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[tune] temporary revert of verbosity changes (#12132)

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Richard Liaw 2020-11-18 18:27:41 -08:00 • committed by GitHub
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181
python/ray/tune/progress_reporter.py
View file

@ -1,21 +1,16 @@
from __future__ import print_function from __future__ import print_function
import collections import collections
import os
import sys import sys
from typing import Dict, List, Optional
import numpy as np import numpy as np
import time import time
from ray.tune.callback import Callback
from ray.tune.logger import pretty_print
from ray.tune.result import (EPISODE_REWARD_MEAN, MEAN_ACCURACY, MEAN_LOSS, from ray.tune.result import (EPISODE_REWARD_MEAN, MEAN_ACCURACY, MEAN_LOSS,
TRAINING_ITERATION, TIME_TOTAL_S, TIMESTEPS_TOTAL, TRAINING_ITERATION, TIME_TOTAL_S, TIMESTEPS_TOTAL,
AUTO_RESULT_KEYS) AUTO_RESULT_KEYS)
from ray.tune.trial import DEBUG_PRINT_INTERVAL, Trial from ray.tune.trial import Trial
from ray.tune.utils import unflattened_lookup from ray.tune.utils import unflattened_lookup
from ray.tune.utils.log import Verbosity, has_verbosity
try: try:
from collections.abc import Mapping from collections.abc import Mapping
@ -229,19 +224,15 @@ class TuneReporterBase(ProgressReporter):
best_trial_str(current_best_trial, metric, best_trial_str(current_best_trial, metric,
self._parameter_columns)) self._parameter_columns))
if has_verbosity(Verbosity.V1_EXPERIMENT): messages.append(
# Will filter the table in `trial_progress_str` trial_progress_str(
messages.append( trials,
trial_progress_str( metric_columns=self._metric_columns,
trials, parameter_columns=self._parameter_columns,
metric_columns=self._metric_columns, total_samples=self._total_samples,
parameter_columns=self._parameter_columns, fmt=fmt,
total_samples=self._total_samples, max_rows=max_progress))
fmt=fmt, messages.append(trial_errors_str(trials, fmt=fmt, max_rows=max_error))
max_rows=max_progress,
done=done))
messages.append(
trial_errors_str(trials, fmt=fmt, max_rows=max_error))
return delim.join(messages) + delim return delim.join(messages) + delim
@ -408,20 +399,12 @@ def memory_debug_str():
"(or ray[debug]) to resolve)") "(or ray[debug]) to resolve)")
def _get_trials_by_state(trials):
trials_by_state = collections.defaultdict(list)
for t in trials:
trials_by_state[t.status].append(t)
return trials_by_state
def trial_progress_str(trials, def trial_progress_str(trials,
metric_columns, metric_columns,
parameter_columns=None, parameter_columns=None,
total_samples=0, total_samples=0,
fmt="psql", fmt="psql",
max_rows=None, max_rows=None):
done=False):
"""Returns a human readable message for printing to the console. """Returns a human readable message for printing to the console.
