def test_create_framework_parser_fail_1(self, *args):
"""Test the function of fail to create framework parser."""
args[0].return_value = True
args[1].return_value = []
with pytest.raises(ProfilerFileNotFoundException) as exc_info:
FrameworkParser('JOB1', '0')
assert exc_info.value.error_code == '50546084'
assert exc_info.value.message == 'The file <Framework> not found.'
def setup_method(self):
"""Initialization before test case execution."""
self._output_path_1 = tempfile.NamedTemporaryFile(prefix='test_framework_parser_').name
shutil.copytree(RAW_DATA_BASE, self._output_path_1)
self._parser_1 = FrameworkParser('JOB1', '0', self._output_path_1)
self._output_path_2 = tempfile.NamedTemporaryFile(prefix='test_framework_parser_').name
shutil.copytree(RAW_DATA_BASE, self._output_path_2)
self._parser_2 = FrameworkParser('JOB2', '0', self._output_path_2)
self._output_path_4 = tempfile.NamedTemporaryFile(prefix='test_framework_parser_').name
shutil.copytree(RAW_DATA_BASE, self._output_path_4)
self._parser_4 = FrameworkParser('JOB4', '0', self._output_path_4)
def setup_method(self):
"""Initialization before test case execution."""
with mock.patch.object(FrameworkParser, '_raw_data_dir',
RAW_DATA_BASE):
self._output_path_1 = tempfile.mkdtemp(
prefix='test_framework_parser_')
self._parser_1 = FrameworkParser('JOB1', '0', self._output_path_1)
self._output_path_2 = tempfile.mkdtemp(
prefix='test_framework_parser_')
self._parser_2 = FrameworkParser('JOB2', '0', self._output_path_2)
self._output_path_4 = tempfile.mkdtemp(
prefix='test_framework_parser_')
self._parser_4 = FrameworkParser('JOB4', '0', self._output_path_4)
def _ascend_analyse(self):
"""Collect and analyse ascend performance data"""
release()
job_id = self._get_profiling_job_id()
logger.info("Profiling: job id is %s ", job_id)
source_path = os.path.join(self._output_path, job_id)
# parse hwts.log.data.45.dev file, and get task profiling data
hwts_output_filename = self._hwts_output_filename_target + self._dev_id + ".txt"
hwts_output_filename = os.path.join(self._output_path,
hwts_output_filename)
source_path = validate_and_normalize_path(source_path)
hwts_output_filename = validate_and_normalize_path(
hwts_output_filename)
hwtslog_parser = HWTSLogParser(source_path, hwts_output_filename)
hwtslog_parser.execute()
# parse Framework file, and get the relation of op and tasks
framework_parser = FrameworkParser(job_id, self._dev_id,
self._output_path)
framework_parser.parse()
op_task_dict = framework_parser.to_task_id_full_op_name_dict()
if not op_task_dict:
logger.error("Profiling: fail to parse framework files.")
return
# get op compute time from hwts data and framework data, write output_op_compute_time.txt
opcompute_output_filename = self._opcompute_output_filename_target + self._dev_id + ".txt"
opcompute_output_filename = os.path.join(self._output_path,
opcompute_output_filename)
opcompute_output_filename = validate_and_normalize_path(
opcompute_output_filename)
optime_parser = OPComputeTimeParser(hwts_output_filename,
opcompute_output_filename,
op_task_dict, self._output_path,
self._dev_id)
optime_parser.execute()
# parse DATA_PREPROCESS.dev.AICPU file, write output_data_preprocess_aicpu_x.txt
output_data_preprocess_aicpu = self._aicpu_op_output_filename_target + self._dev_id + ".txt"
output_data_preprocess_aicpu = os.path.join(
self._output_path, output_data_preprocess_aicpu)
output_data_preprocess_aicpu = validate_and_normalize_path(
output_data_preprocess_aicpu)
aicpu_data_parser = DataPreProcessParser(source_path,
output_data_preprocess_aicpu)
aicpu_data_parser.execute()
# Parsing minddata AICPU profiling
MinddataParser.execute(source_path, self._output_path, self._dev_id)
# parse minddata pipeline operator and queue
try:
pipeline_parser = MinddataPipelineParser(self._output_path,
self._dev_id,
self._output_path)
pipeline_parser.parse()
except ProfilerException as err:
logger.warning(err.message)
# analyse op compute time info
try:
self._analyser_op_info()
except ProfilerException as err:
logger.warning(err.message)
# analyse step trace info
points = None
try:
points = self._analyse_step_trace(source_path, framework_parser)
except ProfilerException as err:
logger.warning(err.message)
# analyse timeline info
try:
self._analyse_timeline(aicpu_data_parser, optime_parser,
source_path)
except (ProfilerIOException, ProfilerFileNotFoundException,
RuntimeError) as err:
logger.warning('Fail to write timeline data: %s', err)
# analyse memory usage info
try:
self._analyse_memory_usage(points)
except (ProfilerIOException, ProfilerFileNotFoundException,
ProfilerRawFileException) as err:
logger.warning(err.message)
os.environ['PROFILING_MODE'] = str("false")
context.set_context(enable_profiling=False)
def analyse(self):
"""
Collect and analyse performance data, called after training or during training.
