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提交 d5ff2b48 authored 作者: Arnaud Bergeron's avatar Arnaud Bergeron
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Partial flake8 for compile/profiling.py

The 'unported' code near the end is full or errors and I don't feel like correcting all of it
上级 843b6249
隐藏空白字符变更
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正在显示 包含 134 行增加 和 119 行删除
theano/compile/profiling.py
浏览文件 @ d5ff2b48
......@@ -240,7 +240,6 @@ class ProfileStats(object):
else:
self.flag_time_thunks = flag_time_thunks
self.__dict__.update(kwargs)
#print >> sys.stderr, "self.message", self.message
if atexit_print:
global _atexit_print_list
_atexit_print_list.append(self)
......@@ -358,7 +357,7 @@ class ProfileStats(object):
local_time = 0
if local_time == 0:
print(('ProfileMode.summary_class: total time 0'
' (did you forget to enable counters?)'), file=file)
' (did you forget to enable counters?)'), file=file)
return
class_time = self.class_time()
class_call = self.class_callcount()
......@@ -377,9 +376,6 @@ class ProfileStats(object):
tot = 0
print('Class', file=file)
print('---', file=file)
#print >> file, '<% time> <cumulative %%> <apply time>,'
#print >>file, '<cumulative seconds> <time per call> <nb_call>'
#print >>file, '<Class name>'
hs = []
# formatting string
es = []
......@@ -421,18 +417,21 @@ class ProfileStats(object):
tot += t
ftot = tot * 100 / local_time
# Remove the useless start and end of the class name:
# "<class 'theano.sandbox.cuda.blas.GpuDot22'>" -> "theano.sandbox.cuda.blas.GpuDot22"
# "<class 'theano.sandbox.cuda.blas.GpuDot22'>" ->
# "theano.sandbox.cuda.blas.GpuDot22"
class_name = str(a)[8:-2][:maxlen]
print(format_str % (f, ftot, t, t / nb_call,
impl, nb_call,
nb_apply, class_name), file=file)
impl, nb_call,
nb_apply, class_name), file=file)
# While this carries over less information, it is arranged such
# that it way more readeable that the previous output of the
# profiler
print(' ... (remaining %i Classes account for %6.2f%%(%.2fs) of the runtime)'\
% (max(0, len(otimes) - N),
print(' ... (remaining %i Classes account for %6.2f%%(%.2fs) of '
'the runtime)' %
(max(0, len(otimes) - N),
sum(f for f, t, a, ci, nb_call, nb_op in otimes[N:]),
sum(t for f, t, a, ci, nb_call, nb_op in otimes[N:])), file=file)
sum(t for f, t, a, ci, nb_call, nb_op in otimes[N:])),
file=file)
print('', file=file)
def summary_ops(self, file=sys.stderr, N=None):
......@@ -442,7 +441,7 @@ class ProfileStats(object):
local_time = 0
if local_time == 0:
print(('ProfileMode.summary_ops: total time 0'
' (did you forget to enable counters?)'), file=file)
' (did you forget to enable counters?)'), file=file)
return
op_time = self.op_time()
op_call = self.op_callcount()
......@@ -459,9 +458,6 @@ class ProfileStats(object):
tot = 0
print('Ops', file=file)
print('---', file=file)
#print >> file, '<% time> <cumulative %%> <apply time>,'
#print >>file, '<cumulative seconds> <time per call> <nb_call>'
#print >>file, '<Op name>'
hs = []
# formatting string
es = []
......@@ -503,15 +499,17 @@ class ProfileStats(object):
tot += t
ftot = tot * 100 / local_time
print(format_str % (f, ftot, t, t / nb_call,
impl, nb_call,
nb_apply, str(a)[:maxlen]), file=file)
impl, nb_call,
nb_apply, str(a)[:maxlen]), file=file)
# While this carries over less information, it is arranged such
# that it way more readeable that the previous output of the
# profiler
print(' ... (remaining %i Ops account for %6.2f%%(%.2fs) of the runtime)'\
