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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
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theano/compile/profiling.py
浏览文件 @ d5ff2b48
...@@ -240,7 +240,6 @@ class ProfileStats(object): ...@@ -240,7 +240,6 @@ class ProfileStats(object):
else: else:
self.flag_time_thunks = flag_time_thunks self.flag_time_thunks = flag_time_thunks
self.__dict__.update(kwargs) self.__dict__.update(kwargs)
#print >> sys.stderr, "self.message", self.message
if atexit_print: if atexit_print:
global _atexit_print_list global _atexit_print_list
_atexit_print_list.append(self) _atexit_print_list.append(self)
...@@ -377,9 +376,6 @@ class ProfileStats(object): ...@@ -377,9 +376,6 @@ class ProfileStats(object):
tot = 0 tot = 0
print('Class', file=file) print('Class', file=file)
print('---', 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 = [] hs = []
# formatting string # formatting string
es = [] es = []
...@@ -421,7 +417,8 @@ class ProfileStats(object): ...@@ -421,7 +417,8 @@ class ProfileStats(object):
tot += t tot += t
ftot = tot * 100 / local_time ftot = tot * 100 / local_time
# Remove the useless start and end of the class name: # 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] class_name = str(a)[8:-2][:maxlen]
print(format_str % (f, ftot, t, t / nb_call, print(format_str % (f, ftot, t, t / nb_call,
impl, nb_call, impl, nb_call,
...@@ -429,10 +426,12 @@ class ProfileStats(object): ...@@ -429,10 +426,12 @@ class ProfileStats(object):
# While this carries over less information, it is arranged such # While this carries over less information, it is arranged such
# that it way more readeable that the previous output of the # that it way more readeable that the previous output of the
# profiler # profiler
print(' ... (remaining %i Classes account for %6.2f%%(%.2fs) of the runtime)'\ print(' ... (remaining %i Classes account for %6.2f%%(%.2fs) of '
% (max(0, len(otimes) - N), 'the runtime)' %
(max(0, len(otimes) - N),
sum(f for f, t, a, ci, nb_call, nb_op in 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) print('', file=file)
def summary_ops(self, file=sys.stderr, N=None): def summary_ops(self, file=sys.stderr, N=None):
...@@ -459,9 +458,6 @@ class ProfileStats(object): ...@@ -459,9 +458,6 @@ class ProfileStats(object):
tot = 0 tot = 0
print('Ops', file=file) print('Ops', file=file)
print('---', 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 = [] hs = []
# formatting string # formatting string
es = [] es = []
...@@ -508,10 +504,12 @@ class ProfileStats(object): ...@@ -508,10 +504,12 @@ class ProfileStats(object):
# While this carries over less information, it is arranged such # While this carries over less information, it is arranged such
# that it way more readeable that the previous output of the # that it way more readeable that the previous output of the
# profiler # profiler
print(' ... (remaining %i Ops account for %6.2f%%(%.2fs) of the runtime)'\ print(' ... (remaining %i Ops account for %6.2f%%(%.2fs) of '
% (max(0, len(otimes) - N), 'the runtime)' %
(max(0, len(otimes) - N),
sum(f for f, t, a, ci, nb_call, nb_op in 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) print('', file=file)
def summary_nodes(self, file=sys.stderr, N=None): def summary_nodes(self, file=sys.stderr, N=None):
...@@ -526,7 +524,6 @@ class ProfileStats(object): ...@@ -526,7 +524,6 @@ class ProfileStats(object):
print('Apply', file=file) print('Apply', file=file)
print('------', file=file) print('------', file=file)
#print >> file, '<% time> <cumulative %%> <apply time> <cumulative seconds> <time per call> <nb_call> <Apply Op name>'
# headers # headers
hs = [] hs = []
# formatting string # formatting string
...@@ -620,10 +617,9 @@ class ProfileStats(object): ...@@ -620,10 +617,9 @@ class ProfileStats(object):
idx, dtype, sh, st), file=file) idx, dtype, sh, st), file=file)
# Same as before, this I've sacrificied some information making # Same as before, this I've sacrificied some information making
# the output more readable # the output more readable
# print >> file, ' %4.1f%% %5.1f%% %5.3fs %5.3fs %.2es %i %s'%( print(' ... (remaining %i Apply instances account for '
# f, ftot, t, tot, t/nb_call,nb_call, str(a)) '%.2f%%(%.2fs) of the runtime)' %
print(' ... (remaining %i Apply instances account for %.2f%%(%.2fs) of the runtime)'\ (max(0, len(atimes) - N),
% (max(0, len(atimes) - N),
sum(f for f, t, a, nd_id, nb_call in 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) sum(t for f, t, a, nd_id, nb_call in atimes[N:])), file=file)
