This is an automated email from the ASF dual-hosted git repository. tqchen pushed a commit to branch refactor in repository https://gitbox.apache.org/repos/asf/tvm.git
commit 93d086f69410a13b850d0c9761f6bb9ec9abdc89 Author: Siyuan Feng <[email protected]> AuthorDate: Mon Feb 17 14:21:44 2025 +0800 remove vitis ai --- CMakeLists.txt | 2 - cmake/config.cmake | 9 - cmake/modules/LibInfo.cmake | 1 - cmake/modules/contrib/VitisAI.cmake | 47 ----- docker/Dockerfile.ci_cpu | 4 - docker/Dockerfile.demo_vitis_ai | 59 ------ docker/bash.sh | 21 --- docker/install/ubuntu_install_vitis_ai_core.sh | 39 ---- python/gen_requirements.py | 11 -- python/tvm/contrib/target/vitis_ai.py | 220 ----------------------- python/tvm/testing/utils.py | 4 - rust/tvm-rt/Cargo.toml | 1 - rust/tvm-sys/Cargo.toml | 1 - rust/tvm-sys/build.rs | 3 - src/runtime/contrib/vitis_ai/vitis_ai_runtime.cc | 195 -------------------- src/runtime/contrib/vitis_ai/vitis_ai_runtime.h | 120 ------------- src/support/libinfo.cc | 1 - tests/scripts/task_config_build_cpu.sh | 1 - 18 files changed, 739 deletions(-) diff --git a/CMakeLists.txt b/CMakeLists.txt index cb8039a264..5a7e1241d6 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -116,7 +116,6 @@ tvm_option(USE_TENSORRT_RUNTIME "Build with TensorRT runtime" OFF) tvm_option(USE_NNAPI_CODEGEN "Build with NNAPI Codegen support" OFF) tvm_option(USE_NNAPI_RUNTIME "Build with NNAPI runtime" OFF) tvm_option(USE_RUST_EXT "Build with Rust based compiler extensions, STATIC, DYNAMIC, or OFF" OFF) -tvm_option(USE_VITIS_AI "Build with VITIS-AI Codegen support" OFF) tvm_option(SUMMARIZE "Print CMake option summary after configuring" OFF) tvm_option(USE_CLML "Build with CLML Codegen support" OFF) tvm_option(USE_CLML_GRAPH_EXECUTOR "Build with CLML graph runtime" OFF) @@ -500,7 +499,6 @@ include(cmake/modules/contrib/ONNX.cmake) include(cmake/modules/contrib/ArmComputeLib.cmake) include(cmake/modules/contrib/TensorRT.cmake) include(cmake/modules/contrib/NNAPI.cmake) -include(cmake/modules/contrib/VitisAI.cmake) include(cmake/modules/contrib/Verilator.cmake) include(cmake/modules/contrib/UMA.cmake) include(cmake/modules/contrib/MSC.cmake) diff --git a/cmake/config.cmake b/cmake/config.cmake index 791751ac98..e5f85380d2 100644 --- a/cmake/config.cmake +++ b/cmake/config.cmake @@ -138,12 +138,6 @@ set(USE_IOS_RPC OFF) # Whether embed stackvm into the runtime set(USE_STACKVM_RUNTIME OFF) -# Whether enable tiny embedded graph executor. -set(USE_GRAPH_EXECUTOR ON) - -# Whether enable tiny graph executor with CUDA Graph -set(USE_GRAPH_EXECUTOR_CUDA_GRAPH OFF) - # Whether enable pipeline executor. set(USE_PIPELINE_EXECUTOR OFF) @@ -285,9 +279,6 @@ set(USE_ARM_COMPUTE_LIB_GRAPH_EXECUTOR OFF) set(USE_TENSORRT_CODEGEN OFF) set(USE_TENSORRT_RUNTIME OFF) -# Whether use VITIS-AI codegen -set(USE_VITIS_AI OFF) - # Build Verilator codegen and runtime set(USE_VERILATOR OFF) diff --git a/cmake/modules/LibInfo.cmake b/cmake/modules/LibInfo.cmake index cfea9b20d8..70ae86fc79 100644 --- a/cmake/modules/LibInfo.cmake +++ b/cmake/modules/LibInfo.cmake @@ -123,7 +123,6 @@ function(add_lib_info src_file) TVM_INFO_USE_THREADS="${USE_THREADS}" TVM_INFO_USE_THRUST="${USE_THRUST}" TVM_INFO_USE_CURAND="${USE_CURAND}" - TVM_INFO_USE_VITIS_AI="${USE_VITIS_AI}" TVM_INFO_USE_VULKAN="${USE_VULKAN}" TVM_INFO_USE_CLML="${USE_CLML}" TVM_INFO_USE_CLML_GRAPH_EXECUTOR="${USE_CLML_GRAPH_EXECUTOR}" diff --git a/cmake/modules/contrib/VitisAI.cmake b/cmake/modules/contrib/VitisAI.cmake deleted file mode 100644 index 5fd07dc2e9..0000000000 --- a/cmake/modules/contrib/VitisAI.cmake +++ /dev/null @@ -1,47 +0,0 @@ -# Licensed to the Apache Software Foundation (ASF) under one -# or more contributor license agreements. See the NOTICE file -# distributed with this work for additional information -# regarding copyright ownership. The ASF licenses this file -# to you under the Apache License, Version 2.0 (the -# "License"); you may not use this file except in compliance -# with the License. You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, -# software distributed under the License is distributed on an -# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY -# KIND, either express or implied. See the License for the -# specific language governing permissions and limitations -# under the License. - -if(USE_VITIS_AI) - set(PYXIR_SHARED_LIB libpyxir.so) - find_package(PythonInterp 3.7 REQUIRED) - if(NOT PYTHON) - find_program(PYTHON NAMES python3 python3.8) - endif() - execute_process(COMMAND "${PYTHON_EXECUTABLE}" "-c" - "import pyxir as px; print(px.get_include_dir()); print(px.get_lib_dir());" - RESULT_VARIABLE __result - OUTPUT_VARIABLE __output - OUTPUT_STRIP_TRAILING_WHITESPACE) - - if(__result MATCHES 0) - string(REGEX REPLACE ";" "\\\\;" __values ${__output}) - string(REGEX REPLACE "\r?