This contains a table where each row represents a trial, its parameters This contains a table where each row represents a trial, its parameters
@ -449,7 +432,9 @@ def trial_progress_str(trials,
return delim.join(messages) return delim.join(messages)
num_trials = len(trials) num_trials = len(trials)
trials_by_state = _get_trials_by_state(trials) trials_by_state = collections.defaultdict(list)
for t in trials:
trials_by_state[t.status].append(t)
for local_dir in sorted({t.local_dir for t in trials}): for local_dir in sorted({t.local_dir for t in trials}):
messages.append("Result logdir: {}".format(local_dir)) messages.append("Result logdir: {}".format(local_dir))
@ -459,30 +444,6 @@ def trial_progress_str(trials,
for state in sorted(trials_by_state) for state in sorted(trials_by_state)
] ]
if total_samples and total_samples >= sys.maxsize:
total_samples = "infinite"
messages.append("Number of trials: {}{} ({})".format(
num_trials, f"/{total_samples}"
if total_samples else "", ", ".join(num_trials_strs)))
if has_verbosity(Verbosity.V3_TRIAL_DETAILS) or (has_verbosity(
Verbosity.V2_TRIAL_NORM) and done):
messages += trial_progress_table(trials, metric_columns,
parameter_columns, fmt, max_rows)
return delim.join(messages)
def trial_progress_table(trials,
metric_columns,
parameter_columns=None,
fmt="psql",
max_rows=None):
messages = []
num_trials = len(trials)
trials_by_state = _get_trials_by_state(trials)
state_tbl_order = [ state_tbl_order = [
Trial.RUNNING, Trial.PAUSED, Trial.PENDING, Trial.TERMINATED, Trial.RUNNING, Trial.PAUSED, Trial.PENDING, Trial.TERMINATED,
Trial.ERROR Trial.ERROR
@ -513,6 +474,13 @@ def trial_progress_table(trials,
continue continue
trials += trials_by_state[state] trials += trials_by_state[state]
if total_samples and total_samples >= sys.maxsize:
total_samples = "infinite"
messages.append("Number of trials: {}{} ({})".format(
num_trials, f"/{total_samples}"
if total_samples else "", ", ".join(num_trials_strs)))
# Pre-process trials to figure out what columns to show. # Pre-process trials to figure out what columns to show.
if isinstance(metric_columns, Mapping): if isinstance(metric_columns, Mapping):
metric_keys = list(metric_columns.keys()) metric_keys = list(metric_columns.keys())
@ -554,7 +522,7 @@ def trial_progress_table(trials,
if overflow: if overflow:
messages.append("... {} more trials not shown ({})".format( messages.append("... {} more trials not shown ({})".format(
overflow, overflow_str)) overflow, overflow_str))
return messages return delim.join(messages)
def trial_errors_str(trials, fmt="psql", max_rows=None): def trial_errors_str(trials, fmt="psql", max_rows=None):
@ -653,108 +621,3 @@ def _get_trial_info(trial, parameters, metrics):
unflattened_lookup(metric, result, default=None) for metric in metrics unflattened_lookup(metric, result, default=None) for metric in metrics
] ]
return trial_info return trial_info
class TrialProgressCallback(Callback):
"""Reports (prints) intermediate trial progress.
This callback is automatically added to the callback stack. When a
result is obtained, this callback will print the results according to
the specified verbosity level.
For ``Verbosity.V3_TRIAL_DETAILS``, a full result list is printed.
For ``Verbosity.V2_TRIAL_NORM``, only one line is printed per received
result.
All other verbosity levels do not print intermediate trial progress.
Result printing is throttled on a per-trial basis. Per default, results are
printed only once every 30 seconds. Results are always printed when a trial
finished or errored.
"""
def __init__(self, metric: Optional[str] = None):
self._last_print = collections.defaultdict(float)
self._completed_trials = set()
self._last_result_str = {}
self._metric = metric
def on_trial_result(self, iteration: int, trials: List["Trial"],
trial: "Trial", result: Dict, **info):
self.log_result(trial, result, error=False)
def on_trial_error(self, iteration: int, trials: List["Trial"],
trial: "Trial", **info):
self.log_result(trial, trial.last_result, error=True)
def on_trial_complete(self, iteration: int, trials: List["Trial"],
trial: "Trial", **info):
# Only log when we never logged that a trial was completed
if trial not in self._completed_trials:
self._completed_trials.add(trial)
print_result_str = self._print_result(trial.last_result)
last_result_str = self._last_result_str.get(trial, "")
# If this is a new result, print full result string
if print_result_str != last_result_str:
self.log_result(trial, trial.last_result, error=False)
else:
print(f"Trial {trial} completed. "
f"Last result: {print_result_str}")
def log_result(self, trial: "Trial", result: Dict, error: bool = False):
done = result.get("done", False) is True
last_print = self._last_print[trial]
if done and trial not in self._completed_trials:
self._completed_trials.add(trial)
if has_verbosity(Verbosity.V3_TRIAL_DETAILS) and \
(done or error or time.time() - last_print > DEBUG_PRINT_INTERVAL):
print("Result for {}:".format(trial))
print(" {}".format(pretty_print(result).replace("\n", "\n ")))
self._last_print[trial] = time.time()
elif has_verbosity(Verbosity.V2_TRIAL_NORM) and (
done or error
or time.time() - last_print > DEBUG_PRINT_INTERVAL):
info = ""
if done:
info = " This trial completed."
