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提交 9755603b authored 作者: Frederic's avatar Frederic
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正在显示 包含 40 行增加 和 44 行删除
theano/scan_module/scan_opt.py
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......@@ -66,7 +66,7 @@ def remove_constants_and_unused_inputs_scan(node):
# We only need to take care of sequences and other arguments
st = op.n_seqs
st += int(numpy.sum([len(x) for x in
op.tap_array[:(op.n_mit_mot + op.n_mit_sot)]]))
op.tap_array[:(op.n_mit_mot + op.n_mit_sot)]]))
st += op.n_sit_sot
st += op.n_shared_outs
op_ins, op_outs = scan_utils.reconstruct_graph(op.inputs, op.outputs)
......@@ -105,8 +105,8 @@ def remove_constants_and_unused_inputs_scan(node):
elif op_ins[idx] in all_ins:
# Check for identical other sequence
identical_seqs = [x for x in nw_outer
if scan_utils.equal_computations(
[x], [node.inputs[idx + 1]])]
if scan_utils.equal_computations(
[x], [node.inputs[idx + 1]])]
if identical_seqs:
index = node.inputs.index(identical_seqs[0]) - 1
givens[op_ins[idx]] = op_ins[index]
......@@ -162,7 +162,7 @@ class PushOutNonSeqScan(gof.Optimizer):
def apply(self, fgraph):
nodelist = [x for x in fgraph.toposort() if isinstance(x.op,
scan_op.Scan)]
scan_op.Scan)]
for node in nodelist:
self.process_node(fgraph, node)
......@@ -170,7 +170,7 @@ class PushOutNonSeqScan(gof.Optimizer):
# 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)
node.op.inputs, node.op.outputs)
local_fgraph = gof.FunctionGraph(clean_inputs, clean_outputs)
max_iterations = 2 * len(local_fgraph.toposort()) + 3
......@@ -196,7 +196,7 @@ class PushOutNonSeqScan(gof.Optimizer):
if (numpy.all([(x in inner_non_seqs) or
(x.owner in to_remove) or
isinstance(x, tensor.Constant)
for x in nd.inputs]) and
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 ..
......@@ -250,7 +250,7 @@ class PushOutNonSeqScan(gof.Optimizer):
clean_replace_with_in = []
clean_replace_with_out = []
existent_nodes = [nd for nd in local_fgraph.toposort()
if nd not in to_remove]
if nd not in to_remove]
to_keep = []
for nd in existent_nodes:
to_keep += nd.inputs
......@@ -270,8 +270,8 @@ class PushOutNonSeqScan(gof.Optimizer):
nw_outer = []
nw_inner = []
for to_repl, repl_in, repl_out in zip(clean_to_replace,
clean_replace_with_in,
clean_replace_with_out):
clean_replace_with_in,
clean_replace_with_out):
if isinstance(repl_out, theano.Constant):
repl_in = repl_out.clone()
else:
......@@ -327,8 +327,8 @@ class PushOutSeqScan(gof.Optimizer):
fgraph.attach_feature(gof.toolbox.ReplaceValidate())
def apply(self, fgraph):
nodelist = [x for x in fgraph.toposort() if isinstance(x.op,
scan_op.Scan)]
nodelist = [x for x in fgraph.toposort()
if isinstance(x.op, scan_op.Scan)]
for node in nodelist:
self.process_node(fgraph, node)
......@@ -336,7 +336,7 @@ class PushOutSeqScan(gof.Optimizer):
# 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)
node.op.inputs, node.op.outputs)
local_fgraph = gof.FunctionGraph(clean_inputs, clean_outputs)
max_iterations = 2 * len(local_fgraph.toposort()) + 3
......@@ -361,12 +361,12 @@ class PushOutSeqScan(gof.Optimizer):
for nd in local_fgraph.toposort():
if (isinstance(nd.op, theano.tensor.Elemwise) and
numpy.all([(x in inner_non_seqs) or
(x.owner in to_remove) or
isinstance(x, tensor.Constant) or
(x in inner_seqs)
for x in nd.inputs]) and
not nd in to_remove):
numpy.all([(x in inner_non_seqs) or
(x.owner in to_remove) or
isinstance(x, tensor.Constant) or
(x in inner_seqs)
for x in nd.inputs]) and
not nd in to_remove):
to_remove.append(nd)
outside_ins = []
for x in nd.inputs:
......@@ -376,8 +376,8 @@ class PushOutSeqScan(gof.Optimizer):
elif x in inner_seqs:
outside_ins += [outer_seqs[inner_seqs.index(x)]]
elif x in to_replace:
outside_ins += [replace_with_out[\
to_replace.index(x)]]
outside_ins += [replace_with_out[
to_replace.index(x)]]
elif isinstance(x, theano.Constant):