\n" ";" __values ${__values}) - list(GET __values 0 PYXIR_INCLUDE_DIR) - list(GET __values 1 PYXIR_LIB_DIR) - else() - message(FATAL_ERROR "Can't build TVM with Vitis-AI because PyXIR can't be found") - endif() - message(STATUS "Build with contrib.vitisai") - include_directories(${PYXIR_INCLUDE_DIR}) - tvm_file_glob(GLOB VAI_CONTRIB_SRC src/runtime/contrib/vitis_ai/*.cc) - tvm_file_glob(GLOB COMPILER_VITIS_AI_SRCS - src/relay/backend/contrib/vitis_ai/*) - list(APPEND COMPILER_SRCS ${COMPILER_VITIS_AI_SRCS}) - link_directories(${PYXIR_LIB_DIR}) - list(APPEND TVM_RUNTIME_LINKER_LIBS "pyxir") - list(APPEND RUNTIME_SRCS ${VAI_CONTRIB_SRC}) -endif(USE_VITIS_AI) diff --git a/docker/Dockerfile.ci_cpu b/docker/Dockerfile.ci_cpu index d41a7e6e1b..5ba1dd7214 100644 --- a/docker/Dockerfile.ci_cpu +++ b/docker/Dockerfile.ci_cpu @@ -101,10 +101,6 @@ RUN bash /install/ubuntu_install_jax.sh "cpu" COPY install/ubuntu_download_arm_compute_lib_binaries.sh /install/ubuntu_download_arm_compute_lib_binaries.sh RUN bash /install/ubuntu_download_arm_compute_lib_binaries.sh -# Vitis-AI PyXIR CI deps -COPY install/ubuntu_install_vitis_ai_packages_ci.sh /install/ubuntu_install_vitis_ai_packages_ci.sh -RUN bash /install/ubuntu_install_vitis_ai_packages_ci.sh - # PaddlePaddle deps COPY install/ubuntu_install_paddle.sh /install/ubuntu_install_paddle.sh RUN bash /install/ubuntu_install_paddle.sh diff --git a/docker/Dockerfile.demo_vitis_ai b/docker/Dockerfile.demo_vitis_ai deleted file mode 100644 index 8cafc653fb..0000000000 --- a/docker/Dockerfile.demo_vitis_ai +++ /dev/null @@ -1,59 +0,0 @@ -# Licensed to the Apache Software Foundation (ASF) under one -# or more contributor license agreements. See the NOTICE file -# distributed with this work for additional information -# regarding copyright ownership. The ASF licenses this file -# to you under the Apache License, Version 2.0 (the -# "License"); you may not use this file except in compliance -# with the License. You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, -# software distributed under the License is distributed on an -# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY -# KIND, either express or implied. See the License for the -# specific language governing permissions and limitations -# under the License. - -# Main Vitis AI docker env -FROM xilinx/vitis-ai:1.4.916 - -COPY utils/apt-install-and-clear.sh /usr/local/bin/apt-install-and-clear - -RUN apt-get update --fix-missing - -COPY install/ubuntu_setup_tz.sh /install/ubuntu_setup_tz.sh -RUN bash /install/ubuntu_setup_tz.sh - -COPY install/ubuntu_install_core.sh /install/ubuntu_install_core.sh -RUN bash /install/ubuntu_install_core.sh - -# Install Vitis-AI ubuntu dependencies -COPY install/ubuntu_install_vitis_ai_core.sh /install/ubuntu_install_vitis_ai_core.sh -RUN bash /install/ubuntu_install_vitis_ai_core.sh - -ENV TVM_VENV /venv/apache-tvm-py3.9 -COPY python/bootstrap/lockfiles /install/python/bootstrap/lockfiles -COPY install/ubuntu_install_python.sh /install/ubuntu_install_python.sh -RUN bash /install/ubuntu_install_python.sh 3.9 -ENV PATH ${TVM_VENV}/bin:$PATH -ENV PYTHONNOUSERSITE 1 # Disable .local directory from affecting CI. - -COPY install/ubuntu_install_python_package.sh /install/ubuntu_install_python_package.sh -RUN bash /install/ubuntu_install_python_package.sh - -COPY install/ubuntu_install_llvm.sh /install/ubuntu_install_llvm.sh -RUN bash /install/ubuntu_install_llvm.sh - -ENV PATH $PATH:$CARGO_HOME/bin:/usr/lib/go-1.10/bin - -# ANTLR deps -COPY install/ubuntu_install_java.sh /install/ubuntu_install_java.sh -RUN bash /install/ubuntu_install_java.sh - -# Install dependencies inside vitis-ai-tensorflow conda -RUN . $VAI_ROOT/conda/etc/profile.d/conda.sh && \ - conda activate vitis-ai-tensorflow && \ - pip install --no-cache-dir antlr4-python3-runtime && bash /install/ubuntu_install_python_package.sh - -ENV USER="root" diff --git a/docker/bash.sh