def __init__(self, trial, searcher_config, training_history: dict,
config_history: dict):
self.trial = trial
self.training_history = training_history
self.training_history[trial] = []
self.searcher_config = EasyDict(deepcopy(searcher_config))
self.config_history = config_history
self.trial_started = time.time()
self.last_reported_time = self.trial_started
self.last_result = None
def get_efficientnet_blockargs():
""" Creates a predefined efficientnet model, which searched by original paper. """
blocks_args = [
EasyDict(kernel=3,
num_repeat=1,
channels=16,
expand_ratio=1,
stride=1,
se_ratio=0.25,
in_channels=32),
EasyDict(kernel=3,
num_repeat=2,
channels=24,
expand_ratio=6,
stride=2,
se_ratio=0.25,
in_channels=16),
EasyDict(kernel=5,
num_repeat=2,
channels=40,
expand_ratio=6,
stride=2,
se_ratio=0.25,
in_channels=24),
EasyDict(kernel=3,
num_repeat=3,
channels=80,
expand_ratio=6,
stride=2,
se_ratio=0.25,
in_channels=40),
EasyDict(kernel=5,
num_repeat=3,
channels=112,
expand_ratio=6,
stride=1,
se_ratio=0.25,
in_channels=80),
EasyDict(kernel=5,
num_repeat=4,
channels=192,
expand_ratio=6,
stride=2,
se_ratio=0.25,
in_channels=112),
EasyDict(kernel=3,
num_repeat=1,
channels=320,
expand_ratio=6,
stride=1,
se_ratio=0.25,
in_channels=192),
]
return blocks_args
class LocalReporter:
"""
Reporter implementation for LocalSequentialScheduler
"""
def __init__(self, trial, searcher_config, training_history: dict,
config_history: dict):
self.trial = trial
self.training_history = training_history
self.training_history[trial] = []
self.searcher_config = EasyDict(deepcopy(searcher_config))
self.config_history = config_history
self.trial_started = time.time()
self.last_reported_time = self.trial_started
self.last_result = None
def __call__(self, *args, **kwargs):
result = deepcopy(kwargs)
if 'done' not in result:
result['trial'] = self.trial
now = time.time()
result['time_this_iter'] = now - self.last_reported_time
result['time_since_start'] = now - self.trial_started
self.last_reported_time = now
self.training_history[self.trial].append(result)
if self.trial not in self.config_history:
self.config_history[self.trial] = self.searcher_config
if 'util_args' in self.searcher_config:
self.searcher_config.pop('util_args')
self.last_result = result
def terminate(self):
pass # compatibility
def run_job_(self, task_id, searcher_config, reporter):
args = deepcopy(EasyDict(self.train_fn.kwvars))
args['task_id'] = task_id
self.searcher.register_pending(searcher_config)
is_failed = False
try:
result = self.train_fn(args,
config=searcher_config,
reporter=reporter)
if type(reporter) is not FakeReporter and reporter.last_result:
self.searcher.update(config=searcher_config,
**reporter.last_result)
except Exception as e:
logger.error(f'Exception during a trial: {e}')
self.searcher.evaluation_failed(config=searcher_config)
reporter(traceback=e)
is_failed = True
result = {'traceback': str(e)}
return is_failed, result
def run_trial(self, task_id=0) -> Tuple[bool, float, float]:
"""
Start a trial with a given task_id
Parameters
----------
task_id
task
Returns
-------
is_failed: bool
True if task completed successfully
trial_start_time
Trial start time
trial_end_time
Trial end time
"""
searcher_config = self.searcher.get_config()
reporter = LocalReporter(task_id, searcher_config,
self.training_history, self.config_history)
args = deepcopy(EasyDict(self.train_fn.kwvars))
args['task_id'] = task_id
self.searcher.register_pending(searcher_config)
is_failed = False
try:
self.train_fn(args, config=searcher_config, reporter=reporter)
if reporter.last_result:
self.searcher.update(config=searcher_config,
**reporter.last_result)
except Exception as e:
logger.error(f'Exception during a trial: {e}')
self.searcher.evaluation_failed(config=searcher_config)
reporter(traceback=e)
is_failed = True
return is_failed