提交 04a07601 authored 作者: Caglar's avatar Caglar

flake8 changes and made the comment more visible.

上级 5f2ae036
...@@ -26,13 +26,16 @@ scan_eqopt2 -> They are all global optimizer. (in2out convert local to global). ...@@ -26,13 +26,16 @@ scan_eqopt2 -> They are all global optimizer. (in2out convert local to global).
registered. (So don't change the order we register them!) registered. (So don't change the order we register them!)
If we convert to local optimizer, we must convert all of them If we convert to local optimizer, we must convert all of them
to local optimizer. But: to local optimizer. But:
1) can ScanMerge be made local? Can we keep only this one global? 1) can ScanMerge be made local? Can we keep only this one
global?
2) ScanSaveMem assert that we remove all nodes outputs, 2) ScanSaveMem assert that we remove all nodes outputs,
we need to keep this. we need to keep this.
3) It is ScanSaveMem suppose the the others ran before. 3) It is ScanSaveMem suppose the the others ran before.
I added an assert at one place, but didn't looked for other place. I added an assert at one place, but didn't looked for
other place.
4) Moving this to local opt could speed up significant this opt, 4) Moving this to local opt could speed up significant this opt,
as we pass frequently on all nodes in the graph for no good reason. as we pass frequently on all nodes in the graph for no
good reason.
5) We register remove_constant_* many places, as some 5) We register remove_constant_* many places, as some
opt create them and let this one clean up the mess. opt create them and let this one clean up the mess.
Doing it that way, make things simpler for those already Doing it that way, make things simpler for those already
...@@ -70,14 +73,16 @@ from theano.compat import OrderedDict ...@@ -70,14 +73,16 @@ from theano.compat import OrderedDict
from six import integer_types, iteritems from six import integer_types, iteritems
from six.moves import xrange from six.moves import xrange
from theano.gof.opt import Optimizer from theano.gof.opt import Optimizer
from theano.gof.opt import pre_constant_merge, pre_greedy_local_optimizer
from theano.gof import toolbox, DestroyHandler, InconsistencyError from theano.gof import toolbox, DestroyHandler, InconsistencyError
from theano.compile import optdb from theano.compile import optdb
from theano.compile.function_module import deep_copy_op from theano.compile.function_module import deep_copy_op
from theano.scan_module import scan_op from theano.scan_module import scan_op
from theano.scan_module import scan_utils from theano.scan_module import scan_utils
from theano.scan_module.scan_utils import equal_computations, find_up, scan_args from theano.scan_module.scan_utils import equal_computations, find_up, \
from theano.gof.opt import pre_constant_merge, pre_greedy_local_optimizer scan_args
# Logging function for sending warning or info # Logging function for sending warning or info
_logger = logging.getLogger('theano.scan_module.scan_opt') _logger = logging.getLogger('theano.scan_module.scan_opt')
...@@ -207,8 +212,8 @@ def remove_constants_and_unused_inputs_scan(node): ...@@ -207,8 +212,8 @@ def remove_constants_and_unused_inputs_scan(node):
# It should be possible to change it to a local opt. # It should be possible to change it to a local opt.
class PushOutNonSeqScan(gof.Optimizer): class PushOutNonSeqScan(gof.Optimizer):
""" """
A global optimizer for pushing out the variables from scan that are not A global optimizer for pushing out the variables inside the scan that
used inside the scan. are not used by the scan.
""" """
def __init__(self): def __init__(self):
gof.Optimizer.__init__(self) gof.Optimizer.__init__(self)
...@@ -224,10 +229,10 @@ class PushOutNonSeqScan(gof.Optimizer): ...@@ -224,10 +229,10 @@ class PushOutNonSeqScan(gof.Optimizer):
def process_node(self, fgraph, node): def process_node(self, fgraph, node):
""" """
Important note: This function uses set and dictionary data structure. Important note: This function uses set and dictionary data structure.
