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pytensor
提交 089fe03d authored 作者: Roy Xue's avatar Roy Xue
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Add comments and code style fix for the while file

上级 92306ee6
隐藏空白字符变更
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正在显示 包含 136 行增加 和 124 行删除
theano/compile/profiling.py
浏览文件 @ 089fe03d
......@@ -61,9 +61,9 @@ AddConfigVar('profiling.min_memory_size',
in_c_key=False)
AddConfigVar('profiling.min_peak_memory',
"""The min peak memory usage of the order""",
BoolParam(False),
in_c_key=False)
"""The min peak memory usage of the order""",
BoolParam(False),
in_c_key=False)
AddConfigVar('profiling.destination',
"""
......@@ -93,10 +93,10 @@ def _atexit_print_fn():
if not isinstance(ps, ScanProfileStats):
to_sum.append(ps)
else:
#TODO print the name if there is one!
# TODO print the name if there is one!
print 'Skipping empty Profile'
if len(to_sum) > 1:
# Make a global profile
# Make a global profile
cum = copy.copy(to_sum[0])
msg = ("Sum of all(%d) printed profiles at exit excluding Scan op"
" profile." % len(to_sum))
......@@ -107,7 +107,7 @@ def _atexit_print_fn():
"validate_time"]:
setattr(cum, attr, getattr(cum, attr) + getattr(ps, attr))
#merge dictonary
# merge dictonary
for attr in ["apply_time", "apply_callcount",
"apply_cimpl", "variable_shape", "variable_strides"]:
cum_attr = getattr(cum, attr)
......@@ -128,10 +128,8 @@ def _atexit_print_fn():
n_apply_to_print=config.profiling.n_apply)
class ProfileStats(object):
"""
Object to store runtime and memory profiling information for all of
Theano's operations: compilation, optimization, execution.
......@@ -211,8 +209,8 @@ class ProfileStats(object):
names of the class vars declared in this class.
"""
if (hasattr(theano, 'sandbox') and
hasattr(theano.sandbox, 'cuda') and
theano.sandbox.cuda.cuda_enabled):
hasattr(theano.sandbox, 'cuda') and
theano.sandbox.cuda.cuda_enabled):
if os.environ.get('CUDA_LAUNCH_BLOCKING', '0') != '1':
raise Exception(
"You are running the Theano profiler with CUDA enabled."
......@@ -332,7 +330,7 @@ class ProfileStats(object):
local_time = 0
if local_time == 0:
print >> file, ('ProfileMode.summary_class: total time 0'
' (did you forget to enable counters?)')
' (did you forget to enable counters?)')
return
class_time = self.class_time()
class_call = self.class_callcount()
......@@ -341,12 +339,12 @@ class ProfileStats(object):
if N is None:
N = len(self.class_time)
otimes = [(t * 100 / local_time,
t,
clas,
class_impl.get(clas, ' '),
class_call.get(clas, 0),
class_apply.get(clas, 0))
for clas, t in class_time.items()]
t,
clas,
class_impl.get(clas, ' '),
class_call.get(clas, 0),
class_apply.get(clas, 0))
for clas, t in class_time.items()]
otimes.sort()
otimes.reverse()
tot = 0
......@@ -405,9 +403,9 @@ class ProfileStats(object):
# that it way more readeable that the previous output of the
# profiler
print >>file, ' ... (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:]))
% (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:]))
print >> file, ''
def summary_ops(self, file=sys.stderr, N=None):
......@@ -417,19 +415,19 @@ class ProfileStats(object):
local_time = 0
if local_time == 0:
print >> file, ('ProfileMode.summary_ops: total time 0'
' (did you forget to enable counters?)')
