You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
106 lines
4.2 KiB
106 lines
4.2 KiB
import paddle.v2.fluid.core as core
|
|
from contextlib import contextmanager
|
|
import os
|
|
|
|
__all__ = ['CudaProfiler']
|
|
|
|
NVPROF_CONFIG = [
|
|
"gpustarttimestamp",
|
|
"gpuendtimestamp",
|
|
"gridsize3d",
|
|
"threadblocksize",
|
|
"streamid",
|
|
"enableonstart 0",
|
|
"conckerneltrace",
|
|
]
|
|
|
|
|
|
@contextmanager
|
|
def cuda_profiler(output_file, output_mode=None, config=None):
|
|
"""The CUDA profiler.
|
|
This fuctions is used to profile CUDA program by CUDA runtime application
|
|
programming interface. The profiling result will be written into
|
|
`output_file` with Key-Value pair format or Comma separated values format.
|
|
The user can set the output mode by `output_mode` argument and set the
|
|
counters/options for profiling by `config` argument. The default config
|
|
is ['gpustarttimestamp', 'gpustarttimestamp', 'gridsize3d',
|
|
'threadblocksize', 'streamid', 'enableonstart 0', 'conckerneltrace'].
|
|
|
|
Args:
|
|
output_file (string) : The output file name, the result will be
|
|
written into this file.
|
|
output_mode (string) : The output mode has Key-Value pair format and
|
|
Comma separated values format. It should be 'kvp' or 'csv'.
|
|
config (list of string) : The profiler options and counters can refer
|
|
to "Compute Command Line Profiler User Guide".
|
|
"""
|
|
if output_mode is None:
|
|
output_mode = 'csv'
|
|
if output_mode not in ['kvp', 'csv']:
|
|
raise ValueError("The output mode must be 'kvp' or 'csv'.")
|
|
config = NVPROF_CONFIG if config is None else config
|
|
config_file = 'nvprof_config_file'
|
|
with open(config_file, 'wb') as fp:
|
|
fp.writelines(["%s\n" % item for item in config])
|
|
core.nvprof_init(output_file, output_mode, config_file)
|
|
# Enables profiler collection by the active CUDA profiling tool.
|
|
core.nvprof_start()
|
|
yield
|
|
# Disables profiler collection.
|
|
core.nvprof_stop()
|
|
os.remove(config_file)
|
|
|
|
|
|
def reset_profiler():
|
|
"""The profiler clear interface.
|
|
reset_profiler will clear the previous time record.
|
|
"""
|
|
core.reset_profiler()
|
|
|
|
|
|
@contextmanager
|
|
def profiler(state, sorted_key=None):
|
|
"""The profiler interface.
|
|
Different from cuda_profiler, this profiler can be used to profile both CPU
|
|
and GPU program. By defalut, it records the CPU and GPU operator kernels,
|
|
if you want to profile other program, you can refer the profiling tutorial
|
|
to add more records.
|
|
|
|
Args:
|
|
state (string) : The profiling state, It should be 'CPU' or 'GPU'.
|
|
Although users may define CPUPlace or CUDAPlace when using Fluid,
|
|
the profiler doesn't get the state based on this Place. Since the
|
|
implementation is an independent part from the Fluid.
|
|
sorted_key (string) : If None, the profiling results will be printed
|
|
in the order of first end time of events. Otherwise, the profiling
|
|
results will be sorted by the this flag. This flag should be one
|
|
of 'calls', 'total', 'max', 'min' or 'ave'.
|
|
The `calls` means sorting by the number of calls.
|
|
The `total` means sorting by the total execution time.
|
|
The `max` means sorting by the maximum execution time.
|
|
The `min` means sorting by the minimum execution time.
|
|
The `ave` means sorting by the average execution time.
|
|
"""
|
|
|
|
if state not in ['CPU', 'GPU']:
|
|
raise ValueError("The state must be 'CPU' or 'GPU'.")
|
|
prof_state = core.ProfilerState.kCUDA if state == "GPU" else core.ProfilerState.kCPU
|
|
core.enable_profiler(prof_state)
|
|
yield
|
|
|
|
if sorted_key not in ['calls', 'total', 'max', 'min', 'ave']:
|
|
raise ValueError("The state must be in 'calls', 'total', "
|
|
"'max', 'min', 'ave'")
|
|
sorted_key = 'default' if sorted_key is None else sorted_key
|
|
key_map = {
|
|
'default': core.EventSortingKey.kDefault,
|
|
'calls': core.EventSortingKey.kCalls,
|
|
'total': core.EventSortingKey.kTotal,
|
|
'max': core.EventSortingKey.kMax,
|
|
'min': core.EventSortingKey.kMin,
|
|
'ave': core.EventSortingKey.kAve,
|
|
}
|
|
# TODO(qingqing) : redirect C++ ostream to Python stream.
|
|
# with core.ostream_redirect(stdout=True, stderr=True):
|
|
core.disable_profiler(key_map[sorted_key])
|