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提交 3578c80c authored 作者: Arnaud Bergeron's avatar Arnaud Bergeron
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Flake8 for compile/debugmode.py

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theano/compile/debugmode.py
浏览文件 @ 3578c80c
...@@ -7,7 +7,10 @@ from __future__ import print_function ...@@ -7,7 +7,10 @@ from __future__ import print_function
__docformat__ = "restructuredtext en" __docformat__ = "restructuredtext en"
import copy, sys, copy_reg, gc import copy
import sys
import copy_reg
import gc
from itertools import izip from itertools import izip
import numpy import numpy
...@@ -16,10 +19,9 @@ import theano ...@@ -16,10 +19,9 @@ import theano
from theano import gof from theano import gof
from theano.compat import get_unbound_function, product as itertools_product from theano.compat import get_unbound_function, product as itertools_product
from theano.compat.six import StringIO from theano.compat.six import StringIO
from theano.gof import (FunctionGraph, graph, utils, link, from theano.gof import (graph, utils, link,
ops_with_inner_function) ops_with_inner_function)
from theano.gof.link import raise_with_op from theano.gof.link import raise_with_op
from theano.gof.cc import CLinker
from theano.configparser import (config, AddConfigVar, BoolParam, IntParam, from theano.configparser import (config, AddConfigVar, BoolParam, IntParam,
StrParam) StrParam)
from theano.compile.function_module import ( from theano.compile.function_module import (
...@@ -30,37 +32,37 @@ from theano.compile.mode import Mode, register_mode ...@@ -30,37 +32,37 @@ from theano.compile.mode import Mode, register_mode
from theano.compile.ops import OutputGuard from theano.compile.ops import OutputGuard
AddConfigVar('DebugMode.patience', AddConfigVar('DebugMode.patience',
"Optimize graph this many times to detect inconsistency", "Optimize graph this many times to detect inconsistency",
IntParam(10, lambda i: i > 0), IntParam(10, lambda i: i > 0),
in_c_key=False) in_c_key=False)
AddConfigVar('DebugMode.check_c', AddConfigVar('DebugMode.check_c',
"Run C implementations where possible", "Run C implementations where possible",
BoolParam(bool(theano.config.cxx)), BoolParam(bool(theano.config.cxx)),
in_c_key=False) in_c_key=False)
AddConfigVar('DebugMode.check_py', AddConfigVar('DebugMode.check_py',
"Run Python implementations where possible", "Run Python implementations where possible",
BoolParam(True), BoolParam(True),
in_c_key=False) in_c_key=False)
AddConfigVar('DebugMode.check_finite', AddConfigVar('DebugMode.check_finite',
"True -> complain about NaN/Inf results", "True -> complain about NaN/Inf results",
BoolParam(True), BoolParam(True),
in_c_key=False) in_c_key=False)
AddConfigVar('DebugMode.check_strides', AddConfigVar('DebugMode.check_strides',
("Check that Python- and C-produced ndarrays have same strides. " ("Check that Python- and C-produced ndarrays have same strides. "
"On difference: (0) - ignore, (1) warn, or (2) raise error"), "On difference: (0) - ignore, (1) warn, or (2) raise error"),
IntParam(1, lambda i: i in (0, 1, 2)), IntParam(1, lambda i: i in (0, 1, 2)),
in_c_key=False) in_c_key=False)
AddConfigVar('DebugMode.warn_input_not_reused', AddConfigVar('DebugMode.warn_input_not_reused',
("Generate a warning when destroy_map or view_map says that an " ("Generate a warning when destroy_map or view_map says that an "
"op works inplace, but the op did not reuse the input for its output." "op works inplace, but the op did not reuse the input for its "
), "output."),
BoolParam(True), BoolParam(True),
in_c_key=False) in_c_key=False)
def is_valid_check_preallocated_output_param(param): def is_valid_check_preallocated_output_param(param):
...@@ -74,25 +76,25 @@ def is_valid_check_preallocated_output_param(param): ...@@ -74,25 +76,25 @@ def is_valid_check_preallocated_output_param(param):
return True return True
AddConfigVar('DebugMode.check_preallocated_output', AddConfigVar('DebugMode.check_preallocated_output',
('Test thunks with pre-allocated memory as output storage. ' ('Test thunks with pre-allocated memory as output storage. '
'This is a list of strings separated by ":". Valid values are: ' 'This is a list of strings separated by ":". Valid values are: '
'"initial" (initial storage in storage map, happens with Scan),' '"initial" (initial storage in storage map, happens with Scan),'
'"previous" (previously-returned memory), ' '"previous" (previously-returned memory), '
'"c_contiguous", "f_contiguous", ' '"c_contiguous", "f_contiguous", '
'"strided" (positive and negative strides), ' '"strided" (positive and negative strides), '
'"wrong_size" (larger and smaller dimensions), and ' '"wrong_size" (larger and smaller dimensions), and '
'"ALL" (all of the above).'), '"ALL" (all of the above).'),
StrParam('', is_valid=is_valid_check_preallocated_output_param), StrParam('', is_valid=is_valid_check_preallocated_output_param),
in_c_key=False) in_c_key=False)
AddConfigVar('DebugMode.check_preallocated_output_ndim', AddConfigVar('DebugMode.check_preallocated_output_ndim',
('When testing with "strided" preallocated output memory, ' ('When testing with "strided" preallocated output memory, '
'test all combinations of strides over that number of ' 'test all combinations of strides over that number of '
'(inner-most) dimensions. You may want to reduce that number ' '(inner-most) dimensions. You may want to reduce that number '
'to reduce memory or time usage, but it is advised to keep a ' 'to reduce memory or time usage, but it is advised to keep a '
'minimum of 2.'), 'minimum of 2.'),
IntParam(4, lambda i: i > 0), IntParam(4, lambda i: i > 0),
in_c_key=False) in_c_key=False)
import logging import logging
_logger = logging.getLogger("theano.compile.debugmode") _logger = logging.getLogger("theano.compile.debugmode")
...@@ -148,7 +150,7 @@ class BadThunkOutput(DebugModeError): ...@@ -148,7 +150,7 @@ class BadThunkOutput(DebugModeError):
def __init__(self, r, thunk1, val1, thunk2, val2, inputs_val=()): def __init__(self, r, thunk1, val1, thunk2, val2, inputs_val=()):
"""Initialize members""" """Initialize members"""
DebugModeError.__init__(self) # to be compatible with python2.4 super(BadThunkOutput, self).__init__()
self.r = r self.r = r
self.thunk1 = thunk1 self.thunk1 = thunk1
self.val1 = val1 self.val1 = val1
...@@ -173,12 +175,14 @@ class BadThunkOutput(DebugModeError): ...@@ -173,12 +175,14 @@ class BadThunkOutput(DebugModeError):