% (max(0, len(otimes) - N),
print(' ... (remaining %i Ops account for %6.2f%%(%.2fs) of '
'the runtime)' %
(max(0, len(otimes) - N),
sum(f for f, t, a, ci, nb_call, nb_op in otimes[N:]),
sum(t for f, t, a, ci, nb_call, nb_op in otimes[N:])), file=file)
sum(t for f, t, a, ci, nb_call, nb_op in otimes[N:])),
file=file)
print('', file=file)
def summary_nodes(self, file=sys.stderr, N=None):
......@@ -521,12 +519,11 @@ class ProfileStats(object):
local_time = 0
if local_time == 0:
print(('ProfileMode.summary_nodes: total time 0'
' (did you forget to enable counters?)'), file=file)
' (did you forget to enable counters?)'), file=file)
return
print('Apply', file=file)
print('------', file=file)
#print >> file, '<% time> <cumulative %%> <apply time> <cumulative seconds> <time per call> <nb_call> <Apply Op name>'
# headers
hs = []
# formatting string
......@@ -601,9 +598,9 @@ class ProfileStats(object):
flops = " "
flops_s = " "
print(format_str % (f, ftot, t, t / nb_call, nb_call,
nd_id,
flops, flops_s,
str(a)[:maxlen]), file=file)
nd_id,
flops, flops_s,
str(a)[:maxlen]), file=file)
if not config.profile_memory:
continue
for idx, var in enumerate(a.inputs):
......@@ -620,10 +617,9 @@ class ProfileStats(object):
idx, dtype, sh, st), file=file)
# Same as before, this I've sacrificied some information making
# the output more readable
# print >> file, ' %4.1f%% %5.1f%% %5.3fs %5.3fs %.2es %i %s'%(
# f, ftot, t, tot, t/nb_call,nb_call, str(a))
print(' ... (remaining %i Apply instances account for %.2f%%(%.2fs) of the runtime)'\
% (max(0, len(atimes) - N),
print(' ... (remaining %i Apply instances account for '
'%.2f%%(%.2fs) of the runtime)' %
(max(0, len(atimes) - N),
sum(f for f, t, a, nd_id, nb_call in atimes[N:]),
sum(t for f, t, a, nd_id, nb_call in atimes[N:])), file=file)
print('', file=file)
......@@ -640,15 +636,17 @@ class ProfileStats(object):
100 * self.vm_call_time / self.fct_call_time), file=file)
local_time = sum(self.apply_time.values())
if local_time > 0:
print(' Time in thunks: %es (%.3f%%)' % (
local_time, 100 * local_time / self.fct_call_time), file=file)
print(' Time in thunks: %es (%.3f%%)' %
(local_time, 100 * local_time / self.fct_call_time),
file=file)
print(' Total compile time: %es' % self.compile_time, file=file)
print(' Number of Apply nodes: %d' % self.nb_nodes, file=file)
print(' Theano Optimizer time: %es' % self.optimizer_time, file=file)
print(' Theano validate time: %es' % self.validate_time, file=file)
print((' Theano Linker time (includes C,'
' CUDA code generation/compiling): %es' %
self.linker_time), file=file)
print(' Theano Optimizer time: %es' % self.optimizer_time,
file=file)
print(' Theano validate time: %es' % self.validate_time,
file=file)
print(' Theano Linker time (includes C, CUDA code '
'generation/compiling): %es' % self.linker_time, file=file)
print(' Import time %es' % self.import_time, file=file)
print('', file=file)
......@@ -656,7 +654,8 @@ class ProfileStats(object):
assert self.validate_time < self.optimizer_time
def summary_globals(self, file):
print('Time in all call to theano.grad() %es' % theano.gradient.grad_time, file=file)
print('Time in all call to theano.grad() %es' %
theano.gradient.grad_time, file=file)
def summary_memory(self, file, N=None):
fct_memory = {} # fgraph->dict(node->[outputs size])
......@@ -742,7 +741,8 @@ class ProfileStats(object):
