def createFromDir(dir):
"""Scan the directory containing a dataset
and create a BenchDataset object from it."""
# Identify the paths where files may be found
input_dir = dir.getChildByName('input')
output_dir = dir.getChildByName('output')
#benchmark_path = path.join(globals.root, 'benchmarks', name)
def check_default_input_files():
# This function is called to see if the input file set
# guessed by scanning the input directory can be used
if invalid_default_input_files:
raise ValueError, "Cannot infer command line when there are multiple input files in a data set\n(Fix by adding an input DESCRIPTION file)"
if input_dir.exists():
input_descr = process.read_description_file(input_dir)
input_files = input_dir.scanAndReturnNames()
# If more than one input file was found, cannot use the default
# input file list produced by scanning the directory
invalid_default_input_files = len(input_files) > 1
else:
# If there's no input directory, assume the benchmark
# takes no input
input_descr = None
input_files = []
invalid_default_input_files = False
# Read the text of the input description file
if input_descr is not None:
(parameters, input_files1, input_descr) = \
unpack_dataset_description(input_descr, input_files=None)
if input_files1 is None:
# No override value given; use the default
check_default_input_files()
else:
input_files = input_files1
else:
check_default_input_files()
parameters = []
# Look for output files
output_descr = process.read_description_file(output_dir)
output_files = output_dir.scanAndReturnNames()
if len(output_files) > 1:
raise ValueError, "Multiple output files not supported"
# Concatenate input and output descriptions
if input_descr and output_descr:
descr = input_descr + "\n\n" + output_descr
else:
descr = input_descr or output_descr
return BenchDataset(dir, input_files, output_files, parameters, descr)
def createFromDir(dir):
"""Scan the directory containing a dataset
and create a BenchDataset object from it."""
# Identify the paths where files may be found
input_dir = dir.getChildByName('input')
output_dir = dir.getChildByName('output')
#benchmark_path = path.join(globals.root, 'benchmarks', name)
def check_default_input_files():
# This function is called to see if the input file set
# guessed by scanning the input directory can be used
if invalid_default_input_files:
raise ValueError, "Cannot infer command line when there are multiple input files in a data set\n(Fix by adding an input DESCRIPTION file)"
if input_dir.exists():
input_descr = process.read_description_file(input_dir)
input_files = input_dir.scanAndReturnNames()
# If more than one input file was found, cannot use the default
# input file list produced by scanning the directory
invalid_default_input_files = len(input_files) > 1
else:
# If there's no input directory, assume the benchmark
# takes no input
input_descr = None
input_files = []
invalid_default_input_files = False
# Read the text of the input description file
if input_descr is not None:
(parameters, input_files1, input_descr) = \
unpack_dataset_description(input_descr, input_files=None)
if input_files1 is None:
# No override value given; use the default
check_default_input_files()
else:
input_files = input_files1
else:
check_default_input_files()
parameters = []
# Look for output files
output_descr = process.read_description_file(output_dir)
output_files = output_dir.scanAndReturnNames()
if len(output_files) > 1:
raise ValueError, "Multiple output files not supported"
# Concatenate input and output descriptions
if input_descr and output_descr:
descr = input_descr + "\n\n" + output_descr
else:
descr = input_descr or output_descr
return BenchDataset(dir, input_files, output_files, parameters, descr)
def createFromDir(dir):
"""Scan the directory containing a benchmark implementation
and create a BenchImpl object from it."""
# Get the description from a file, if provided
descr = process.read_description_file(dir)
return BenchImpl(dir, descr)
def createFromDir(dir):
"""Scan the directory containing a benchmark implementation
and create a BenchImpl object from it."""
# Get the description from a file, if provided
descr = process.read_description_file(dir)
return BenchImpl(dir, descr)
def createFromName(name, impl):
"""Scan the directory containing a benchmark implementation
and create a BenchImpl object from it."""
# Path to the implementation
impl_path = path.join(globals.root, "benchmarks", name, "src", impl)
# Get the description from a file, if provided
descr = process.read_description_file(impl_path)
return BenchImpl(impl, descr)
def createFromName(name, impl):
"""Scan the directory containing a benchmark implementation
and create a BenchImpl object from it."""
