def test_query_single_train_task_with_plugin_name_not_exist(self, client, plugin_name):
"""
Parsing unavailable plugin name to single train task.
Test Params:
request route: GET('/v1/mindinsight/datavisual/single-job').
request params: plugin_name.
Expect:
response status code: 400.
response json: {
'error_code': '50540002',
'error_message': "Invalid parameter value. 'plugin_name' only can
be one of ['graph', 'image', 'scalar']"
}
"""
plugin_name_list = PluginNameEnum.list_members()
params = dict(plugin_name=plugin_name, train_id="not_exist")
url = get_url(TRAIN_ROUTES['single_job'], params)
response = client.get(url)
assert response.status_code == 400
response = response.get_json()
assert response['error_code'] == '5054500B'
assert response['error_msg'] == f"Plugin is not available. " \
f"Detail: 'plugin_name' only can be one of {plugin_name_list}"
def create_summary(self, log_dir, steps_list, tag_name_list):
"""Create summary in log_dir."""
metadata_dict = dict()
timestamp = time.time() + self._time_count
file_path = os.path.join(log_dir, f'test.summary.{int(timestamp)}')
metadata_dict.update({"plugins": dict()})
metadata_dict.update({"metadata": dict()})
metadata_dict.update({"actual_values": dict()})
for plugin_name in PluginNameEnum.list_members():
metadata_dict["plugins"].update({plugin_name: list()})
log_generator = log_generators.get(plugin_name)
if plugin_name == PluginNameEnum.GRAPH.value:
with open(self._graph_base_path, 'r') as load_f:
graph_dict = json.load(load_f)
values = log_generator.generate_log(file_path, graph_dict)
metadata_dict["actual_values"].update({plugin_name: values})
metadata_dict["plugins"][plugin_name].append("UUID str")
else:
for tag_name in tag_name_list:
metadata, values = log_generator.generate_log(
file_path, steps_list, tag_name)
full_tag_name = f'{tag_name}/{plugin_name}'
metadata_dict["metadata"].update({full_tag_name: metadata})
metadata_dict["plugins"][plugin_name].append(full_tag_name)
if plugin_name == PluginNameEnum.IMAGE.value:
metadata_dict["actual_values"].update(
{full_tag_name: values})
os.utime(file_path, (timestamp, timestamp))
self._time_count += 1
return metadata_dict
def get_plugins(self, train_id, manual_update=True):
"""
Queries the plug-in data for the specified training job
Args:
train_id (str): Specify a training job to query.
manual_update (bool): Specifies whether to refresh automatically.
Returns:
dict, refer to restful api.
"""
Validation.check_param_empty(train_id=train_id)
if contains_null_byte(train_id=train_id):
raise QueryStringContainsNullByteError("train job id: {} contains null byte.".format(train_id))
if manual_update:
self._data_manager.cache_train_job(train_id)
train_job = self._data_manager.get_train_job(train_id)
try:
data_visual_content = train_job.get_detail(DATAVISUAL_CACHE_KEY)
plugins = data_visual_content.get(DATAVISUAL_PLUGIN_KEY)
except exceptions.TrainJobDetailNotInCacheError:
plugins = []
if not plugins:
default_result = dict()
for plugin_name in PluginNameEnum.list_members():
default_result.update({plugin_name: list()})
return dict(plugins=default_result)
return dict(
plugins=plugins
)
def test_get_single_train_task_with_not_exists_train_id(self):
"""Test getting single train task with not exists train_id."""
train_task_manager = TrainTaskManager(self._mock_data_manager)
for plugin_name in PluginNameEnum.list_members():
test_train_id = "not_exist_id"
with pytest.raises(TrainJobNotExistError) as exc_info:
_ = train_task_manager.get_single_train_task(plugin_name, test_train_id)
assert exc_info.value.message == "Train job is not exist. " \
"Detail: Can not find the train job in data manager."
assert exc_info.value.error_code == '50545005'
def test_plugins_with_train_id_not_in_cache(self, client):
"""Test getting plugins with train id that not in loader pool."""
train_id = "./summary0"
params = dict(train_id=train_id)
url = get_url(BASE_URL, params)
response = client.get(url)
plugins = response.get_json().get('plugins')
for plugin_name in PluginNameEnum.list_members():
# Empty list.
assert not plugins.get(plugin_name)
def test_get_single_train_task_with_not_exists_train_id(self, load_data):
"""Test getting single train task with not exists train_id."""
train_task_manager = TrainTaskManager(self._mock_data_manager)
for plugin_name in PluginNameEnum.list_members():
test_train_id = "not_exist_id"
with pytest.raises(ParamValueError) as exc_info:
_ = train_task_manager.get_single_train_task(
plugin_name, test_train_id)
assert exc_info.type == ParamValueError
assert exc_info.value.message == "Invalid parameter value. Can not find " \
"the train job in data manager."
assert exc_info.value.error_code == '50540002'
def test_get_single_train_task_with_params(self):
"""Test getting single train task with params."""
train_task_manager = TrainTaskManager(self._mock_data_manager)
for plugin_name in PluginNameEnum.list_members():
for test_train_id in self._train_id_list:
result = train_task_manager.get_single_train_task(plugin_name, test_train_id)
tags = result.get("train_jobs")[0].get("tags")
# if it is a UUID
if tags:
assert test_train_id in self._plugins_id_map.get(plugin_name)
else:
assert test_train_id not in self._plugins_id_map.get(plugin_name)
def check_plugin_name(cls, plugin_name):
"""
Check plugin name.
Args:
plugin_name (str): The plugin name.
Raises:
PluginNotAvailableError: When plugin name is not valid.
