提交 5f2ae036 authored 作者: Caglar's avatar Caglar

changed the order in the if condition and remove the while loop.

上级 6fe5f212
......@@ -206,7 +206,10 @@ def remove_constants_and_unused_inputs_scan(node):
# This is a global opt for historical reason
# It should be possible to change it to a local opt.
class PushOutNonSeqScan(gof.Optimizer):
"""
A global optimizer for pushing out the variables from scan that are not
used inside the scan.
"""
def __init__(self):
gof.Optimizer.__init__(self)
......@@ -220,24 +223,31 @@ class PushOutNonSeqScan(gof.Optimizer):
self.process_node(fgraph, node)
def process_node(self, fgraph, node):
"""
Important note: This function uses set and dictionary data structure.
By default they are not ordered for efficiency reasons. Take care and make
sure of changing them to Ordered versions if you need to iterate over those
variables.
"""
# this flag tells if there was any change during the last iterations
changed = True
clean_inputs, clean_outputs = scan_utils.reconstruct_graph(
node.op.inputs, node.op.outputs)
local_fgraph = gof.FunctionGraph(clean_inputs, clean_outputs, clone=False)
local_fgraph = gof.FunctionGraph(clean_inputs,
clean_outputs,
clone=False)
local_fgraph_topo = local_fgraph.toposort()
local_fgraph_outs_set = set(local_fgraph.outputs)
local_fgraph_outs_map = dict([(v, k) for k,v in enumerate(local_fgraph.outputs)])
max_iterations = 2 * len(local_fgraph_topo) + 3
counts = 0
to_remove_set = set()
to_remove_add = to_remove_set.add
to_replace_set = set()
to_replace_add = to_replace_set.add
to_replace_map = {}
to_replace_map = OrderedDict()
nto_replace = 0
def add_to_replace(y, nto_replace):
to_replace_add(y)
to_replace_map[y] = nto_replace
......@@ -245,6 +255,7 @@ class PushOutNonSeqScan(gof.Optimizer):
replace_with_in = []
replace_with_out = []
op = node.op
# Construct the list of non_sequences to simplify a few things
inner_non_seqs = op.inner_non_seqs(clean_inputs)
......@@ -259,65 +270,55 @@ class PushOutNonSeqScan(gof.Optimizer):
assert len(inner_non_seqs) == len(outer_non_seqs)
assert len(inner_seqs) == len(outer_seqs)
while changed and counts < max_iterations:
counts += 1
changed = False
for nd in local_fgraph_topo:
if (all([(x in inner_non_seqs_set) or
(x.owner in to_remove_set) or
isinstance(x, tensor.Constant)
for x in nd.inputs]) and
# we can do this because the assumption is that a
# viewOp or deepCopyOp will be just at the end of the
# function and not somewhere in the middle ..
not isinstance(nd.op, theano.compile.ViewOp) and
not isinstance(nd.op, theano.compile.DeepCopyOp) and
# and we didn't already looked at this node
nd not in to_remove_set):
# We have a candidate node to removable
# Step 1. Reconstruct it on outside
to_remove_add(nd)
outside_ins = []
for x in nd.inputs:
if x in inner_non_seqs_set:
_idx = inner_non_seqs_map[x]
outside_ins.append(outer_non_seqs[_idx])
elif x in to_replace_set:
outside_ins.append(replace_with_out[to_replace_map[x]])
elif isinstance(x, theano.Constant):
outside_ins.append(x.clone())
else:
raise Exception(
('Error in the `scan_pushout_non_seq_'
'operations`. The optimization tries '
'to move some computation fron scan '
'which is not allowed to move. Report '
'this on theano-users list'), x)
outside_ins = [x.type.filter_variable(y) for x, y in
zip(nd.inputs, outside_ins)]
# Do not call make_node for test_value
nw_outer_node = nd.op(*outside_ins,
**dict(return_list=True))[0].owner
# Step 2. Create variables for replacements
for idx, y in enumerate(nd.outputs):
y_place_holder = scan_utils.safe_new(y, '_replace')
nto_replace = add_to_replace(y, nto_replace)
replace_with_in.append(y_place_holder)
assert isinstance(y, type(nw_outer_node.outputs[idx]))
replace_with_out.append(nw_outer_node.outputs[idx])
changed = True
if counts >= max_iterations:
raise Exception('Error in the `scan_pushout_non_seq_operations`.'