b/docker/bash.sh index f83becbf61..5303aadb94 100755 --- a/docker/bash.sh +++ b/docker/bash.sh @@ -460,27 +460,6 @@ if [[ "${DOCKER_IMAGE_NAME}" == *"ci"* ]]; then DOCKER_ENV+=( --env PYTHONPATH="${REPO_MOUNT_POINT}"/python ) fi - - -# If the Vitis-AI docker image is selected, expose the Xilinx FPGA -# devices and required volumes containing e.g. DSA's and overlays -if [[ "${DOCKER_IMAGE_NAME}" == *"demo_vitis_ai"* && -d "/dev/shm" && -d "/opt/xilinx/dsa" && -d "/opt/xilinx/overlaybins" ]]; then - DOCKER_MOUNT+=( --volume /dev/shm:/dev/shm - --volume /opt/xilinx/dsa:/opt/xilinx/dsa - --volume /opt/xilinx/overlaybins:/opt/xilinx/overlaybins - ) - - XCLMGMT_DRIVER="$(find /dev -name xclmgmt\*)" - for DRIVER in "${XCLMGMT_DRIVER}"; do - DOCKER_DEVICES+=( --device="${DRIVER}" ) - done - - RENDER_DRIVER="$(find /dev/dri -name renderD\*)" - for DRIVER in "${RENDER_DRIVER}"; do - DOCKER_DEVICES+=( --device="${DRIVER}" ) - done -fi - # Add ROCm devices and set ROCM_ENABLED=1 which is used in the with_the_same_user script # to add the user to the video group if [[ "${DOCKER_IMAGE_NAME}" == *"rocm"* && -d "/dev/dri" ]]; then diff --git a/docker/install/ubuntu_install_vitis_ai_core.sh b/docker/install/ubuntu_install_vitis_ai_core.sh deleted file mode 100755 index 2e395b45da..0000000000 --- a/docker/install/ubuntu_install_vitis_ai_core.sh +++ /dev/null @@ -1,39 +0,0 @@ -#!/bin/bash -# Licensed to the Apache Software Foundation (ASF) under one -# or more contributor license agreements. See the NOTICE file -# distributed with this work for additional information -# regarding copyright ownership. The ASF licenses this file -# to you under the Apache License, Version 2.0 (the -# "License"); you may not use this file except in compliance -# with the License. You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, -# software distributed under the License is distributed on an -# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY -# KIND, either express or implied. See the License for the -# specific language governing permissions and limitations -# under the License. - -set -e -set -u -set -o pipefail - -export PYXIR_HOME=/opt/pyxir -mkdir "$PYXIR_HOME" - -# install libraries for building Vitis-AI on ubuntu -apt-get update && apt-install-and-clear -y \ - graphviz \ - gnupg2 \ - gpg-agent \ - gcc-aarch64-linux-gnu - - -. $VAI_ROOT/conda/etc/profile.d/conda.sh -conda activate vitis-ai-tensorflow -pip3 install progressbar h5py==2.10.0 - -git clone --recursive --branch rel-v0.3.1 --depth 1 https://github.com/Xilinx/pyxir.git "${PYXIR_HOME}" -cd "${PYXIR_HOME}" && python3 setup.py install --use_vart_cloud_dpu --use_dpuczdx8g_vart diff --git a/python/gen_requirements.py b/python/gen_requirements.py index d22544db48..aafa35d08f 100644 --- a/python/gen_requirements.py +++ b/python/gen_requirements.py @@ -170,17 +170,6 @@ REQUIREMENTS_BY_PIECE: RequirementsByPieceType = [ ], ), ), - # Vitis AI requirements - ( - "vitis-ai", - ( - "Requirements for the Vitis AI codegen", - [ - "h5py", - "progressbar", - ], - ), - ), # XGBoost, useful for autotuning on some targets. ( "xgboost", diff --git a/python/tvm/contrib/target/vitis_ai.py b/python/tvm/contrib/target/vitis_ai.py deleted file mode 100644 index 1ab52ed724..0000000000 --- a/python/tvm/contrib/target/vitis_ai.py +++ /dev/null @@ -1,220 +0,0 @@ -# Licensed to the Apache Software Foundation (ASF) under one -# or more contributor license agreements. See the NOTICE file -# distributed with this work for additional information -# regarding copyright ownership. The ASF licenses this file -# to you under the Apache License, Version 2.0 (the -# "License"); you may not use this file except in compliance -# with the License. You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, -# software distributed under the License is distributed on an -# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY -# KIND, either express or implied. See the License for the -# specific language governing permissions and limitations -# under the License. -# pylint: disable=invalid-name, unused-argument, import-outside-toplevel - -"""Utility to offload (sub-)models to Vitis-AI""" - -import warnings -import importlib - -from tvm.relay.expr import Tuple, Call, TupleGetItem -import tvm._ffi - -# Placeholder for PyXIR module -pyxir = None - - -def vitis_ai_available(): - """Return whether Vitis AI tools are