' (did you forget to enable counters?)')
return
op_time = self.op_time()
op_call = self.op_callcount()
op_apply = self.op_nodes()
op_impl = self.op_impl()
otimes = [(t * 100 / local_time,
t,
op,
op_impl.get(op, ' '),
op_call.get(op, 0),
op_apply.get(op, 0))
for op, t in op_time.items()]
t,
op,
op_impl.get(op, ' '),
op_call.get(op, 0),
op_apply.get(op, 0))
for op, t in op_time.items()]
otimes.sort()
otimes.reverse()
tot = 0
......@@ -485,9 +483,9 @@ class ProfileStats(object):
# that it way more readeable that the previous output of the
# profiler
print >>file, ' ... (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:]))
% (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:]))
print >> file, ''
def summary_nodes(self, file=sys.stderr, N=None):
......@@ -497,7 +495,7 @@ class ProfileStats(object):
local_time = 0
if local_time == 0:
print >> file, ('ProfileMode.summary_nodes: total time 0'
' (did you forget to enable counters?)')
' (did you forget to enable counters?)')
return
print >> file, 'Apply'
......@@ -572,15 +570,15 @@ class ProfileStats(object):
for var in a.inputs],
[self.variable_shape[var]
for var in a.outputs])
flops = '%8.1f' % (fl/1024./1024)
flops_s = '%10.1f' % (fl/1024./1024/1024/t)
flops = '%8.1f' % (fl / 1024. / 1024)
flops_s = '%10.1f' % (fl / 1024. / 1024 / 1024 / t)
else:
flops = " "
flops_s = " "
print >> file, format_str %(f, ftot, t, t / nb_call, nb_call,
nd_id,
flops, flops_s,
str(a)[:maxlen])
print >> file, format_str % (f, ftot, t, t / nb_call, nb_call,
nd_id,
flops, flops_s,
str(a)[:maxlen])
if not config.profile_memory:
continue
for idx, var in enumerate(a.inputs):
......@@ -597,12 +595,12 @@ class ProfileStats(object):
idx, dtype, sh, st)
# 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'%(
# 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 >> file, ' ... (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:]))
% (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:]))
print >> file, ''
def summary_function(self, file):
......@@ -610,15 +608,15 @@ class ProfileStats(object):
print >> file, '=================='
print >> file, ' Message: %s' % self.message
print >> file, ' Time in %i calls to Function.__call__: %es' % (
self.fct_callcount, self.fct_call_time)
self.fct_callcount, self.fct_call_time)
if self.fct_call_time > 0:
print >> file, ' Time in Function.fn.__call__: %es (%.3f%%)' % (
self.vm_call_time,
100 * self.vm_call_time / self.fct_call_time)
self.vm_call_time,
100 * self.vm_call_time / self.fct_call_time)
local_time = sum(self.apply_time.values())
if local_time > 0:
print >> file, ' Time in thunks: %es (%.3f%%)' % (
local_time, 100*local_time / self.fct_call_time)
local_time, 100 * local_time / self.fct_call_time)
print >> file, ' Total compile time: %es' % self.compile_time
print >> file, ' Number of Apply nodes: %s' % len(self.apply_time)
print >> file, ' Theano Optimizer time: %es' % self.optimizer_time
......@@ -656,7 +654,7 @@ class ProfileStats(object):
fct_shapes[node.fgraph][node].append(sh)
node_mem[node] = sum_dense
#Find the function that used the most of that statistic
# Find the function that used the most of that statistic
max_sum_size = 0
max_node_memory_size = 0
max_running_max_memory_size = 0
......@@ -707,12 +705,13 @@ 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] = []
