def report_asv(results_df,
output_dir,
cudaVer="",
pythonVer="",
osType="",
machineName=""):
"""Logs the dataframe `results_df` to airspeed velocity format.
This writes (or appends to) JSON files in `output_dir`
Parameters
----------
results_df : pd.DataFrame
DataFrame with one row per benchmark run
output_dir : str
Directory for ASV output database
"""
import asvdb
import platform
import psutil
uname = platform.uname()
(commitHash, commitTime) = asvdb.utils.getCommitInfo()
b_info = asvdb.BenchmarkInfo(
machineName=machineName or uname.machine,
cudaVer=cudaVer or "unknown",
osType=osType or "%s %s" % (uname.system, uname.release),
pythonVer=pythonVer or platform.python_version(),
commitHash=commitHash,
commitTime=commitTime,
gpuType="unknown",
cpuType=uname.processor,
arch=uname.machine,
ram="%d" % psutil.virtual_memory().total,
)
(
repo,
branch,
) = asvdb.utils.getRepoInfo() # gets repo info from CWD by default
db = asvdb.ASVDb(dbDir=output_dir, repo=repo, branches=[branch])
for index, row in results_df.iterrows():
val_keys = ['cu_time', 'cpu_time', 'speedup', 'cuml_acc', 'cpu_acc']
params = [(k, v) for k, v in row.items() if k not in val_keys]
result = asvdb.BenchmarkResult(row['algo'],
params,
result=row['cu_time'])
db.addResult(b_info, result)
def openAsvdbAtPath(dbDir,
repo=None,
branches=None,
projectName=None,
commitUrl=None):
"""
Either reads the ASV db at dbDir and creates a new db object, or creates a
new db object and sets up the db at dbDir for (presumably) writing new
results to.
"""
db = asvdb.ASVDb(dbDir,
repo=repo,
branches=branches,
projectName=projectName,
commitUrl=commitUrl)
if path.isdir(dbDir):
db.loadConfFile()
else:
db.updateConfFile()
return db