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base-stats,python: Add Python Stats

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This model is used to store and represent the "new" hierarchical stats
at the Python level. Over time these classes may be extended with
functions to ease in the analysis of gem5 stats. Though, for this
commit, such functions have been kept to a minimum.

`m5/pystats/loader.py` contains functions for translating the gem5  `_m5.stats`
statistics exposed via Pybind11 to the Python Stats model. For example:

```
import m5.pystats.gem5stats as gem5stats

simstat = gem5stats.get_simstat(root)
```

All the python Stats model classes inherit from JsonSerializable meaning
they can be translated to JSON. For example:

```
import m5.pystats.gem5stats as gem5stats

simstat = gem5stats.get_simstat(root)
with open('test.json', 'w') as f:
    simstat.dump(f)
```

The stats have also been exposed via the python statistics API. Via
command line, a JSON output may be specified with the argument
`--stats-file json://<file path>`.

Change-Id: I253a869f6b6d8c0de4dbed708892ee0cc33c5665
Reviewed-on: https://gem5-review.googlesource.com/c/public/gem5/+/38615
Reviewed-by: Jason Lowe-Power <power.jg@gmail.com>
Reviewed-by: Andreas Sandberg <andreas.sandberg@arm.com>
Maintainer: Jason Lowe-Power <power.jg@gmail.com>
Tested-by: kokoro <noreply+kokoro@google.com>
This commit is contained in:
Bobby R. Bruce
2021-01-17 20:52:31 -08:00
parent bd6e1fc9c5
commit f11617736e
10 changed files with 945 additions and 4 deletions
Download Patch File Download Diff File Expand all files Collapse all files

26
src/python/m5/stats/__init__.py
View File

@@ -42,6 +42,7 @@ import m5
import _m5.stats
from m5.objects import Root
from m5.params import isNullPointer
from .gem5stats import JsonOutputVistor
from m5.util import attrdict, fatal
# Stat exports
@@ -182,6 +183,17 @@ def _hdf5Factory(fn, chunking=10, desc=True, formulas=True):
return _m5.stats.initHDF5(fn, chunking, desc, formulas)
@_url_factory(["json"])
def _jsonFactory(fn):
"""Output stats in JSON format.
Example:
json://stats.json
"""
return JsonOutputVistor(fn)
def addStatVisitor(url):
"""Add a stat visitor specified using a URL string
@@ -383,10 +395,16 @@ def dump(roots=None):
prepare()
for output in outputList:
if output.valid():
output.begin()
_dump_to_visitor(output, roots=all_roots)
output.end()
if isinstance(output, JsonOutputVistor):
if not all_roots:
output.dump(Root.getInstance())
else:
output.dump(all_roots)
else:
if output.valid():
output.begin()
_dump_to_visitor(output, roots=all_roots)
output.end()
def reset():
'''Reset all statistics to the base state'''

294
src/python/m5/stats/gem5stats.py Normal file
View File

@@ -0,0 +1,294 @@
# Copyright (c) 2021 The Regents of The University of California
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met: redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer;
# redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution;
# neither the name of the copyright holders nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
"""
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 = None # TODO https://gem5.atlassian.net/browse/GEM5-850.
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 = None # TODO https://gem5.atlassian.net/browse/GEM5-850.
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 = None # TODO https://gem5.atlassian.net/browse/GEM5-850.
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 getStatGroups().values():
_prepare_stats(child)
def get_simstat(root: Union[Root, List[SimObject]],
prepare_stats: bool = True) -> SimStat:
"""
This function will return the SimStat object for a simulation. From the
SimStat object all stats within the current gem5 simulation are present.
Parameters
----------
root: Union[Root, List[Root]]
The root, or a list of Simobjects, of the simulation for translation to
a 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):
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.name] = get_stats_group(r)
else:
raise TypeError("Object (" + str(r) + ") passed is neither Root "
"nor SimObject. " + __name__ + " only processes "
"Roots, SimObjects, or a list of Roots and/or "
"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,
)