view_of = {} # {var1: original var viewed by var1}
# The orignal mean that we don't keep trac of all the intermediate relationship in the view.
# The orignal mean that we don't keep trac of all the intermediate
# relationship in the view.
for node in order:
for var in node.outputs:
......@@ -738,12 +737,14 @@ 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
......@@ -768,17 +769,17 @@ class ProfileStats(object):
assert not (ins in view_of and viewed_by[ins])
# we trac the original var, so this shouldn't happen
if (dependencies[ins] and
ins not in fgraph.outputs and
ins.owner and
all([compute_map[v][0] for v in dependencies[ins]])):
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, []):
running_memory_size -= var_mem[ins]
elif ins in view_of:
origin = view_of[ins]
viewed_by[origin].remove(ins)
if (not viewed_by[origin] and
origin not in fgraph.inputs and
not isinstance(origin, theano.Constant)):
origin not in fgraph.inputs and
not isinstance(origin, theano.Constant)):
running_memory_size -= var_mem[origin]
else:
# ins is viewed_by something else, so its
......@@ -859,12 +860,14 @@ 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 destroy one input"
ins = node.inputs[vidx[0]]
if ins is not None:
# This is needed for destroy_map in case it
......@@ -889,11 +892,12 @@ class ProfileStats(object):
for ins in node.inputs:
assert not (ins in view_of and
viewed_by[ins])
# We track of the original var, so this shouldn't happen
# We track of the original var, so this shouldn't
# happen
if (dependencies[ins] and
ins not in fgraph.outputs and
ins.owner and
all([compute_map[v][0] for v in dependencies[ins]])):
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, []):
mem_freed += var_mem[ins]
elif ins in view_of:
......@@ -901,8 +905,8 @@ class ProfileStats(object):
viewed_by[origin].remove(ins)
viewedby_remove[origin].append(ins)
if (not viewed_by[origin] and
origin not in fgraph.inputs and
not isinstance(origin, theano.Constant)):
origin not in fgraph.inputs and
not isinstance(origin, theano.Constant)):
mem_freed += var_mem[origin]
else:
# ins is viewed_by something else, so its
......@@ -913,9 +917,14 @@ 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
# bigger, update the value and continue
# smaller, stop this iteration, move to next node
done_dict[frozen_set] = max_mem_count
for var in node.outputs:
for c, _ in var.clients:
if c != "output":
......@@ -928,7 +937,8 @@ class ProfileStats(object):
if max_mem_count < mem_bound:
mem_bound = max_mem_count
else:
min_memory_generator(new_exec_nodes, viewed_by, view_of)
min_memory_generator(
new_exec_nodes, viewed_by, view_of)
# Reset track variables
done_set.remove(node)
......@@ -949,7 +959,6 @@ class ProfileStats(object):
for k in viewof_change:
del view_of[k]
# 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.
......@@ -957,7 +966,8 @@ class ProfileStats(object):
for var in fgraph.variables:
viewed_by[var] = []
view_of = {} # {var1: original var viewed by var1}
# The orignal mean that we don't keep trac of all the intermediate relationship in the view.
# The orignal mean that we don't keep trac of all the intermediate
# relationship in the view.
min_memory_generator(executable_nodes, viewed_by, view_of)
......@@ -1027,11 +1037,11 @@ class ProfileStats(object):
# round(max_sum_size / 1024))
print >> file, " Max if no gc (allow_gc=False): %dKB (%dKB)" % (int(round(
new_max_node_memory_size / 1024.)), int(round(
max_node_memory_size / 1024.)))
new_max_node_memory_size / 1024.)), int(round(
max_node_memory_size / 1024.)))
print >> file, " Max if linker=cvm(default): %dKB (%dKB)" % (int(round(
new_max_running_max_memory_size / 1024.)), int(round(
max_running_max_memory_size / 1024.)))
max_running_max_memory_size / 1024.)))
if min_max_peak:
print >> file, " Minimum peak from all valid apply node order is %dKB(took %.3fs to compute)" % (int(round(
min_max_peak / 1024.)), min_peak_time)
......@@ -1039,7 +1049,8 @@ class ProfileStats(object):
round(new_max_node_memory_saved_by_view / 1024.)), int(
round(max_node_memory_saved_by_view / 1024.)))
print >> file, " 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.)))
(int(round(new_max_node_memory_saved_by_inplace / 1024.)),
int(round(max_node_memory_saved_by_inplace / 1024.)))
print >> file, " Memory saved if gc is enabled: %dKB (%dKB)" % (int(
round(new_max_node_memory_size - new_max_running_max_memory_size) / 1024.), int(
round(max_node_memory_size - max_running_max_memory_size) / 1024.))
