提交 6e91c9d4 authored 作者: Frederic Bastien's avatar Frederic Bastien

white space fix.

上级 b69d2aae
......@@ -1147,18 +1147,18 @@ def apply_rebroadcast_opt(rval):
changed = True
while changed and rval.owner:
changed = False
rval2 = theano.tensor.opt.local_useless_rebroadcast.transform(rval.owner)
if rval2:
assert len(rval2)==1
rval = rval2[0]
changed = True
if rval.owner:
rval2 = theano.tensor.opt.local_rebroadcast_lift.transform(rval.owner)
changed = False
rval2 = theano.tensor.opt.local_useless_rebroadcast.transform(rval.owner)
if rval2:
assert len(rval2)==1
rval = rval2[0]
changed = True
assert len(rval2)==1
rval = rval2[0]
changed = True
if rval.owner:
rval2 = theano.tensor.opt.local_rebroadcast_lift.transform(rval.owner)
if rval2:
assert len(rval2)==1
rval = rval2[0]
changed = True
return rval
......@@ -1216,7 +1216,7 @@ def local_mul_switch_sink(node):
fct[0].values_eq_approx = fct[0].type.values_eq_approx_remove_nan
return fct
except TypeError:
pass
pass
try:
if get_constant_value(switch.inputs[2]) == 0.:
listmul = node.inputs[:idx] + node.inputs[idx+1:]
......@@ -2398,9 +2398,9 @@ def local_log_add(node):
def add_calculate(num, denum, aslist = False, out_type=None):
#TODO: make sure that this function and mul_calculate are similar
if out_type is None:
zero = 0.0
zero = 0.0
else:
zero = theano._asarray(0, dtype=out_type.dtype)
zero = theano._asarray(0, dtype=out_type.dtype)
#zero = 0.0 if out_type is None else theano._asarray(0, dtype=out_type.dtype)
v = reduce(N.add, num, zero) - reduce(N.add, denum, zero)
if aslist:
......@@ -2856,7 +2856,7 @@ def local_grad_log_erfc_neg(node):
#The constant is valid. Must check that the
elif erfc_x is not x:
return False
return False
else:
return False
......@@ -3098,5 +3098,3 @@ if config.tensor.local_elemwise_fusion:
else:
_logger.debug("not enabling optimization fusion elemwise in fast_run")
compile.optdb.register('elemwise_fusion', FusionOptimizer(local_elemwise_fusion), 71.00, 'fusion', 'local_elemwise_fusion')
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