# AUTOGENERATED FILE! PLEASE DON'T EDIT HERE. EDIT THE SOURCE NOTEBOOKS INSTEAD
from .callbacks import Callback, Callbacks, Cbs
import k1lib, time, math, logging, numpy as np
from functools import partial; plt = k1lib.dep("matplotlib.pyplot")
try: import torch; from torch import nn; hasTorch = True
except: hasTorch = False
__all__ = ["Profiler"]
if hasTorch:
import k1lib.callbacks.profilers as ps
ComputationProfiler = ps.computation.ComputationProfiler
IOProfiler = ps.io.IOProfiler
MemoryProfiler = ps.memory.MemoryProfiler
TimeProfiler = ps.time.TimeProfiler
else:
class ComputationProfiler: pass
class IOProfiler: pass
class MemoryProfiler: pass
class TimeProfiler: pass
[docs]@k1lib.patch(Cbs)
class Profiler(Callback): # Profiler
"""Profiles memory, time, and computational complexity of the network. See over
:mod:`k1lib.callbacks.profilers` for more details on each of these profilers""" # Profiler
def __init__(self): # Profiler
super().__init__(); self.clear(); self.dependsOn=["Recorder"] # Profiler
[docs] def clear(self): # Profiler
"""Clears every child profilers""" # Profiler
self._mpCache=None; self._tpCache=None # Profiler
self._cpCache=None; self._ioCache=None # Profiler
def _memory(self): # do this to quickly debug, cause if not, Callback will just raise AttributeError on .memory # Profiler
if self._mpCache != None: return self._mpCache # Profiler
with self.cbs.context(): # Profiler
mp = MemoryProfiler(); self.cbs.add(mp) # Profiler
mp._run(); self._mpCache = mp; return mp # Profiler
@property # Profiler
def memory(self) -> MemoryProfiler: # Profiler
"""Gets :class:`~k1lib.callbacks.profilers.memory.MemoryProfiler`""" # Profiler
return self._memory() # Profiler
def _computation(self): # Profiler
if self._cpCache != None: return self._cpCache # Profiler
with self.cbs.context(): # Profiler
cp = ComputationProfiler(self); self.cbs.add(cp) # Profiler
cp._run(); self._cpCache = cp; return cp # Profiler
@property # Profiler
def computation(self) -> ComputationProfiler: # Profiler
"""Gets :class:`~k1lib.callbacks.profilers.computation.ComputationProfiler`""" # Profiler
return self._computation() # Profiler
def _time(self): # Profiler
if self._tpCache != None: return self._tpCache # Profiler
with self.cbs.context(): # Profiler
tp = TimeProfiler(); self.cbs.add(tp) # Profiler
tp._run(); self._tpCache = tp; return tp # Profiler
@property # Profiler
def time(self) -> TimeProfiler: # Profiler
"""Gets :class:`~k1lib.callbacks.profilers.time.TimeProfiler`""" # Profiler
return self._time() # Profiler
def _io(self): # Profiler
if self._ioCache != None: return self._ioCache # Profiler
with self.cbs.context(): # Profiler
io = IOProfiler(); self.cbs.add(io) # Profiler
io._run(); self._ioCache = io; return io # Profiler
@property # Profiler
def io(self) -> IOProfiler: # Profiler
"""Gets :class:`~k1lib.callbacks.profilers.io.IOProfiler`""" # Profiler
return self._io() # Profiler
def __repr__(self): # Profiler
return f"""{self._reprHead}, can...
- p.memory: to profile module memory requirements
- p.time: to profile module execution times
- p.computation: to estimate module computation
- p.io: to get input and output shapes of
{self._reprCan}""" # Profiler