print('', file=file) print('', file=file)
...@@ -640,15 +636,17 @@ class ProfileStats(object): ...@@ -640,15 +636,17 @@ class ProfileStats(object):
100 * self.vm_call_time / self.fct_call_time), file=file) 100 * self.vm_call_time / self.fct_call_time), file=file)
local_time = sum(self.apply_time.values()) local_time = sum(self.apply_time.values())
if local_time > 0: if local_time > 0:
print(' Time in thunks: %es (%.3f%%)' % ( print(' Time in thunks: %es (%.3f%%)' %
local_time, 100 * local_time / self.fct_call_time), file=file) (local_time, 100 * local_time / self.fct_call_time),
file=file)
print(' Total compile time: %es' % self.compile_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(' Number of Apply nodes: %d' % self.nb_nodes, file=file)
print(' Theano Optimizer time: %es' % self.optimizer_time, file=file) print(' Theano Optimizer time: %es' % self.optimizer_time,
print(' Theano validate time: %es' % self.validate_time, file=file) file=file)
print((' Theano Linker time (includes C,' print(' Theano validate time: %es' % self.validate_time,
' CUDA code generation/compiling): %es' % file=file)
self.linker_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(' Import time %es' % self.import_time, file=file)
print('', file=file) print('', file=file)
...@@ -656,7 +654,8 @@ class ProfileStats(object): ...@@ -656,7 +654,8 @@ class ProfileStats(object):
assert self.validate_time < self.optimizer_time assert self.validate_time < self.optimizer_time
def summary_globals(self, file): 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): def summary_memory(self, file, N=None):
fct_memory = {} # fgraph->dict(node->[outputs size]) fct_memory = {} # fgraph->dict(node->[outputs size])
...@@ -742,7 +741,8 @@ class ProfileStats(object): ...@@ -742,7 +741,8 @@ class ProfileStats(object):
# two data structure used to mimic Python gc # two data structure used to mimic Python gc
viewed_by = {} # {var1: [vars that view var1]} 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 # This is more safe to help detect potential bug in the algo
for var in fgraph.variables: for var in fgraph.variables:
viewed_by[var] = [] viewed_by[var] = []
...@@ -778,14 +778,16 @@ class ProfileStats(object): ...@@ -778,14 +778,16 @@ class ProfileStats(object):
ins = None ins = None
if dmap and idx2 in dmap: if dmap and idx2 in dmap:
vidx = dmap[idx2] vidx = dmap[idx2]
assert len( assert len(vidx) == 1, ("Here we only support the "
vidx) == 1, "Here we only support the possibility to destroy one input" "possibility to destroy one "
"input")
ins = node.inputs[vidx[0]] ins = node.inputs[vidx[0]]
if vmap and idx2 in vmap: if vmap and idx2 in vmap:
assert ins is None assert ins is None
vidx = vmap[idx2] vidx = vmap[idx2]
assert len( assert len(vidx) == 1, ("Here we only support the "
vidx) == 1, "Here we only support the possibility to view one input" "possibility to view one "
"input")
ins = node.inputs[vidx[0]] ins = node.inputs[vidx[0]]
if ins is not None: if ins is not None:
# This is needed for destroy_map in case it # This is needed for destroy_map in case it
...@@ -818,7 +820,8 @@ class ProfileStats(object): ...@@ -818,7 +820,8 @@ class ProfileStats(object):
if (dependencies[ins] and if (dependencies[ins] and
ins not in fgraph.outputs and ins not in fgraph.outputs and
ins.owner 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, []): if ins not in view_of and not viewed_by.get(ins, []):
running_memory_size[cg] -= var_mem[ins] running_memory_size[cg] -= var_mem[ins]
elif ins in view_of: elif ins in view_of:
...@@ -907,14 +910,16 @@ class ProfileStats(object): ...@@ -907,14 +910,16 @@ class ProfileStats(object):
ins = None ins = None
if dmap and idx in dmap: if dmap and idx in dmap:
vidx = dmap[idx] vidx = dmap[idx]
assert len( assert len(vidx) == 1, ("Here we only support "
vidx) == 1, "Here we only support the possibility to destroy one input" "the possibility to "
"destroy one input")
ins = node.inputs[vidx[0]] ins = node.inputs[vidx[0]]
if vmap and idx in vmap: if vmap and idx in vmap:
assert ins is None assert ins is None
vidx = vmap[idx] vidx = vmap[idx]
assert len( assert len(vidx) == 1, ("Here we only support "
vidx) == 1, "Here we only support the possibility to destroy one input" "the possibility to "
"view one input")
ins = node.inputs[vidx[0]] ins = node.inputs[vidx[0]]
if ins is not None: if ins is not None:
# This is needed for destroy_map in case it # This is needed for destroy_map in case it
...@@ -922,7 +927,7 @@ class ProfileStats(object): ...@@ -922,7 +927,7 @@ class ProfileStats(object):
