def build_checker():
if hasattr(build_checker, "dll"):
return build_checker.dll
checker_code_path = os.path.join(
os.path.dirname(inspect.getfile(daceml.onnx)), "include",
"op_checker.h")
with open(checker_code_path, "r") as f:
checker_code = f.read()
program = codeobject.CodeObject("onnx_op_checker",
checker_code,
"cpp",
targets.cpu.CPUCodeGen,
"ONNXOpChecker",
environments={"ONNXRuntime"})
BUILD_PATH = os.path.join('.dacecache', "onnx_op_checker")
compiler.generate_program_folder(None, [program], BUILD_PATH)
compiler.configure_and_compile(BUILD_PATH)
checker_dll = ctypes.CDLL(
compiler.get_binary_name(BUILD_PATH, "onnx_op_checker"))
build_checker.dll = checker_dll
return checker_dll
def cuda_helper():
helper_code = """
#include <dace/dace.h>
extern "C" {
int host_to_gpu(void* gpu, void* host, size_t size) {
auto result = cudaMemcpy(gpu, host, size, cudaMemcpyHostToDevice);
DACE_CUDA_CHECK(cudaGetLastError());
DACE_CUDA_CHECK(cudaDeviceSynchronize());
return result;
}
}
"""
program = codeobject.CodeObject("cuda_helper", helper_code, "cpp",
targets.cpu.CPUCodeGen, "CudaHelper")
dummy_cuda_target = codeobject.CodeObject("dummy", "", "cu",
targets.cuda.CUDACodeGen,
"CudaDummy")
build_folder = dace.Config.get('default_build_folder')
BUILD_PATH = os.path.join(build_folder, "cuda_helper")
compiler.generate_program_folder(None, [program, dummy_cuda_target],
BUILD_PATH)
compiler.configure_and_compile(BUILD_PATH)
checker_dll = compiled_sdfg.ReloadableDLL(
compiler.get_binary_name(BUILD_PATH, "cuda_helper"), "cuda_helper")
class CudaHelper:
def __init__(self):
self.dll = checker_dll
checker_dll.load()
self._host_to_gpu = checker_dll.get_symbol("host_to_gpu")
self._host_to_gpu.restype = ctypes.c_int
def __del__(self):
self.dll.unload()
def host_to_gpu(self, gpu_ptr: int, numpy_array: np.ndarray):
size = ctypes.sizeof(
dtypes._FFI_CTYPES[numpy_array.dtype.type]) * numpy_array.size
result = ctypes.c_int(
self._host_to_gpu(
ctypes.c_void_p(gpu_ptr),
ctypes.c_void_p(
numpy_array.__array_interface__["data"][0]),
ctypes.c_size_t(size)))
if result.value != 0:
raise ValueError("host_to_gpu returned nonzero result!")
return CudaHelper()
def run_local(self, sdfg: SDFG, driver_file: str):
workdir = sdfg.build_folder
if Config.get_bool('diode', 'general', 'library_autoexpand'):
sdfg.expand_library_nodes()
code_objects = sdfg.generate_code()
use_mpi = Executor._use_mpi(code_objects)
# TODO: Implement (instead of pyrun, use mpirun/mpiexec)
if use_mpi:
raise NotImplementedError('Running MPI locally unimplemented')
# Pipe stdout/stderr back to client output
stdout = sys.stdout
stderr = sys.stderr
sys.stdout = FunctionStreamWrapper(self.show_output, stdout.write)
sys.stderr = FunctionStreamWrapper(self.show_output, stderr.write)
# Compile SDFG
generate_program_folder(sdfg, code_objects, workdir, self._config)
configure_and_compile(workdir, sdfg.name)
self.show_output("Running script\n")
# Run driver script with the compiled SDFG(s) as the default
old_usecache = Config.get_bool('compiler', 'use_cache')
Config.set('compiler', 'use_cache', value=True)
try:
runpy.run_path(driver_file, run_name='__main__')
# Catching all exceptions, including SystemExit
except (Exception, SystemExit) as ex:
# Corner case: If exited with error code 0, it is a success
if isinstance(ex, SystemExit):
# If the exit code is nonzero, "raise" will not trigger a
# printout on the server
if ex.code != 0:
traceback.print_exc()
raise
else:
raise
self.show_output("Execution Terminated\n")
# Revert configuration and output redirection
Config.set('compiler', 'use_cache', value=old_usecache)
sys.stdout = stdout
sys.stderr = stderr