metric_name = self._metric or "_metric"
metric_value = result.get(metric_name, -99.)
print_result_str = self._print_result(result)
self._last_result_str[trial] = print_result_str
error_file = os.path.join(trial.logdir, "error.txt")
if error:
message = f"The trial {trial} errored with " \
f"parameters={trial.config}. " \
f"Error file: {error_file}"
elif self._metric:
message = f"Trial {trial} reported " \
f"{metric_name}={metric_value:.2f} " \
f"with parameters={trial.config}.{info}"
else:
message = f"Trial {trial} reported " \
f"{print_result_str} " \
f"with parameters={trial.config}.{info}"
print(message)
self._last_print[trial] = time.time()
def _print_result(self, result: Dict):
print_result = result.copy()
print_result.pop("config", None)
print_result.pop("trial_id", None)
print_result.pop("experiment_tag", None)
print_result.pop("done", None)
for auto_result in AUTO_RESULT_KEYS:
print_result.pop(auto_result, None)
print_result_str = ",".join(
[f"{k}={v}" for k, v in print_result.items()])
return print_result_str

102
python/ray/tune/tests/test_progress_reporter.py
View file

@ -73,7 +73,7 @@ tune.run_experiments({
"c": tune.grid_search(list(range(10))), "c": tune.grid_search(list(range(10))),
}, },
}, },
}, verbose=3, progress_reporter=reporter)""" }, verbose=1, progress_reporter=reporter)"""
EXPECTED_END_TO_END_START = """Number of trials: 1/30 (1 RUNNING) EXPECTED_END_TO_END_START = """Number of trials: 1/30 (1 RUNNING)
+---------------+----------+-------+-----+ +---------------+----------+-------+-----+
@ -160,48 +160,6 @@ EXPECTED_BEST_1 = "Current best trial: 00001 with metric_1=0.5 and " \
EXPECTED_BEST_2 = "Current best trial: 00004 with metric_1=2.0 and " \ EXPECTED_BEST_2 = "Current best trial: 00004 with metric_1=2.0 and " \
"parameters={'a': 4}" "parameters={'a': 4}"
VERBOSE_EXP_OUT_1 = "Number of trials: 1/3 (1 RUNNING)"
VERBOSE_EXP_OUT_2 = "Number of trials: 3/3 (3 TERMINATED)"
VERBOSE_TRIAL_NORM = "Trial train_xxxxx_00000 reported acc=5 with " + \
"""parameters={'do': 'complete'}. This trial completed.
Trial train_xxxxx_00001 reported _metric=6 with parameters={'do': 'once'}.
Trial train_xxxxx_00001 completed. Last result: _metric=6
Trial train_xxxxx_00002 reported acc=7 with parameters={'do': 'twice'}.
Trial train_xxxxx_00002 reported acc=8 with parameters={'do': 'twice'}. """ + \
"This trial completed."
