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pytensor
提交 a31fc8e7 authored 作者: Iulian Vlad Serban's avatar Iulian Vlad Serban
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Fixed flake8 errors.

上级 8d6ff922
隐藏空白字符变更
内嵌 并排
正在显示 包含 46 行增加 和 46 行删除
theano/tensor/opt.py
浏览文件 @ a31fc8e7
......@@ -91,7 +91,7 @@ def copy_stack_trace(from_var, to_var):
tr += getattr(v.tag, 'trace', [])
else:
# If from_var is not a list, it must be a single tensor variable,
# If from_var is not a list, it must be a single tensor variable,
# so just store that particular stack trace
tr = getattr(from_var.tag, 'trace', [])
......@@ -1841,7 +1841,7 @@ def local_subtensor_make_vector(node):
elif isinstance(idx, Variable):
if idx.ndim == 0:
# if it is a constant we can do something with it
try:
try:
v = get_scalar_constant_value(idx)
if isinstance(v, numpy.integer):
# Python 2.4 wants to index only with Python integers
......@@ -2390,7 +2390,7 @@ def local_set_to_inc_subtensor(node):
ret = advanced_inc_subtensor1(node.inputs[0], other, node.inputs[2])
# Copy over previous output stacktrace
# Julian: I'm not sure about this at all...
copy_stack_trace(node.outputs, ret)
copy_stack_trace(node.outputs, ret)
return [ret]
......@@ -2565,7 +2565,7 @@ def local_subtensor_lift(node):
# Copy over previous output stacktrace
copy_stack_trace(node.outputs, x_idx)
ret = u.owner.op(x_idx)
# Copy over previous output stacktrace
# Copy over previous output stacktrace
# and stacktrace from previous unary operation
copy_stack_trace([node.outputs[0], node.inputs[0]], ret)
return [ret]
......@@ -2580,7 +2580,7 @@ def local_subtensor_lift(node):
copy_stack_trace(node.outputs[0], new_inputs)
ret = u.owner.op(*new_inputs)
# Copy over previous output stacktrace
# Copy over previous output stacktrace
# and stacktrace from previous unary operation
copy_stack_trace([node.outputs[0], node.inputs[0]], ret)
return [ret]
......@@ -2605,7 +2605,7 @@ def local_subtensor_lift(node):
copy_stack_trace(node.outputs[0], new_inputs)
ret = u.owner.op(*new_inputs)
# Copy over previous output stacktrace
# Copy over previous output stacktrace
# and stacktrace from previous unary operation
copy_stack_trace([node.outputs[0], node.inputs[0]], ret)
return [ret]
......@@ -2638,7 +2638,7 @@ def local_subtensor_lift(node):
copy_stack_trace(node.outputs[0], subt_x)
rbcast_subt_x = T.Rebroadcast(*new_axis)(subt_x)
# Copy over previous output stacktrace
# Copy over previous output stacktrace
# and stacktrace from previous unary operation
copy_stack_trace([node.outputs[0], node.inputs[0]], rbcast_subt_x)
......@@ -2961,13 +2961,13 @@ def local_subtensor_of_dot(node):
a_sub = a.__getitem__(tuple(a_indices))
b_sub = b.__getitem__(tuple(b_indices)) if b_indices else b
# Copy over previous output stacktrace to a_sub and b_sub,
# because an error in the subtensor operation (e.g. an index error)
# on either a or b must correspond to an error in the
# because an error in the subtensor operation (e.g. an index error)
# on either a or b must correspond to an error in the
# subtensor operation on their dot product.
copy_stack_trace(node.outputs[0], [a_sub, b_sub])
# Copy over previous output stacktrace and previous dot product stacktrace,
# because an error here may correspond to an either in either the original
# dot product, or in the dot product after the subtensor operation.
......@@ -3029,9 +3029,9 @@ def local_IncSubtensor_serialize(node):
new_inputs = ([i for i in node.inputs if not movable(i)] +
[mi.owner.inputs[0] for mi in movable_inputs])
new_add = T.add(*new_inputs)
# Copy over stacktrace from original output, as an error
# (e.g. an index error) in this add operation should
# Copy over stacktrace from original output, as an error
# (e.g. an index error) in this add operation should
# correspond to an error in the original add operation.
copy_stack_trace(node.outputs[0], new_add)
......@@ -3041,10 +3041,10 @@ def local_IncSubtensor_serialize(node):
assert tip.type == o_type
assert tip.type == mi.owner.inputs[0].type
tip = mi.owner.op(tip, *mi.owner.inputs[1:])