print(" op :", self.offending_op(), file=sio) print(" op :", self.offending_op(), file=sio)
print(" Outputs Type:", self.r.type, file=sio) print(" Outputs Type:", self.r.type, file=sio)
print(" Outputs Shape:", getattr(self.val1, 'shape', None), file=sio) print(" Outputs Shape:", getattr(self.val1, 'shape', None), file=sio)
print(" Outputs Strides:", getattr(self.val1, 'strides', None), file=sio) print(" Outputs Strides:", getattr(self.val1, 'strides', None),
print(" Inputs Type :", [i.type for i in self.r.owner.inputs], file=sio) file=sio)
print(" Inputs Type :", [i.type for i in self.r.owner.inputs],
file=sio)
print(" Inputs Shape:", [getattr(val, 'shape', None) print(" Inputs Shape:", [getattr(val, 'shape', None)
for val in self.inputs_val], file=sio) for val in self.inputs_val], file=sio)
print(" Inputs Strides:", [getattr(val, 'strides', None) print(" Inputs Strides:", [getattr(val, 'strides', None)
for val in self.inputs_val], file=sio) for val in self.inputs_val], file=sio)
print(" Bad Variable:", self.r, file=sio) print(" Bad Variable:", self.r, file=sio)
print(" thunk1 :", self.thunk1, file=sio) print(" thunk1 :", self.thunk1, file=sio)
print(" thunk2 :", self.thunk2, file=sio) print(" thunk2 :", self.thunk2, file=sio)
...@@ -226,7 +230,7 @@ class BadOptimization(DebugModeError): ...@@ -226,7 +230,7 @@ class BadOptimization(DebugModeError):
def __init__(self, old_r, new_r, old_r_val, new_r_val, reason, def __init__(self, old_r, new_r, old_r_val, new_r_val, reason,
old_graph, new_graph): old_graph, new_graph):
"""Initialize members""" """Initialize members"""
DebugModeError.__init__(self) # to be compatible with python2.4 super(BadOptimization, self).__init__()
self.old_r = old_r self.old_r = old_r
self.new_r = new_r self.new_r = new_r
self.old_r_val = old_r_val self.old_r_val = old_r_val
...@@ -244,7 +248,7 @@ class BadOptimization(DebugModeError): ...@@ -244,7 +248,7 @@ class BadOptimization(DebugModeError):
sio = StringIO() sio = StringIO()
val_str_len_limit = 800 val_str_len_limit = 800
print("BadOptimization Error", super(BadOptimization, print("BadOptimization Error", super(BadOptimization,
self).__str__(), file=sio) self).__str__(), file=sio)
print(" Variable: id", id(self.new_r), self.new_r, file=sio) print(" Variable: id", id(self.new_r), self.new_r, file=sio)
print(" Op", self.new_r.owner, file=sio) print(" Op", self.new_r.owner, file=sio)
print(" Value Type:", type(self.new_r_val), file=sio) print(" Value Type:", type(self.new_r_val), file=sio)
...@@ -287,25 +291,21 @@ class BadOptimization(DebugModeError): ...@@ -287,25 +291,21 @@ class BadOptimization(DebugModeError):
ov = numpy.asarray(self.old_r_val) ov = numpy.asarray(self.old_r_val)
nv = numpy.asarray(self.new_r_val) nv = numpy.asarray(self.new_r_val)
ssio = StringIO() ssio = StringIO()
print(" Max Abs Diff: ", numpy.max(numpy.absolute(nv - abs_diff = numpy.absolute(nv - ov)
ov)), file=ssio) print(" Max Abs Diff: ", numpy.max(abs_diff), file=ssio)
print(" Mean Abs Diff: ", numpy.mean(numpy.absolute(nv - print(" Mean Abs Diff: ", numpy.mean(abs_diff), file=ssio)
ov)), file=ssio) print(" Median Abs Diff: ", numpy.median(abs_diff), file=ssio)
print(" Median Abs Diff: ", numpy.median(numpy.absolute( print(" Std Abs Diff: ", numpy.std(abs_diff), file=ssio)
nv - ov)), file=ssio) arg_max_val = numpy.argmax(abs_diff)
print(" Std Abs Diff: ", numpy.std(numpy.absolute(
nv - ov)), file=ssio)
arg_max_val = numpy.argmax(numpy.absolute(nv - ov))
values_at_max = (nv.flatten()[arg_max_val], values_at_max = (nv.flatten()[arg_max_val],
ov.flatten()[arg_max_val]) ov.flatten()[arg_max_val])
print(" Value at Max Diff: ", values_at_max, file=ssio) print(" Value at Max Diff: ", values_at_max, file=ssio)
# N.B. the maximum(..., 1e-8) protects against div by 0 when # N.B. the maximum(..., 1e-8) protects against div by 0 when
# nv == ov == 0 # nv == ov == 0
reldiff = (numpy.absolute(nv - ov) reldiff = (abs_diff
/ numpy.maximum( / numpy.maximum(numpy.absolute(nv) + numpy.absolute(ov),
numpy.absolute(nv) + numpy.absolute(ov), 1e-8))
1e-8))
print(" Max Rel Diff: ", numpy.max(reldiff), file=ssio) print(" Max Rel Diff: ", numpy.max(reldiff), file=ssio)
print(" Mean Rel Diff: ", numpy.mean(reldiff), file=ssio) print(" Mean Rel Diff: ", numpy.mean(reldiff), file=ssio)
print(" Median Rel Diff: ", numpy.median(reldiff), file=ssio) print(" Median Rel Diff: ", numpy.median(reldiff), file=ssio)
...@@ -325,8 +325,10 @@ class BadOptimization(DebugModeError): ...@@ -325,8 +325,10 @@ class BadOptimization(DebugModeError):
print(" New Graph:", file=sio) print(" New Graph:", file=sio)
print(self.new_graph, file=sio) print(self.new_graph, file=sio)
print("", file=sio) print("", file=sio)
print("Hint: relax the tolerance by setting tensor.cmp_sloppy=1", file=sio) print("Hint: relax the tolerance by setting tensor.cmp_sloppy=1",
print(" or even tensor.cmp_sloppy=2 for less-strict comparison", file=sio) file=sio)
print(" or even tensor.cmp_sloppy=2 for less-strict comparison",
file=sio)
return sio.getvalue() return sio.getvalue()
...@@ -334,8 +336,7 @@ class BadDestroyMap(DebugModeError): ...@@ -334,8 +336,7 @@ class BadDestroyMap(DebugModeError):
"""Exception: Some perform() or c_code() modified an input that """Exception: Some perform() or c_code() modified an input that
wasn't in the destroy_map""" wasn't in the destroy_map"""
def __init__(self, node, idx, old_val, new_val, perform): def __init__(self, node, idx, old_val, new_val, perform):
#super(BadDestroyMap, self).__init__() super(BadDestroyMap, self).__init__()
DebugModeError.__init__(self) # to be compatible with python2.4
self.node = node self.node = node
self.idx = idx self.idx = idx
self.old_val = old_val self.old_val = old_val
...@@ -347,30 +348,42 @@ class BadDestroyMap(DebugModeError): ...@@ -347,30 +348,42 @@ class BadDestroyMap(DebugModeError):
print(" node:", self.node, file=sio) print(" node:", self.node, file=sio)
print(" perform:", self.perform, file=sio) print(" perform:", self.perform, file=sio)
print(" node.inputs:", [(str(i), id(i)) print(" node.inputs:", [(str(i), id(i))
for i in self.node.inputs], file=sio) for i in self.node.inputs], file=sio)
print(" destroy_map:", getattr(self.node.op, print(" destroy_map:", getattr(self.node.op,
'destroy_map', {}), file=sio) 'destroy_map', {}), file=sio)
print(" changed input idx:", self.idx, file=sio) print(" changed input idx:", self.idx, file=sio)
