of CUDA.
# Setting this variable sidesteps the issue by calling the driver directly.
target_compile_definitions(_C PRIVATE CUTLASS_ENABLE_DIRECT_CUDA_DRIVER_CALL=1)
#
# _moe_C extension
#
set(VLLM_MOE_EXT_SRC
"csrc/moe/torch_bindings.cpp"
"csrc/moe/moe_align_sum_kernels.cu"
"csrc/moe/topk_softmax_kernels.cu")
set_gencode_flags_for_srcs(
SRCS "${VLLM_MOE_EXT_SRC}"
CUDA_ARCHS "${CUDA_ARCHS}")
if(VLLM_GPU_LANG STREQUAL "CUDA")
cuda_archs_loose_intersection(MARLIN_MOE_ARCHS "8.0;8.6;8.9;9.0" "${CUDA_ARCHS}")
if (MARLIN_MOE_ARCHS)
set(MARLIN_MOE_SRC
"csrc/moe/marlin_kernels/marlin_moe_kernel.h"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku4b8.h"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku4b8.cu"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku8b128.h"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku8b128.cu"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku4.h"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku4.cu"
"csrc/moe/marlin_moe_ops.cu")
set_gencode_flags_for_srcs(
SRCS "${MARLIN_MOE_SRC}"
CUDA_ARCHS "${MARLIN_MOE_ARCHS}")
list(APPEND VLLM_MOE_EXT_SRC "${MARLIN_MOE_SRC}")
message(STATUS "Building Marlin MOE kernels for archs: ${MARLIN_MOE_ARCHS}")
else()
message(STATUS "Not building Marlin MOE kernels as no compatible archs found"
" in CUDA target architectures")
endif()
endif()
message(STATUS "Enabling moe extension.")
define_gpu_extension_target(
_moe_C
DESTINATION vllm
LANGUAGE ${VLLM_GPU_LANG}
SOURCES ${VLLM_MOE_EXT_SRC}
COMPILE_FLAGS ${VLLM_GPU_FLAGS}
ARCHITECTURES ${VLLM_GPU_ARCHES}
USE_SABI 3
WITH_SOABI)
if(VLLM_GPU_LANG STREQUAL "HIP")
#
# _rocm_C extension
#
set(VLLM_ROCM_EXT_SRC
"csrc/rocm/torch_bindings.cpp"
"csrc/rocm/attention.cu")
define_gpu_extension_target(
_rocm_C
DESTINATION vllm
LANGUAGE ${VLLM_GPU_LANG}
SOURCES ${VLLM_ROCM_EXT_SRC}
COMPILE_FLAGS ${VLLM_GPU_FLAGS}
ARCHITECTURES ${VLLM_GPU_ARCHES}
USE_SABI 3
WITH_SOABI)
endif()
# vllm-flash-attn currently only supported on CUDA
if (NOT VLLM_TARGET_DEVICE STREQUAL "cuda")
return()
endif ()
# vLLM flash attention requires VLLM_GPU_ARCHES to contain the set of target
# arches in the CMake syntax (75-real, 89-virtual, etc), since we clear the
# arches in the CUDA case (and instead set the gencodes on a per file basis)
# we need to manually set VLLM_GPU_ARCHES here.
if(VLLM_GPU_LANG STREQUAL "CUDA")
foreach(_ARCH ${CUDA_ARCHS})
string(REPLACE "." "" _ARCH "${_ARCH}")
list(APPEND VLLM_GPU_ARCHES "${_ARCH}-real")
endforeach()
endif()
#
# Build vLLM flash attention from source
#
# IMPORTANT: This has to be the last thing we do, because vllm-flash-attn uses the same macros/functions as vLLM.
# Because functions all belong to the global scope, vllm-flash-attn's functions overwrite vLLMs.
# They should be identical but if they aren't, this is a massive footgun.
#
# The vllm-flash-attn install rules are nested under vllm to make sure the library gets installed in the correct place.
# To only install vllm-flash-attn, use --component vllm_flash_attn_c.
# If no component is specified, vllm-flash-attn is still installed.
# If VLLM_FLASH_ATTN_SRC_DIR is set, vllm-flash-attn is installed from that directory instead of downloading.
# This is to enable local development of vllm-flash-attn within vLLM.
# It can be set as an environment variable or passed as a cmake argument.
# The environment variable takes precedence.
if (DEFINED ENV{VLLM_FLASH_ATTN_SRC_DIR})
set(VLLM_FLASH_ATTN_SRC_DIR $ENV{VLLM_FLASH_ATTN_SRC_DIR})
endif()
if(VLLM_FLASH_ATTN_SRC_DIR)
FetchContent_Declare(vllm-flash-attn SOURCE_DIR ${VLLM_FLASH_ATTN_SRC_DIR})
else()
FetchContent_Declare(
vllm-flash-attn
GIT_REPOSITORY https://github.com/vllm-project/flash-attention.git
GIT_TAG 5259c586c403a4e4d8bf69973c159b40cc346fb9
GIT_PROGRESS TRUE
# Don't share the vllm-flash-attn build between build types
BINARY_DIR ${CMAKE_BINARY_DIR}/vllm-flash-attn
)
endif()
# Set the parent build flag so that the vllm-flash-attn library does not redo compile flag and arch initialization.
set(VLLM_PARENT_BUILD ON)
# Ensure the vllm/vllm_flash_attn directory exists before installation
install(CODE "file(MAKE_DIRECTORY \"\${CMAKE_INSTALL_PREFIX}/vllm/vllm_flash_attn\")" COMPONENT vllm_flash_attn_c)
# Make sure vllm-flash-attn install rules are nested under vllm/
install(CODE "set(CMAKE_INSTALL_LOCAL_ONLY FALSE)" COMPONENT vllm_flash_attn_c)
install(CODE "set(OLD_CMAKE_INSTALL_PREFIX \"\${CMAKE_INSTALL_PREFIX}\")" COMPONENT vllm_flash_attn_c)
install(CODE "set(CMAKE_INSTALL_PREFIX \"\${CMAKE_INSTALL_PREFIX}/vllm/\")" COMPONENT vllm_flash_attn_c)
# Fetch the vllm-flash-attn library
FetchContent_MakeAvailable(vllm-flash-attn)
message(STATUS "vllm-flash-attn is available at ${vllm-flash-attn_SOURCE_DIR}")
# Restore the install prefix
install(CODE "set(CMAKE_INSTALL_PREFIX \"\${OLD_CMAKE_INSTALL_PREFIX}\")" COMPONENT vllm_flash_attn_c)
install(CODE "set(CMAKE_INSTALL_LOCAL_ONLY TRUE)" COMPONENT vllm_flash_attn_c)
# Copy over the vllm-flash-attn python files
install(
DIRECTORY ${vllm-flash-attn_SOURCE_DIR}/vllm_flash_attn/
DESTINATION vllm/vllm_flash_attn
COMPONENT vllm_flash_attn_c
FILES_MATCHING PATTERN "*.py"
)
# Nothing after vllm-flash-attn, see comment about macros above