By default they are not ordered for efficiency reasons. Take care and make By default they are not ordered for efficiency reasons. Take care
sure of changing them to Ordered versions if you need to iterate over those and make sure of changing them to Ordered versions if you need to
variables. iterate over those variables.
""" """
# this flag tells if there was any change during the last iterations # this flag tells if there was any change during the last iterations
clean_inputs, clean_outputs = scan_utils.reconstruct_graph( clean_inputs, clean_outputs = scan_utils.reconstruct_graph(
...@@ -239,7 +244,8 @@ class PushOutNonSeqScan(gof.Optimizer): ...@@ -239,7 +244,8 @@ class PushOutNonSeqScan(gof.Optimizer):
local_fgraph_topo = local_fgraph.toposort() local_fgraph_topo = local_fgraph.toposort()
local_fgraph_outs_set = set(local_fgraph.outputs) local_fgraph_outs_set = set(local_fgraph.outputs)
local_fgraph_outs_map = dict([(v, k) for k,v in enumerate(local_fgraph.outputs)]) local_fgraph_outs_map = dict([(v, k) for k, v in \
enumerate(local_fgraph.outputs)])
to_remove_set = set() to_remove_set = set()
to_remove_add = to_remove_set.add to_remove_add = to_remove_set.add
...@@ -401,7 +407,7 @@ class PushOutNonSeqScan(gof.Optimizer): ...@@ -401,7 +407,7 @@ class PushOutNonSeqScan(gof.Optimizer):
# It should be possible to change it to a local opt. # It should be possible to change it to a local opt.
class PushOutSeqScan(gof.Optimizer): class PushOutSeqScan(gof.Optimizer):
""" """
A global optimizer for pushing out the input variables that are not being A global optimizer for pushing out the input variables that are not being
used inside the scan and provided in the sequences. used inside the scan and provided in the sequences.
""" """
def __init__(self): def __init__(self):
...@@ -418,19 +424,21 @@ class PushOutSeqScan(gof.Optimizer): ...@@ -418,19 +424,21 @@ class PushOutSeqScan(gof.Optimizer):
def process_node(self, fgraph, node): def process_node(self, fgraph, node):
""" """
Important note: This function uses set and dictionary data structure. IMPORTANT NOTE: This function uses set and dictionary data structure.
By default they are not ordered for efficiency reasons. Take care and make By default they are not ordered for efficiency reasons. Take care
sure of changing them to Ordered versions if you need to iterate over those and make sure of changing them to Ordered versions if you need to
variables. iterate over those variables.
""" """
# this flag tells if there was any change during the last iterations # this flag tells if there was any change during the last iterations
clean_inputs, clean_outputs = scan_utils.reconstruct_graph( 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, clone=False) local_fgraph = gof.FunctionGraph(clean_inputs, clean_outputs,
clone=False)
local_fgraph_topo = local_fgraph.toposort() local_fgraph_topo = local_fgraph.toposort()
local_fgraph_outs_set = set(local_fgraph.outputs) local_fgraph_outs_set = set(local_fgraph.outputs)
local_fgraph_outs_map = dict([(v,k) for k,v in enumerate(local_fgraph.outputs)]) local_fgraph_outs_map = dict([(v,k) for k,v in \
enumerate(local_fgraph.outputs)])
to_remove_set = set() to_remove_set = set()
to_remove_add = to_remove_set.add to_remove_add = to_remove_set.add
...@@ -640,10 +648,9 @@ class PushOutSeqScan(gof.Optimizer): ...@@ -640,10 +648,9 @@ class PushOutSeqScan(gof.Optimizer):
class PushOutScanOutput(gof.Optimizer): class PushOutScanOutput(gof.Optimizer):
""" """
This optimization can push operations performed at the end of the inner This is an optimization that can push operations performed
graph of scan to outside of scan at the end of the inner graph of scan to outside of scan.