VERBOSE_TRIAL_DETAIL = """+-------------------+----------+-------+----------+
| Trial name | status | loc | do |
|-------------------+----------+-------+----------|
| train_xxxxx_00000 | RUNNING | | complete |
+-------------------+----------+-------+----------+"""
VERBOSE_CMD = """from ray import tune
import random
import numpy as np
def train(config):
if config["do"] == "complete":
tune.report(acc=5, done=True)
elif config["do"] == "once":
tune.report(6)
else:
tune.report(acc=7)
tune.report(acc=8)
random.seed(1234)
np.random.seed(1234)
tune.run(
train,
config={
"do": tune.grid_search(["complete", "once", "twice"])
},"""
# Add "verbose=3)" etc
class ProgressReporterTest(unittest.TestCase): class ProgressReporterTest(unittest.TestCase):
def mock_trial(self, status, i): def mock_trial(self, status, i):
@ -405,64 +363,6 @@ class ProgressReporterTest(unittest.TestCase):
finally: finally:
del os.environ["_TEST_TUNE_TRIAL_UUID"] del os.environ["_TEST_TUNE_TRIAL_UUID"]
def testVerboseReporting(self):
try:
os.environ["_TEST_TUNE_TRIAL_UUID"] = "xxxxx"
verbose_0_cmd = VERBOSE_CMD + "verbose=0)"
output = run_string_as_driver(verbose_0_cmd)
try:
assert VERBOSE_EXP_OUT_1 not in output
assert VERBOSE_EXP_OUT_2 not in output
assert VERBOSE_TRIAL_NORM not in output
assert VERBOSE_TRIAL_DETAIL not in output
except Exception:
print("*** BEGIN OUTPUT ***")
print(output)
print("*** END OUTPUT ***")
raise
verbose_1_cmd = VERBOSE_CMD + "verbose=1)"
output = run_string_as_driver(verbose_1_cmd)
try:
assert VERBOSE_EXP_OUT_1 in output
assert VERBOSE_EXP_OUT_2 in output
assert VERBOSE_TRIAL_NORM not in output
assert VERBOSE_TRIAL_DETAIL not in output
except Exception:
print("*** BEGIN OUTPUT ***")
print(output)
print("*** END OUTPUT ***")
raise
verbose_2_cmd = VERBOSE_CMD + "verbose=2)"
output = run_string_as_driver(verbose_2_cmd)
try:
assert VERBOSE_EXP_OUT_1 in output
assert VERBOSE_EXP_OUT_2 in output
assert VERBOSE_TRIAL_NORM in output
assert VERBOSE_TRIAL_DETAIL not in output
except Exception:
print("*** BEGIN OUTPUT ***")
print(output)
print("*** END OUTPUT ***")
raise
verbose_3_cmd = VERBOSE_CMD + "verbose=3)"
output = run_string_as_driver(verbose_3_cmd)
try:
assert VERBOSE_EXP_OUT_1 in output
assert VERBOSE_EXP_OUT_2 in output
assert VERBOSE_TRIAL_NORM not in output
assert VERBOSE_TRIAL_DETAIL in output
except Exception:
print("*** BEGIN OUTPUT ***")
print(output)
print("*** END OUTPUT ***")
raise
finally:
del os.environ["_TEST_TUNE_TRIAL_UUID"]
if __name__ == "__main__": if __name__ == "__main__":
import sys import sys

11
python/ray/tune/trial.py
View file

@ -16,6 +16,7 @@ from ray.tune.checkpoint_manager import Checkpoint, CheckpointManager
# NOTE(rkn): We import ray.tune.registry here instead of importing the names we # NOTE(rkn): We import ray.tune.registry here instead of importing the names we
# need because there are cyclic imports that may cause specific names to not # need because there are cyclic imports that may cause specific names to not
# have been defined yet. See https://github.com/ray-project/ray/issues/1716. # have been defined yet. See https://github.com/ray-project/ray/issues/1716.
