mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 00:21:07 +01:00
56 lines
1.3 KiB
Python
56 lines
1.3 KiB
Python
import ctypes
|
|
import tempfile
|
|
import contextlib
|
|
from . import cudart, check_error
|
|
|
|
|
|
class cudaOutputMode(object):
|
|
cudaKeyValuePair = ctypes.c_int(0)
|
|
cudaCSV = ctypes.c_int(1)
|
|
|
|
@staticmethod
|
|
def for_key(key):
|
|
if key == 'key_value':
|
|
return cudaOutputMode.cudaKeyValuePair
|
|
elif key == 'csv':
|
|
return cudaOutputMode.cudaCSV
|
|
else:
|
|
raise RuntimeError("supported CUDA profiler output modes are: key_value and csv")
|
|
|
|
DEFAULT_FLAGS = [
|
|
"gpustarttimestamp",
|
|
"gpuendtimestamp",
|
|
"gridsize3d",
|
|
"threadblocksize",
|
|
"streamid",
|
|
"enableonstart 0",
|
|
"conckerneltrace",
|
|
]
|
|
|
|
|
|
def init(output_file, flags=None, output_mode='key_value'):
|
|
flags = DEFAULT_FLAGS if flags is None else flags
|
|
output_mode = cudaOutputMode.for_key(output_mode)
|
|
with tempfile.NamedTemporaryFile(delete=True) as f:
|
|
f.write(b'\n'.join(map(lambda f: f.encode('ascii'), flags)))
|
|
f.flush()
|
|
check_error(cudart().cudaProfilerInitialize(
|
|
ctypes.c_char_p(f.name.encode('ascii')), ctypes.c_char_p(output_file.encode('ascii')), output_mode))
|
|
|
|
|
|
def start():
|
|
check_error(cudart().cudaProfilerStart())
|
|
|
|
|
|
def stop():
|
|
check_error(cudart().cudaProfilerStop())
|
|
|
|
|
|
@contextlib.contextmanager
|
|
def profile():
|
|
try:
|
|
start()
|
|
yield
|
|
finally:
|
|
stop()
|