' The optimization exhausted the maximal number '
'of iterations allowed!')
for nd in local_fgraph_topo:
if (# we haven't already looked at this node
nd not in to_remove_set and
all([((x in inner_non_seqs_set) or
(x.owner in to_remove_set) or
isinstance(x, tensor.Constant))
for x in nd.inputs]) and
# we can do this because the assumption is that a
# viewOp or deepCopyOp will be just at the end of the
# function and not somewhere in the middle ..
not isinstance(nd.op, theano.compile.ViewOp) and
not isinstance(nd.op, theano.compile.DeepCopyOp)):
# We have a candidate node to removable
# Step 1. Reconstruct it on outside
to_remove_add(nd)
outside_ins = []
for x in nd.inputs:
if x in inner_non_seqs_set:
_idx = inner_non_seqs_map[x]
outside_ins.append(outer_non_seqs[_idx])
elif x in to_replace_set:
outside_ins.append(replace_with_out[to_replace_map[x]])
elif isinstance(x, theano.Constant):
outside_ins.append(x.clone())
else:
raise Exception(
('Error in the `scan_pushout_non_seq_'
'operations`. The optimization tries '
'to move some computation fron scan '
'which is not allowed to move. Report '
'this on theano-users list'), x)
outside_ins = [x.type.filter_variable(y) for x, y in
zip(nd.inputs, outside_ins)]
# Do not call make_node for test_value
nw_outer_node = nd.op(*outside_ins,
**dict(return_list=True))[0].owner
# Step 2. Create variables for replacements
for idx, y in enumerate(nd.outputs):
y_place_holder = scan_utils.safe_new(y, '_replace')
nto_replace = add_to_replace(y, nto_replace)
replace_with_in.append(y_place_holder)
assert isinstance(y, type(nw_outer_node.outputs[idx]))
replace_with_out.append(nw_outer_node.outputs[idx])
# We need to check all candidate replacements and choose those that
# make sense for us
# Step 1. which elements of `to_replace` are used by remaining
# components of the inner function
clean_to_replace = []
......@@ -330,11 +331,11 @@ class PushOutNonSeqScan(gof.Optimizer):
to_keep_set = set(to_keep)
for out, idx in to_replace_map.items():
if (out in to_keep_set
and out.owner not in existent_nodes_set
# If types are different, conversion Op will be inserted,
# and it may trigger an infinite loop.
and replace_with_in[idx].type == out.type):
if (# If types are different, conversion Op will be inserted,
# and it may trigger an infinite loop.
replace_with_in[idx].type == out.type and
out in to_keep_set and
out.owner not in existent_nodes_set):
clean_to_replace.append(out)
clean_replace_with_in.append(replace_with_in[idx])
clean_replace_with_out.append(replace_with_out[idx])
......@@ -356,6 +357,7 @@ class PushOutNonSeqScan(gof.Optimizer):
_op_outs = scan_utils.clone(clean_outputs,
replace=givens)
_op_ins = clean_inputs + nw_inner
op_ins, op_outs = scan_utils.reconstruct_graph(_op_ins, _op_outs)
# Reconstruct node
......@@ -398,7 +400,10 @@ class PushOutNonSeqScan(gof.Optimizer):
# This is a global opt for historical reason
# It should be possible to change it to a local opt.
class PushOutSeqScan(gof.Optimizer):
"""
A global optimizer for pushing out the input variables that are not being
used inside the scan and provided in the sequences.
"""
def __init__(self):
gof.Optimizer.__init__(self)
......@@ -412,8 +417,13 @@ class PushOutSeqScan(gof.Optimizer):
self.process_node(fgraph, node)
def process_node(self, fgraph, node):
"""
Important note: This function uses set and dictionary data structure.
By default they are not ordered for efficiency reasons. Take care and make
sure of changing them to Ordered versions if you need to iterate over those
variables.
