def __call__(self):
if self.time_thunks:
for cont in self.pre_call_clear:
cont[0] = None
try:
i = 0
for thunk, node, old_storage in zip(self.thunks, self.nodes,
self.post_thunk_clear):
t0 = time.time()
thunk()
t1 = time.time()
self.call_counts[i] += 1
self.call_times[i] += t1 - t0
for old_s in old_storage:
old_s[0] = None
i += 1
except Exception:
raise_with_op(self.fgraph, node, thunk)
else:
for cont in self.pre_call_clear:
cont[0] = None
try:
for thunk, node, old_storage in zip(self.thunks, self.nodes,
self.post_thunk_clear):
thunk()
for old_s in old_storage:
old_s[0] = None
except Exception:
raise_with_op(self.fgraph, node, thunk)
def f():
for inputs in input_lists[1:]:
for input1, input2 in zip(inputs0, inputs):
input2.storage[0] = copy(input1.storage[0])
for x in to_reset:
x[0] = None
pre(self, [input.data for input in input_lists[0]], order, thunk_groups)
for i, (thunks, node) in enumerate(zip(thunk_groups, order)):
try:
wrapper(self.fgraph, i, node, *thunks)
except Exception:
raise_with_op(self.fgraph, node, *thunks)
def __call__(self):
if self.time_thunks:
for cont in self.pre_call_clear:
cont[0] = None
try:
for i, (thunk, node) in enumerate(zip(self.thunks,
self.nodes)):
t0 = time.time()
thunk()
t1 = time.time()
self.call_counts[i] += 1
self.call_times[i] += t1 - t0
except Exception:
raise_with_op(self.fgraph, node, thunk)
else:
for cont in self.pre_call_clear:
cont[0] = None
try:
for thunk, node in zip(self.thunks, self.nodes):
thunk()
except Exception:
raise_with_op(self.fgraph, node, thunk)
def __call__(self, output_subset=None):
storage_map = self.storage_map
compute_map = self.compute_map
thunks = self.thunks
dependencies = self.dependencies
self.node_executed_order = []
self.node_cleared_order = []
for cont in self.pre_call_clear:
cont[0] = None
for k in self.storage_map:
compute_map[k][0] = k.owner is None
if self.callback_input and compute_map[k][0]:
self.callback_input(k, self.storage_map[k][0])
# apply_stack contains nodes
if output_subset is not None:
first_updated = len(self.outputs) - self.n_updates
output_subset = output_subset + list(
range(first_updated, len(self.outputs)))
apply_stack = [
self.outputs[i].owner for i in output_subset
if self.outputs[i].owner
]
else:
apply_stack = list(self.base_apply_stack)
last_apply_stack_len = -1
# This record all function inputs/shared variables and constants
for var, data in self.storage_map.items():
if data[0] is None:
continue
if hasattr(var.type, "get_shape_info"):
sh = var.type.get_shape_info(data[0])
else:
sh = "no shape"
self.variable_shape[var] = sh
st = getattr(data[0], "strides", "no strides")
if getattr(data[0], "flags", False) and data[0].flags.c_contiguous:
st = "c"
elif hasattr(data[0],
"is_c_contiguous") and data[0].is_c_contiguous():
st = "c"
self.variable_strides[var] = st
off = getattr(data[0], "offset", "")
self.variable_offset[var] = off
while apply_stack:
# Make sure something happened last time round. This is
# just a safety check to make sure the op is written
# correctly apply_stack should either decrease in length
# by one (a thunk successfully applied), or increase in
# length (added dependencies over and above the original).
# NB: this doesn't catch cycles (would be too expensive/slow),
# just stalls.
apply_stack_len = len(apply_stack)
assert apply_stack_len != last_apply_stack_len
last_apply_stack_len = apply_stack_len
current_apply = apply_stack.pop()
current_inputs = current_apply.inputs
current_outputs = current_apply.outputs
current_deps = current_inputs + current_apply.destroy_dependencies
computed_ins = all(compute_map[v][0] for v in current_deps)
computed_outs = all(compute_map[v][0] for v in current_outputs)
if not thunks[self.node_idx[current_apply]].lazy:
#
# stack loop: Normal Non-Lazy Case
# ================================
#
# Check if all inputs are in place
# If so compute thunk and remove it from the apply_stack
# If not leave it in, and add to the apply_stack those
# that will produce you those inputs
if computed_ins and not computed_outs:
# -- Non-lazy case: have inputs, time to compute outputs
try:
_, dt = self.run_thunk_of_node(current_apply)
del _
if config.profile or config.print_global_stats:
current_idx = self.node_idx[current_apply]