print(" changed input type:", self.node.inputs[self.idx].type, file=sio) print(" changed input type:", self.node.inputs[self.idx].type,
file=sio)
print(" repr (old val):", repr(self.old_val), file=sio) print(" repr (old val):", repr(self.old_val), file=sio)
print(" repr (new val):", repr(self.new_val), file=sio) print(" repr (new val):", repr(self.new_val), file=sio)
try: try:
npy_old_val = numpy.asarray(self.old_val) npy_old_val = numpy.asarray(self.old_val)
npy_new_val = numpy.asarray(self.new_val) npy_new_val = numpy.asarray(self.new_val)
print(" value dtype (new <space> old):", npy_new_val.dtype, npy_old_val.dtype, file=sio) print(" value dtype (new <space> old):", npy_new_val.dtype,
print(" value shape (new <space> old):", npy_new_val.shape, npy_old_val.shape, file=sio) npy_old_val.dtype, file=sio)
print(" value min (new <space> old):", npy_new_val.min(), npy_old_val.min(), file=sio) print(" value shape (new <space> old):", npy_new_val.shape,
print(" value max (new <space> old):", npy_new_val.max(), npy_old_val.max(), file=sio) npy_old_val.shape, file=sio)
print(" value min (new <space> old):", npy_new_val.min(),
npy_old_val.min(), file=sio)
print(" value max (new <space> old):", npy_new_val.max(),
npy_old_val.max(), file=sio)
delta = npy_new_val - npy_old_val delta = npy_new_val - npy_old_val
print(" value min (new-old):", delta.min(), file=sio) print(" value min (new-old):", delta.min(), file=sio)
print(" value max (new-old):", delta.max(), file=sio) print(" value max (new-old):", delta.max(), file=sio)
print(" value argmin (new-old):", numpy.unravel_index(delta.argmin(), npy_new_val.shape), file=sio) print(" value argmin (new-old):",
print(" value argmax (new-old):", numpy.unravel_index(delta.argmax(), npy_new_val.shape), file=sio) numpy.unravel_index(delta.argmin(), npy_new_val.shape),
print(" location of first 10 mismatches:", numpy.transpose(numpy.nonzero(delta))[:10], file=sio) file=sio)
print(" value argmax (new-old):",
numpy.unravel_index(delta.argmax(), npy_new_val.shape),
file=sio)
print(" location of first 10 mismatches:",
numpy.transpose(numpy.nonzero(delta))[:10], file=sio)
print("", file=sio) print("", file=sio)
except Exception as e: except Exception as e:
print("(Numpy-hints failed with: %s)" % str(e), file=sio) print("(Numpy-hints failed with: %s)" % str(e), file=sio)
print(" Hint: this can also be caused by a deficient values_eq_approx() or __eq__() implementation [which compared input values]", file=sio) print(" Hint: this can also be caused by a deficient "
"values_eq_approx() or __eq__() implementation "
"[which compared input values]", file=sio)
return sio.getvalue() return sio.getvalue()
...@@ -379,8 +392,7 @@ class BadViewMap(DebugModeError): ...@@ -379,8 +392,7 @@ class BadViewMap(DebugModeError):
that wasn't in the view_map""" that wasn't in the view_map"""
def __init__(self, node, output_idx, out_storage, def __init__(self, node, output_idx, out_storage,
in_alias_idx=None, out_alias_idx=None): in_alias_idx=None, out_alias_idx=None):
#super(BadViewMap, self).__init__() super(BadViewMap, self).__init__()
DebugModeError.__init__(self) # to be compatible with python2.4
self.node = node self.node = node
self.output_idx = output_idx self.output_idx = output_idx
self.out_storage = out_storage self.out_storage = out_storage
...@@ -391,12 +403,12 @@ class BadViewMap(DebugModeError): ...@@ -391,12 +403,12 @@ class BadViewMap(DebugModeError):
sio = StringIO() sio = StringIO()
print(" node:", self.node, file=sio) print(" node:", self.node, file=sio)
print(" node.inputs:", [(str(i), id(i)) print(" node.inputs:", [(str(i), id(i))
for i in self.node.inputs], file=sio) for i in self.node.inputs], file=sio)
print(" node.outputs:", [(str(i), id(i)) print(" node.outputs:", [(str(i), id(i))
for i in self.node.outputs], file=sio) for i in self.node.outputs], file=sio)
print(" view_map:", getattr(self.node.op, 'view_map', {}), file=sio) print(" view_map:", getattr(self.node.op, 'view_map', {}), file=sio)
print(" destroy_map:", getattr(self.node.op, print(" destroy_map:", getattr(self.node.op,
'destroy_map', {}), file=sio) 'destroy_map', {}), file=sio)
print(" aliased output:", self.output_idx, file=sio) print(" aliased output:", self.output_idx, file=sio)
print(" aliased output storage:", self.out_storage, file=sio) print(" aliased output storage:", self.out_storage, file=sio)
if self.in_alias_idx: if self.in_alias_idx:
...@@ -425,8 +437,7 @@ class InvalidValueError(DebugModeError): ...@@ -425,8 +437,7 @@ class InvalidValueError(DebugModeError):
the Type of that output""" the Type of that output"""
def __init__(self, r, v, client_node=None, hint='none', def __init__(self, r, v, client_node=None, hint='none',
specific_hint='none'): specific_hint='none'):
#super(InvalidValueError, self).__init__() super(InvalidValueError, self).__init__()
DebugModeError.__init__(self) # to be compatible with python2.4
self.r = r self.r = r
self.v = v self.v = v
self.client_node = client_node self.client_node = client_node
...@@ -454,7 +465,8 @@ class InvalidValueError(DebugModeError): ...@@ -454,7 +465,8 @@ class InvalidValueError(DebugModeError):
client_node = self.client_node client_node = self.client_node
hint = self.hint hint = self.hint
specific_hint = self.specific_hint specific_hint = self.specific_hint
context = debugprint(r, prefix=' ', depth=12, file=StringIO()).getvalue() context = debugprint(r, prefix=' ', depth=12,
file=StringIO()).getvalue()
return """InvalidValueError return """InvalidValueError
type(variable) = %(type_r)s type(variable) = %(type_r)s
variable = %(r)s variable = %(r)s
...@@ -512,7 +524,8 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False, ...@@ -512,7 +524,8 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False,
and their associated printed ids and their associated printed ids
:param print_type: whether to print the Variable type after the other infos :param print_type: whether to print the Variable type after the other infos
:param file: file-like object to which to print :param file: file-like object to which to print
:param print_destroy_map: whether to print the op destroy_map after other info :param print_destroy_map: whether to print the op destroy_map after
other info
:param print_view_map: whether to print the op view_map after other info :param print_view_map: whether to print the op view_map after other info
:param order: If not empty will print the index in the toposort. :param order: If not empty will print the index in the toposort.