Examples:
>>> from mindspore.profiler import Profiler
>>> import mindspore.context
>>> context.set_context(mode=context.GRAPH_MODE, device_target="Ascend",
>>> device_id=int(os.environ["DEVICE_ID"]))
>>> profiler = Profiler()
>>> model = Model()
>>> model.train()
>>> profiler.analyse()
"""
if self._device_target and self._device_target == "GPU":
if context.get_auto_parallel_context(
'device_num') > 1 and self._dev_id != get_rank():
self._dev_id = get_rank()
logger.error(
'Please check the Profiler object initialized after set_auto_parallel_context() '
'and init(). Profiler should be initialized after these code. '
)
self._gpu_profiler.stop()
timeline_generator = self._generate_timeline()
# parse minddata pipeline operator and queue for GPU
try:
pipeline_parser = MinddataPipelineParser(
self._output_path, self._dev_id, self._output_path)
pipeline_parser.parse()
except ProfilerException as err:
logger.warning(err.message)
# analyse step trace info
try:
self._analyse_step_trace(
is_training_mode_flag=timeline_generator.check_op_name(
'Gradients'))
except ProfilerException as err:
logger.warning(err.message)
os.environ['PROFILING_MODE'] = str("false")
elif self._device_target and self._device_target == "Ascend":
release()
job_id = self._get_profiling_job_id()
logger.info("Profiling: job id is %s ", job_id)
source_path = os.path.join(self._output_path, job_id)
# parse hwts.log.data.45.dev file, and get task profiling data
hwts_output_filename = self._hwts_output_filename_target + self._dev_id + ".txt"
hwts_output_filename = os.path.join(self._output_path,
hwts_output_filename)
source_path = validate_and_normalize_path(source_path)
hwts_output_filename = validate_and_normalize_path(
hwts_output_filename)
hwtslog_parser = HWTSLogParser(source_path, hwts_output_filename)
_ = hwtslog_parser.execute()
# parse Framework file, and get the relation of op and tasks
framework_parser = FrameworkParser(job_id, self._dev_id,
self._output_path)
framework_parser.parse()
op_task_dict = framework_parser.to_task_id_full_op_name_dict()
if not op_task_dict:
logger.error("Profiling: fail to parse framework files.")