""" """
def __init__(self): def __init__(self):
gof.Optimizer.__init__(self) gof.Optimizer.__init__(self)
...@@ -756,7 +763,8 @@ class PushOutScanOutput(gof.Optimizer): ...@@ -756,7 +763,8 @@ class PushOutScanOutput(gof.Optimizer):
# Modify the outer graph to add the outer Dot # Modify the outer graph to add the outer Dot
fgraph.replace_all([ fgraph.replace_all([
(new_scan_args.outer_out_nit_sot[dot_out_nitsot_idx], (new_scan_args.outer_out_nit_sot[
dot_out_nitsot_idx],
outer_dot_output)], outer_dot_output)],
reason="scanOp_pushout_output") reason="scanOp_pushout_output")
...@@ -780,7 +788,8 @@ class PushOutScanOutput(gof.Optimizer): ...@@ -780,7 +788,8 @@ class PushOutScanOutput(gof.Optimizer):
# otherwise doing a Dot in the outer graph will only # otherwise doing a Dot in the outer graph will only
# duplicate computation. # duplicate computation.
sitsot_in_idx = nd.inputs.index(args.inner_in_sit_sot[sitsot_idx]) sitsot_in_idx = nd.inputs.index(args.inner_in_sit_sot[
sitsot_idx])
dot_in_idx = 1 - sitsot_in_idx # 0 if sitsot_in_idx==1, dot_in_idx = 1 - sitsot_in_idx # 0 if sitsot_in_idx==1,
# 1 if sitsot_in_idx==0 # 1 if sitsot_in_idx==0
...@@ -791,8 +800,10 @@ class PushOutScanOutput(gof.Optimizer): ...@@ -791,8 +800,10 @@ class PushOutScanOutput(gof.Optimizer):
len(dot_input.clients) == 1 and len(dot_input.clients) == 1 and
dot_input.owner.inputs[0].ndim == 2 and dot_input.owner.inputs[0].ndim == 2 and
dot_input.owner.inputs[1].ndim == 2 and dot_input.owner.inputs[1].ndim == 2 and
self.get_outer_ndim(dot_input.owner.inputs[0], args) == 3 and self.get_outer_ndim(dot_input.owner.inputs[0], args) \
self.get_outer_ndim(dot_input.owner.inputs[1], args) == 3): == 3 and
self.get_outer_ndim(dot_input.owner.inputs[1], args) \
== 3):
# The optimization can be be applied in this case. # The optimization can be be applied in this case.
...@@ -801,9 +812,10 @@ class PushOutScanOutput(gof.Optimizer): ...@@ -801,9 +812,10 @@ class PushOutScanOutput(gof.Optimizer):
inner_dot_inputs = nd.inputs[dot_in_idx].owner.inputs inner_dot_inputs = nd.inputs[dot_in_idx].owner.inputs
(outer_dot_inputs, (outer_dot_inputs,
new_scan_node, new_scan_node,
new_scan_args) = self.push_out_inner_vars(fgraph, new_scan_args) = \
inner_dot_inputs, self.push_out_inner_vars(fgraph,
node, args) inner_dot_inputs,
node, args)
# Collapse some of the dimensions of the tensors # Collapse some of the dimensions of the tensors
# so that they become matrices. This is because a # so that they become matrices. This is because a
...@@ -814,20 +826,23 @@ class PushOutScanOutput(gof.Optimizer): ...@@ -814,20 +826,23 @@ class PushOutScanOutput(gof.Optimizer):
outdim=2) outdim=2)
shape_input1 = theano.tensor.shape(outer_dot_inputs[1]) shape_input1 = theano.tensor.shape(outer_dot_inputs[1])
outer_dot_inputs[1] = outer_dot_inputs[1].reshape((shape_input1[0] * outer_dot_inputs[1] =\