# Copy over stacktrace from outputs of the original
# "movable" operation to the new operation.
# Copy over stacktrace from outputs of the original
# "movable" operation to the new operation.
copy_stack_trace(node.outputs + mi.owner.outputs, tip)
return [tip]
# print incsub_inputs, [id(i.owner.inputs[0]) for i in incsub_inputs]
......@@ -3075,7 +3075,7 @@ def local_inplace_setsubtensor(node):
destroyhandler_tolerate_aliased=dta)
new_node = new_op(*node.inputs)
# Copy stacktrace from original outputs to new outputs.
# This is sensible, because the new operation is the
# This is sensible, because the new operation is the
# same as the old one, but now with different attributes.
copy_stack_trace(node.outputs, new_node)
return [new_node]
......@@ -3098,7 +3098,7 @@ def local_inplace_incsubtensor1(node):
new_node = new_op(*node.inputs)
# Copy stacktrace from original outputs to new outputs.
# This is sensible, because the new operation is the
# This is sensible, because the new operation is the
# same as the old one, but now with different attributes.
copy_stack_trace(node.outputs, new_node)
return [new_node]
......@@ -3331,7 +3331,7 @@ def local_useless_inc_subtensor_alloc(node):
r = node.op(x, z, *i)
# Copy over stacktrace from previous output, since
# we don't expect problems when removing the intermediate
# we don't expect problems when removing the intermediate
# alloc operation and so we still want to point at the line
# of the inc_subtensor operation.
copy_stack_trace(node.outputs, r)
......@@ -3355,7 +3355,7 @@ def local_useless_rebroadcast(node):
x = node.inputs[0]
if numpy.all(x.broadcastable == node.outputs[0].broadcastable):
# No broadcastable flag was modified
# No need to copy over stack trace,
# No need to copy over stack trace,
# because x should already have a stack trace.
return [x]
else:
......@@ -3411,8 +3411,8 @@ def local_rebroadcast_lift(node):
# and input (after elemwise operation) to new output, because an
# error in the new graph could have been caused by either of the
# two ops.
copy_stack_trace(node.outputs+node.inputs, rval)
copy_stack_trace(node.outputs + node.inputs, rval)
return rval
if inode and isinstance(inode.op, T.Rebroadcast):
# the "axis" specification in the outer Rebroadcast overrides
......@@ -3427,7 +3427,7 @@ def local_rebroadcast_lift(node):
# and from previous input (after first rebroadcast op) because an error in
# the new graph could have been caused by either of the two
# rebroadcast ops.
copy_stack_trace(node.outputs+node.inputs, rval)
copy_stack_trace(node.outputs + node.inputs, rval)
return rval
......@@ -3532,10 +3532,10 @@ def local_join_empty(node):
assert ret.ndim == o.ndim
ret = T.patternbroadcast(ret, node.outputs[0].broadcastable)
# Copy over stacktrace from previous output
# Copy over stacktrace from previous output
# (after patternbroadcast op) for same reasons as before.
copy_stack_trace(node.outputs, ret)
return [ret]
......@@ -3562,7 +3562,7 @@ def local_join_make_vector(node):
inp.owner.op == new_inputs[-1].owner.op):
inps = new_inputs[-1].owner.inputs + inp.owner.inputs
new_inputs[-1] = inp.owner.op(*inps)
# Copy over stacktrace from previous output (after join op)
# to new intermediate output, because an error in the intermediate
# op must be caused by an error in the old join op.
......@@ -3571,7 +3571,7 @@ def local_join_make_vector(node):
new_inputs.append(inp)
if len(new_inputs) < len(node.inputs) - 1:
ret = T.join(node.inputs[0], *new_inputs)
# Copy over stacktrace from previous output (after join op)
# to new output, because an error in the new op must be caused
# by an error in the old join op.
......@@ -3619,7 +3619,7 @@ def local_useless_switch(node):
in xrange(out.ndim)])
else:
out = out
# Copy over stacktrace from selected output to new output
copy_stack_trace(node.outputs + correct_out, out)
return [out]
......@@ -3633,7 +3633,7 @@ def local_useless_switch(node):
ret = T.fill(cond, node.inputs[1])
# Copy over stacktrace from switch output and correct branch
copy_stack_trace(node.outputs+node.inputs[1], ret)
copy_stack_trace(node.outputs + node.inputs[1], ret)
return [ret]