return
# get op compute time from hwts data and framework data, write output_op_compute_time.txt
opcompute_output_filename = self._opcompute_output_filename_target + self._dev_id + ".txt"
opcompute_output_filename = os.path.join(
self._output_path, opcompute_output_filename)
opcompute_output_filename = validate_and_normalize_path(
opcompute_output_filename)
optime_parser = OPComputeTimeParser(hwts_output_filename,
opcompute_output_filename,
op_task_dict,
self._output_path,
self._dev_id)
optime_parser.execute()
# parse DATA_PREPROCESS.dev.AICPU file, write output_data_preprocess_aicpu_x.txt
output_data_preprocess_aicpu = self._aicpu_op_output_filename_target + self._dev_id + ".txt"
output_data_preprocess_aicpu = os.path.join(
self._output_path, output_data_preprocess_aicpu)
output_data_preprocess_aicpu = validate_and_normalize_path(
output_data_preprocess_aicpu)
aicpu_data_parser = DataPreProcessParser(
source_path, output_data_preprocess_aicpu)
aicpu_data_parser.execute()
# Parsing minddata AICPU profiling
MinddataParser.execute(source_path, self._output_path,
self._dev_id)
# parse minddata pipeline operator and queue
try:
pipeline_parser = MinddataPipelineParser(
self._output_path, self._dev_id, self._output_path)
pipeline_parser.parse()
except ProfilerException as err:
logger.warning(err.message)
# analyse op compute time info
try:
self._analyser_op_info()
except ProfilerException as err:
logger.warning(err.message)
# analyse step trace info
try:
self._analyse_step_trace(source_path, framework_parser)
except ProfilerException as err:
logger.warning(err.message)
# analyse timeline info
try:
self._analyse_timeline(aicpu_data_parser, optime_parser)
except (ProfilerIOException, ProfilerFileNotFoundException,
RuntimeError) as err:
logger.warning('Fail to write timeline data: %s', err)
os.environ['PROFILING_MODE'] = str("false")
context.set_context(enable_profiling=False)
def analyse(self):
"""
Collect and analyse performance data, called after training or during training.
Examples:
>>> from mindspore.profiler import Profiler
>>> import mindspore.context
>>> context.set_context(mode=context.GRAPH_MODE, device_target="Ascend",
>>> device_id=int(os.environ["DEVICE_ID"]))
>>> profiler = Profiler(subgraph='all', is_detail=True, is_show_op_path=False, output_path='./data')
>>> model = Model()
>>> model.train()
>>> profiler.analyse()
"""
release()
job_id = self._get_profiling_job_id()
logger.info("Profiling: job id is %s ", job_id)
source_path = os.path.join(PROFILING_LOG_BASE_PATH, job_id)
# parse hwts.log.data.45.dev file, and get task profiling data
hwts_output_filename = self._hwts_output_filename_target + self._dev_id + ".txt"
hwts_output_filename = os.path.join(self._output_path,
hwts_output_filename)
hwtslog_parser = HWTSLogParser(source_path, hwts_output_filename)
result = hwtslog_parser.execute()
if not result:
logger.error("Profiling: fail to parse hwts log file.")
return
# parse Framework file, and get the relation of op and tasks
framework_parser = FrameworkParser(job_id, self._dev_id,
self._output_path)
framework_parser.parse()
op_task_dict = framework_parser.to_task_id_full_op_name_dict()
if not op_task_dict:
logger.error("Profiling: fail to parse framework files.")
return
# get op compute time from hwts data and framework data, write output_op_compute_time.txt
opcompute_output_filename = self._opcompute_output_filename_target + self._dev_id + ".txt"
opcompute_output_filename = os.path.join(self._output_path,
opcompute_output_filename)
optime_parser = OPComputeTimeParser(hwts_output_filename,
opcompute_output_filename,
op_task_dict, self._output_path,
self._dev_id)
optime_parser.execute()
# parse DATA_PREPROCESS.dev.AICPU file, write output_data_preprocess_aicpu_x.txt
output_data_preprocess_aicpu = self._aicpu_op_output_filename_target + self._dev_id + ".txt"
output_data_preprocess_aicpu = os.path.join(
self._output_path, output_data_preprocess_aicpu)
aicpu_data_parser = DataPreProcessParser(source_path,
output_data_preprocess_aicpu)
aicpu_data_parser.execute()
# Parsing minddata AICPU profiling
MinddataParser.execute(source_path, self._output_path, self._dev_id)
# parse minddata pipeline operator and queue
try:
pipeline_parser = MinddataPipelineParser(self._output_path,
self._dev_id,
self._output_path)
pipeline_parser.parse()
except ProfilerException as err:
logger.warning(err.message)
# analyse op compute time info
try:
self._analyser_op_info()
except ProfilerException as err:
logger.warning(err.message)
# analyse step trace info
try:
self._analyse_step_trace(source_path, framework_parser)
except ProfilerException as err:
logger.warning(err.message)
# analyse timeline info
try:
self._analyse_timeline(aicpu_data_parser, optime_parser)
except (ProfilerIOException, ProfilerFileNotFoundException,
RuntimeError) as err:
logger.warning('Fail to write timeline data: %s', err)
class TestFrameworkParser:
"""Test the class of `FrameworkParser`."""