:param ids: How do we print the identifier of the variable :param ids: How do we print the identifier of the variable
...@@ -592,23 +605,23 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False, ...@@ -592,23 +605,23 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False,
already_printed = a in done # get_id_str put it in the dict already_printed = a in done # get_id_str put it in the dict
id_str = get_id_str(a) id_str = get_id_str(a)
if profile == None or a not in profile.apply_time: if profile is None or a not in profile.apply_time:
if len(a.outputs) == 1: if len(a.outputs) == 1:
print('%s%s %s%s \'%s\' %s %s %s' % (prefix, a.op, print('%s%s %s%s \'%s\' %s %s %s' % (prefix, a.op,
id_str, id_str,
type_str, type_str,
r_name, r_name,
destroy_map_str, destroy_map_str,
view_map_str, view_map_str,
o), file=file) o), file=file)
else: else:
print('%s%s.%i %s%s \'%s\' %s %s %s' % (prefix, a.op, print('%s%s.%i %s%s \'%s\' %s %s %s' % (prefix, a.op,
a.outputs.index(r), a.outputs.index(r),
id_str, type_str, id_str, type_str,
r_name, r_name,
destroy_map_str, destroy_map_str,
view_map_str, view_map_str,
o), file=file) o), file=file)
else: else:
op_time = profile.apply_time[a] op_time = profile.apply_time[a]
op_time_percent = (op_time / profile.fct_call_time) * 100 op_time_percent = (op_time / profile.fct_call_time) * 100
...@@ -617,33 +630,35 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False, ...@@ -617,33 +630,35 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False,
tot_time_percent = (tot_time_dict[a] / profile.fct_call_time) * 100 tot_time_percent = (tot_time_dict[a] / profile.fct_call_time) * 100
if len(a.outputs) == 1: if len(a.outputs) == 1:
print('%s%s %s%s \'%s\' %s %s %s --> %8.2es %4.1f%% %8.2es %4.1f%%'\ print("%s%s %s%s '%s' %s %s %s --> "
% (prefix, a.op, "%8.2es %4.1f%% %8.2es %4.1f%%"
id_str, % (prefix, a.op,
type_str, id_str,
r_name, type_str,
destroy_map_str, r_name,
view_map_str, destroy_map_str,
o, op_time, view_map_str,
op_time_percent, o, op_time,
tot_time, op_time_percent,
tot_time_percent), file=file) tot_time,
tot_time_percent), file=file)
else: else:
print('%s%s.%i %s%s \'%s\' %s %s %s --> %8.2es %4.1f%% %8.2es %4.1f%%'\ print("%s%s.%i %s%s '%s' %s %s %s --> "
% (prefix, a.op, "%8.2es %4.1f%% %8.2es %4.1f%%"
a.outputs.index(r), % (prefix, a.op,
id_str, type_str, a.outputs.index(r),
r_name, id_str, type_str,
destroy_map_str, r_name,
view_map_str, destroy_map_str,
o, op_time, view_map_str,
op_time_percent, o, op_time,
tot_time, op_time_percent,
tot_time_percent), file=file) tot_time,
tot_time_percent), file=file)
if not already_printed: if not already_printed:
if (not stop_on_name or if (not stop_on_name or
not (hasattr(r, 'name') and r.name is not None)): not (hasattr(r, 'name') and r.name is not None)):
new_prefix = prefix_child + ' |' new_prefix = prefix_child + ' |'
new_prefix_child = prefix_child + ' |' new_prefix_child = prefix_child + ' |'
...@@ -652,14 +667,15 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False, ...@@ -652,14 +667,15 @@ def debugprint(r, prefix='', depth=-1, done=None, print_type=False,
new_prefix_child = prefix_child + ' ' new_prefix_child = prefix_child + ' '
if hasattr(i, 'owner') and hasattr(i.owner, 'op'): if hasattr(i, 'owner') and hasattr(i.owner, 'op'):
if isinstance(i.owner.op, theano.scan_module.scan_op.Scan): if isinstance(i.owner.op,
theano.scan_module.scan_op.Scan):
scan_ops.append(i) scan_ops.append(i)
debugprint(i, new_prefix, depth=depth - 1, done=done, debugprint(i, new_prefix, depth=depth - 1, done=done,
print_type=print_type, file=file, order=order, print_type=print_type, file=file, order=order,
ids=ids, stop_on_name=stop_on_name, ids=ids, stop_on_name=stop_on_name,
prefix_child=new_prefix_child, scan_ops=scan_ops, prefix_child=new_prefix_child,
profile=profile) scan_ops=scan_ops, profile=profile)
else: else:
# this is an input variable # this is an input variable
...@@ -679,7 +695,8 @@ def _optcheck_fgraph(input_specs, output_specs, accept_inplace=False): ...@@ -679,7 +695,8 @@ def _optcheck_fgraph(input_specs, output_specs, accept_inplace=False):
:param accept_inplace: are inplace ops permitted in the original graph? :param accept_inplace: are inplace ops permitted in the original graph?
:type accept_inplace: Bool :type accept_inplace: Bool
:rtype: `FunctionGraph` :rtype: `FunctionGraph`
:returns: a new FunctionGraph with a cloned graph, with debugging `Feature` instances already installed. :returns: a new FunctionGraph with a cloned graph, with debugging
`Feature` instances already installed.
""" """
orig_inputs = [spec.variable for spec in input_specs] orig_inputs = [spec.variable for spec in input_specs]
updates = [spec.update for spec in input_specs if spec.update] updates = [spec.update for spec in input_specs if spec.update]
...@@ -687,15 +704,15 @@ def _optcheck_fgraph(input_specs, output_specs, accept_inplace=False): ...@@ -687,15 +704,15 @@ def _optcheck_fgraph(input_specs, output_specs, accept_inplace=False):
equivalence_tracker = _VariableEquivalenceTracker() equivalence_tracker = _VariableEquivalenceTracker()
fgraph = gof.fg.FunctionGraph(orig_inputs, orig_outputs, fgraph = gof.fg.FunctionGraph(orig_inputs, orig_outputs,
# DestroyHandler may not be needed yet, as there is usually no features=[equivalence_tracker])
# inplace operation in the graph at this stage. DestroyHandler # DestroyHandler may not be needed yet, as there is usually no
# will be installed by an optimization after canonicalization, # inplace operation in the graph at this stage. DestroyHandler
# before the inplace operations are applied. # will be installed by an optimization after canonicalization,
# This results in a big speed gain. # before the inplace operations are applied. This results in a big
# If inplace operations are accepted and present, however, # speed gain.
# DestroyHandler will be inserted in the loop below. #
# features=[equivalence_tracker, gof.DestroyHandler(do_imports_on_attach=False)]) # If inplace operations are accepted and present, however,
features=[equivalence_tracker]) # DestroyHandler will be inserted in the loop below.
if not accept_inplace: if not accept_inplace:
for node in fgraph.apply_nodes: for node in fgraph.apply_nodes:
...@@ -711,9 +728,10 @@ def _optcheck_fgraph(input_specs, output_specs, accept_inplace=False): ...@@ -711,9 +728,10 @@ def _optcheck_fgraph(input_specs, output_specs, accept_inplace=False):
break break
# We need to protect all immutable inputs from inplace operations. # We need to protect all immutable inputs from inplace operations.