available""" - pyxir_spec = importlib.util.find_spec("pyxir") - if not tvm.get_global_func("tvm.vitis_ai_runtime.from_xgraph", True) or pyxir_spec is None: - return False - return True - - -class CodegenVitisAI: - - """Traverse Relay expression and convert into PyXIR XGraph format - - Parameters - ---------- - function : Function - The Relay function - dpu_target : str - The Vitis AI DPU target identifier - """ - - def __init__(self, function, dpu_target): - global pyxir - try: - if pyxir is None: - pyxir = __import__("pyxir") - __import__("pyxir.frontend.tvm") - except ImportError: - # add "from None" to silence - # "During handling of the above exception, another exception occurred" - raise ImportError( - "The pyxir package is required for the Vitis AI backend. " - "Please install it first. " - "Help: (https://tvm.apache.org/docs/deploy/vitis_ai.html) " - ) from None - - self.function = function - self.dpu_target = dpu_target - self.params = {} - - def build(self): - """ "Convert the Relay expression to a PyXIR XGraph to instantiate - the Vitis AI runtime - - Returns - ------- - xgraph_str : str - Serialized XGraph - """ - xgraph = pyxir.frontend.tvm.from_relay( - self.function, params=self.params, postprocessing=None - ) - xgraph = pyxir.partition(xgraph, targets=[self.dpu_target]) - output_relay_ids = self.get_output_names() - layers = xgraph.get_layers() - - # Get the output tensor names using XGraph and output Relay ids - out_tensor_names = ["unknown_name"] * len(output_relay_ids) - for layer in layers: - if not layer.internal: - for relay_id in layer.attrs["relay_id"]: - if relay_id in output_relay_ids: - out_tensor_names[output_relay_ids.index(relay_id)] = layer.name - break - if any([name == "unkown_name" for name in out_tensor_names]): - raise ValueError( - "During codegeneration the loading of subexpression" - " failed due to output tensor name mismatch in Relay PyXIR interface." - ) - xgraph.meta_attrs["tvm_out_tensors"] = out_tensor_names - xgraph_str = pyxir.get_xgraph_str(xgraph) - return xgraph_str - - def get_output_names(self): - """Get output names from Relay expression""" - func = self.function - output_relay_ids = [] - expr = func.body - if isinstance(expr, Tuple): - for field in expr.fields: - output_relay_ids.append(hash(field)) - elif isinstance(expr, Call): - output_relay_ids.append(hash(expr)) - elif isinstance(expr, TupleGetItem): - output_relay_ids.append(hash(expr.tuple_value)) - else: - raise ValueError(f"Vitis-AI codegen does not support {type(expr)} as output") - return output_relay_ids - - -@tvm._ffi.register_func("relay.ext.vitis_ai") -def vitis_ai_compiler(ref): - """Create a Vitis-AI runtime from the provided Relay expression""" - assert isinstance(ref, tvm.relay.function.Function) - - name = str(ref.attrs.global_symbol) - - pass_context = tvm.get_global_func("transform.GetCurrentPassContext")() - - cfg = ( - pass_context.config["relay.ext.vitis_ai.options"] - if "relay.ext.vitis_ai.options" in pass_context.config - else None - ) - - # Backward compatibility with old pass context configs - if cfg is None: - warnings.warn( - "You are using a deprecated way of passing build configs (e.g." - " `relay.ext.vitis_ai.options.target`). Check out the Vitis AI " - " documentation here: https://tvm.apache.org/docs/deploy/vitis_ai.html"; - " to switch to recommended way for passing build configs." - ) - - # The target Vitis-AI accelerator device - dpu_target = ( - str(pass_context.config["relay.ext.vitis_ai.options.target"]) - if "relay.ext.vitis_ai.options.target" in pass_context.config - else None - ) - - # (Optional configs) The build and work directories to be used by Vitis-AI - vai_build_dir = ( - str(pass_context.config["relay.ext.vitis_ai.options.build_dir"]) - if "relay.ext.vitis_ai.options.build_dir" in pass_context.config - else tvm.contrib.utils.tempdir().relpath("") - ) - vai_work_dir = ( - str(pass_context.config["relay.ext.vitis_ai.options.work_dir"]) - if "relay.ext.vitis_ai.options.work_dir" in pass_context.config - else tvm.contrib.utils.tempdir().relpath("") - ) - - # (Optional configs) Export and load PyXIR runtime module to file if provided. This is - # used to compile and quantize a model on the host and deploy it at the edge - export_runtime_module = ( - str(pass_context.config["relay.ext.vitis_ai.options.export_runtime_module"]) - if "relay.ext.vitis_ai.options.export_runtime_module" in pass_context.config - else "" - ) - load_runtime_module = ( - str(pass_context.config["relay.ext.vitis_ai.options.load_runtime_module"]) - if "relay.ext.vitis_ai.options.load_runtime_module" in pass_context.config - else "" - ) - else: - dpu_target = cfg.dpu if cfg.dpu else None - # (Optional configs) The build and work directories to be used by Vitis AI - vai_build_dir = cfg.build_dir if cfg.build_dir else tvm.contrib.utils.tempdir().relpath("") - - # (Optional configs) Export and load PyXIR runtime module to file if provided. This is - # used to compile and quantize a model on the host and deploy it at the edge - vai_work_dir = cfg.work_dir if cfg.work_dir else tvm.contrib.utils.tempdir().relpath("") - export_runtime_module = cfg.export_runtime_module - load_runtime_module = cfg.load_runtime_module - - # Config checks - if load_runtime_module and dpu_target is not None: - warnings.warn( - "Both `load_runtime_module` and `dpu` configs were specified." - " The `load_runtime_module` points to a prebuilt runtime module with" - " an internal DPU target so the `dpu` config will be ignored" - ) - if load_runtime_module and "relay.ext.vitis_ai.options.build_dir" in pass_context.config: - warnings.warn( - "Both `load_runtime_module` and `build_dir` configs were specified." - " The `load_runtime_module` points to a prebuilt runtime module with" - " an internal build directory so the `build_dir` config will be ignored" - ) - if load_runtime_module and "relay.ext.vitis_ai.options.work_dir" in pass_context.config: - warnings.warn( - "Both `load_runtime_module` and `work_dir` configs were specified." - " The `load_runtime_module` points to a prebuilt runtime module with" - " an internal work directory so the `work_dir` config will be ignored" - ) - - # If load_runtime_module is not set, we will build the PyXIR runtime module from scratch - if load_runtime_module == "": - # Convert Relay expression into XGraph and do partitioning inside PyXIR - codegen = CodegenVitisAI(ref, dpu_target) - xgraph_str = codegen.build() - - runtime_func = "tvm.vitis_ai_runtime.from_xgraph" - fcreate = tvm._ffi.get_global_func(runtime_func) - return fcreate( - name, xgraph_str, dpu_target, vai_build_dir, vai_work_dir, export_runtime_module - ) - - runtime_func = "tvm.vitis_ai_runtime.from_rt_mod" - fcreate = tvm._ffi.get_global_func(runtime_func) - return fcreate(name, load_runtime_module, export_runtime_module) diff --git a/python/tvm/testing/utils.py b/python/tvm/testing/utils.py index b3123a20d3..b01f7bf5dc 100644 --- a/python/tvm/testing/utils.py +++ b/python/tvm/testing/utils.py @@ -1022,10 +1022,6 @@ requires_aprofile_aem_fvp = Feature( compile_time_check=_aprofile_aem_fvp_compile_time_check, ) -# Mark a test as requiring Vitis AI to run -requires_vitis_ai = Feature("vitis_ai", "Vitis AI", cmake_flag="USE_VITIS_AI") - - # check cpu features def _has_cpu_feat(features): cpu = codegen.llvm_get_system_cpu() diff --git a/rust/tvm-rt/Cargo.toml b/rust/tvm-rt/Cargo.toml index 789c15a6be..cb8c560c3e 100644 --- a/rust/tvm-rt/Cargo.toml +++ b/rust/tvm-rt/Cargo.toml @@ -74,7 +74,6 @@ use-arm-compute-lib = ["tvm-sys/use-arm-compute-lib"] use-arm-compute-lib-graph-runtime = ["tvm-sys/use-arm-compute-lib-graph-runtime"] use-tensorrt-codegen = ["tvm-sys/use-tensorrt-codegen"] use-tensorrt-runtime = ["tvm-sys/use-tensorrt-runtime"] -use-vitis-ai = ["tvm-sys/use-vitis-ai"] build-static-runtime = ["tvm-sys/build-static-runtime"] [dependencies] diff --git a/rust/tvm-sys/Cargo.toml b/rust/tvm-sys/Cargo.toml index 70daf3b388..03e1d4e13d 100644 --- a/rust/tvm-sys/Cargo.toml +++ b/rust/tvm-sys/Cargo.toml @@ -67,7 +67,6 @@ use-arm-compute-lib = [] use-arm-compute-lib-graph-runtime = [] use-tensorrt-codegen = [] use-tensorrt-runtime = [] -use-vitis-ai = [] build-static-runtime = [] [dependencies] diff --git a/rust/tvm-sys/build.rs b/rust/tvm-sys/build.rs index eb2c1ee3a2..3b19f56fb1 100644 --- a/rust/tvm-sys/build.rs +++ b/rust/tvm-sys/build.rs @@ -186,9 +186,6 @@ fn find_using_tvm_build() -> Result<TVMInstall> { if cfg!(feature = "use-tensorrt-runtime") { build_config.settings.use_tensorrt_runtime = CMakeSetting::from_str("on").ok(); } - if cfg!(feature = "use-vitis-ai") { - build_config.settings.use_vitis_ai = Some(true); - } if cfg!