# two data structure used to mimic Python gc
viewed_by = {} # {var1: [vars that view var1]}
# The len of the list is the value of python ref count. But we use a list, not just the ref count value.
# The len of the list is the value of python ref
# count. But we use a list, not just the ref count value.
# This is more safe to help detect potential bug in the algo
for var in fgraph.variables:
viewed_by[var] = []
......@@ -778,14 +778,16 @@ class ProfileStats(object):
ins = None
if dmap and idx2 in dmap:
vidx = dmap[idx2]
assert len(
vidx) == 1, "Here we only support the possibility to destroy one input"
assert len(vidx) == 1, ("Here we only support the "
"possibility to destroy one "
"input")
ins = node.inputs[vidx[0]]
if vmap and idx2 in vmap:
assert ins is None
vidx = vmap[idx2]
assert len(
vidx) == 1, "Here we only support the possibility to view one input"
assert len(vidx) == 1, ("Here we only support the "
"possibility to view one "
"input")
ins = node.inputs[vidx[0]]
if ins is not None:
# This is needed for destroy_map in case it
......@@ -818,7 +820,8 @@ class ProfileStats(object):
if (dependencies[ins] and
ins not in fgraph.outputs and
ins.owner and
all([compute_map[v][0] for v in dependencies[ins]])):
all([compute_map[v][0]
for v in dependencies[ins]])):
if ins not in view_of and not viewed_by.get(ins, []):
running_memory_size[cg] -= var_mem[ins]
elif ins in view_of:
......@@ -907,22 +910,24 @@ class ProfileStats(object):
ins = None
if dmap and idx in dmap:
vidx = dmap[idx]
assert len(
vidx) == 1, "Here we only support the possibility to destroy one input"
assert len(vidx) == 1, ("Here we only support "
"the possibility to "
"destroy one input")
ins = node.inputs[vidx[0]]
if vmap and idx in vmap:
assert ins is None
vidx = vmap[idx]
assert len(
vidx) == 1, "Here we only support the possibility to destroy one input"
assert len(vidx) == 1, ("Here we only support "
"the possibility to "
"view one input")
ins = node.inputs[vidx[0]]
if ins is not None:
# This is needed for destroy_map in case it
# return a partial view that is destroyed. So
# return a partial view that is destroyed. So
# the output could be different then the
# input.
assert isinstance(ins, theano.Variable)
# We keep trac of view only again the original
# We keep track of view only again the original
origin = view_of.get(ins, ins)
view_of[out] = origin
viewof_change.append(out)
......@@ -944,8 +949,10 @@ class ProfileStats(object):
if (dependencies[ins] and
ins not in fgraph.outputs and
ins.owner and
all([compute_map[v][0] for v in dependencies[ins]])):
if ins not in view_of and not viewed_by.get(ins, []):
all([compute_map[v][0]
for v in dependencies[ins]])):
if (ins not in view_of and
not viewed_by.get(ins, [])):
mem_freed += var_mem[ins]
elif ins in view_of:
origin = view_of[ins]
......@@ -953,7 +960,8 @@ class ProfileStats(object):
viewedby_remove[origin].append(ins)
if (not viewed_by[origin] and
origin not in fgraph.inputs and
not isinstance(origin, theano.Constant)):
not isinstance(origin,
theano.Constant)):
mem_freed += var_mem[origin]
else:
# ins is viewed_by something else, so its
......@@ -964,7 +972,8 @@ class ProfileStats(object):
done_set.add(node)
frozen_set = frozenset(done_set)
if done_dict.get(frozen_set, max_mem_count + 1) > max_mem_count:
if (done_dict.get(frozen_set, max_mem_count + 1) >
max_mem_count):
# check if frozen_set is in done_set
# no, add it to done_set
# yes, then compare the past mem and current mem
......@@ -1008,7 +1017,8 @@ class ProfileStats(object):