shape_input1[1], outer_dot_inputs[1].reshape((shape_input1[0] *
shape_input1[2])) shape_input1[1],
shape_input1[2]))
# Perform the dot on the newly obtained matrices and # Perform the dot on the newly obtained matrices and
# add the initial value # add the initial value
outer_dot_output = theano.tensor.dot(*outer_dot_inputs) outer_dot_output = theano.tensor.dot(*outer_dot_inputs)
init_value = new_scan_args.outer_in_sit_sot[sitsot_idx][0] init_value = \
new_scan_args.outer_in_sit_sot[sitsot_idx][0]
replacement = outer_dot_output + init_value replacement = outer_dot_output + init_value
# Alter the outer graph to use the output of the # Alter the outer graph to use the output of the
# external Dot instead of the output of scan # external Dot instead of the output of scan
# Modify the outer graph to add the outer Dot # Modify the outer graph to add the outer Dot
outer_sitsot = new_scan_args.outer_out_sit_sot[sitsot_idx] outer_sitsot = \
new_scan_args.outer_out_sit_sot[sitsot_idx]
subtensor_node = outer_sitsot.clients[0][0] subtensor_node = outer_sitsot.clients[0][0]
outer_sitsot_last_step = subtensor_node.outputs[0] outer_sitsot_last_step = subtensor_node.outputs[0]
...@@ -1295,7 +1310,8 @@ class ScanSaveMem(gof.Optimizer): ...@@ -1295,7 +1310,8 @@ class ScanSaveMem(gof.Optimizer):
# for mitsots and sitsots (because mitmots are not # for mitsots and sitsots (because mitmots are not
# currently supported by the mechanism) and only if # currently supported by the mechanism) and only if
# the pre-allocation mechanism is activated. # the pre-allocation mechanism is activated.
prealloc_outs = theano.config.scan.allow_output_prealloc prealloc_outs = \
theano.config.scan.allow_output_prealloc
first_mitsot_idx = node.op.n_mit_mot first_mitsot_idx = node.op.n_mit_mot
last_sitsot_idx = (node.op.n_mit_mot + last_sitsot_idx = (node.op.n_mit_mot +
...@@ -1317,11 +1333,13 @@ class ScanSaveMem(gof.Optimizer): ...@@ -1317,11 +1333,13 @@ class ScanSaveMem(gof.Optimizer):
# TODO: Simplify the number of steps needed. # TODO: Simplify the number of steps needed.
# FB: This need good testing, left to later. # FB: This need good testing, left to later.
# call get_scalar_constant_value()? it can # call get_scalar_constant_value()? it can
# return python/numpy scalar or numpy.ndarray currently. # return python/numpy scalar or numpy.ndarray
# currently.
# pval = pre_greedy_local_optimizer(list_opt_slice, # pval = pre_greedy_local_optimizer(list_opt_slice,
# pval) # pval)
#pval = pre_constant_merge([pval])[0] #pval = pre_constant_merge([pval])[0]
# if (isinstance(pval, theano.tensor.TensorConstant) and # if (isinstance(pval, theano.tensor.TensorConstant)
# and
# pval.dtype.startswith('int')): # pval.dtype.startswith('int')):
# try: # try:
# pval = int(pval.data) # pval = int(pval.data)
...@@ -1365,7 +1383,6 @@ class ScanSaveMem(gof.Optimizer): ...@@ -1365,7 +1383,6 @@ class ScanSaveMem(gof.Optimizer):
