frigate/docker/rocm/migraphx/CMakeLists.txt

120 lines
2.5 KiB
CMake
Raw Normal View History

AMD GPU support with the rocm detector and YOLOv8 pretrained model download (#9762) * ROCm AMD/GPU based build and detector, WIP * detectors/rocm: separate yolov8 postprocessing into own function; fix box scaling; use cv2.dnn.blobForImage for preprocessing; assert on required model parameters * AMD/ROCm: add couple of more ultralytics models; comments * docker/rocm: make imported model files readable by all * docker/rocm: readme about running on AMD GPUs * docker/rocm: updated README * docker/rocm: updated README * docker/rocm: updated README * detectors/rocm: separated preprocessing functions into yolo_utils.py * detector/plugins: added onnx cpu plugin * docker/rocm: updated container with limite label sets * example detectors view * docker/rocm: updated README.md * docker/rocm: update README.md * docker/rocm: do not set HSA_OVERRIDE_GFX_VERSION at all for the general version as the empty value broke rocm * detectors: simplified/optimized yolov8_postprocess * detector/yolo_utils: indentation, remove unused variable * detectors/rocm: default option to conserve cpu usage at the expense of latency * detectors/yolo_utils: use nms to prefilter overlapping boxes if too many detected * detectors/edgetpu_tfl: add support for yolov8 * util/download_models: script to download yolov8 model files * docker/main: add download-models overlay into s6 startup * detectors/rocm: assume models are in /config/model_cache/yolov8/ * docker/rocm: compile onnx files into mxr files at startup * switch model download into bash script * detectors/rocm: automatically override HSA_OVERRIDE_GFX_VERSION for couple of known chipsets * docs: rocm detector first notes * typos * describe builds (harakas temporary) * docker/rocm: also build a version for gfx1100 * docker/rocm: use cp instead of tar * docker.rocm: remove README as it is now in detector config * frigate/detectors: renamed yolov8_preprocess->preprocess, pass input tensor element type * docker/main: use newer openvino (2023.3.0) * detectors: implement class aggregation * update yolov8 model * add openvino/yolov8 support for label aggregation * docker: remove pointless s6/timeout-up files * Revert "detectors: implement class aggregation" This reverts commit dcfe6bbf6fc6fbb90c61288c7ecf1439ba2b96b4. * detectors/openvino: remove class aggregation * detectors: increase yolov8 postprocessing score trershold to 0.5 * docker/rocm: separate rocm distributed files into its own build stage * Update object_detectors.md * updated CODEOWNERS file for rocm * updated build names for documentation * Revert "docker/main: use newer openvino (2023.3.0)" This reverts commit dee95de908b31393b718191f5c4b5ab6793cbba4. * reverrted openvino detector * reverted edgetpu detector * scratched rocm docs from any mention of edgetpu or openvino * Update docs/docs/configuration/object_detectors.md Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com> * renamed frigate.detectors.yolo_utils.py -> frigate.detectors.util.py * clarified rocm example performance * Improved wording and clarified text * Mentioned rocm detector for AMD GPUs * applied ruff formating * applied ruff suggested fixes * docker/rocm: fix missing argument resulting in larger docker image sizes * docs/configuration/object_detectors: fix links to yolov8 release files --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2024-02-10 15:41:46 +03:00
cmake_minimum_required(VERSION 3.1)
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
set(CMAKE_CXX_EXTENSIONS OFF)
2025-02-05 00:36:53 +03:00
add_library(migraphx
adjust_allocation.cpp
analyze_streams.cpp
apply_alpha_beta.cpp
argument.cpp
autocast_fp8.cpp
auto_contiguous.cpp
base64.cpp
common.cpp
common_dims.cpp
compile_src.cpp
convert_to_json.cpp
cpp_generator.cpp
dead_code_elimination.cpp
dom_info.cpp
dynamic_loader.cpp
eliminate_allocation.cpp
eliminate_common_subexpression.cpp
eliminate_concat.cpp
eliminate_contiguous.cpp
eliminate_convert.cpp
eliminate_data_type.cpp
eliminate_identity.cpp
eliminate_pad.cpp
env.cpp
file_buffer.cpp
fileutils.cpp
fp_to_double.cpp
fp8_ocp_to_fnuz.cpp
fuse_concat.cpp
fuse_pointwise.cpp
fuse_pointwise_reduce.cpp
fuse_reduce.cpp
generate.cpp
inline_module.cpp
insert_pad.cpp
instruction.cpp
json.cpp
layout_convolution.cpp
lexing.cpp
load_save.cpp
make_op.cpp
memory_coloring.cpp
module.cpp
msgpack.cpp
netron_output.cpp
normalize_attributes.cpp
normalize_ops.cpp
op_enums.cpp
operation.cpp
optimize_module.cpp