# two data structure used to mimic Python gc
viewed_by = {} # {var1: [vars that view var1]}
# The len of the list is the value of python ref count. But we use a list, not just the ref count value.
# The len of the list is the value of python ref
# count. But we use a list, not just the ref count value.
# This is more safe to help detect potential bug in the algo
for var in fgraph.variables:
viewed_by[var] = []
......@@ -1043,44 +1053,48 @@ class ProfileStats(object):
max_sum_size = max(max_sum_size, sum_size)
max_node_memory_size[0] = max(max_node_memory_size[0],
sum(old_running_memory[0]))
max_running_max_memory_size[0] = max(max_running_max_memory_size[0],
sum(old_running_memory[2]))
max_running_max_memory_size[0] = \
max(max_running_max_memory_size[0], sum(old_running_memory[2]))
# Separate CPU and GPU
max_node_memory_size[1] = max(max_node_memory_size[1],
old_running_memory[0][0])
max_node_memory_size[2] = max(max_node_memory_size[2],
old_running_memory[0][1])
max_running_max_memory_size[1] = max(max_running_max_memory_size[1],
old_running_memory[2][0])
max_running_max_memory_size[2] = max(max_running_max_memory_size[2],
old_running_memory[2][1])
max_running_max_memory_size[1] = \
max(max_running_max_memory_size[1], old_running_memory[2][0])
max_running_max_memory_size[2] = \
max(max_running_max_memory_size[2], old_running_memory[2][1])
max_node_memory_saved_by_inplace = max(
max_node_memory_saved_by_inplace, old_running_memory[3])
max_node_memory_saved_by_inplace = \
max(max_node_memory_saved_by_inplace, old_running_memory[3])
max_node_memory_saved_by_view = max(max_node_memory_saved_by_view,
old_running_memory[4])
# Store max of some stats with new order
new_max_node_memory_size[0] = max(new_max_node_memory_size[0],
sum(new_running_memory[0]))
new_max_running_max_memory_size[0] = max(new_max_running_max_memory_size[0],
sum(new_running_memory[2]))
new_max_running_max_memory_size[0] = \
max(new_max_running_max_memory_size[0],
sum(new_running_memory[2]))
# Separate CPU and GPU
new_max_node_memory_size[1] = max(new_max_node_memory_size[1],
new_running_memory[0][0])
new_max_node_memory_size[2] = max(new_max_node_memory_size[2],
new_running_memory[0][1])
new_max_running_max_memory_size[1] = max(new_max_running_max_memory_size[1],
new_running_memory[2][0])
new_max_running_max_memory_size[2] = max(new_max_running_max_memory_size[2],
new_running_memory[2][1])
new_max_node_memory_saved_by_inplace = max(
new_max_node_memory_saved_by_inplace, new_running_memory[3])
new_max_node_memory_saved_by_view = max(new_max_node_memory_saved_by_view,
new_running_memory[4])
new_max_running_max_memory_size[1] = \
max(new_max_running_max_memory_size[1],
new_running_memory[2][0])
new_max_running_max_memory_size[2] = \
max(new_max_running_max_memory_size[2],
new_running_memory[2][1])
new_max_node_memory_saved_by_inplace = \
max(new_max_node_memory_saved_by_inplace,
new_running_memory[3])
new_max_node_memory_saved_by_view = \
max(new_max_node_memory_saved_by_view, new_running_memory[4])
# Config: whether print min memory peak
if config.profiling.min_peak_memory:
......@@ -1093,8 +1107,8 @@ class ProfileStats(object):
del fgraph, nodes_mem
if len(fct_memory) > 1:
print(("Memory Profile "
"(the max between all functions in that profile)"), file=file)
print("Memory Profile (the max between all functions in "
"that profile)", file=file)
else:
print("Memory Profile", file=file)
......@@ -1129,17 +1143,21 @@ class ProfileStats(object):
print("---", file=file)
if min_max_peak:
print(" Minimum peak from all valid apply node order is %dKB(took %.3fs to compute)" % (int(round(
min_max_peak / 1024.)), min_peak_time), file=file)
print(" Memory saved if views are used: %dKB (%dKB)" % (int(
round(new_max_node_memory_saved_by_view / 1024.)), int(
round(max_node_memory_saved_by_view / 1024.))), file=file)
print(" Memory saved if inplace ops are used: %dKB (%dKB)" % \
(int(round(new_max_node_memory_saved_by_inplace / 1024.)),
int(round(max_node_memory_saved_by_inplace / 1024.))), file=file)
print(" Memory saved if gc is enabled: %dKB (%dKB)" % (int(
round(new_max_node_memory_size[0] - new_max_running_max_memory_size[0]) / 1024.), int(
round(max_node_memory_size[0] - max_running_max_memory_size[0]) / 1024.)), file=file)
print(" Minimum peak from all valid apply node order is "
"%dKB(took %.3fs to compute)" %
(int(round(min_max_peak / 1024.)), min_peak_time), file=file)
print(" Memory saved if views are used: %dKB (%dKB)" %
(int(round(new_max_node_memory_saved_by_view / 1024.)),
