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Fix debug output being spammed by other libraries.
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Fixes #70
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@kiudee
kiudee committed Aug 24, 2020
1 parent df57383 commit 5d156ad
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Showing 2 changed files with 25 additions and 24 deletions.
1 change: 1 addition & 0 deletions HISTORY.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@ History
-------------------------
* Improve default parameters to be slightly more robust for most use cases and
be more in line with what a user might expect.
* Fix debug output being spammed by other libraries.

0.6.0-beta.0 (2020-08-24)
-------------------------
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48 changes: 24 additions & 24 deletions tune/cli.py
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Original file line number Diff line number Diff line change
Expand Up @@ -256,8 +256,9 @@ def local( # noqa: C901
settings, commands, fixed_params, param_ranges = load_tuning_config(json_dict)
log_level = logging.DEBUG if verbose else logging.INFO
log_format = logging.Formatter("%(asctime)s %(levelname)-8s %(message)s")
root_logger = logging.getLogger()
root_logger = logging.getLogger("ChessTuner")
root_logger.setLevel(log_level)
root_logger.propagate = False
file_logger = logging.FileHandler(settings.get("logfile", logfile))
file_logger.setFormatter(log_format)
root_logger.addHandler(file_logger)
Expand Down Expand Up @@ -298,7 +299,7 @@ def local( # noqa: C901
y = importa["arr_1"].tolist()
noise = importa["arr_2"].tolist()
if len(X[0]) != opt.space.n_dims:
logging.error(
root_logger.error(
"The number of parameters are not matching the number of "
"dimensions. Rename the existing data file or ensure that the "
"parameter ranges are correct."
Expand All @@ -311,7 +312,7 @@ def local( # noqa: C901
backup_path = path.parent / (
path.stem + f"_backup_{int(time.time())}" + path.suffix
)
logging.warning(
root_logger.warning(
f"The parameter ranges are smaller than the existing data. "
f"Some points will have to be discarded. "
f"The original {len(X)} data points will be saved to "
Expand All @@ -325,7 +326,7 @@ def local( # noqa: C901
noise = noise_reduced

iteration = len(X)
logging.info(
root_logger.info(
f"Importing {iteration} existing datapoints. This could take a while..."
)
opt.tell(
Expand All @@ -337,11 +338,11 @@ def local( # noqa: C901
n_samples=settings.get("n_samples", 1),
progress=True,
)
logging.info("Importing finished.")
root_logger.info("Importing finished.")

# 4. Main optimization loop:
while True:
logging.info("Starting iteration {}".format(iteration))
root_logger.info("Starting iteration {}".format(iteration))
result_every_n = settings.get("result_every", result_every)
if (
result_every_n > 0
Expand All @@ -352,8 +353,8 @@ def local( # noqa: C901
try:
best_point, best_value = expected_ucb(result_object, alpha=0.0)
best_point_dict = dict(zip(param_ranges.keys(), best_point))
logging.info(f"Current optimum:\n{best_point_dict}")
logging.info(f"Estimated value: {best_value}")
root_logger.info(f"Current optimum:\n{best_point_dict}")
root_logger.info(f"Estimated value: {best_value}")
confidence_val = settings.get("confidence", confidence)
confidence_out = confidence_intervals(
optimizer=opt,
Expand All @@ -362,11 +363,11 @@ def local( # noqa: C901
opt_samples=1000,
multimodal=False,
)
logging.info(
root_logger.info(
f"{confidence_val*100}% confidence intervals:\n{confidence_out}"
)
except ValueError:
logging.info(
root_logger.info(
"Computing current optimum was not successful. "
"This can happen in rare cases and running the "
"tuner again usually works."
Expand All @@ -377,13 +378,12 @@ def local( # noqa: C901
and iteration % plot_every_n == 0
and opt.gp.chain_ is not None
):
logging.getLogger("matplotlib.font_manager").disabled = True
if opt.space.n_dims == 1:
logging.warning(
root_logger.warning(
"Plotting for only 1 parameter is not supported yet."
)
else:
logging.debug("Starting to compute the next plot.")
root_logger.debug("Starting to compute the next plot.")
result_object = create_result(
Xi=X, yi=y, space=opt.space, models=[opt.gp]
)
Expand Down Expand Up @@ -411,26 +411,26 @@ def local( # noqa: C901
bbox_inches="tight",
facecolor="#36393f",
)
logging.info(f"Saving a plot to {full_plotpath}.")
root_logger.info(f"Saving a plot to {full_plotpath}.")
plt.close(fig)
point = opt.ask()
point_dict = dict(zip(param_ranges.keys(), point))
logging.info("Testing {}".format(point_dict))
root_logger.info("Testing {}".format(point_dict))

engine_json = prepare_engines_json(commands=commands, fixed_params=fixed_params)
logging.debug(f"engines.json is prepared:\n{engine_json}")
root_logger.debug(f"engines.json is prepared:\n{engine_json}")
write_engines_json(engine_json, point_dict)
logging.info("Start experiment")
root_logger.info("Start experiment")
now = datetime.now()
out_exp, out_exp_err = run_match(**settings)
later = datetime.now()
difference = (later - now).total_seconds()
logging.info(f"Experiment finished ({difference}s elapsed).")
logging.debug(f"Raw result:\n{out_exp}\n{out_exp_err}")
root_logger.info(f"Experiment finished ({difference}s elapsed).")
root_logger.debug(f"Raw result:\n{out_exp}\n{out_exp_err}")

score, error = parse_experiment_result(out_exp, **settings)
logging.info("Got score: {} +- {}".format(score, error))
logging.info("Updating model")
root_logger.info("Got score: {} +- {}".format(score, error))
root_logger.info("Updating model")
while True:
try:
now = datetime.now()
Expand Down Expand Up @@ -458,10 +458,10 @@ def local( # noqa: C901
)
later = datetime.now()
difference = (later - now).total_seconds()
logging.info(f"GP sampling finished ({difference}s)")
logging.debug(f"GP kernel: {opt.gp.kernel_}")
root_logger.info(f"GP sampling finished ({difference}s)")
root_logger.debug(f"GP kernel: {opt.gp.kernel_}")
except ValueError:
logging.warning(
root_logger.warning(
"Error encountered during fitting. Trying to sample chain a bit. "
"If this problem persists, restart the tuner to reinitialize."
)
Expand Down

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