# Path to the implementation
impl_path = path.join(globals.root, 'benchmarks', name, 'src', impl)
# Get the description from a file, if provided
descr = process.read_description_file(impl_path)
return BenchImpl(impl, descr)
def createFromName(name):
"""Scan the benchmark directory for the benchmark named 'name'
and create a benchmark object for it."""
bmkpath = path.join(globals.root, "benchmarks", name)
descr = process.read_description_file(bmkpath)
try:
# Scan implementations of the benchmark
impls = [BenchImpl.createFromName(name, impl) for impl in process.scan_for_benchmark_versions(bmkpath)]
# Scan data sets of the benchmark
datas = [BenchDataset.createFromName(name, data) for data in process.scan_for_benchmark_datasets(bmkpath)]
# If no exception occurred, the benchmark is valid
return Benchmark(name, bmkpath, impls, datas, descr)
except Exception, e:
return Benchmark(name, invalid=e)
def createFromName(name):
"""Scan the benchmark directory for the benchmark named 'name'
and create a benchmark object for it."""
bmkdir = globals.benchdir.getChildByName(name)
datadir = globals.datadir.getChildByName(name)
descr = process.read_description_file(bmkdir)
try:
# Scan implementations of the benchmark
impls = [BenchImpl.createFromDir(impl) for impl in process.scan_for_benchmark_versions(bmkdir)]
# Scan data sets of the benchmark
datas = [BenchDataset.createFromDir(data) for data in process.scan_for_benchmark_datasets(datadir)]
# If no exception occurred, the benchmark is valid
return Benchmark(name, bmkdir.getPath(), impls, datas, descr)
finally:
pass
def createFromName(name):
"""Scan the benchmark directory for the benchmark named 'name'
and create a benchmark object for it."""
bmkdir = globals.benchdir.getChildByName(name)
datadir = globals.datadir.getChildByName(name)
descr = process.read_description_file(bmkdir)
try:
# Scan implementations of the benchmark
impls = [BenchImpl.createFromDir(impl)
for impl in process.scan_for_benchmark_versions(bmkdir)]
# Scan data sets of the benchmark
datas = [BenchDataset.createFromDir(data)
for data in process.scan_for_benchmark_datasets(datadir)]
# If no exception occurred, the benchmark is valid
return Benchmark(name, bmkdir.getPath(), impls, datas, descr)
finally:
pass
def createFromName(name):
"""Scan the benchmark directory for the benchmark named 'name'
and create a benchmark object for it."""
bmkpath = path.join(globals.root, 'benchmarks', name)
descr = process.read_description_file(bmkpath)
try:
# Scan implementations of the benchmark
impls = [
BenchImpl.createFromName(name, impl)
for impl in process.scan_for_benchmark_versions(bmkpath)
]
# Scan data sets of the benchmark
datas = [
BenchDataset.createFromName(name, data)
for data in process.scan_for_benchmark_datasets(bmkpath)
]
# If no exception occurred, the benchmark is valid
return Benchmark(name, bmkpath, impls, datas, descr)
except Exception, e:
return Benchmark(name, invalid=e)
def createFromName(name, dset):
"""Scan the directory containing a dataset
and create a BenchDataset object from it."""
# Identify the paths where files may be found
benchmark_path = path.join(globals.root, "benchmarks", name)
if path.exists(path.join(benchmark_path, "input")):
input_path = path.join(benchmark_path, "input", dset)
else:
input_path = None
output_path = path.join(benchmark_path, "output", dset)
# Look for input files
def check_default_input_files():
# This function is called to see if the input file set
# guessed by scanning the input directory can be used
if invalid_default_input_files:
raise ValueError, "Cannot infer command line when there are multiple input files in a data set\n(Fix by adding an input DESCRIPTION file)"
if input_path:
input_descr = process.read_description_file(input_path)
input_files = list(process.scan_for_files(input_path, boring=["DESCRIPTION", ".svn"]))
# If more than one input file was found, cannot use the default
# input file list produced by scanning the directory
invalid_default_input_files = len(input_files) > 1
else:
# If there's no input directory, assume the benchmark
# takes no input
input_descr = None
input_files = []
invalid_default_input_files = False
# Read the text of the input description file
if input_descr is not None:
(parameters, input_files1, input_descr) = unpack_dataset_description(input_descr, input_files=None)
if input_files1 is None:
# No override vaule given; use the default
check_default_input_files()
else:
input_files = input_files1
else:
check_default_input_files()
parameters = []
# Look for output files
output_descr = process.read_description_file(output_path)
output_files = list(process.scan_for_files(output_path, boring=["DESCRIPTION", ".svn"]))
if len(output_files) > 1:
raise ValueError, "Multiple output files not supported"
# Concatenate input and output descriptions
if input_descr and output_descr:
descr = input_descr + "\n\n" + output_descr
else:
descr = input_descr or output_descr
return BenchDataset(dset, input_files, output_files, parameters, descr)