fgraph.attach_feature(Supervisor(input for spec, input in zip(input_specs, fgraph.inputs) fgraph.attach_feature(Supervisor(
if not (spec.mutable or (hasattr(fgraph, 'destroyers') input for spec, input in zip(input_specs, fgraph.inputs)
and fgraph.destroyers(input))))) if not (spec.mutable or (hasattr(fgraph, 'destroyers')
and fgraph.destroyers(input)))))
for feature in std_fgraph.features: for feature in std_fgraph.features:
fgraph.attach_feature(feature()) fgraph.attach_feature(feature())
...@@ -762,7 +780,7 @@ def _check_inputs(node, storage_map, r_vals, dr_vals, active_nodes, ...@@ -762,7 +780,7 @@ def _check_inputs(node, storage_map, r_vals, dr_vals, active_nodes,
out_var = storage_map[var][0] out_var = storage_map[var][0]
in_var = storage_map[node.inputs[ii[0]]][0] in_var = storage_map[node.inputs[ii[0]]][0]
if (hasattr(var.type, 'may_share_memory') and if (hasattr(var.type, 'may_share_memory') and
var.type.may_share_memory(out_var, in_var)): var.type.may_share_memory(out_var, in_var)):
actually_inplace_outputs.append(node.outputs[oo]) actually_inplace_outputs.append(node.outputs[oo])
if warn_input_not_reused and destroyed_res_list: if warn_input_not_reused and destroyed_res_list:
...@@ -772,8 +790,8 @@ def _check_inputs(node, storage_map, r_vals, dr_vals, active_nodes, ...@@ -772,8 +790,8 @@ def _check_inputs(node, storage_map, r_vals, dr_vals, active_nodes,
continue continue
if out_var is not in_var: if out_var is not in_var:
_logger.warning("Optimization Warning: input idx %d marked " _logger.warning("Optimization Warning: input idx %d marked "
"as destroyed was not changed for node '%s'", "as destroyed was not changed for node '%s'",
ii[0], str(node)) ii[0], str(node))
vmap = getattr(node.op, 'view_map', {}) vmap = getattr(node.op, 'view_map', {})
for oo, ii in vmap.iteritems(): for oo, ii in vmap.iteritems():
...@@ -797,8 +815,8 @@ def _check_inputs(node, storage_map, r_vals, dr_vals, active_nodes, ...@@ -797,8 +815,8 @@ def _check_inputs(node, storage_map, r_vals, dr_vals, active_nodes,
continue continue
if not may_share: if not may_share:
_logger.warning("Optimization Warning: input idx %d marked " _logger.warning("Optimization Warning: input idx %d marked "
"as viewed but new memory allocated by node '%s'", "as viewed but new memory allocated by node "
ii[0], str(node)) "'%s'", ii[0], str(node))
for r_idx, r in enumerate(node.inputs): for r_idx, r in enumerate(node.inputs):
if not r.type.values_eq(r_vals[r], storage_map[r][0]): if not r.type.values_eq(r_vals[r], storage_map[r][0]):
...@@ -808,10 +826,12 @@ def _check_inputs(node, storage_map, r_vals, dr_vals, active_nodes, ...@@ -808,10 +826,12 @@ def _check_inputs(node, storage_map, r_vals, dr_vals, active_nodes,
# ok, we expected r to be destroyed # ok, we expected r to be destroyed
if node in active_nodes: if node in active_nodes:
if dr_vals.get(r, (0, node))[1] is not node: if dr_vals.get(r, (0, node))[1] is not node:
# bad: there should only be one active node that destroys any variable # bad: there should only be one active node
# that destroys any variable
raise Exception('failure in topological ordering') raise Exception('failure in topological ordering')
if clobber_dr_vals: if clobber_dr_vals:
dr_vals[r] = (storage_map[r][0], node) # no copy, this is the last use of this variable # no copy, this is the last use of this variable
dr_vals[r] = (storage_map[r][0], node)
# make sure that dr_vals[r] doens't get used again # make sure that dr_vals[r] doens't get used again
storage_map[r][0] = data_destroyed storage_map[r][0] = data_destroyed
else: else:
...@@ -823,8 +843,10 @@ def _check_inputs(node, storage_map, r_vals, dr_vals, active_nodes, ...@@ -823,8 +843,10 @@ def _check_inputs(node, storage_map, r_vals, dr_vals, active_nodes,
def _check_viewmap(node, storage_map): def _check_viewmap(node, storage_map):
""" """
This functions raises a BadViewMap exception when it detects the following: This functions raises a BadViewMap exception when it detects the
- output node storages aliased to input storage, with no declaration in view_map following:
- output node storages aliased to input storage, with no declaration
in view_map
- if not aliased to an input, check if two outputs are aliased together - if not aliased to an input, check if two outputs are aliased together
and used subsequently in the graph and used subsequently in the graph
""" """
...@@ -851,14 +873,14 @@ def _check_viewmap(node, storage_map): ...@@ -851,14 +873,14 @@ def _check_viewmap(node, storage_map):
# useless check. # useless check.
continue continue
if (hasattr(inode.type, 'may_share_memory') and if (hasattr(inode.type, 'may_share_memory') and
inode.type.may_share_memory(outstorage, in_storage)): inode.type.may_share_memory(outstorage, in_storage)):
nodeid = id(inode) nodeid = id(inode)
bad_alias[nodeid] = ii bad_alias[nodeid] = ii
# check that the aliasing was declared in [view|destroy]_map # check that the aliasing was declared in [view|destroy]_map
if ([ii] == view_map.get(oi, None) or if ([ii] == view_map.get(oi, None) or
[ii] == destroy_map.get(oi, None)): [ii] == destroy_map.get(oi, None)):
good_alias[nodeid] = bad_alias.pop(nodeid) good_alias[nodeid] = bad_alias.pop(nodeid)
...@@ -970,12 +992,12 @@ def _find_bad_optimizations0(order, reasons, r_vals): ...@@ -970,12 +992,12 @@ def _find_bad_optimizations0(order, reasons, r_vals):