int(round(max_node_memory_saved_by_view / 1024.))), file=file)
print(" Memory saved if inplace ops are used: %dKB (%dKB)" %
(int(round(new_max_node_memory_saved_by_inplace / 1024.)),
int(round(max_node_memory_saved_by_inplace / 1024.))),
file=file)
print(" Memory saved if gc is enabled: %dKB (%dKB)" %
(int(round(new_max_node_memory_size[0] -
new_max_running_max_memory_size[0]) / 1024.),
int(round(max_node_memory_size[0] -
max_running_max_memory_size[0]) / 1024.)), file=file)
print("---", file=file)
......@@ -1148,19 +1166,19 @@ class ProfileStats(object):
hasattr(theano.sandbox.cuda, 'cuda_ndarray') and
hasattr(theano.sandbox.cuda.cuda_ndarray.cuda_ndarray,
'theano_allocated')):
_, gpu_max = theano.sandbox.cuda.cuda_ndarray.cuda_ndarray.theano_allocated()
print((" Max Memory allocated on the GPU "
"(for all functions): %dKB" %
int(round(gpu_max / 1024.))), file=file)
cuda_ndarray = theano.sandbox.cuda.cuda_ndarray.cuda_ndarray
_, gpu_max = cuda_ndarray.theano_allocated()
print(" Max Memory allocated on the GPU (for all functions): "
"%dKB" % int(round(gpu_max / 1024.)), file=file)
print("", file=file)
if len(fct_memory) > 1:
print((
" This list is based on all functions in the profile"), file=file)
print((" <Sum apply outputs (bytes)>"
" <Apply outputs shape>"
" <created/inplace/view>"
" <Apply node>"), file=file)
print(" This list is based on all functions in the profile",
file=file)
print(" <Sum apply outputs (bytes)>"
" <Apply outputs shape>"
" <created/inplace/view>"
" <Apply node>", file=file)
print("", file=file)
items = node_mem.items()
items.sort(key=lambda a: a[1], reverse=True)
......@@ -1181,9 +1199,8 @@ class ProfileStats(object):
else:
size = "%10s" % "Unknown"
print(' %s %s %s %s' % (size,
shapes,
' '.join(code), node), file=file)
print(' %s %s %s %s' % (size, shapes, ' '.join(code), node),
file=file)
sum_remaining = sum(size for _, size in items[N:])
size_sum_dense = sum(node_mem.values())
......@@ -1191,23 +1208,21 @@ class ProfileStats(object):
p = "0%"
else:
p = "(%.2f%%)" % (float(sum_remaining) / size_sum_dense * 100)
print((
' ... (remaining %i Apply account for %4dB/%dB (%s) of the'
' Apply with dense outputs sizes)') % (max(0, len(node_mem) - N),
sum_remaining,
size_sum_dense, p
), file=file)
print(' ... (remaining %i Apply account for %4dB/%dB (%s) of the'
' Apply with dense outputs sizes)' % (max(0, len(node_mem) - N),
sum_remaining,
size_sum_dense, p),
file=file)
print('', file=file)
if N == 0:
print((' All Apply nodes have output sizes that take'
' less than %dB.' %
config.profiling.min_memory_size), file=file)
print((
" <created/inplace/view> is taken from the Op's declaration."), file=file)
print((" Apply nodes marked 'inplace' or 'view' may"
" actually allocate memory, this is not reported"
" here. If you use DebugMode, warnings will be"
" emitted in those cases."), file=file)
print(' All Apply nodes have output sizes that take less '
'than %dB.' % config.profiling.min_memory_size, file=file)
print(" <created/inplace/view> is taken from the Op's declaration.",
file=file)
print(" Apply nodes marked 'inplace' or 'view' may"
" actually allocate memory, this is not reported"
" here. If you use DebugMode, warnings will be"
" emitted in those cases.", file=file)
print('', file=file)
def summary(self, file=sys.stderr, n_ops_to_print=20,
......@@ -1220,8 +1235,8 @@ class ProfileStats(object):
self.summary_ops(file, n_ops_to_print)
self.summary_nodes(file, n_apply_to_print)
elif self.fct_callcount > 0:
print((" No execution time accumulated "
"(hint: try config profiling.time_thunks=1)"), file=file)
print(" No execution time accumulated "
"(hint: try config profiling.time_thunks=1)", file=file)
if self.variable_shape or self.variable_strides:
self.summary_memory(file, n_apply_to_print)
if self.optimizer_profile:
......@@ -1231,7 +1246,7 @@ class ProfileStats(object):
self.optimizer_profile[1])
if 0: # old code still to be ported from ProfileMode
if False: # old code still to be ported from ProfileMode
def long_print(self, file=sys.stderr, fct_name=None, message=None,
n_apply_to_print=15, n_ops_to_print=20, print_apply=False):
"""
......@@ -1565,8 +1580,8 @@ class ScanProfileStats(ProfileStats):
print(' Message: %s' % self.message, file=file)
print((' Time in %i calls of the op (for a total of %i '
'steps) %es' %
(self.callcount, self.nbsteps, self.call_time)), file=file)
'steps) %es' %
(self.callcount, self.nbsteps, self.call_time)), file=file)
print('', file=file)
val = 0
if self.call_time > 0:
......
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