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Merge pull request 'cap_core' (#29) from cap_core into master
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Reviewed-on: #29
This commit is contained in:
Deepak Mallubhotla
2023-04-14 01:24:01 +00:00
parent 959b9af378 1cf4454153
commit c4b6cbbb6f
2 changed files with 14 additions and 2 deletions
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8
deepdog/real_spectrum_run.py
View File

@@ -88,6 +88,7 @@ class RealSpectrumRun:
chunksize: int = CHUNKSIZE, chunksize: int = CHUNKSIZE,
initial_seed: int = 12345, initial_seed: int = 12345,
use_fast_filter: bool = True, use_fast_filter: bool = True,
cap_core_count: int = 0,
) -> None: ) -> None:
self.measurements = measurements self.measurements = measurements
self.dot_inputs = [(measure.r, measure.f) for measure in self.measurements] self.dot_inputs = [(measure.r, measure.f) for measure in self.measurements]
@@ -123,6 +124,8 @@ class RealSpectrumRun:
self.filename = f"{timestamp}-{filename_slug}.realdata.{ff_string}.bayesrun.csv" self.filename = f"{timestamp}-{filename_slug}.realdata.{ff_string}.bayesrun.csv"
self.initial_seed = initial_seed self.initial_seed = initial_seed
self.cap_core_count = cap_core_count
def go(self) -> None: def go(self) -> None:
with open(self.filename, "a", newline="") as outfile: with open(self.filename, "a", newline="") as outfile:
writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect="unix") writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect="unix")
@@ -140,11 +143,14 @@ class RealSpectrumRun:
results = [] results = []
_logger.debug("Going to iterate over models now") _logger.debug("Going to iterate over models now")
core_count = multiprocessing.cpu_count() - 1 or 1
if (self.cap_core_count >= 1) and (self.cap_core_count < core_count):
core_count = self.cap_core_count
_logger.info(f"Using {core_count} cores")
for model_count, (model, model_name) in enumerate( for model_count, (model, model_name) in enumerate(
zip(self.models, self.model_names) zip(self.models, self.model_names)
): ):
_logger.debug(f"Doing model #{model_count}: {model_name}") _logger.debug(f"Doing model #{model_count}: {model_name}")
core_count = multiprocessing.cpu_count() - 1 or 1
with multiprocessing.Pool(core_count) as pool: with multiprocessing.Pool(core_count) as pool:
cycle_count = 0 cycle_count = 0
cycle_success = 0 cycle_success = 0

8
deepdog/temp_aware_real_spectrum_run.py
View File

@@ -90,6 +90,7 @@ class TempAwareRealSpectrumRun:
max_monte_carlo_cycles_steps: int = 10, max_monte_carlo_cycles_steps: int = 10,
chunksize: int = CHUNKSIZE, chunksize: int = CHUNKSIZE,
initial_seed: int = 12345, initial_seed: int = 12345,
cap_core_count: int = 0,
) -> None: ) -> None:
self.measurements_dict = measurements_dict self.measurements_dict = measurements_dict
self.dot_inputs_dict = { self.dot_inputs_dict = {
@@ -126,6 +127,8 @@ class TempAwareRealSpectrumRun:
self.filename = f"{timestamp}-{filename_slug}.realdata.{ff_string}.bayesrun.csv" self.filename = f"{timestamp}-{filename_slug}.realdata.{ff_string}.bayesrun.csv"
self.initial_seed = initial_seed self.initial_seed = initial_seed
self.cap_core_count = cap_core_count
def go(self) -> None: def go(self) -> None:
with open(self.filename, "a", newline="") as outfile: with open(self.filename, "a", newline="") as outfile:
writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect="unix") writer = csv.DictWriter(outfile, fieldnames=self.csv_fields, dialect="unix")
@@ -146,11 +149,14 @@ class TempAwareRealSpectrumRun:
results = [] results = []
_logger.debug("Going to iterate over models now") _logger.debug("Going to iterate over models now")
core_count = multiprocessing.cpu_count() - 1 or 1
if (self.cap_core_count >= 1) and (self.cap_core_count < core_count):
core_count = self.cap_core_count
_logger.info(f"Using {core_count} cores")
for model_count, (model, model_name) in enumerate( for model_count, (model, model_name) in enumerate(
zip(self.models, self.model_names) zip(self.models, self.model_names)
): ):
_logger.debug(f"Doing model #{model_count}: {model_name}") _logger.debug(f"Doing model #{model_count}: {model_name}")
core_count = multiprocessing.cpu_count() - 1 or 1
with multiprocessing.Pool(core_count) as pool: with multiprocessing.Pool(core_count) as pool:
cycle_count = 0 cycle_count = 0
cycle_success = 0 cycle_success = 0