def setup_method(self):
"""Initialization before test case execution."""
with mock.patch.object(FrameworkParser, '_raw_data_dir',
RAW_DATA_BASE):
self._output_path_1 = tempfile.mkdtemp(
prefix='test_framework_parser_')
self._parser_1 = FrameworkParser('JOB1', '0', self._output_path_1)
self._output_path_2 = tempfile.mkdtemp(
prefix='test_framework_parser_')
self._parser_2 = FrameworkParser('JOB2', '0', self._output_path_2)
self._output_path_4 = tempfile.mkdtemp(
prefix='test_framework_parser_')
self._parser_4 = FrameworkParser('JOB4', '0', self._output_path_4)
def teardown_method(self) -> None:
"""Clear up after test case execution."""
shutil.rmtree(self._output_path_1)
shutil.rmtree(self._output_path_2)
shutil.rmtree(self._output_path_4)
def test_save_path(self):
"""Test the querying save path function."""
expect_result = os.path.join(self._output_path_1,
'framework_raw_0.csv')
assert expect_result == self._parser_1.save_path
expect_result = os.path.join(self._output_path_2,
'framework_raw_0.csv')
assert expect_result == self._parser_2.save_path
def test_point_info(self):
"""Test the querying point info function."""
expect_result = {1: 'Default/Cast-op6', 2: 'Default/TransData-op7'}
assert expect_result == self._parser_4.point_info
def test_to_task_id_full_op_name_dict(self):
"""Test the querying task id and full operator name dict function."""
expect_result = {
'51517':
'Default/Cast-op6',
'51518':
'Default/TransData-op7',
'51519':
'Default/network-WithLossCell/_backbone-ResNet/conv1-Conv2d/Cast-op5',
'51522':
'Default/network-WithLossCell/_backbone-ResNet/'
'layer1-SequentialCell/0-ResidualBlock/conv1-Conv2d/Cast-op28'
}
assert expect_result == self._parser_1.to_task_id_full_op_name_dict()
assert expect_result == self._parser_2.to_task_id_full_op_name_dict()
expect_result = {
'0_1':
'Default/Cast-op6',
'0_2':
'Default/TransData-op7',
'0_3':
'Default/network-WithLossCell/_backbone-ResNet/conv1-Conv2d/Cast-op5',
'0_4':
'Default/network-WithLossCell/_backbone-ResNet/layer1-SequentialCell/'
'0-ResidualBlock/conv1-Conv2d/Cast-op28'
}
assert expect_result == self._parser_4.to_task_id_full_op_name_dict()
def test_parse(self):
"""Test the parse function."""
expect_framework_file = os.path.join(PROFILER_DIR,
'framework_raw_0.csv')
expect_framework_file = os.path.realpath(expect_framework_file)
expect_result = get_framework_result(expect_framework_file)
self._parser_1.parse()
framework_file = os.path.join(self._output_path_1,
'framework_raw_0.csv')
result = get_framework_result(framework_file)
assert expect_result == result
self._parser_2.parse()
framework_file = os.path.join(self._output_path_2,
'framework_raw_0.csv')
result = get_framework_result(framework_file)
assert expect_result == result
@mock.patch('os.listdir')
@mock.patch('os.path.isdir')
def test_create_framework_parser_fail_1(self, *args):
"""Test the function of fail to create framework parser."""
args[0].return_value = True
args[1].return_value = []
with pytest.raises(ProfilerFileNotFoundException) as exc_info:
FrameworkParser('JOB1', '0')
assert exc_info.value.error_code == '50546084'
assert exc_info.value.message == 'The file <Framework> not found.'