......@@ -1096,8 +1107,8 @@ class ProfileStats(object):
print >> file, (
' ... (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
sum_remaining,
size_sum_dense, p
)
print >> file, ''
if N == 0:
......@@ -1112,7 +1123,6 @@ class ProfileStats(object):
" emitted in those cases.")
print >> file, ''
def summary(self, file=sys.stderr, n_ops_to_print=20,
n_apply_to_print=20):
self.summary_function(file)
......@@ -1133,11 +1143,9 @@ class ProfileStats(object):
self.optimizer_profile[1])
if 0: # old code still to be ported from ProfileMode
if 0: # 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):
n_apply_to_print=15, n_ops_to_print=20, print_apply=False):
"""
Print a readable summary of the stats.
......@@ -1159,7 +1167,7 @@ if 0: # old code still to be ported from ProfileMode
sop_time = {}
sop_call = {}
sop_op = {}
#map each op class to Bool. True iff all applies were done in c.
# map each op class to Bool. True iff all applies were done in c.
sop_c = {}
for a, t in op_time.items():
typ = type(a)
......@@ -1186,13 +1194,13 @@ if 0: # old code still to be ported from ProfileMode
msg = '*'
else:
msg = ' '
print ' %4.1f%% %5.1f%% %5.3fs %5.3fs %.2es %s %5d %2d %s' % (f, ftot, t, tot, t/nb_call, msg, nb_call, nb_op, a)
print ' %4.1f%% %5.1f%% %5.3fs %5.3fs %.2es %s %5d %2d %s' % (f, ftot, t, tot, t / nb_call, msg, nb_call, nb_op, a)
print ' ... (remaining %i Ops account for %.2f%%(%.2fs) of the runtime)'\
% (max(0, len(sotimes) - n_ops_to_print),
sum(f for f, t, a, ci, nb_call, nb_op in
sotimes[n_ops_to_print:]),
sum(t for f, t, a, ci, nb_call, nb_op in
sotimes[n_ops_to_print:]))
% (max(0, len(sotimes) - n_ops_to_print),
sum(f for f, t, a, ci, nb_call, nb_op in
sotimes[n_ops_to_print:]),
sum(t for f, t, a, ci, nb_call, nb_op in
sotimes[n_ops_to_print:]))
total_time = time.time() - import_time
total_fct_time = sum(fct_call_time.values())
......@@ -1202,13 +1210,13 @@ if 0: # old code still to be ported from ProfileMode
print 'Theano fct summary: <% total fct time> <total time> <time per call> <nb call> <fct name>'
for key in fct_call.keys():
if fct_call[key] > 0:
print ' %4.1f%% %.3fs %.2es %d %s'%(
print ' %4.1f%% %.3fs %.2es %d %s' % (
fct_call_time[key] / total_fct_time * 100,
fct_call_time[key],
fct_call_time[key] / fct_call[key],
fct_call[key], key.name)
else:
print ' NOT CALLED',key.name
print ' NOT CALLED', key.name
if total_fct_time > 0:
time_pr_in_fct = local_time / total_fct_time * 100
......@@ -1227,8 +1235,8 @@ if 0: # old code still to be ported from ProfileMode
print (' Theano Op time (included in fct call, Time spent '
'running thunks) %.3fs %.1f%%(of total) %.1f%%(of fct call)' %
(local_time, local_time / total_time * 100, time_pr_in_fct))
print 'Other time since import %.3fs %.1f%%'%(other_time,other_time/total_time*100)
print '%i Theano fct call, %.3fs per call'%(total_fct_call, time_per_call)
print 'Other time since import %.3fs %.1f%%' % (other_time, other_time / total_time * 100)
print '%i Theano fct call, %.3fs per call' % (total_fct_call, time_per_call)
print
print "List of apply that don't have float64 as input but have float64 in outputs. Usefull to know if we forgot some cast when using floatX=float32 or gpu code."