outside_ins += [x.clone()]
else:
......@@ -436,7 +436,7 @@ class PushOutSeqScan(gof.Optimizer):
clean_replace_with_out = []
existent_nodes = [nd for nd in local_fgraph.toposort()
if nd not in to_remove]
if nd not in to_remove]
to_keep = []
for nd in existent_nodes:
to_keep += nd.inputs
......@@ -456,8 +456,8 @@ class PushOutSeqScan(gof.Optimizer):
nw_outer = []
nw_inner = []
for to_repl, repl_in, repl_out in zip(clean_to_replace,
clean_replace_with_in,
clean_replace_with_out):
clean_replace_with_in,
clean_replace_with_out):
if isinstance(repl_out, theano.Constant):
repl_in = repl_out.clone()
else:
......@@ -532,7 +532,7 @@ class ScanInplaceOptimizer(Optimizer):
nodes = fgraph.toposort()
scan_nodes = [x for x in nodes
if (isinstance(x.op, scan_op.Scan) and
x.op.info['gpu'] == self.gpu_flag)]
x.op.info['gpu'] == self.gpu_flag)]
for scan_idx in xrange(len(scan_nodes)):
node = scan_nodes[scan_idx]
op = node.op
......@@ -720,7 +720,7 @@ class ScanSaveMem(gof.Optimizer):
except KeyError:
length = out.shape[0]
cf_slice = tensor.get_canonical_form_slice(
this_slice[0], length)
this_slice[0], length)
slices[i] += [(cf_slice, this_slice)]
if (isinstance(this_slice[0], slice) and
......@@ -847,9 +847,8 @@ class ScanSaveMem(gof.Optimizer):
nw_inputs[0] = nw_steps
# 3.2 check orphane outputs to see if we can eliminate any
required, not_required = \
scan_utils.scan_can_remove_outs(node.op,
orphane_outs)
required, not_required = scan_utils.scan_can_remove_outs(
node.op, orphane_outs)
# 3.3. compose replace pairs for those nodes that need not
# to store everything in memory ( or ar orphane and required
# by the inner function .. )
......@@ -978,7 +977,7 @@ class ScanSaveMem(gof.Optimizer):
sl_ins = tensor.Subtensor.collapse(
nw_slice,
lambda entry: isinstance(entry,
tensor.Variable))
tensor.Variable))
new_o = subtens.make_node(new_outs[nw_pos],
*sl_ins).outputs[0]
if new_o.ndim > 0:
......@@ -1009,11 +1008,10 @@ class ScanSaveMem(gof.Optimizer):
else:
position = (cnf_slice[0] - nw_steps -
init_l[pos] + store_steps[pos])
nw_slice = (sanitize(position),) + \
tuple(old_slices[1:])
init_l[pos] + store_steps[pos])
nw_slice = (sanitize(position),) + tuple(
old_slices[1:])
subtens = tensor.Subtensor(nw_slice)
sl_ins = tensor.Subtensor.collapse(
nw_slice,
......@@ -1047,7 +1045,7 @@ class ScanSaveMem(gof.Optimizer):
def apply(self, fgraph):
nodelist = [x for x in fgraph.toposort() if isinstance(x.op,
scan_op.Scan)]
scan_op.Scan)]
for node in nodelist:
if not hasattr(node.op, '_scan_savemem_visited'):
self.process_node(fgraph, node)
......@@ -1389,13 +1387,13 @@ def scan_merge_inouts(node):
# items scan is supposed to store for this nit_sot sequence
shapes.append(x)
tmp = [map_nitsot_out(i, o, sh, seen)
for i, o, sh in zip(na.inner_out_nit_sot,
na.outer_out_nit_sot,
shapes)]
for i, o, sh in zip(na.inner_out_nit_sot,
na.outer_out_nit_sot,
shapes)]
na.outer_out_nit_sot = [map_nitsot_out(i, o, sh, seen)
for i, o, sh in zip(na.inner_out_nit_sot,
na.outer_out_nit_sot,
shapes)]
na.outer_out_nit_sot,
shapes)]
seen = []
na.outer_out_sit_sot = [map_out(i, o, seen)
......@@ -1592,10 +1590,8 @@ class PushOutDot1(gof.Optimizer):
old = node.outputs[pos].clients[0][0].outputs[0]
old_new.append((old, new_out))
old_new += zip(node.outputs[pos+1:], new_outs[pos:])
fgraph.replace_all_validate_remove(old_new,
remove = [node],
reason='scan_pushout_dot1')
fgraph.replace_all_validate_remove(
old_new, remove=[node], reason='scan_pushout_dot1')
# I've added an equilibrium because later scan optimization in the sequence
......@@ -1612,7 +1608,7 @@ optdb.register('scan_eqopt1', scan_eqopt1, .1, 'fast_run', 'scan')
optdb.register('scan_eqopt2', scan_eqopt2, 1.6, 'fast_run', 'scan')
optdb.register('scanOp_make_inplace',
ScanInplaceOptimizer(typeConstructor=None,
gpu_flag=False),
gpu_flag=False),
75,
'fast_run',
'inplace',
......
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