# the output could be different then the # the output could be different then the
# input. # input.
assert isinstance(ins, theano.Variable) 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) origin = view_of.get(ins, ins)
view_of[out] = origin view_of[out] = origin
viewof_change.append(out) viewof_change.append(out)
...@@ -944,8 +949,10 @@ class ProfileStats(object): ...@@ -944,8 +949,10 @@ class ProfileStats(object):
if (dependencies[ins] and if (dependencies[ins] and
ins not in fgraph.outputs and ins not in fgraph.outputs and
ins.owner and ins.owner and
all([compute_map[v][0] for v in dependencies[ins]])): all([compute_map[v][0]
if ins not in view_of and not viewed_by.get(ins, []): for v in dependencies[ins]])):
if (ins not in view_of and
not viewed_by.get(ins, [])):
mem_freed += var_mem[ins] mem_freed += var_mem[ins]
elif ins in view_of: elif ins in view_of:
origin = view_of[ins] origin = view_of[ins]
...@@ -953,7 +960,8 @@ class ProfileStats(object): ...@@ -953,7 +960,8 @@ class ProfileStats(object):
viewedby_remove[origin].append(ins) viewedby_remove[origin].append(ins)
if (not viewed_by[origin] and if (not viewed_by[origin] and
origin not in fgraph.inputs and origin not in fgraph.inputs and
not isinstance(origin, theano.Constant)): not isinstance(origin,
theano.Constant)):
mem_freed += var_mem[origin] mem_freed += var_mem[origin]
else: else:
# ins is viewed_by something else, so its # ins is viewed_by something else, so its
...@@ -964,7 +972,8 @@ class ProfileStats(object): ...@@ -964,7 +972,8 @@ class ProfileStats(object):
done_set.add(node) done_set.add(node)
frozen_set = frozenset(done_set) 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 # check if frozen_set is in done_set
# no, add it to done_set # no, add it to done_set
# yes, then compare the past mem and current mem # yes, then compare the past mem and current mem
...@@ -1008,7 +1017,8 @@ class ProfileStats(object): ...@@ -1008,7 +1017,8 @@ class ProfileStats(object):
# two data structure used to mimic Python gc # two data structure used to mimic Python gc
viewed_by = {} # {var1: [vars that view var1]} 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 # This is more safe to help detect potential bug in the algo
for var in fgraph.variables: for var in fgraph.variables:
viewed_by[var] = [] viewed_by[var] = []
...@@ -1043,28 +1053,29 @@ class ProfileStats(object): ...@@ -1043,28 +1053,29 @@ class ProfileStats(object):
max_sum_size = max(max_sum_size, sum_size) max_sum_size = max(max_sum_size, sum_size)
max_node_memory_size[0] = max(max_node_memory_size[0], max_node_memory_size[0] = max(max_node_memory_size[0],
sum(old_running_memory[0])) sum(old_running_memory[0]))
max_running_max_memory_size[0] = max(max_running_max_memory_size[0], max_running_max_memory_size[0] = \
sum(old_running_memory[2])) max(max_running_max_memory_size[0], sum(old_running_memory[2]))
# Separate CPU and GPU # Separate CPU and GPU
max_node_memory_size[1] = max(max_node_memory_size[1], max_node_memory_size[1] = max(max_node_memory_size[1],
old_running_memory[0][0]) old_running_memory[0][0])
max_node_memory_size[2] = max(max_node_memory_size[2], max_node_memory_size[2] = max(max_node_memory_size[2],
old_running_memory[0][1]) old_running_memory[0][1])
max_running_max_memory_size[1] = max(max_running_max_memory_size[1], max_running_max_memory_size[1] = \
old_running_memory[2][0]) 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], max_running_max_memory_size[2] = \
old_running_memory[2][1]) 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 = \
max_node_memory_saved_by_inplace, old_running_memory[3]) max(max_node_memory_saved_by_inplace, old_running_memory[3])
max_node_memory_saved_by_view = max(max_node_memory_saved_by_view, max_node_memory_saved_by_view = max(max_node_memory_saved_by_view,
old_running_memory[4]) old_running_memory[4])
# Store max of some stats with new order # Store max of some stats with new order
new_max_node_memory_size[0] = max(new_max_node_memory_size[0], new_max_node_memory_size[0] = max(new_max_node_memory_size[0],