from ray.tune.logger import pretty_print
from ray.tune.registry import get_trainable_cls, validate_trainable from ray.tune.registry import get_trainable_cls, validate_trainable
from ray.tune.result import DEFAULT_RESULTS_DIR, DONE, TRAINING_ITERATION from ray.tune.result import DEFAULT_RESULTS_DIR, DONE, TRAINING_ITERATION
from ray.tune.resources import Resources, json_to_resources, resources_to_json from ray.tune.resources import Resources, json_to_resources, resources_to_json
@ -229,6 +230,7 @@ class Trial:
or not len(self.log_to_file) == 2: or not len(self.log_to_file) == 2:
self.log_to_file = (None, None) self.log_to_file = (None, None)
self.verbose = True
self.max_failures = max_failures self.max_failures = max_failures
# Local trial state that is updated during the run # Local trial state that is updated during the run
@ -478,7 +480,11 @@ class Trial:
def update_last_result(self, result, terminate=False): def update_last_result(self, result, terminate=False):
if self.experiment_tag: if self.experiment_tag:
result.update(experiment_tag=self.experiment_tag) result.update(experiment_tag=self.experiment_tag)
if self.verbose and (terminate or time.time() - self.last_debug >
DEBUG_PRINT_INTERVAL):
print("Result for {}:".format(self))
print(" {}".format(pretty_print(result).replace("\n", "\n ")))
self.last_debug = time.time()
self.set_location(Location(result.get("node_ip"), result.get("pid"))) self.set_location(Location(result.get("node_ip"), result.get("pid")))
self.last_result = result self.last_result = result
self.last_update_time = time.time() self.last_update_time = time.time()
@ -521,6 +527,9 @@ class Trial:
def get_trainable_cls(self): def get_trainable_cls(self):
return get_trainable_cls(self.trainable_name) return get_trainable_cls(self.trainable_name)
def set_verbose(self, verbose):
self.verbose = verbose
def is_finished(self): def is_finished(self):
return self.status in [Trial.ERROR, Trial.TERMINATED] return self.status in [Trial.ERROR, Trial.TERMINATED]

11
python/ray/tune/trial_runner.py
View file

@ -19,7 +19,6 @@ from ray.tune.trial import Checkpoint, Trial
from ray.tune.schedulers import FIFOScheduler, TrialScheduler from ray.tune.schedulers import FIFOScheduler, TrialScheduler
from ray.tune.suggest import BasicVariantGenerator from ray.tune.suggest import BasicVariantGenerator
from ray.tune.utils import warn_if_slow, flatten_dict, env_integer from ray.tune.utils import warn_if_slow, flatten_dict, env_integer
from ray.tune.utils.log import Verbosity, has_verbosity
from ray.tune.utils.serialization import TuneFunctionDecoder, \ from ray.tune.utils.serialization import TuneFunctionDecoder, \
TuneFunctionEncoder TuneFunctionEncoder
from ray.tune.web_server import TuneServer from ray.tune.web_server import TuneServer
@ -79,6 +78,8 @@ class TrialRunner:
If fail_fast='raise' provided, Tune will automatically If fail_fast='raise' provided, Tune will automatically
raise the exception received by the Trainable. fail_fast='raise' raise the exception received by the Trainable. fail_fast='raise'
can easily leak resources and should be used with caution. can easily leak resources and should be used with caution.
verbose (bool): Flag for verbosity. If False, trial results
will not be output.
checkpoint_period (int): Trial runner checkpoint periodicity in checkpoint_period (int): Trial runner checkpoint periodicity in
seconds. Defaults to 10. seconds. Defaults to 10.
trial_executor (TrialExecutor): Defaults to RayTrialExecutor. trial_executor (TrialExecutor): Defaults to RayTrialExecutor.
