def test_analyser_proposal(self):
"""Test the function of querying the proposals from multiple different proposers"""
expect_result = {
"minddata_device_queue": [1, 1, 0, 1],
"minddata_get_next_queue": [0, 3],
"minddata_pipeline-dataset_op": ["ImageFolderOp_3"],
"minddata_pipeline-general": ["ImageFolderOp_3"]
}
step_trace_condition = {
"filter_condition": {
"mode": "proc",
"proc_name": "iteration_interval",
"step_id": 0
}
}
options = {'step_trace': {"iter_interval": step_trace_condition}}
proposal_type_list = [
'step_trace', 'minddata', 'minddata_pipeline', 'common'
]
proposal_obj = ComposeProposal(self.profiler, '1', proposal_type_list)
proposal_info = proposal_obj.get_proposal(options)
assert expect_result["minddata_device_queue"] == proposal_info[
"minddata_device_queue"]
assert expect_result["minddata_get_next_queue"] == proposal_info[
"minddata_get_next_queue"]
assert expect_result["minddata_pipeline-dataset_op"] == proposal_info[
"minddata_pipeline-dataset_op"]
assert expect_result["minddata_pipeline-general"] == proposal_info[
"minddata_pipeline-general"]
def get_profile_summary_proposal():
"""
Get summary profiling proposal.
Returns:
str, the summary profiling proposal.
Raises:
ParamValueError: If the parameters contain some errors.
Examples:
>>> GET http://xxxx/v1/mindinsight/profile/summary/propose
"""
profiler_dir = get_profiler_dir(request)
train_id = get_train_id(request)
device_id = get_device_id(request)
if not profiler_dir or not train_id:
raise ParamValueError("No profiler_dir or train_id.")
to_int(device_id, 'device_id')
profiler_dir_abs = os.path.join(settings.SUMMARY_BASE_DIR, train_id,
profiler_dir)
try:
profiler_dir_abs = validate_and_normalize_path(profiler_dir_abs,
"profiler")
except ValidationError:
raise ParamValueError("Invalid profiler dir")
check_train_job_and_profiler_dir(profiler_dir_abs)
step_trace_condition = {
"filter_condition": {
"mode": "proc",
"proc_name": "iteration_interval",
"step_id": 0
}
}
options = {'step_trace': {"iter_interval": step_trace_condition}}
proposal_type_list = [
'step_trace', 'minddata', 'minddata_pipeline', 'common'
]
proposal_obj = ComposeProposal(profiler_dir_abs, device_id,
proposal_type_list)
proposal_info = proposal_obj.get_proposal(options)
# Use json.dumps for orderly return
return CustomResponse(json.dumps(proposal_info),
mimetype='application/json')
def test_propose_compose(self):
"""Test the class of ComposeProposal."""
proposal_dict = OrderedDict()
proposal_dict["step_trace-proposer_type_label"] = None
proposal_dict.update(self.step_trace_proposal_dict)
proposal_dict["common-proposer_type_label"] = None
proposal_dict.update(self.common_proposal_dict)
type_list = ['step_trace', 'minddata', 'minddata_pipeline', 'common']
condition = {
"filter_condition": {
'mode': "proc",
"proc_name": "iteration_interval",
"step_id": 0
}
}
options = {'step_trace': {"iter_interval": condition}}
cp = ComposeProposal(self.profiling_dir, self.device_id, type_list)
result = cp.get_proposal(options=options)
self.assertDictEqual(proposal_dict, result)
def test_propose_compose_exception(self):
"""Test the class of ComposeProposal."""
profiling_dir = os.path.realpath(
os.path.join(os.path.dirname(__file__),
'../../../utils/resource/'))
proposal_dict = OrderedDict()
proposal_dict["common-proposer_type_label"] = None
proposal_dict.update(self.common_proposal_dict)
type_list = ['step_trace', 'common']
condition = {
"filter_condition": {
'mode': "proc",
"proc_name": "iteration_interval",
"step_id": 0
}
}
options = {'step_trace': {"iter_interval": condition}}
cp = ComposeProposal(profiling_dir, self.device_id, type_list)
result = cp.get_proposal(options=options)
self.assertDictEqual(proposal_dict, result)