check = r.type.values_eq_approx(r_val, new_r_val) check = r.type.values_eq_approx(r_val, new_r_val)
if not check: if not check:
raise BadOptimization(old_r=r, raise BadOptimization(old_r=r,
new_r=new_r, new_r=new_r,
old_r_val=r_val, old_r_val=r_val,
new_r_val=new_r_val, new_r_val=new_r_val,
reason=reason, reason=reason,
old_graph=old_graph_str, old_graph=old_graph_str,
new_graph=new_graph_str) new_graph=new_graph_str)
def _find_bad_optimizations1(order, reasons, r_vals): def _find_bad_optimizations1(order, reasons, r_vals):
...@@ -993,7 +1015,7 @@ def _find_bad_optimizations1(order, reasons, r_vals): ...@@ -993,7 +1015,7 @@ def _find_bad_optimizations1(order, reasons, r_vals):
equivalence_sets.setdefault(new_r, set([new_r])) equivalence_sets.setdefault(new_r, set([new_r]))
for reason, r, old_graph_str, new_graph_str in reasons[new_r]: for reason, r, old_graph_str, new_graph_str in reasons[new_r]:
equivalence_sets[new_r].update(equivalence_sets.setdefault( equivalence_sets[new_r].update(equivalence_sets.setdefault(
r, set([r]))) r, set([r])))
for er in equivalence_sets[r]: for er in equivalence_sets[r]:
equivalence_sets[er] = equivalence_sets[new_r] equivalence_sets[er] = equivalence_sets[new_r]
...@@ -1050,28 +1072,25 @@ def _find_bad_optimizations2(order, reasons, r_vals): ...@@ -1050,28 +1072,25 @@ def _find_bad_optimizations2(order, reasons, r_vals):
if (r.type != new_r.type) or (not r.type.values_eq_approx( if (r.type != new_r.type) or (not r.type.values_eq_approx(
r_val, new_r_val)): r_val, new_r_val)):
raise BadOptimization(old_r=r, raise BadOptimization(old_r=r,
new_r=new_r, new_r=new_r,
old_r_val=r_val, old_r_val=r_val,
new_r_val=new_r_val, new_r_val=new_r_val,
reason=reason, reason=reason,
old_graph=old_graph_str, old_graph=old_graph_str,
new_graph=new_graph_str) new_graph=new_graph_str)
def check_variable(r): def check_variable(r):
if r in checked_variables: if r in checked_variables:
return return
checked_variables.add(r) checked_variables.add(r)
# (recursively) first check all the variables that could make r look bad: # (recursively) first check all the variables that could make
# r look bad:
list_of_vars = [old_r for (reason, old_r, olds, news) in reasons[r]] list_of_vars = [old_r for (reason, old_r, olds, news) in reasons[r]]
if (None is not r.owner): if (None is not r.owner):
list_of_vars += r.owner.inputs list_of_vars += r.owner.inputs
for var_that_could_make_r_look_bad in \ for var_that_could_make_r_look_bad in list_of_vars:
list_of_vars:
# backport
#[old_r for (reason, old_r, olds, news) in reasons[r]] \
#+ ([] if (None is r.owner) else r.owner.inputs):
check_variable(var_that_could_make_r_look_bad) check_variable(var_that_could_make_r_look_bad)
check_variable_norec(r) check_variable_norec(r)
...@@ -1087,8 +1106,8 @@ _find_bad_optimizations = _find_bad_optimizations0 ...@@ -1087,8 +1106,8 @@ _find_bad_optimizations = _find_bad_optimizations0
def _get_preallocated_maps(node, thunk, prealloc_modes, def_val, def _get_preallocated_maps(node, thunk, prealloc_modes, def_val,
storage_map, r_vals, dr_vals, perform, active_order_set, storage_map, r_vals, dr_vals, perform,
inplace_outs, init_outputs): active_order_set, inplace_outs, init_outputs):
'''Preallocate outputs in different memory layouts''' '''Preallocate outputs in different memory layouts'''
# To avoid circular imports # To avoid circular imports
...@@ -1137,7 +1156,7 @@ def _get_preallocated_maps(node, thunk, prealloc_modes, def_val, ...@@ -1137,7 +1156,7 @@ def _get_preallocated_maps(node, thunk, prealloc_modes, def_val,
# inplace. # inplace.
if isinstance(r.type, (TensorType, CudaNdarrayType)): if isinstance(r.type, (TensorType, CudaNdarrayType)):
reuse_outputs[r][...] = numpy.asarray( reuse_outputs[r][...] = numpy.asarray(
def_val).astype(r.type.dtype) def_val).astype(r.type.dtype)
if reuse_outputs: if reuse_outputs:
yield ('previous', reuse_outputs) yield ('previous', reuse_outputs)
...@@ -1169,16 +1188,16 @@ def _get_preallocated_maps(node, thunk, prealloc_modes, def_val, ...@@ -1169,16 +1188,16 @@ def _get_preallocated_maps(node, thunk, prealloc_modes, def_val,
for r in considered_outputs: for r in considered_outputs:
if isinstance(r.type, (TensorType, CudaNdarrayType)): if isinstance(r.type, (TensorType, CudaNdarrayType)):
new_buf = numpy.zeros( new_buf = numpy.zeros(
shape=r_vals[r].shape, shape=r_vals[r].shape,
dtype=r_vals[r].dtype, dtype=r_vals[r].dtype,
order='F') order='F')
new_buf[...] = def_val new_buf[...] = def_val
if isinstance(r.type, CudaNdarrayType): if isinstance(r.type, CudaNdarrayType):
# When the CudaNdarray is built, the underlying memory # When the CudaNdarray is built, the underlying memory
# is c-contiguous, so we transpose it before and after. # is c-contiguous, so we transpose it before and after.
new_buf = CudaNdarray(new_buf.T) new_buf = CudaNdarray(new_buf.T)
new_buf = cuda_dimshuffle(new_buf, new_buf = cuda_dimshuffle(new_buf,
range(new_buf.ndim)[::-1]) range(new_buf.ndim)[::-1])
f_cont_outputs[r] = new_buf f_cont_outputs[r] = new_buf
...@@ -1195,8 +1214,8 @@ def _get_preallocated_maps(node, thunk, prealloc_modes, def_val, ...@@ -1195,8 +1214,8 @@ def _get_preallocated_maps(node, thunk, prealloc_modes, def_val,
# Dimensions should be align by the innermost index, so we iterate # Dimensions should be align by the innermost index, so we iterate