# a) the input is a set_subtensor, in that case we # a) the input is a set_subtensor, in that case we
# can replace the initial tensor by a slice, # can replace the initial tensor by a slice,
# b) it is not, and we simply take a slice of it. # b) it is not, and we simply take a slice of it.
# TODO: commit change below with Razvan # TODO: commit change below with Razvan
if (nw_inputs[offset + idx].owner and if (nw_inputs[offset + idx].owner and
isinstance(nw_inputs[offset + idx].owner.op, isinstance(nw_inputs[offset + idx].owner.op,
...@@ -1549,7 +1566,8 @@ class ScanSaveMem(gof.Optimizer): ...@@ -1549,7 +1566,8 @@ class ScanSaveMem(gof.Optimizer):
# 3.9. Get replace pairs for all other nodes # 3.9. Get replace pairs for all other nodes
if flag_store or global_nsteps is not None: if flag_store or global_nsteps is not None:
for idx, o in enumerate(node.outputs): for idx, o in enumerate(node.outputs):
if not (idx in replaced_outs) and not idx in not_required: if not (idx in replaced_outs) and \
not idx in not_required:
nw_pos = compress_map[idx] nw_pos = compress_map[idx]
old_new += [(o, new_outs[nw_pos])] old_new += [(o, new_outs[nw_pos])]
# Check if the new outputs depend on the old scan node # Check if the new outputs depend on the old scan node
...@@ -2090,12 +2108,16 @@ class PushOutDot1(gof.Optimizer): ...@@ -2090,12 +2108,16 @@ class PushOutDot1(gof.Optimizer):
new_info = op.info.copy() new_info = op.info.copy()
st = len(op.mitmot_taps()) + len(op.mitsot_taps()) st = len(op.mitmot_taps()) + len(op.mitsot_taps())
new_info['tap_array'] = (new_info['tap_array'][:st + idx] + new_info['tap_array'] = (\
new_info['tap_array'][st + idx + 1:]) new_info['tap_array'][:st + idx] +
new_info['tap_array'][st +
idx + 1:])
new_info['n_sit_sot'] -= 1 new_info['n_sit_sot'] -= 1
new_info['n_nit_sot'] += 1 new_info['n_nit_sot'] += 1
inner_sitsot = inner_sitsot[:idx] + inner_sitsot[idx + 1:] inner_sitsot = inner_sitsot[:idx] + \
outer_sitsot = outer_sitsot[:idx] + outer_sitsot[idx + 1:] inner_sitsot[idx + 1:]
outer_sitsot = outer_sitsot[:idx] + \
outer_sitsot[idx + 1:]
inner_sitsot_outs = inner_sitsot_outs[:idx] +\ inner_sitsot_outs = inner_sitsot_outs[:idx] +\
inner_sitsot_outs[idx + 1:] inner_sitsot_outs[idx + 1:]
# add n_steps as the length # add n_steps as the length
...@@ -2131,8 +2153,9 @@ class PushOutDot1(gof.Optimizer): ...@@ -2131,8 +2153,9 @@ class PushOutDot1(gof.Optimizer):
if type(new_outs) not in (list, tuple): if type(new_outs) not in (list, tuple):
new_outs = [new_outs] new_outs = [new_outs]
# We need now to pair correctly the new outputs with the # We need now to pair correctly the new outputs
# old ones # with the old ones
outer_mitmot_outs = new_op.outer_mitmot_outs(new_outs) outer_mitmot_outs = new_op.outer_mitmot_outs(new_outs)
outer_mitsot_outs = new_op.outer_mitsot_outs(new_outs) outer_mitsot_outs = new_op.outer_mitsot_outs(new_outs)
outer_sitsot_outs = new_op.outer_sitsot_outs(new_outs) outer_sitsot_outs = new_op.outer_sitsot_outs(new_outs)
...@@ -2171,7 +2194,8 @@ class PushOutDot1(gof.Optimizer): ...@@ -2171,7 +2194,8 @@ class PushOutDot1(gof.Optimizer):
old_new = list(zip(node.outputs[:pos], new_outs[:pos])) old_new = list(zip(node.outputs[:pos], new_outs[:pos]))
old = node.outputs[pos].clients[0][0].outputs[0] old = node.outputs[pos].clients[0][0].outputs[0]
old_new.append((old, new_out)) old_new.append((old, new_out))
old_new += list(zip(node.outputs[pos+1:], new_outs[pos:])) old_new += list(zip(node.outputs[pos+1:],
new_outs[pos:]))
fgraph.replace_all_validate_remove( fgraph.replace_all_validate_remove(
old_new, remove=[node], reason='scan_pushout_dot1') old_new, remove=[node], reason='scan_pushout_dot1')
......
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