@ -101,6 +102,7 @@ class TrialRunner:
resume=False, resume=False,
server_port=None, server_port=None,
fail_fast=False, fail_fast=False,
verbose=True,
checkpoint_period=None, checkpoint_period=None,
trial_executor=None, trial_executor=None,
callbacks=None, callbacks=None,
@ -133,6 +135,7 @@ class TrialRunner:
else: else:
raise ValueError("fail_fast must be one of {bool, RAISE}. " raise ValueError("fail_fast must be one of {bool, RAISE}. "
f"Got {self._fail_fast}.") f"Got {self._fail_fast}.")
self._verbose = verbose
self._server = None self._server = None
self._server_port = server_port self._server_port = server_port
@ -162,7 +165,7 @@ class TrialRunner:
self.resume(run_errored_only=errored_only) self.resume(run_errored_only=errored_only)
self._resumed = True self._resumed = True
except Exception as e: except Exception as e:
if has_verbosity(Verbosity.V3_TRIAL_DETAILS): if self._verbose:
logger.error(str(e)) logger.error(str(e))
logger.exception("Runner restore failed.") logger.exception("Runner restore failed.")
if self._fail_fast: if self._fail_fast:
@ -401,6 +404,7 @@ class TrialRunner:
Args: Args:
trial (Trial): Trial to queue. trial (Trial): Trial to queue.
""" """
trial.set_verbose(self._verbose)
self._trials.append(trial) self._trials.append(trial)
with warn_if_slow("scheduler.on_trial_add"): with warn_if_slow("scheduler.on_trial_add"):
self._scheduler_alg.on_trial_add(self, trial) self._scheduler_alg.on_trial_add(self, trial)
@ -558,8 +562,6 @@ class TrialRunner:
with warn_if_slow("scheduler.on_trial_result"): with warn_if_slow("scheduler.on_trial_result"):
decision = self._scheduler_alg.on_trial_result( decision = self._scheduler_alg.on_trial_result(
self, trial, flat_result) self, trial, flat_result)
if decision == TrialScheduler.STOP:
result.update(done=True)
with warn_if_slow("search_alg.on_trial_result"): with warn_if_slow("search_alg.on_trial_result"):
self._search_alg.on_trial_result(trial.trial_id, self._search_alg.on_trial_result(trial.trial_id,
flat_result) flat_result)
@ -578,6 +580,7 @@ class TrialRunner:
iteration=self._iteration, iteration=self._iteration,
trials=self._trials, trials=self._trials,
trial=trial) trial=trial)
result.update(done=True)
if not is_duplicate: if not is_duplicate:
trial.update_last_result( trial.update_last_result(

29
python/ray/tune/tune.py
View file

@ -18,7 +18,6 @@ from ray.tune.syncer import wait_for_sync, set_sync_periods, \
from ray.tune.trial_runner import TrialRunner from ray.tune.trial_runner import TrialRunner
from ray.tune.progress_reporter import CLIReporter, JupyterNotebookReporter from ray.tune.progress_reporter import CLIReporter, JupyterNotebookReporter
from ray.tune.schedulers import FIFOScheduler from ray.tune.schedulers import FIFOScheduler
from ray.tune.utils.log import Verbosity, has_verbosity, set_verbosity
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -71,7 +70,7 @@ def run(
checkpoint_score_attr=None, checkpoint_score_attr=None,
checkpoint_freq=0, checkpoint_freq=0,
checkpoint_at_end=False, checkpoint_at_end=False,
verbose=Verbosity.V3_TRIAL_DETAILS, verbose=2,
progress_reporter=None, progress_reporter=None,
log_to_file=False, log_to_file=False,
trial_name_creator=None, trial_name_creator=None,
@ -189,9 +188,8 @@ def run(
checkpoint_at_end (bool): Whether to checkpoint at the end of the checkpoint_at_end (bool): Whether to checkpoint at the end of the
experiment regardless of the checkpoint_freq. Default is False. experiment regardless of the checkpoint_freq. Default is False.
This has no effect when using the Functional Training API. This has no effect when using the Functional Training API.
verbose (int): 0, 1, 2, or 3. Verbosity mode. 0 = silent, verbose (int): 0, 1, or 2. Verbosity mode. 0 = silent,
1 = only status updates, 2 = status and brief trial results, 1 = only status updates, 2 = status and trial results.