# from the end of shapes. # from the end of shapes.
if ('strided' in prealloc_modes or if ('strided' in prealloc_modes or
'wrong_size' in prealloc_modes or 'wrong_size' in prealloc_modes or
'ALL' in prealloc_modes): 'ALL' in prealloc_modes):
max_ndim = 0 max_ndim = 0
rev_out_broadcastable = [] rev_out_broadcastable = []
for r in considered_outputs: for r in considered_outputs:
...@@ -1297,11 +1316,11 @@ def _get_preallocated_maps(node, thunk, prealloc_modes, def_val, ...@@ -1297,11 +1316,11 @@ def _get_preallocated_maps(node, thunk, prealloc_modes, def_val,
if isinstance(r.type, (TensorType, CudaNdarrayType)): if isinstance(r.type, (TensorType, CudaNdarrayType)):
r_shape_diff = shape_diff[:r.ndim] r_shape_diff = shape_diff[:r.ndim]
out_shape = [max((s + sd), 0) out_shape = [max((s + sd), 0)
for s, sd in zip(r_vals[r].shape, for s, sd in zip(r_vals[r].shape,
r_shape_diff)] r_shape_diff)]
new_buf = r.type.value_zeros(out_shape) new_buf = r.type.value_zeros(out_shape)
new_buf[...] = numpy.asarray( new_buf[...] = numpy.asarray(
def_val).astype(r.type.dtype) def_val).astype(r.type.dtype)
wrong_size[r] = new_buf wrong_size[r] = new_buf
if wrong_size: if wrong_size:
...@@ -1310,8 +1329,8 @@ def _get_preallocated_maps(node, thunk, prealloc_modes, def_val, ...@@ -1310,8 +1329,8 @@ def _get_preallocated_maps(node, thunk, prealloc_modes, def_val,
def _check_preallocated_output(node, thunk, prealloc_modes, def_val, def _check_preallocated_output(node, thunk, prealloc_modes, def_val,
storage_map, r_vals, dr_vals, perform, active_order_set, storage_map, r_vals, dr_vals, perform,
inplace_outs, init_outputs): active_order_set, inplace_outs, init_outputs):
'''Try to apply thunk() on different output storages''' '''Try to apply thunk() on different output storages'''
# If node has an inner compiled Theano function with mode DebugMode, # If node has an inner compiled Theano function with mode DebugMode,
...@@ -1325,7 +1344,7 @@ def _check_preallocated_output(node, thunk, prealloc_modes, def_val, ...@@ -1325,7 +1344,7 @@ def _check_preallocated_output(node, thunk, prealloc_modes, def_val,
or not hasattr(fn, 'maker') or not hasattr(fn, 'maker')
or not hasattr(fn.maker, 'mode')): or not hasattr(fn.maker, 'mode')):
_logger.warn('Expected theano function not found in %s.%s', _logger.warn('Expected theano function not found in %s.%s',
node.op, fn_attr_name) node.op, fn_attr_name)
else: else:
if isinstance(fn.maker.mode, DebugMode): if isinstance(fn.maker.mode, DebugMode):
backup_mode = fn.maker.mode backup_mode = fn.maker.mode
...@@ -1378,9 +1397,10 @@ def _check_preallocated_output(node, thunk, prealloc_modes, def_val, ...@@ -1378,9 +1397,10 @@ def _check_preallocated_output(node, thunk, prealloc_modes, def_val,
# Check outputs # Check outputs
for r in node.outputs: for r in node.outputs:
if not r.type.is_valid_value(storage_map[r][0]): if not r.type.is_valid_value(storage_map[r][0]):
raise InvalidValueError(r, storage_map[r][0], raise InvalidValueError(
hint=thunk_name, r, storage_map[r][0],
specific_hint=r.type.value_validity_msg( hint=thunk_name,
specific_hint=r.type.value_validity_msg(
storage_map[r][0])) storage_map[r][0]))
_check_inputs(node, storage_map, r_vals, dr_vals, active_order_set, _check_inputs(node, storage_map, r_vals, dr_vals, active_order_set,
...@@ -1393,11 +1413,14 @@ def _check_preallocated_output(node, thunk, prealloc_modes, def_val, ...@@ -1393,11 +1413,14 @@ def _check_preallocated_output(node, thunk, prealloc_modes, def_val,
for r in node.outputs: for r in node.outputs:
if not check_eq(r, r_vals[r], storage_map[r][0]): if not check_eq(r, r_vals[r], storage_map[r][0]):
# TODO: indicate it is not a C/Py problem # TODO: indicate it is not a C/Py problem
inputs_val = [storage_map[inp][0] for inp in r.owner.inputs] inputs_val = [storage_map[inp][0] for inp in
r.owner.inputs]
raise BadThunkOutput(r, raise BadThunkOutput(r,
thunk1='Reference value', val1=r_vals[r], thunk1='Reference value',
thunk2=thunk_name, val2=storage_map[r][0], val1=r_vals[r],
inputs_val=inputs_val) thunk2=thunk_name,
val2=storage_map[r][0],
inputs_val=inputs_val)
# Clear storage_map # Clear storage_map
for r in node.outputs: for r in node.outputs:
...@@ -1451,12 +1474,10 @@ class _FunctionGraphEvent(object): ...@@ -1451,12 +1474,10 @@ class _FunctionGraphEvent(object):
msg = '' msg = ''
return ' '.join(['change', return ' '.join(['change',
self.reason, self.reason,
str(self.op), str(self.op),
str(self.idx), str(self.idx),
msg]) msg])
# backport
# str(len(self.node.inputs)) if (self.op != 'output') else ''])
else: else:
return str(self.__dict__) return str(self.__dict__)
...@@ -1475,7 +1496,8 @@ class _FunctionGraphEvent(object): ...@@ -1475,7 +1496,8 @@ class _FunctionGraphEvent(object):
class _VariableEquivalenceTracker(object): class _VariableEquivalenceTracker(object):
"""A FunctionGraph Feature that keeps tabs on an FunctionGraph and tries to detect problems.""" """A FunctionGraph Feature that keeps tabs on an FunctionGraph and
tries to detect problems."""
fgraph = None fgraph = None
"""WRITEME""" """WRITEME"""
...@@ -1524,7 +1546,6 @@ class _VariableEquivalenceTracker(object): ...@@ -1524,7 +1546,6 @@ class _VariableEquivalenceTracker(object):
def on_prune(self, fgraph, node, reason): def on_prune(self, fgraph, node, reason):
self.event_list.append(_FunctionGraphEvent('prune', node, self.event_list.append(_FunctionGraphEvent('prune', node,
reason=reason)) reason=reason))
# print 'PRUNING NODE', node, id(node)
assert node in self.active_nodes assert node in self.active_nodes
assert node not in self.inactive_nodes assert node not in self.inactive_nodes
self.active_nodes.remove(node) self.active_nodes.remove(node)
...@@ -1534,7 +1555,6 @@ class _VariableEquivalenceTracker(object): ...@@ -1534,7 +1555,6 @@ class _VariableEquivalenceTracker(object):
self.event_list.append(_FunctionGraphEvent('import', node, self.event_list.append(_FunctionGraphEvent('import', node,
reason=reason)) reason=reason))
# print 'NEW NODE', node, id(node)
assert node not in self.active_nodes assert node not in self.active_nodes
self.active_nodes.add(node) self.active_nodes.add(node)
...@@ -1554,9 +1574,8 @@ class _VariableEquivalenceTracker(object): ...@@ -1554,9 +1574,8 @@ class _VariableEquivalenceTracker(object):
self.replaced_by.setdefault(r, []) self.replaced_by.setdefault(r, [])
def on_change_input(self, fgraph, node, i, r, new_r, reason=None): def on_change_input(self, fgraph, node, i, r, new_r, reason=None):
# print 'CHANGE by', reason, 'to use', new_r, type(new_r)
self.event_list.append(_FunctionGraphEvent('change', node, self.event_list.append(_FunctionGraphEvent('change', node,
reason=str(reason), idx=i)) reason=str(reason), idx=i))
self.reasons.setdefault(new_r, []) self.reasons.setdefault(new_r, [])
self.replaced_by.setdefault(new_r, []) self.replaced_by.setdefault(new_r, [])
...@@ -1570,12 +1589,13 @@ class _VariableEquivalenceTracker(object): ...@@ -1570,12 +1589,13 @@ class _VariableEquivalenceTracker(object):
# N.B. compute the debugprint now, because future # N.B. compute the debugprint now, because future
# optimizations will change the graph # optimizations will change the graph
done = dict() done = dict()
self.reasons[new_r].append((reason, self.reasons[new_r].append(
r, (reason,
debugprint(r, prefix=' ', depth=6, r,
file=StringIO(), done=done).getvalue(), debugprint(r, prefix=' ', depth=6,
debugprint(new_r, prefix=' ', depth=6, file=StringIO(), done=done).getvalue(),
file=StringIO(), done=done).getvalue())) debugprint(new_r, prefix=' ', depth=6,
file=StringIO(), done=done).getvalue()))
self.replaced_by[r].append((reason, new_r)) self.replaced_by[r].append((reason, new_r))
if r in self.equiv: if r in self.equiv:
...@@ -1647,26 +1667,28 @@ class _Linker(gof.link.LocalLinker): ...@@ -1647,26 +1667,28 @@ class _Linker(gof.link.LocalLinker):
self.no_recycling = no_recycling self.no_recycling = no_recycling
return self return self
def make_all(self, profiler=None, input_storage=None def make_all(self, profiler=None, input_storage=None,
, output_storage=None): output_storage=None):
# can't import at toplevel because of circular import TODO:
# don't do this ugly hacky way of setting the
# filter_checks_isfinite
from theano.tensor import TensorType # to set filter_check_isfinite
if 1:
# can't import at toplevel because of circular import TODO:
# don't do this ugly hacky way of setting the
# filter_checks_isfinite
from theano.tensor import TensorType # to set filter_check_isfinite
fgraph = self.fgraph fgraph = self.fgraph
input_storage_ = input_storage input_storage_ = input_storage
output_storage_ = output_storage output_storage_ = output_storage
#order = self.schedule(fgraph)
# Compute a topological ordering that IGNORES the destroy_map of destructive Ops. # Compute a topological ordering that IGNORES the destroy_map
# This will be OK, because every thunk is evaluated on a copy of its input. # of destructive Ops. This will be OK, because every thunk is
order_outputs = copy.copy(fgraph.equivalence_tracker.all_variables_ever) # evaluated on a copy of its input.