pad_calc.cpp
param_utils.cpp
pass.cpp
pass_manager.cpp
permutation.cpp
preallocate_param.cpp
process.cpp
program.cpp
propagate_constant.cpp
promote_literals.cpp
quantization.cpp
quantize_int4.cpp
quantize_8bits.cpp
reduce_dims.cpp
register_op.cpp
register_target.cpp
replace_allocate.cpp
rewrite_reduce.cpp
simplify_qdq.cpp
split_reduce.cpp
sqlite.cpp
rewrite_gelu.cpp
rewrite_low_precision.cpp
rewrite_pooling.cpp
rewrite_quantization.cpp
rewrite_rnn.cpp
schedule.cpp
serialize.cpp
shape.cpp
shape_transform_descriptor.cpp
simplify_algebra.cpp
simplify_dyn_ops.cpp
simplify_reshapes.cpp
split_single_dyn_dim.cpp
target.cpp
tmp_dir.cpp
truncate_float.cpp
value.cpp
verify_args.cpp
)
AMD GPU support with the rocm detector and YOLOv8 pretrained model download (#9762) * ROCm AMD/GPU based build and detector, WIP * detectors/rocm: separate yolov8 postprocessing into own function; fix box scaling; use cv2.dnn.blobForImage for preprocessing; assert on required model parameters * AMD/ROCm: add couple of more ultralytics models; comments * docker/rocm: make imported model files readable by all * docker/rocm: readme about running on AMD GPUs * docker/rocm: updated README * docker/rocm: updated README * docker/rocm: updated README * detectors/rocm: separated preprocessing functions into yolo_utils.py * detector/plugins: added onnx cpu plugin * docker/rocm: updated container with limite label sets * example detectors view * docker/rocm: updated README.md * docker/rocm: update README.md * docker/rocm: do not set HSA_OVERRIDE_GFX_VERSION at all for the general version as the empty value broke rocm * detectors: simplified/optimized yolov8_postprocess * detector/yolo_utils: indentation, remove unused variable * detectors/rocm: default option to conserve cpu usage at the expense of latency * detectors/yolo_utils: use nms to prefilter overlapping boxes if too many detected * detectors/edgetpu_tfl: add support for yolov8 * util/download_models: script to download yolov8 model files * docker/main: add download-models overlay into s6 startup * detectors/rocm: assume models are in /config/model_cache/yolov8/ * docker/rocm: compile onnx files into mxr files at startup * switch model download into bash script * detectors/rocm: automatically override HSA_OVERRIDE_GFX_VERSION for couple of known chipsets * docs: rocm detector first notes * typos * describe builds (harakas temporary) * docker/rocm: also build a version for gfx1100 * docker/rocm: use cp instead of tar * docker.rocm: remove README as it is now in detector config * frigate/detectors: renamed yolov8_preprocess->preprocess, pass input tensor element type * docker/main: use newer openvino (2023.3.0) * detectors: implement class aggregation * update yolov8 model * add openvino/yolov8 support for label aggregation * docker: remove pointless s6/timeout-up files * Revert "detectors: implement class aggregation" This reverts commit dcfe6bbf6fc6fbb90c61288c7ecf1439ba2b96b4. * detectors/openvino: remove class aggregation * detectors: increase yolov8 postprocessing score trershold to 0.5 * docker/rocm: separate rocm distributed files into its own build stage * Update object_detectors.md * updated CODEOWNERS file for rocm * updated build names for documentation * Revert "docker/main: use newer openvino (2023.3.0)" This reverts commit dee95de908b31393b718191f5c4b5ab6793cbba4. * reverrted openvino detector * reverted edgetpu detector * scratched rocm docs from any mention of edgetpu or openvino * Update docs/docs/configuration/object_detectors.md Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com> * renamed frigate.detectors.yolo_utils.py -> frigate.detectors.util.py * clarified rocm example performance * Improved wording and clarified text * Mentioned rocm detector for AMD GPUs * applied ruff formating * applied ruff suggested fixes * docker/rocm: fix missing argument resulting in larger docker image sizes * docs/configuration/object_detectors: fix links to yolov8 release files --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2024-02-10 15:41:46 +03:00
if(NOT CMAKE_BUILD_TYPE)
set(CMAKE_BUILD_TYPE Release)
endif()
SET(CMAKE_INSTALL_RPATH_USE_LINK_PATH TRUE)
project(migraphx_py)
include_directories(/opt/rocm/include)
find_package(pybind11 REQUIRED)
pybind11_add_module(migraphx migraphx_py.cpp)
target_link_libraries(migraphx PRIVATE /opt/rocm/lib/libmigraphx.so /opt/rocm/lib/libmigraphx_tf.so /opt/rocm/lib/libmigraphx_onnx.so)
install(TARGETS migraphx
COMPONENT python
LIBRARY DESTINATION /opt/rocm/lib
)