self.call_counts[current_idx] += 1
self.call_times[current_idx] += dt
# Computing the memory footprint of the the op
# ?? What about inplace .. if the op is inplace
# you don't actually ask for more memory!
for (idx, o) in enumerate(thunks[
self.node_idx[current_apply]].outputs):
var = self.nodes[current_idx].outputs[idx]
if hasattr(var.type, "get_shape_info"):
sh = var.type.get_shape_info(o[0])
else:
sh = "no shape"
self.variable_shape[var] = sh
st = getattr(o[0], "strides", "no strides")
if (getattr(o[0], "flags", False)
and o[0].flags.c_contiguous):
st = "c"
elif (hasattr(o[0], "is_c_contiguous")
and o[0].is_c_contiguous()):
st = "c"
self.variable_strides[var] = st
off = getattr(o[0], "offset", "")
self.variable_offset[var] = off
except Exception:
raise_with_op(
self.fgraph,
current_apply,
self.thunks[self.node_idx[current_apply]],
storage_map=storage_map,
)
for o in current_apply.outputs:
compute_map[o][0] = 1
input_index = []
# A list store the index of inputs variables
if self.allow_gc:
for i in current_apply.inputs:
# Garbage Collection -> check if anybody else uses
# this input
if dependencies[
i] and i.owner and i not in self.outputs:
if all(compute_map[v][0]
for v in dependencies[i]):
storage_map[i][0] = None
input_index.append(
current_apply.inputs.index(i))
# DO NOT set compute_map to 0
# If values become False and the
# current_apply is still in the
# stack, this will cause it to be
# recomputed! This can cause wrong value
# with some combination of inplace op.
compute_map[i][0] = 2
if (config.warn__vm_gc_bug
and current_apply in apply_stack
and getattr(
current_apply.op,
"destroy_map", False)):
warnings.warn(
"There was a bug that existed in "
"the default Theano configuration,"
" only in the development version "
"between July 5th 2012 and "
"July 30th 2012. This was not in "
"a released version. The bug was "
"affecting this script.",
# The stack level is not good when
# inside a Scan.
stacklevel=3,
)
self.node_cleared_order.append(input_index)
elif not computed_ins:
# -- Non-lazy case, need inputs
apply_stack.append(current_apply)
apply_stack.extend(inp.owner for inp in current_deps
if inp.owner)
elif not computed_outs:
#
# stack loop: Lazy Evaluation Case
# ================================
#
# Lazy evaluation protocol is to run the thunk with the
# current storage_map and compute_map accessed via closure,
# and the thunk will return a list of variables from its input
# list that it requires.
try:
requires, dt = self.run_thunk_of_node(current_apply)
current_idx = self.node_idx[current_apply]
self.call_counts[current_idx] += 1
self.call_times[current_idx] += dt
except Exception:
raise_with_op(
self.fgraph,
current_apply,
self.thunks[self.node_idx[current_apply]],
storage_map=storage_map,
)
if requires:
for r in requires:
# We are not done with this op .. so we added
# back and see to get the inputs we are
# missing
apply_stack.append(current_apply)
if current_apply.inputs[r].owner:
apply_stack.append(current_apply.inputs[r].owner)
else:
if config.profile or config.print_global_stats:
for (idx, o) in enumerate(
thunks[self.node_idx[current_apply]].outputs):
var = self.nodes[
self.node_idx[current_apply]].outputs[idx]
if hasattr(var.type, "get_shape_info"):
sh = var.type.get_shape_info(o[0])
else:
sh = "no shape"
self.variable_shape[var] = sh
st = getattr(o[0], "strides", "no strides")
if (getattr(o[0], "flags", False)
and o[0].flags.c_contiguous):
st = "c"
elif (hasattr(o[0], "is_c_contiguous")
and o[0].is_c_contiguous()):
st = "c"
self.variable_strides[var] = st
off = getattr(o[0], "offset", "")
self.variable_offset[var] = off
input_index = []
if self.allow_gc:
for i in current_apply.inputs:
if dependencies[
i] and i.owner and i not in self.outputs:
empty_storage_map = True
for x in dependencies[i]:
if not compute_map[x][0]:
empty_storage_map = False
break
if empty_storage_map:
storage_map[i][0] = None
input_index.append(
current_apply.inputs.index(i))
# See the not lazy gc code for explanations
# of compute_map change
compute_map[i][0] = 2
self.node_cleared_order.append(input_index)
# Hacky coarse gc final pass
# This is required until we have a proper gc algorithm for graphs with
# lazy evaluation. See discussion on theano-dev June 19 2012.
final_index = []
if self.allow_gc:
for v in storage_map:
if v.owner and v not in self.outputs:
if compute_map[v][0] == 2:
continue
else:
storage_map[v][0] = None
final_index.append(v)
compute_map[v][0] = 2
self.node_cleared_order.append(final_index)