(any( feature = "static-linking", feature = "build-static-runtime" diff --git a/src/runtime/contrib/vitis_ai/vitis_ai_runtime.cc b/src/runtime/contrib/vitis_ai/vitis_ai_runtime.cc deleted file mode 100755 index 46246b0295..0000000000 --- a/src/runtime/contrib/vitis_ai/vitis_ai_runtime.cc +++ /dev/null @@ -1,195 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one - * or more contributor license agreements. See the NOTICE file - * distributed with this work for additional information - * regarding copyright ownership. The ASF licenses this file - * to you under the Apache License, Version 2.0 (the - * "License"); you may not use this file except in compliance - * with the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, - * software distributed under the License is distributed on an - * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - * KIND, either express or implied. See the License for the - * specific language governing permissions and limitations - * under the License. - */ - -/*! - * \file vitis_ai_runtime.cc - */ - -#include "vitis_ai_runtime.h" - -#include <tvm/runtime/registry.h> - -#include <cassert> -#include <fstream> -#include <streambuf> -#include <string> -#include <vector> - -using namespace pyxir::runtime; - -namespace tvm { -namespace runtime { - -VitisAIRuntime::VitisAIRuntime(const std::string& symbol_name, const Array<String> const_names, - const std::string& serialized_rt_mod, - const std::string& export_rt_mod_path) - : symbol_name_(symbol_name), - const_names_(const_names), - export_rt_mod_path_(export_rt_mod_path) { - std::istringstream sstream(serialized_rt_mod); - rt_mod_.reset(new RuntimeModule()); - rt_mod_->deserialize(sstream); - in_tensor_names_ = rt_mod_->get_in_tensor_names(); - out_tensor_names_ = rt_mod_->get_out_tensor_names(); -} - -VitisAIRuntime::VitisAIRuntime(const std::string& symbol_name, const std::string& xgraph_str, - const Array<String> const_names, const std::string& dpu_target, - const std::string& build_dir, const std::string& work_dir, - const std::string& export_rt_mod_path) - : symbol_name_(symbol_name), - const_names_(const_names), - export_rt_mod_path_(export_rt_mod_path) { - std::istringstream xgraph_sstream(xgraph_str); - pyxir::XGraphHolder xgraph = std::make_shared<pyxir::graph::XGraph>(""); - pyxir::read(xgraph, xgraph_sstream); - in_tensor_names_ = xgraph->get_input_names(); - out_tensor_names_ = xgraph->get_meta_attr("tvm_out_tensors").get_strings(); - - pyxir::partition(xgraph, std::vector<std::string>{dpu_target}, ""); - - pyxir::RunOptionsHolder run_options(new pyxir::runtime::RunOptions()); - run_options->on_the_fly_quantization = true; - run_options->build_dir = build_dir; - run_options->export_runtime_module_path = export_rt_mod_path_; - if (!work_dir.empty()) run_options->work_dir = work_dir; - rt_mod_ = - pyxir::build_rt(xgraph, dpu_target, in_tensor_names_, out_tensor_names_, "vai", run_options); -} - -Module VitisAIRuntimeCreate(const std::string& name, const std::string& xgraph_str, - const std::string& dpu_target, const std::string& build_dir, - const std::string& work_dir, const std::string& export_rt_mod_path) { - Array<String> const_vars; - auto exec = make_object<VitisAIRuntime>(name, xgraph_str, const_vars, dpu_target, build_dir, - work_dir, export_rt_mod_path); - return Module(exec); -} - -TVM_REGISTER_GLOBAL("tvm.vitis_ai_runtime.from_xgraph").set_body([](TVMArgs args, TVMRetValue* rv) { - *rv = VitisAIRuntimeCreate(args[0], args[1], args[2], args[3], args[4], args[5]); -}); - -Module VitisAIRuntimeCreate(const std::string& name, const std::string& serialized_rt_mod, - const std::string& export_rt_mod_path) { - Array<String> const_vars; - auto exec = make_object<VitisAIRuntime>(name, const_vars, serialized_rt_mod, export_rt_mod_path); - return Module(exec); -} - -TVM_REGISTER_GLOBAL("tvm.vitis_ai_runtime.from_rt_mod").set_body([](TVMArgs args, TVMRetValue* rv) { - std::string load_rt_mod_path = args[1]; - assert(!load_rt_mod_path.empty()); - std::ifstream in_file(load_rt_mod_path); - std::stringstream buffer; - buffer << in_file.rdbuf(); - std::string serialized_rt_mod = buffer.str(); - in_file.close(); - *rv = VitisAIRuntimeCreate(args[0], serialized_rt_mod, args[2]); -}); - -Module VitisAIRuntimeLoadFromBinary(void* strm) { - dmlc::Stream* stream = static_cast<dmlc::Stream*>(strm); - std::string symbol_name; - std::vector<std::string> const_vars; - std::string serialized_rt_mod; - std::string