sum(new_running_memory[0])) sum(new_running_memory[0]))
new_max_running_max_memory_size[0] = max(new_max_running_max_memory_size[0], new_max_running_max_memory_size[0] = \
max(new_max_running_max_memory_size[0],
sum(new_running_memory[2])) sum(new_running_memory[2]))
# Separate CPU and GPU # Separate CPU and GPU
...@@ -1072,15 +1083,18 @@ class ProfileStats(object): ...@@ -1072,15 +1083,18 @@ class ProfileStats(object):
new_running_memory[0][0]) new_running_memory[0][0])
new_max_node_memory_size[2] = max(new_max_node_memory_size[2], new_max_node_memory_size[2] = max(new_max_node_memory_size[2],
new_running_memory[0][1]) new_running_memory[0][1])
new_max_running_max_memory_size[1] = max(new_max_running_max_memory_size[1], new_max_running_max_memory_size[1] = \
max(new_max_running_max_memory_size[1],
new_running_memory[2][0]) new_running_memory[2][0])
new_max_running_max_memory_size[2] = max(new_max_running_max_memory_size[2], new_max_running_max_memory_size[2] = \
max(new_max_running_max_memory_size[2],
new_running_memory[2][1]) new_running_memory[2][1])
new_max_node_memory_saved_by_inplace = max( new_max_node_memory_saved_by_inplace = \
new_max_node_memory_saved_by_inplace, new_running_memory[3]) max(new_max_node_memory_saved_by_inplace,
new_max_node_memory_saved_by_view = max(new_max_node_memory_saved_by_view, new_running_memory[3])
new_running_memory[4]) 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 # Config: whether print min memory peak
if config.profiling.min_peak_memory: if config.profiling.min_peak_memory:
...@@ -1093,8 +1107,8 @@ class ProfileStats(object): ...@@ -1093,8 +1107,8 @@ class ProfileStats(object):
del fgraph, nodes_mem del fgraph, nodes_mem
if len(fct_memory) > 1: if len(fct_memory) > 1:
print(("Memory Profile " print("Memory Profile (the max between all functions in "
"(the max between all functions in that profile)"), file=file) "that profile)", file=file)
else: else:
print("Memory Profile", file=file) print("Memory Profile", file=file)
...@@ -1129,17 +1143,21 @@ class ProfileStats(object): ...@@ -1129,17 +1143,21 @@ class ProfileStats(object):
print("---", file=file) print("---", file=file)
if min_max_peak: if min_max_peak:
print(" Minimum peak from all valid apply node order is %dKB(took %.3fs to compute)" % (int(round( print(" Minimum peak from all valid apply node order is "
min_max_peak / 1024.)), min_peak_time), file=file) "%dKB(took %.3fs to compute)" %
print(" Memory saved if views are used: %dKB (%dKB)" % (int( (int(round(min_max_peak / 1024.)), min_peak_time), file=file)
round(new_max_node_memory_saved_by_view / 1024.)), int( print(" Memory saved if views are used: %dKB (%dKB)" %
round(max_node_memory_saved_by_view / 1024.))), file=file) (int(round(new_max_node_memory_saved_by_view / 1024.)),
print(" Memory saved if inplace ops are used: %dKB (%dKB)" % \ 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(new_max_node_memory_saved_by_inplace / 1024.)),
int(round(max_node_memory_saved_by_inplace / 1024.))), file=file) int(round(max_node_memory_saved_by_inplace / 1024.))),
print(" Memory saved if gc is enabled: %dKB (%dKB)" % (int( file=file)
round(new_max_node_memory_size[0] - new_max_running_max_memory_size[0]) / 1024.), int( print(" Memory saved if gc is enabled: %dKB (%dKB)" %
round(max_node_memory_size[0] - max_running_max_memory_size[0]) / 1024.)), file=file) (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) print("---", file=file)
...@@ -1148,19 +1166,19 @@ class ProfileStats(object): ...@@ -1148,19 +1166,19 @@ class ProfileStats(object):
hasattr(theano.sandbox.cuda, 'cuda_ndarray') and hasattr(theano.sandbox.cuda, 'cuda_ndarray') and
hasattr(theano.sandbox.cuda.cuda_ndarray.cuda_ndarray, hasattr(theano.sandbox.cuda.cuda_ndarray.cuda_ndarray,
'theano_allocated')): 'theano_allocated')):
_, gpu_max = theano.sandbox.cuda.cuda_ndarray.cuda_ndarray.theano_allocated() cuda_ndarray = theano.sandbox.cuda.cuda_ndarray.cuda_ndarray
print((" Max Memory allocated on the GPU " _, gpu_max = cuda_ndarray.theano_allocated()
