提交 acc19605 authored 作者: Frederic's avatar Frederic

pep8

上级 0776ceb1
......@@ -672,12 +672,12 @@ class ProfileStats(object):
dependencies = fgraph.profile.dependencies
# 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.
# 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}
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.
for node in order:
......@@ -695,40 +695,53 @@ class ProfileStats(object):
node_memory_saved_by_view += v
idx += 1
# Update the Python emulating dicts and add the memory allocated by the node
# Update the Python emulating dicts and add the memory
# allocated by the node
idx2 = 0
for out in node.outputs:
if (dmap and idx2 in dmap) or (vmap and idx2 in vmap):
# This is needed for destroy_map in case it return a partial view that is destroyed.
# So the output could be different then the input.
# This is needed for destroy_map in case it
# return a partial view that is destroyed. So
# the output could be different then the
# input.
for ins in node.inputs:
assert isinstance(ins, theano.Variable)
view_of[out] = view_of.get(ins, ins)# This get make that we keep trac of view only again the original
# we keep trac of view only again the original
view_of[out] = view_of.get(ins, ins)
viewed_by[ins].append(out)
else:
running_memory_size += var_mem[out]
node_memory_size += var_mem[out]
idx2 += 1
running_max_memory_size = max(running_max_memory_size, running_memory_size)
running_max_memory_size = max(running_max_memory_size,
running_memory_size)
# Mimic the combination of Theano and Python gc
for ins in node.inputs:
assert not (ins in view_of and viewed_by[ins])
# we keep trac of the original var, so this shouldn't happen
if dependencies[ins] and ins not in fgraph.outputs and ins.owner:
# we trac the original var, so this shouldn't happen
if (dependencies[ins] and
ins not in fgraph.outputs and
ins.owner):
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:
if (not viewed_by[origin] and
origin not in fgraph.inputs):
running_memory_size -= var_mem[origin]
else:
# ins is viewed_by something else, so its memory isn't freed
# ins is viewed_by something else, so its
# memory isn't freed
pass
return [node_memory_size, running_memory_size, running_max_memory_size, node_memory_saved_by_inplace, node_memory_saved_by_view]
return [node_memory_size, running_memory_size,
running_max_memory_size, node_memory_saved_by_inplace,
node_memory_saved_by_view]
def count_minimum_peak(node_list, fgraph, nodes_mem):
global mem_count, mem_bound, max_mem_count
......
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