export_rt_mod_path; - stream->Read(&serialized_rt_mod); - stream->Read(&export_rt_mod_path); - stream->Read(&symbol_name); - stream->Read(&const_vars); - Array<String> const_names; - for (const auto& it : const_vars) { - const_names.push_back(it); - } - auto exec = - make_object<VitisAIRuntime>(symbol_name, const_names, serialized_rt_mod, export_rt_mod_path); - return Module(exec); -} - -TVM_REGISTER_GLOBAL("runtime.module.loadbinary_VitisAIRuntime") - .set_body_typed(VitisAIRuntimeLoadFromBinary); - -void VitisAIRuntime::SaveToBinary(dmlc::Stream* stream) { - std::ostringstream sstream; - rt_mod_->serialize(sstream); - stream->Write(sstream.str()); - stream->Write(export_rt_mod_path_); - stream->Write(symbol_name_); - std::vector<std::string> consts; - for (const auto& it : const_names_) { - consts.push_back(it); - } - stream->Write(consts); - - // If export_rt_mod_path_ member variable is set, we will additionally export the PyXIR - // runtime_module to the specified file - if (!export_rt_mod_path_.empty()) { - std::ofstream out_file(export_rt_mod_path_); - out_file << sstream.str(); - out_file.close(); - } -} - -PackedFunc VitisAIRuntime::GetFunction(const String& name, const ObjectPtr<Object>& sptr_to_self) { - if (name == "get_symbol") { - return PackedFunc( - [sptr_to_self, this](TVMArgs args, TVMRetValue* rv) { *rv = this->symbol_name_; }); - } else if (name == "get_const_vars") { - return PackedFunc( - [sptr_to_self, this](TVMArgs args, TVMRetValue* rv) { *rv = this->const_names_; }); - } else if ("__init_" + this->symbol_name_ == name) { - // The function to initialize constant tensors. - return PackedFunc([sptr_to_self, this](TVMArgs args, TVMRetValue* rv) { - CHECK_EQ(args.size(), 1U); - this->initialized_ = true; - *rv = 0; - }); - } else if (this->symbol_name_ == name) { - return PackedFunc([sptr_to_self, this](TVMArgs args, TVMRetValue* rv) { - // Initialize input tensors - DLTensor* inputs = args[0]; - std::vector<pyxir::XBufferHolder> in_tensors; - std::vector<ssize_t> in_shape; - for (int i = 0; i < inputs->ndim; ++i) in_shape.push_back(inputs->shape[i]); - in_tensors.push_back(std::shared_ptr<pyxir::XBuffer>( - new pyxir::XBuffer(reinterpret_cast<void*>(static_cast<float*>(inputs->data)), 4, "f", - in_shape.size(), in_shape, false, false))); - - // Initialize output tensors - std::vector<pyxir::XBufferHolder> out_tensors; - for (unsigned i = 0; i < out_tensor_names_.size(); ++i) { - DLTensor* output_tensor = args[args.size() - out_tensor_names_.size() + i]; - std::vector<ssize_t> out_shape; - for (int i = 0; i < output_tensor->ndim; ++i) out_shape.push_back(output_tensor->shape[i]); - void* output_data = reinterpret_cast<void*>(static_cast<float*>(output_tensor->data)); - out_tensors.push_back(std::shared_ptr<pyxir::XBuffer>( - new pyxir::XBuffer(output_data, 4, "f", out_shape.size(), out_shape, false, false))); - } - - // Execute the subgraph. - rt_mod_->execute(in_tensors, out_tensors); - }); - } else { - return PackedFunc(); - } -} - -} // namespace runtime -} // namespace tvm diff --git a/src/runtime/contrib/vitis_ai/vitis_ai_runtime.h b/src/runtime/contrib/vitis_ai/vitis_ai_runtime.h deleted file mode 100755 index 2cc5918c8f..0000000000 --- a/src/runtime/contrib/vitis_ai/vitis_ai_runtime.h +++ /dev/null @@ -1,120 +0,0 @@ -/* - * Licensed to the Apache Software Foundation (ASF) under one - * or more contributor license agreements. See the NOTICE file - * distributed with this work for additional information - * regarding copyright ownership. The ASF licenses this file - * to you under the Apache License, Version 2.0 (the - * "License"); you may not use this file except in compliance - * with the License. You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, - * software distributed under the License is distributed on an - * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY - * KIND, either express or implied. See the License for the - * specific language governing permissions and limitations - * under the License. - */ - -/*! - * \brief Vitis-AI runtime that can run model - * containing only tvm PackedFunc. - * \file vitis_ai_runtime.h - */ -#ifndef TVM_RUNTIME_CONTRIB_VITIS_AI_VITIS_AI_RUNTIME_H_ -#define TVM_RUNTIME_CONTRIB_VITIS_AI_VITIS_AI_RUNTIME_H_ -#include <dlpack/dlpack.h> -#include <tvm/runtime/ndarray.h> -#include <tvm/runtime/packed_func.h> -// clang-format