"""
# this flag tells if there was any change during the last iterations
changed = True
clean_inputs, clean_outputs = scan_utils.reconstruct_graph(
node.op.inputs, node.op.outputs)
......@@ -422,14 +432,11 @@ class PushOutSeqScan(gof.Optimizer):
local_fgraph_outs_set = set(local_fgraph.outputs)
local_fgraph_outs_map = dict([(v,k) for k,v in enumerate(local_fgraph.outputs)])
max_iterations = 2 * len(local_fgraph_topo) + 3
counts = 0
to_remove_set = set()
to_remove_add = to_remove_set.add
to_replace_set = set()
to_replace_add = to_replace_set.add
to_replace_map = {}
to_replace_map = OrderedDict()
nto_replace = 0
def add_to_replace(y, nto_replace):
......@@ -455,102 +462,90 @@ class PushOutSeqScan(gof.Optimizer):
assert len(inner_non_seqs) == len(outer_non_seqs)
assert len(inner_seqs) == len(outer_seqs)
while changed and counts < max_iterations:
counts += 1
changed = False
for nd in local_fgraph_topo:
if (isinstance(nd.op, theano.tensor.Elemwise) and
all([(x in inner_non_seqs_set) or
(x.owner in to_remove_set) or
isinstance(x, tensor.Constant) or
(x in inner_seqs_set)
for x in nd.inputs]) and
nd not in to_remove_set):
to_remove_add(nd)
outside_ins = []
depends_on_seqs = False
for x in nd.inputs:
if x in inner_non_seqs_set:
_idx = inner_non_seqs_map[x]
outside_ins.append(outer_non_seqs[_idx])
elif x in inner_seqs_set:
outside_ins.append(outer_seqs[inner_seqs_map[x]])
depends_on_seqs = True
elif x in to_replace_set:
outside_ins.append(replace_with_out[
to_replace_map[x]])
depends_on_seqs = True
elif isinstance(x, theano.Constant):
outside_ins.append(x.clone())
else:
raise Exception(
('Error in the `scan_pushout_seq_'
'operations`. The optimization tries '
'to move some computation fron scan '
'which is not allowed to move. Report '
'this on theano-users list'), x)
if not depends_on_seqs:
# Removing this node from the inner graph of scan
# should be handled by the PushOutNonSeqScan
# optimization. The current optimization only tries
# to pull sequence-dependant computation out of
# scan.
continue
# Do not call make_node for test_value
nw_outer_node = nd.op(*outside_ins,
**dict(return_list=True))[0].owner
# Step 2. Create variables for replacements
for idx, y in enumerate(nd.outputs):
y_place_holder = scan_utils.safe_new(y, '_replace')
nto_replace = add_to_replace(y, nto_replace)
replace_with_in.append(y_place_holder)
replace_with_out.append(nw_outer_node.outputs[idx])
changed = True
elif (isinstance(nd.op, theano.tensor.DimShuffle) and
(nd.inputs[0] in inner_seqs_set or
nd.inputs[0].owner in to_remove_set) and
not nd in to_remove_set):
to_remove_add(nd)
x = nd.inputs[0]
if x in inner_seqs_set:
outside_ins = outer_seqs[inner_seqs_map[x]]
for nd in local_fgraph_topo:
if (nd not in to_remove_set and
all([(x in inner_non_seqs_set) or
(x.owner in to_remove_set) or
isinstance(x, tensor.Constant) or
(x in inner_seqs_set) for x in nd.inputs]) and
isinstance(nd.op, theano.tensor.Elemwise)):
to_remove_add(nd)
outside_ins = []
depends_on_seqs = False
for x in nd.inputs:
if x in inner_non_seqs_set:
_idx = inner_non_seqs_map[x]
outside_ins.append(outer_non_seqs[_idx])
elif x in inner_seqs_set:
outside_ins.append(outer_seqs[inner_seqs_map[x]])
depends_on_seqs = True
elif x in to_replace_set:
outside_ins = replace_with_out[to_replace_map[x]]
new_ord = (0,)
for old_ord in nd.op.new_order:
if (old_ord == 'x'):
new_ord += (old_ord,)
else:
new_ord += (old_ord + 1,)
new_outer = outside_ins.dimshuffle(new_ord)
y = nd.outputs[0]
outside_ins.append(replace_with_out[
to_replace_map[x]])
depends_on_seqs = True
elif isinstance(x, theano.Constant):
outside_ins.append(x.clone())
else:
raise Exception(
('Error in the `scan_pushout_seq_'
'operations`. The optimization tries '
'to move some computation fron scan '
'which is not allowed to move. Report '
'this on theano-users list'), x)
if not depends_on_seqs:
# Removing this node from the inner graph of scan
# should be handled by the PushOutNonSeqScan
# optimization. The current optimization only tries
# to pull sequence-dependant computation out of
# scan.
continue
# Do not call make_node for test_value
nw_outer_node = nd.op(*outside_ins,
**dict(return_list=True))[0].owner
# Step 2. Create variables for replacements
for idx, y in enumerate(nd.outputs):
y_place_holder = scan_utils.safe_new(y, '_replace')
nto_replace = add_to_replace(y, nto_replace)
replace_with_in.append(y_place_holder)
replace_with_out.append(new_outer)
if hasattr(new_outer.tag, "test_value"):
new_sh = new_outer.tag.test_value.shape
ref_sh = (outside_ins.tag.test_value.shape[0],)
ref_sh += nd.outputs[0].tag.test_value.shape
assert new_sh == ref_sh
changed = True
replace_with_out.append(nw_outer_node.outputs[idx])
elif (nd not in to_remove_set and
isinstance(nd.op, theano.tensor.DimShuffle) and
(nd.inputs[0] in inner_seqs_set or
nd.inputs[0].owner in to_remove_set)):
to_remove_add(nd)
x = nd.inputs[0]
if x in inner_seqs_set:
outside_ins = outer_seqs[inner_seqs_map[x]]
elif x in to_replace_set:
outside_ins = replace_with_out[to_replace_map[x]]
new_ord = (0,)
for old_ord in nd.op.new_order:
if (old_ord == 'x'):
new_ord += (old_ord,)
else:
new_ord += (old_ord + 1,)
new_outer = outside_ins.dimshuffle(new_ord)
y = nd.outputs[0]
y_place_holder = scan_utils.safe_new(y, '_replace')
nto_replace = add_to_replace(y, nto_replace)
replace_with_in.append(y_place_holder)
replace_with_out.append(new_outer)
if hasattr(new_outer.tag, "test_value"):
new_sh = new_outer.tag.test_value.shape
ref_sh = (outside_ins.tag.test_value.shape[0],)
ref_sh += nd.outputs[0].tag.test_value.shape
assert new_sh == ref_sh
if counts >= max_iterations:
raise Exception('Error in the `scan_pushout_seq_operations`.'
' The optimization exhausted the maximal number '
'of iterations allowed!')
# We need to check all candidate replacements and choose those that
# make sense for us
# Step 1. which elements of `to_replace` are used by remaining
# components of the inner function
clean_to_replace = []
......@@ -565,10 +560,10 @@ class PushOutSeqScan(gof.Optimizer):
for out, idx in to_replace_map.items():
if (out in to_keep_set
and out.owner not in existent_nodes_set
# If types are different, conversion Op will be inserted,
# and it may trigger an infinite loop.
and replace_with_in[idx].type == out.type):
and out.owner not in existent_nodes_set
# If types are different, conversion Op will be inserted,
# and it may trigger an infinite loop.
and replace_with_in[idx].type == out.type):
clean_to_replace.append(out)
clean_replace_with_in.append(replace_with_in[idx])
......@@ -684,10 +679,8 @@ class PushOutScanOutput(gof.Optimizer):
new_scan_node = None
local_fgraph_topo = local_fgraph.toposort()
for nd in local_fgraph_topo:
if (isinstance(nd.op, theano.tensor.Dot) and
nd.out in args.inner_out_nit_sot):
"""
The following optimization involves pushing out, after the
scan, a Dot whose output is nitsot (not feed back to the inner
......@@ -857,9 +850,7 @@ class PushOutScanOutput(gof.Optimizer):
outer_var = scan_args.outer_out_sit_sot[idx]
if len(outer_var.clients) == 1:
client = outer_var.clients[0][0]
if (client != 'output' and
isinstance(client.op, theano.tensor.Subtensor)):
lst = theano.tensor.subtensor.get_idx_list(
......
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