3 = status and detailed trial results. Defaults to 3.
progress_reporter (ProgressReporter): Progress reporter for reporting progress_reporter (ProgressReporter): Progress reporter for reporting
intermediate experiment progress. Defaults to CLIReporter if intermediate experiment progress. Defaults to CLIReporter if
running in command-line, or JupyterNotebookReporter if running in running in command-line, or JupyterNotebookReporter if running in
@ -283,8 +281,6 @@ def run(
"The `mode` parameter passed to `tune.run()` has to be one of " "The `mode` parameter passed to `tune.run()` has to be one of "
"['min', 'max']") "['min', 'max']")
set_verbosity(verbose)
config = config or {} config = config or {}
sync_config = sync_config or SyncConfig() sync_config = sync_config or SyncConfig()
set_sync_periods(sync_config) set_sync_periods(sync_config)
@ -357,9 +353,9 @@ def run(
"own `metric` and `mode` parameters. Either remove the arguments " "own `metric` and `mode` parameters. Either remove the arguments "
"from your scheduler or from your call to `tune.run()`") "from your scheduler or from your call to `tune.run()`")
# Create syncer callbacks # Create logger and syncer callbacks
callbacks = create_default_callbacks( callbacks = create_default_callbacks(
callbacks, sync_config, metric=metric, loggers=loggers) callbacks, sync_config, loggers=loggers)
runner = TrialRunner( runner = TrialRunner(
search_alg=search_alg, search_alg=search_alg,
@ -370,6 +366,7 @@ def run(
stopper=experiments[0].stopper, stopper=experiments[0].stopper,
resume=resume, resume=resume,
server_port=server_port, server_port=server_port,
verbose=bool(verbose > 1),
fail_fast=fail_fast, fail_fast=fail_fast,
trial_executor=trial_executor, trial_executor=trial_executor,
callbacks=callbacks, callbacks=callbacks,
@ -383,8 +380,7 @@ def run(
if progress_reporter is None: if progress_reporter is None:
if IS_NOTEBOOK: if IS_NOTEBOOK:
progress_reporter = JupyterNotebookReporter( progress_reporter = JupyterNotebookReporter(overwrite=verbose < 2)
overwrite=not has_verbosity(Verbosity.V2_TRIAL_NORM))
else: else:
progress_reporter = CLIReporter() progress_reporter = CLIReporter()
@ -417,7 +413,7 @@ def run(
tune_start = time.time() tune_start = time.time()
while not runner.is_finished(): while not runner.is_finished():
runner.step() runner.step()
if has_verbosity(Verbosity.V1_EXPERIMENT): if verbose:
_report_progress(runner, progress_reporter) _report_progress(runner, progress_reporter)
tune_taken = time.time() - tune_start tune_taken = time.time() - tune_start
@ -426,7 +422,7 @@ def run(
except Exception as e: except Exception as e:
logger.warning(f"Trial Runner checkpointing failed: {str(e)}") logger.warning(f"Trial Runner checkpointing failed: {str(e)}")
if has_verbosity(Verbosity.V1_EXPERIMENT): if verbose:
_report_progress(runner, progress_reporter, done=True) _report_progress(runner, progress_reporter, done=True)
wait_for_sync() wait_for_sync()
@ -444,9 +440,8 @@ def run(
logger.error("Trials did not complete: %s", incomplete_trials) logger.error("Trials did not complete: %s", incomplete_trials)
all_taken = time.time() - all_start all_taken = time.time() - all_start
if has_verbosity(Verbosity.V1_EXPERIMENT): logger.info(f"Total run time: {all_taken:.2f} seconds "
logger.info(f"Total run time: {all_taken:.2f} seconds " f"({tune_taken:.2f} seconds for the tuning loop).")