"(for all functions): %dKB" % print(" Max Memory allocated on the GPU (for all functions): "
int(round(gpu_max / 1024.))), file=file) "%dKB" % int(round(gpu_max / 1024.)), file=file)
print("", file=file) print("", file=file)
if len(fct_memory) > 1: if len(fct_memory) > 1:
print(( print(" This list is based on all functions in the profile",
" This list is based on all functions in the profile"), file=file) file=file)
print((" <Sum apply outputs (bytes)>" print(" <Sum apply outputs (bytes)>"
" <Apply outputs shape>" " <Apply outputs shape>"
" <created/inplace/view>" " <created/inplace/view>"
" <Apply node>"), file=file) " <Apply node>", file=file)
print("", file=file) print("", file=file)
items = node_mem.items() items = node_mem.items()
items.sort(key=lambda a: a[1], reverse=True) items.sort(key=lambda a: a[1], reverse=True)
...@@ -1181,9 +1199,8 @@ class ProfileStats(object): ...@@ -1181,9 +1199,8 @@ class ProfileStats(object):
else: else:
size = "%10s" % "Unknown" size = "%10s" % "Unknown"
print(' %s %s %s %s' % (size, print(' %s %s %s %s' % (size, shapes, ' '.join(code), node),
shapes, file=file)
' '.join(code), node), file=file)
sum_remaining = sum(size for _, size in items[N:]) sum_remaining = sum(size for _, size in items[N:])
size_sum_dense = sum(node_mem.values()) size_sum_dense = sum(node_mem.values())
...@@ -1191,23 +1208,21 @@ class ProfileStats(object): ...@@ -1191,23 +1208,21 @@ class ProfileStats(object):
p = "0%" p = "0%"
else: else:
p = "(%.2f%%)" % (float(sum_remaining) / size_sum_dense * 100) p = "(%.2f%%)" % (float(sum_remaining) / size_sum_dense * 100)
print(( print(' ... (remaining %i Apply account for %4dB/%dB (%s) of the'
' ... (remaining %i Apply account for %4dB/%dB (%s) of the' ' Apply with dense outputs sizes)' % (max(0, len(node_mem) - N),
' Apply with dense outputs sizes)') % (max(0, len(node_mem) - N),
sum_remaining, sum_remaining,
size_sum_dense, p size_sum_dense, p),
), file=file) file=file)
print('', file=file) print('', file=file)
if N == 0: if N == 0:
print((' All Apply nodes have output sizes that take' print(' All Apply nodes have output sizes that take less '
' less than %dB.' % 'than %dB.' % config.profiling.min_memory_size, file=file)
config.profiling.min_memory_size), file=file) print(" <created/inplace/view> is taken from the Op's declaration.",
print(( file=file)
" <created/inplace/view> is taken from the Op's declaration."), file=file) print(" Apply nodes marked 'inplace' or 'view' may"
print((" Apply nodes marked 'inplace' or 'view' may"
" actually allocate memory, this is not reported" " actually allocate memory, this is not reported"
" here. If you use DebugMode, warnings will be" " here. If you use DebugMode, warnings will be"
" emitted in those cases."), file=file) " emitted in those cases.", file=file)
print('', file=file) print('', file=file)
def summary(self, file=sys.stderr, n_ops_to_print=20, def summary(self, file=sys.stderr, n_ops_to_print=20,
...@@ -1220,8 +1235,8 @@ class ProfileStats(object): ...@@ -1220,8 +1235,8 @@ class ProfileStats(object):
self.summary_ops(file, n_ops_to_print) self.summary_ops(file, n_ops_to_print)
self.summary_nodes(file, n_apply_to_print) self.summary_nodes(file, n_apply_to_print)
elif self.fct_callcount > 0: elif self.fct_callcount > 0:
print((" No execution time accumulated " print(" No execution time accumulated "
"(hint: try config profiling.time_thunks=1)"), file=file) "(hint: try config profiling.time_thunks=1)", file=file)
if self.variable_shape or self.variable_strides: if self.variable_shape or self.variable_strides:
self.summary_memory(file, n_apply_to_print) self.summary_memory(file, n_apply_to_print)
if self.optimizer_profile: if self.optimizer_profile:
...@@ -1231,7 +1246,7 @@ class ProfileStats(object): ...@@ -1231,7 +1246,7 @@ class ProfileStats(object):
self.optimizer_profile[1]) 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, 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): n_apply_to_print=15, n_ops_to_print=20, print_apply=False):
""" """
......
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