"""
plugin_name_list = PluginNameEnum.list_members()
if plugin_name not in plugin_name_list:
raise PluginNotAvailableError(f"'plugin_name' only can be one of {plugin_name_list}")
def check_plugin_name(cls, plugin_name):
"""
Check plugin name.
Args:
plugin_name (str): The plugin name.
Raises:
ParamValueError: When plugin name is not valid.
"""
plugin_name_list = PluginNameEnum.list_members()
if plugin_name not in plugin_name_list:
raise ParamValueError("'plugin_name' only can be one of {}"
"".format(plugin_name_list))
def test_query_single_train_task(self, client):
""""Test query single train task."""
for train_id in gbl.summaries_metadata:
expected = gbl.summaries_metadata.get(train_id).get("plugins")
for plugin_name in PluginNameEnum.list_members():
params = dict(train_id=train_id, plugin_name=plugin_name)
url = get_url(BASE_URL, params)
response = client.get(url)
result = response.get_json()
tags = result["train_jobs"][0]["tags"]
if plugin_name == PluginNameEnum.GRAPH.value:
assert len(tags) == len(expected[plugin_name])
else:
assert sorted(tags) == sorted(expected[plugin_name])
def test_plugins(self, client):
"""Test getting plugins."""
train_id = gbl.get_train_ids()[0]
expected_plugins = gbl.summaries_metadata.get(train_id).get("plugins")
params = dict(train_id=train_id)
url = get_url(BASE_URL, params)
response = client.get(url)
plugins = response.get_json().get('plugins')
for plugin_name in PluginNameEnum.list_members():
if plugin_name == PluginNameEnum.GRAPH.value:
assert len(plugins.get(plugin_name)) == len(
expected_plugins.get(plugin_name))
else:
assert sorted(plugins.get(plugin_name)) == sorted(
expected_plugins.get(plugin_name))
def get_train_job(self, train_id):
"""
Get train job by train ID.
This method overrides parent method.
Args:
train_id (str): Train ID for train job.
Returns:
dict, single train job, if can not find any data, will return None.
"""
self._check_train_job_exist(train_id, self._loader_pool)
loader = self._get_loader(train_id)
if loader is None:
logger.warning(
"No valid summary log in train job %s, "
"or it is not in the cache.", train_id)
return None
train_job = loader.to_dict()
train_job.pop('data_loader')
plugin_data = {}
for plugin_name in PluginNameEnum.list_members():
job = self.get_train_job_by_plugin(train_id,
plugin_name=plugin_name)
if job is None:
plugin_data[plugin_name] = []
else:
plugin_data[plugin_name] = job['tags']
train_job.update({DATAVISUAL_PLUGIN_KEY: plugin_data})
# Will fill basic_info value in future.
train_job_obj = CachedTrainJob(basic_info=None)
train_job_obj.set(DATAVISUAL_CACHE_KEY, train_job)
train_job_obj.cache_status = loader.cache_status
return train_job_obj
def get_plugins(self, train_id, manual_update=True):
"""
Queries the plug-in data for the specified training job
Args:
train_id (str): Specify a training job to query.
manual_update (bool): Specifies whether to refresh automatically.
Returns:
dict, refer to restful api.
"""
Validation.check_param_empty(train_id=train_id)
train_job = self._data_manager.get_single_train_job(
train_id, manual_update=manual_update)
if not train_job:
default_result = dict()
for plugin_name in PluginNameEnum.list_members():
default_result.update({plugin_name: list()})
return dict(plugins=default_result)
return dict(plugins=train_job['tag_mapping'])
def _get_train_job_item(self, train_id):
"""
Get train job item.
Args:
train_id (str): Specify train id.
Returns:
dict, a dict of train job item.
"""
try:
train_job = self._data_manager.get_train_job(train_id)
except exceptions.TrainJobNotExistError:
logger.warning('Train job %s not existed', train_id)
return None
basic_info = train_job.get_basic_info()
train_job_item = dict(
train_id=basic_info.train_id,
relative_path=basic_info.train_id,
create_time=basic_info.create_time.strftime('%Y-%m-%d %H:%M:%S'),
update_time=basic_info.update_time.strftime('%Y-%m-%d %H:%M:%S'),
profiler_dir=basic_info.profiler_dir,
cache_status=train_job.cache_status.value,
profiler_type=basic_info.profiler_type,
summary_files=basic_info.summary_files,
graph_files=basic_info.graph_files,
lineage_files=basic_info.lineage_files,
dump_dir=basic_info.dump_dir)
if train_job.cache_status != CacheStatus.NOT_IN_CACHE:
plugins = self.get_plugins(train_id, manual_update=False)
else:
plugins = dict(plugins={
plugin: []
for plugin in PluginNameEnum.list_members()
})
train_job_item.update(plugins)
return train_job_item
def get_single_train_job(self, train_id, manual_update=False):
"""
Get train job by train ID.
Args:
train_id (str): Train ID for train job.
manual_update (bool): If manual update, True.
Returns:
dict, single train job, if can not find any data, will return None.
"""
self._check_status_valid()
self._check_train_job_exist(train_id, self._loader_pool)
loader = self._get_loader(train_id, manual_update)
if loader is None:
logger.warning(
"No valid summary log in train job %s, "
"or it is not in the cache.", train_id)
return None
train_job = loader.to_dict()
train_job.pop('data_loader')
plugin_data = {}
for plugin_name in PluginNameEnum.list_members():
job = self.get_train_job_by_plugin(train_id,
plugin_name=plugin_name)
if job is None:
plugin_data[plugin_name] = []
else:
plugin_data[plugin_name] = job['tags']
train_job.update({'tag_mapping': plugin_data})
return train_job