f"({tune_taken:.2f} seconds for the tuning loop).")
trials = runner.get_trials() trials = runner.get_trials()
return ExperimentAnalysis( return ExperimentAnalysis(
@ -459,7 +454,7 @@ def run(
def run_experiments(experiments, def run_experiments(experiments,
scheduler=None, scheduler=None,
server_port=None, server_port=None,
verbose=Verbosity.V3_TRIAL_DETAILS, verbose=2,
progress_reporter=None, progress_reporter=None,
resume=False, resume=False,
queue_trials=False, queue_trials=False,

33
python/ray/tune/utils/callback.py
View file

@ -3,7 +3,6 @@ import os
from typing import List, Optional from typing import List, Optional
from ray.tune.callback import Callback from ray.tune.callback import Callback
from ray.tune.progress_reporter import TrialProgressCallback
from ray.tune.syncer import SyncConfig from ray.tune.syncer import SyncConfig
from ray.tune.logger import CSVLoggerCallback, CSVLogger, \ from ray.tune.logger import CSVLoggerCallback, CSVLogger, \
LoggerCallback, \ LoggerCallback, \
@ -16,44 +15,14 @@ logger = logging.getLogger(__name__)
def create_default_callbacks(callbacks: Optional[List[Callback]], def create_default_callbacks(callbacks: Optional[List[Callback]],
sync_config: SyncConfig, sync_config: SyncConfig,
loggers: Optional[List[Logger]], loggers: Optional[List[Logger]]):
metric: Optional[str] = None):
"""Create default callbacks for `tune.run()`.
This function takes a list of existing callbacks and adds default
callbacks to it.
Specifically, three kinds of callbacks will be added:
1. Loggers. Ray Tune's experiment analysis relies on CSV and JSON logging.
2. Syncer. Ray Tune synchronizes logs and checkpoint between workers and
the head node.
2. Trial progress reporter. For reporting intermediate progress, like trial
results, Ray Tune uses a callback.
These callbacks will only be added if they don't already exist, i.e. if
they haven't been passed (and configured) by the user. A notable case
is when a Logger is passed, which is not a CSV or JSON logger - then
a CSV and JSON logger will still be created.
Lastly, this function will ensure that the Syncer callback comes after all
Logger callbacks, to ensure that the most up-to-date logs and checkpoints
are synced across nodes.
"""
callbacks = callbacks or [] callbacks = callbacks or []
has_syncer_callback = False has_syncer_callback = False
has_csv_logger = False has_csv_logger = False
has_json_logger = False has_json_logger = False
has_tbx_logger = False has_tbx_logger = False
has_trial_progress_callback = any(
isinstance(c, TrialProgressCallback) for c in callbacks)
if not has_trial_progress_callback:
trial_progress_callback = TrialProgressCallback(metric=metric)
callbacks.append(trial_progress_callback)
# Track syncer obj/index to move callback after loggers # Track syncer obj/index to move callback after loggers
last_logger_index = None last_logger_index = None
syncer_index = None syncer_index = None

34
python/ray/tune/utils/log.py
View file

@ -1,34 +0,0 @@
from enum import Enum
from typing import Union
class Verbosity(Enum):
V0_MINIMAL = 0
V1_EXPERIMENT = 1
V2_TRIAL_NORM = 2
V3_TRIAL_DETAILS = 3
def __int__(self):
return self.value
verbosity: Union[int, Verbosity] = Verbosity.V3_TRIAL_DETAILS
def set_verbosity(level: Union[int, Verbosity]):
global verbosity
if isinstance(level, int):
verbosity = Verbosity(level)
else:
verbosity = verbosity
def has_verbosity(level: Union[int, Verbosity]) -> bool:
"""Return True if passed level exceeds global verbosity level."""
global verbosity
log_level = int(level)
verbosity_level = int(verbosity)
return verbosity_level >= log_level