......@@ -1236,7 +1244,7 @@ if 0: # old code still to be ported from ProfileMode
for fct in fct_call.keys():
for idx, node in enumerate(fct.maker.fgraph.toposort()):
if any(hasattr(i, 'dtype') and i.dtype == 'float64' for i in node.outputs) and not any(hasattr(i, 'dtype') and i.dtype == 'float64' for i in node.inputs):
print str(node), idx, fct.name, str([getattr(i,'dtype',None) for i in node.inputs]),str([getattr(i,'dtype',None) for i in node.outputs])
print str(node), idx, fct.name, str([getattr(i, 'dtype', None) for i in node.inputs]), str([getattr(i, 'dtype', None) for i in node.outputs])
if any([x[2].__name__.startswith("Gpu") for x in sotimes]):
cpu = []
......@@ -1254,8 +1262,8 @@ if 0: # old code still to be ported from ProfileMode
sum_trans = sum(so[1] for so in trans)
print
print "Spent %.3fs(%.3f%%) in cpu Op, %.3fs(%.3f%%) in gpu Op and %.3fs(%.3f%%) transfert Op"%(
sum_cpu, sum_cpu/local_time*100, sum_gpu, sum_gpu/local_time*100, sum_trans, sum_trans/local_time*100)
print "Spent %.3fs(%.3f%%) in cpu Op, %.3fs(%.3f%%) in gpu Op and %.3fs(%.3f%%) transfert Op" % (
sum_cpu, sum_cpu / local_time * 100, sum_gpu, sum_gpu / local_time * 100, sum_trans, sum_trans / local_time * 100)
print "Theano function input that are float64"
print "<fct name> <input name> <input type> <str input>"
......@@ -1270,20 +1278,25 @@ if 0: # old code still to be ported from ProfileMode
from theano.tensor.raw_random import RandomFunction
import theano
import theano.scalar as scal
scalar_op_amdlibm_no_speed_up = [scal.LT, scal.GT, scal.LE, scal.GE, scal.EQ, scal.NEQ, scal.InRange, scal.Switch, scal.OR, scal.XOR, scal.AND, scal.Invert, scal.Maximum, scal.Minimum, scal.Add, scal.Mul, scal.Sub, scal.TrueDiv, scal.IntDiv, scal.Clip, scal.First, scal.Second, scal.Identity, scal.Cast, scal.Sgn, scal.Neg, scal.Inv, scal.Sqr ]
scalar_op_amdlibm_speed_up = [scal.Mod, scal.Pow, scal.Ceil, scal.Floor, scal.RoundHalfToEven, scal.RoundHalfAwayFromZero, scal.Log, scal.Log2, scal.Log10, scal.Log1p, scal.Exp, scal.Sqrt, scal.Abs, scal.Cos, scal.Sin, scal.Tan, scal.Tanh, scal.Cosh, scal.Sinh, T.nnet.sigm.ScalarSigmoid, T.nnet.sigm.ScalarSoftplus ]#Abs, Mod in float{32,64} only
scalar_op_amdlibm_no_speed_up = [scal.LT, scal.GT, scal.LE, scal.GE, scal.EQ, scal.NEQ, scal.InRange, scal.Switch, scal.OR, scal.XOR, scal.AND, scal.Invert, scal.Maximum,
scal.Minimum, scal.Add, scal.Mul, scal.Sub, scal.TrueDiv, scal.IntDiv, scal.Clip, scal.First, scal.Second, scal.Identity, scal.Cast, scal.Sgn, scal.Neg, scal.Inv, scal.Sqr]
scalar_op_amdlibm_speed_up = [scal.Mod, scal.Pow, scal.Ceil, scal.Floor, scal.RoundHalfToEven, scal.RoundHalfAwayFromZero, scal.Log, scal.Log2, scal.Log10, scal.Log1p, scal.Exp,
scal.Sqrt, scal.Abs, scal.Cos, scal.Sin, scal.Tan, scal.Tanh, scal.Cosh, scal.Sinh, T.nnet.sigm.ScalarSigmoid, T.nnet.sigm.ScalarSoftplus] # Abs, Mod in float{32,64} only
def get_scalar_ops(s):
if isinstance(s, theano.scalar.Composite):
l = []
for node in s.fgraph.toposort():
l+=get_scalar_ops(node.op)
l += get_scalar_ops(node.op)
return l
else: return [s]
else:
return [s]
def list_scalar_op(op):
if isinstance(op.scalar_op, theano.scalar.Composite):
return get_scalar_ops(op.scalar_op)
else: return [op.scalar_op]
else:
return [op.scalar_op]
def amdlibm_speed_up(op):
if not isinstance(op, T.Elemwise):
......@@ -1296,6 +1309,7 @@ if 0: # old code still to be ported from ProfileMode
elif s_op.__class__ not in scalar_op_amdlibm_no_speed_up:
print "We don't know if amdlibm will accelerate this scalar op.", s_op
return False
def exp_float32_op(op):
if not isinstance(op, T.Elemwise):
return False
......@@ -1303,30 +1317,30 @@ if 0: # old code still to be ported from ProfileMode
l = list_scalar_op(op)
return any([s_op.__class__ in [scal.Exp] for s_op in l])
#tip 1
if config.floatX=='float64':
# tip 1
if config.floatX == 'float64':
print " - Try the Theano flag floatX=float32"
#tip 2
if not config.lib.amdlibm and any([amdlibm_speed_up(a.op) for i,a in apply_time]):
# tip 2
if not config.lib.amdlibm and any([amdlibm_speed_up(a.op) for i, a in apply_time]):
print " - Try installing amdlibm and set the Theano flag lib.amdlibm=True. This speed up only some Elemwise operation."
#tip 3
if not config.lib.amdlibm and any([exp_float32_op(a.op) and a.inputs[0].dtype=='float32' for i,a in apply_time]):
# tip 3
if not config.lib.amdlibm and any([exp_float32_op(a.op) and a.inputs[0].dtype == 'float32' for i, a in apply_time]):
print " - With the default gcc libm, exp in float32 is slower than in float64! Try Theano flags floatX=float64 or install amdlibm and set the theano flags lib.amdlibm=True"
#tip 4
# tip 4
for a, t in apply_time.iteritems():
node = a
if (isinstance(node.op, T.Dot) and
all([len(i.type.broadcastable) == 2 for i in node.inputs])):
all([len(i.type.broadcastable) == 2 for i in node.inputs])):
print (" - You have a dot operation that was not optimized "
"to dot22 that is faster. Make sure the inputs are "
"float32 or float64 and are the same for both inputs. "
"Currently they are: %s" %
[i.type for i in node.inputs])
#tip 5
# tip 5
for a, t in apply_time.iteritems():
node = a
if isinstance(node.op, RandomFunction):
......@@ -1378,15 +1392,15 @@ if 0: # old code still to be ported from ProfileMode
outputs_size = self.outputs_size
self.print_summary_("print_summary",
None,
None,
None,
apply_time,
op_cimpl,
message,
outputs_size,
n_apply_to_print,
n_ops_to_print)
None,
None,
None,
apply_time,
op_cimpl,
message,
outputs_size,
n_apply_to_print,
n_ops_to_print)
def print_diff_summary(self, other, n_apply_to_print=15,
n_ops_to_print=20):
......@@ -1414,7 +1428,7 @@ if 0: # old code still to be ported from ProfileMode
tb = b_time.pop(a, 0)
r[a] += ta - tb
#they are missing in a
# they are missing in a
for a, t in b_time.items():
r.setdefault(a, 0)
r[a] += t
......@@ -1429,12 +1443,10 @@ if 0: # old code still to be ported from ProfileMode
outputs_size = diff_dict(self.outputs_size, other.outputs_size)
self.print_summary_(
"print_diff_summary", compile_time, fct_call_time, fct_call,
apply_time, op_cimpl, message, outputs_size,
n_apply_to_print=n_apply_to_print,
n_ops_to_print=n_ops_to_print, print_apply=False)
"print_diff_summary", compile_time, fct_call_time, fct_call,
apply_time, op_cimpl, message, outputs_size,
n_apply_to_print=n_apply_to_print,
n_ops_to_print=n_ops_to_print, print_apply=False)
class ScanProfileStats(ProfileStats):
......
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