off -#include <memory> -#include <string> -#include <vector> -// clang-format on -#include <pyxir/pyxir.hpp> -#include <pyxir/runtime/run_options.hpp> - -namespace tvm { -namespace runtime { - -/*! - * \brief VAI runtime. - * - * This runtime can be accessed in various language via - * TVM runtime PackedFunc API. - */ -class VitisAIRuntime : public ModuleNode { - public: - /*! - * \brief Create VitisAI runtime from serialized XGraph - * \param symbol_name The name of the function. - * \param const_names The names of each constant in the sub-graph. - * \param serialized_rt_mod The serialized runtime module. - * \param export_rt_mod_path The path to the file to be used for exporting the - * PyXIR runtime module. - */ - VitisAIRuntime(const std::string& symbol_name, const Array<String> const_names, - const std::string& serialized_rt_mod, const std::string& export_rt_mod); - - /*! - * \brief Create VitisAI runtime from serialized XGraph - * \param symbol_name The name of the function. - * \param xgraph_str serialized XGraph representation - * \param const_names The names of each constant in the sub-graph. - * \param dpu_target The Vitis-AI DPU target identifier (e.g. DPUCADX8G, DPUCZDX8G-zcu104). - * \param build_dir The directory to be used for Vitis-AI build files. - * \param work_dir The directory to be used for Vitis-AI work files. - * \param export_rt_mod_path The path to the file to be used for exporting the - * PyXIR runtime module. - */ - VitisAIRuntime(const std::string& symbol_name, const std::string& xgraph_str, - const Array<String> const_names, const std::string& dpu_target, - const std::string& build_dir, const std::string& work_dir, - const std::string& export_runtime_module_path); - - /*! - * \brief Get member function to front-end. - * \param name The name of the function. - * \param sptr_to_self The pointer to the module node. - * \return The corresponding member function. - */ - virtual PackedFunc GetFunction(const String& name, const ObjectPtr<Object>& sptr_to_self); - - /*! - * \return The type key of the executor. - */ - const char* type_key() const { return "VitisAIRuntime"; } - - /*! \brief Get the property of the runtime module .*/ - int GetPropertyMask() const final { - return ModulePropertyMask::kBinarySerializable | ModulePropertyMask::kRunnable; - }; - - /*! - * \brief Serialize the content of the pyxir directory and save it to - * binary stream. - * \param stream The binary stream to save to. - */ - void SaveToBinary(dmlc::Stream* stream) final; - - private: - /*! \brief The only subgraph name for this module */ - std::string symbol_name_; - /*! \brief The required constant names */ - Array<String> const_names_; - /*! \brief The runtime module */ - pyxir::RtModHolder rt_mod_; - /*! \brief The XGraph input tensor names in the order as provided by TVM */ - std::vector<std::string> in_tensor_names_; - /*! \brief The XGraph output tensor names in the order as provided by TVM */ - std::vector<std::string> out_tensor_names_; - /*! \brief The file path for exporting the runtime module if set */ - std::string export_rt_mod_path_; - /*! \brief Whether constant tensors have been initialized */ - bool initialized_{false}; -}; - -} // namespace runtime -} // namespace tvm -#endif // TVM_RUNTIME_CONTRIB_VITIS_AI_VITIS_AI_RUNTIME_H_ diff --git a/src/support/libinfo.cc b/src/support/libinfo.cc index d55181aab7..1af5e6e095 100644 --- a/src/support/libinfo.cc +++ b/src/support/libinfo.cc @@ -364,7 +364,6 @@ TVM_DLL Map<String, String> GetLibInfo() { {"USE_THREADS", TVM_INFO_USE_THREADS}, {"USE_THRUST", TVM_INFO_USE_THRUST}, {"USE_CURAND", TVM_INFO_USE_CURAND}, - {"USE_VITIS_AI", TVM_INFO_USE_VITIS_AI}, {"USE_VULKAN", TVM_INFO_USE_VULKAN}, {"USE_CLML", TVM_INFO_USE_CLML}, {"TVM_CLML_VERSION", TVM_INFO_USE_TVM_CLML_VERSION}, diff --git a/tests/scripts/task_config_build_cpu.sh b/tests/scripts/task_config_build_cpu.sh index f9065ece6e..42d6c06f7a 100755 --- a/tests/scripts/task_config_build_cpu.sh +++ b/tests/scripts/task_config_build_cpu.sh @@ -42,7 +42,6 @@ fi echo set\(USE_TENSORFLOW_PATH \"/tensorflow\"\) >> config.cmake echo set\(USE_FLATBUFFERS_PATH \"/flatbuffers\"\) >> config.cmake -echo set\(USE_VITIS_AI ON\) >> config.cmake echo set\(USE_LIBBACKTRACE COMPILE\) >> config.cmake echo set\(BACKTRACE_ON_SEGFAULT ON\) >> config.cmake echo set\(USE_CCACHE OFF\) >> config.cmake
