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# Copyright (c) 2021 The Regents of The University of California
# All rights reserved.
#
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# modification, are permitted provided that the following conditions are
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# redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
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# neither the name of the copyright holders nor the names of its
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# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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"""
This serves as the bridge between the gem5 statistics exposed via PyBind11 and
the Python Stats model.
"""
from datetime import datetime
from typing import IO, List, Union
import _m5.stats
from m5.objects import *
from m5.ext.pystats.group import *
from m5.ext.pystats.simstat import *
from m5.ext.pystats.statistic import *
from m5.ext.pystats.storagetype import *
class JsonOutputVistor:
"""
This is a helper vistor class used to include a JSON output via the stats
API (`src/python/m5/stats/__init__.py`).
"""
file: str
json_args: Dict
def __init__(self, file: str, **kwargs):
"""
Parameters
----------
file: str
The output file location in which the JSON will be dumped.
kwargs: Dict[str, Any]
Additional parameters to be passed to the `json.dumps` method.
"""
self.file = file
self.json_args = kwargs
def dump(self, roots: Union[List[SimObject], Root]) -> None:
"""
Dumps the stats of a simulation root (or list of roots) to the output
JSON file specified in the JsonOutput constructor.
WARNING: This dump assumes the statistics have already been prepared
for the target root.
Parameters
----------
roots: Union[List[Root], Root]]
The Root, or List of roots, whose stats are are to be dumped JSON.
"""
with open(self.file, "w") as fp:
simstat = get_simstat(root=roots, prepare_stats=False)
simstat.dump(fp=fp, **self.json_args)
def get_stats_group(group: _m5.stats.Group) -> Group:
"""
Translates a gem5 Group object into a Python stats Group object. A Python
statistic Group object is a dictionary of labeled Statistic objects. Any
gem5 object passed to this will have its `getStats()` and `getStatGroups`
function called, and all the stats translated (inclusive of the stats
further down the hierarchy).
Parameters
----------
group: _m5.stats.Group
The gem5 _m5.stats.Group object to be translated to be a Python stats
Group object. Typically this will be a gem5 SimObject.
Returns
-------
Group
The stats group object translated from the input gem5 object.
"""
stats_dict = {}
for stat in group.getStats():
statistic = __get_statistic(stat)
if statistic is not None:
stats_dict[stat.name] = statistic
for key in group.getStatGroups():
stats_dict[key] = get_stats_group(group.getStatGroups()[key])
return Group(**stats_dict)
def __get_statistic(statistic: _m5.stats.Info) -> Optional[Statistic]:
"""
Translates a _m5.stats.Info object into a Statistic object, to process
statistics at the Python level.
Parameters
----------
statistic: Info
The Info object to be translated to a Statistic object.
Returns
-------
Optional[Statistic]
The Statistic object of the Info object. Returns None if Info object
cannot be translated.
"""
assert isinstance(statistic, _m5.stats.Info)
statistic.prepare()
if isinstance(statistic, _m5.stats.ScalarInfo):
return __get_scaler(statistic)
elif isinstance(statistic, _m5.stats.DistInfo):
return __get_distribution(statistic)
elif isinstance(statistic, _m5.stats.FormulaInfo):
# We don't do anything with Formula's right now.
# We may never do so, see https://gem5.atlassian.net/browse/GEM5-868.
pass
elif isinstance(statistic, _m5.stats.VectorInfo):
return __get_vector(statistic)
return None
def __get_scaler(statistic: _m5.stats.ScalarInfo) -> Scalar:
value = statistic.value
unit = statistic.unit
description = statistic.desc
# ScalarInfo uses the C++ `double`.
datatype = StorageType["f64"]
return Scalar(
value=value, unit=unit, description=description, datatype=datatype
)
def __get_distribution(statistic: _m5.stats.DistInfo) -> Distribution:
unit = statistic.unit
description = statistic.desc
value = statistic.values
bin_size = statistic.bucket_size
min = statistic.min_val
max = statistic.max_val
num_bins = len(value)
sum_val = statistic.sum
sum_squared = statistic.squares
underflow = statistic.underflow
overflow = statistic.overflow
logs = statistic.logs
# DistInfo uses the C++ `double`.
datatype = StorageType["f64"]
return Distribution(
value=value,
min=min,
max=max,
num_bins=num_bins,
bin_size=bin_size,
sum=sum_val,
sum_squared=sum_squared,
underflow=underflow,
overflow=overflow,
logs=logs,
unit=unit,
description=description,
datatype=datatype,
)
def __get_vector(statistic: _m5.stats.VectorInfo) -> Vector:
to_add = dict()
for index in range(statistic.size):
# All the values in a Vector are Scalar values
value = statistic.value[index]
unit = statistic.unit
description = statistic.subdescs[index]
# ScalarInfo uses the C++ `double`.
datatype = StorageType["f64"]
# Sometimes elements within a vector are defined by their name. Other
# times they have no name. When a name is not available, we name the
# stat the index value.
if str(statistic.subnames[index]):
index_string = str(statistic.subnames[index])
else:
index_string = str(index)
to_add[index_string] = Scalar(
value=value, unit=unit, description=description, datatype=datatype
)
return Vector(scalar_map=to_add)
def _prepare_stats(group: _m5.stats.Group):
"""
Prepares the statistics for dumping.
"""
group.preDumpStats()
for stat in group.getStats():
stat.prepare()
for child in group.getStatGroups().values():
_prepare_stats(child)
def get_simstat(
root: Union[SimObject, List[SimObject]], prepare_stats: bool = True
) -> SimStat:
"""
This function will return the SimStat object for a simulation given a
SimObject (typically a Root SimObject), or list of SimObjects. The returned
SimStat object will contain all the stats for all the SimObjects contained
within the "root", inclusive of the "root" SimObject/SimObjects.
Parameters
----------
root: Union[SimObject, List[SimObject]]
A SimObject, or list of SimObjects, of the simulation for translation
into a SimStat object. Typically this is the simulation's Root
SimObject as this will obtain the entirety of a run's statistics in a
single SimStat object.
prepare_stats: bool
Dictates whether the stats are to be prepared prior to creating the
SimStat object. By default this is 'True'.
Returns
-------
SimStat
The SimStat Object of the current simulation.
"""
stats_map = {}
creation_time = datetime.now()
time_converstion = None # TODO https://gem5.atlassian.net/browse/GEM5-846
final_tick = Root.getInstance().resolveStat("finalTick").value
sim_ticks = Root.getInstance().resolveStat("simTicks").value
simulated_begin_time = int(final_tick - sim_ticks)
simulated_end_time = int(final_tick)
if prepare_stats:
_m5.stats.processDumpQueue()
for r in root:
if isinstance(r, Root):
# The Root is a special case, we jump directly into adding its
# constituent Groups.
if prepare_stats:
_prepare_stats(r)
for key in r.getStatGroups():
stats_map[key] = get_stats_group(r.getStatGroups()[key])
elif isinstance(r, SimObject):
if prepare_stats:
_prepare_stats(r)
stats_map[r.get_name()] = get_stats_group(r)
else:
raise TypeError(
"Object (" + str(r) + ") passed is not a "
"SimObject. " + __name__ + " only processes "
"SimObjects, or a list of SimObjects."
)
return SimStat(
creation_time=creation_time,
time_conversion=time_converstion,
simulated_begin_time=simulated_begin_time,
simulated_end_time=simulated_end_time,
**stats_map,
)