# This case happens with scan.
......@@ -3650,7 +3650,7 @@ def local_useless_switch(node):
T.extract_constant(left) == 0 and \
right is cond_var.owner.inputs[0]:
assert right.type == node.outputs[0].type
# No need to copy over stacktrace, because the right input node
# No need to copy over stacktrace, because the right input node
# already has its own stacktrace
return [right]
return False
......@@ -3696,8 +3696,8 @@ def local_mul_switch_sink(node):
# Copy over stacktrace for elementwise multiplication op
# from previous elementwise multiplication op.
# An error in the multiplication (e.g. errors due to
# inconsistent shapes), will point to the
# An error in the multiplication (e.g. errors due to
# inconsistent shapes), will point to the
# multiplication op.
copy_stack_trace(node.outputs, fmul)
......@@ -3709,7 +3709,7 @@ def local_mul_switch_sink(node):
# elementwise multiplication op and previous switch op,
# because an error in this part can be caused by either
# of the two previous ops.
copy_stack_trace(node.outputs+switch.outputs, fct)
copy_stack_trace(node.outputs + switch.outputs, fct)
return fct
except NotScalarConstantError:
pass
......@@ -3720,11 +3720,11 @@ def local_mul_switch_sink(node):
fmul = T.mul(*(listmul + [switch.inputs[1]]))
# Copy over stacktrace for elementwise multiplication op
# from previous elementwise multiplication op.
# An error in the multiplication (e.g. errors due to
# inconsistent shapes), will point to the
# An error in the multiplication (e.g. errors due to
# inconsistent shapes), will point to the
# multiplication op.
copy_stack_trace(node.outputs, fmul)
fct = [T.switch(switch.inputs[0],
fmul, 0)]
fct[0].values_eq_approx = values_eq_approx_remove_nan
......@@ -3733,7 +3733,7 @@ def local_mul_switch_sink(node):
# elementwise multiplication op and previous switch op,
# because an error in this part can be caused by either
# of the two previous ops.
copy_stack_trace(node.outputs+switch.outputs, fct)
copy_stack_trace(node.outputs + switch.outputs, fct)
return fct
except NotScalarConstantError:
pass
......@@ -3764,8 +3764,8 @@ def local_div_switch_sink(node):
fdiv = op(switch.inputs[2], node.inputs[1])
# Copy over stacktrace for elementwise division op
# from previous elementwise multiplication op.
# An error in the division (e.g. errors due to
# inconsistent shapes or division by zero),
# An error in the division (e.g. errors due to
# inconsistent shapes or division by zero),
# will point to the new division op.
copy_stack_trace(node.outputs, fdiv)
......@@ -3777,7 +3777,7 @@ def local_div_switch_sink(node):
# elementwise division op and previous switch op,
# because an error in this part can be caused by either
# of the two previous ops.
copy_stack_trace(node.outputs+switch.outputs, fct)
copy_stack_trace(node.outputs + switch.outputs, fct)
return fct
except NotScalarConstantError:
pass
......@@ -3786,8 +3786,8 @@ def local_div_switch_sink(node):
fdiv = op(switch.inputs[1], node.inputs[1])
# Copy over stacktrace for elementwise division op
# from previous elementwise multiplication op.
# An error in the division (e.g. errors due to
# inconsistent shapes or division by zero),
# An error in the division (e.g. errors due to
# inconsistent shapes or division by zero),
# will point to the new division op.
copy_stack_trace(node.outputs, fdiv)
......@@ -3799,7 +3799,7 @@ def local_div_switch_sink(node):
# elementwise division op and previous switch op,
# because an error in this part can be caused by either
# of the two previous ops.
copy_stack_trace(node.outputs+switch.outputs, fct)
copy_stack_trace(node.outputs + switch.outputs, fct)
return fct
except NotScalarConstantError:
pass
......@@ -3843,7 +3843,7 @@ def local_useless_tile(node):
ret = node.inputs[0].dimshuffle(broad)
# Copy over stacktrace from previous output node,
# and from node before tiling operation.
copy_stack_trace(node.outputs+node.inputs[0], ret)
copy_stack_trace(node.outputs + node.inputs[0], ret)
return [ret]
except ValueError:
return
......@@ -3868,7 +3868,7 @@ def local_useless_split(node):
x, axis, splits = node.inputs
out = assert_op(x, T.eq(splits.shape[0], 1))
out = assert_op(out, T.eq(x.shape[axis], splits[0]))
# Copy over stacktrace from previous output node.
copy_stack_trace(node.outputs, out)
return [out]
......
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