fgraph_equiv = fgraph.equivalence_tracker
order_outputs = copy.copy(fgraph_equiv.all_variables_ever)
del fgraph_equiv
order_outputs.reverse() order_outputs.reverse()
order = graph.io_toposort(fgraph.inputs, order_outputs) order = graph.io_toposort(fgraph.inputs, order_outputs)
active_order = self.schedule(fgraph) # an ordering of just the active nodes # an ordering of just the active nodes
active_order = self.schedule(fgraph)
active_order_set = set(active_order) active_order_set = set(active_order)
# Disable no_recycling, in order to be able to use # Disable no_recycling, in order to be able to use
...@@ -1682,9 +1704,6 @@ class _Linker(gof.link.LocalLinker): ...@@ -1682,9 +1704,6 @@ class _Linker(gof.link.LocalLinker):
thunks_c = [] # c thunks thunks_c = [] # c thunks
for node in order: for node in order:
node_input_storage = [storage_map[r] for r in node.inputs]
node_output_storage = [storage_map[r] for r in node.outputs]
compute_map = {} compute_map = {}
for k in node.inputs: for k in node.inputs:
compute_map[k] = [True] compute_map[k] = [True]
...@@ -1696,7 +1715,8 @@ class _Linker(gof.link.LocalLinker): ...@@ -1696,7 +1715,8 @@ class _Linker(gof.link.LocalLinker):
# the compilation of some dependency is triggered there. # the compilation of some dependency is triggered there.
thunk_other = None thunk_other = None
if get_unbound_function(node.op.make_thunk) not in default_make_thunk: if (get_unbound_function(node.op.make_thunk) not in
default_make_thunk):
thunk = node.op.make_thunk(node, thunk = node.op.make_thunk(node,
storage_map, storage_map,
compute_map, compute_map,
...@@ -1725,7 +1745,8 @@ class _Linker(gof.link.LocalLinker): ...@@ -1725,7 +1745,8 @@ class _Linker(gof.link.LocalLinker):
# raises an not implemented exception), so in those cases we # raises an not implemented exception), so in those cases we
# consider that we don't have a python implementation # consider that we don't have a python implementation
if ((self.maker.mode.check_py_code or thunks_c[-1] is None) and if ((self.maker.mode.check_py_code or thunks_c[-1] is None) and
node.op.perform.func_code != gof.op.PureOp.perform.func_code): (node.op.perform.func_code !=
gof.op.PureOp.perform.func_code)):
thunk = node.op.make_py_thunk(node, storage_map, compute_map, thunk = node.op.make_py_thunk(node, storage_map, compute_map,
no_recycling) no_recycling)
thunks_py.append(thunk) thunks_py.append(thunk)
...@@ -1739,7 +1760,9 @@ class _Linker(gof.link.LocalLinker): ...@@ -1739,7 +1760,9 @@ class _Linker(gof.link.LocalLinker):
elif thunks_c[-1] is None: elif thunks_c[-1] is None:
thunks_c[-1] = thunk_other thunks_c[-1] = thunk_other
else: else:
_logger.warn("We won't check the perform function of node '%s' but we will check its make_thunk function" % node) _logger.warn("We won't check the perform function "
"of node '%s' but we will check its "
"make_thunk function" % node)
thunks_py[-1] = thunk_other thunks_py[-1] = thunk_other
# Use self.no_recycling (that was passed in accept()) to always # Use self.no_recycling (that was passed in accept()) to always
...@@ -1747,10 +1770,11 @@ class _Linker(gof.link.LocalLinker): ...@@ -1747,10 +1770,11 @@ class _Linker(gof.link.LocalLinker):
# function's outputs. no_recycling_map will be used in f() below. # function's outputs. no_recycling_map will be used in f() below.
if self.no_recycling is True: if self.no_recycling is True:
no_recycling_map = storage_map.values() no_recycling_map = storage_map.values()
no_recycling_map = utils.difference(no_recycling_map, input_storage) no_recycling_map = utils.difference(no_recycling_map,
input_storage)
else: else:
no_recycling_map = [storage_map[r] for r in self.no_recycling no_recycling_map = [storage_map[r] for r in self.no_recycling
if r not in fgraph.inputs] if r not in fgraph.inputs]
# Precompute some things for storage pre-allocation # Precompute some things for storage pre-allocation
try: try:
...@@ -1769,7 +1793,7 @@ class _Linker(gof.link.LocalLinker): ...@@ -1769,7 +1793,7 @@ class _Linker(gof.link.LocalLinker):
##### #####
_logger.debug("starting a DebugMode call") _logger.debug("starting a DebugMode call")
_logger.debug("self.maker.mode.check_preallocated_output: %s", _logger.debug("self.maker.mode.check_preallocated_output: %s",
self.maker.mode.check_preallocated_output) self.maker.mode.check_preallocated_output)
for x in no_recycling_map: for x in no_recycling_map:
x[0] = None x[0] = None
...@@ -1784,14 +1808,17 @@ class _Linker(gof.link.LocalLinker): ...@@ -1784,14 +1808,17 @@ class _Linker(gof.link.LocalLinker):
# the evaluation of this function, even when the graph # the evaluation of this function, even when the graph
# has destructive ops in it # has destructive ops in it
# #
# This dictionary is used to populate the storage_map as necessary # This dictionary is used to populate the storage_map
# as necessary
r_vals = {} r_vals = {}
# dr_vals are the values taken by variables after being destroyed # dr_vals are the values taken by variables after
# being destroyed
dr_vals = {} dr_vals = {}
assert len(thunks_py) == len(order) assert len(thunks_py) == len(order)
# transfer the initial values from the storage_map to the r_vals # transfer the initial values from the storage_map to
# the r_vals
_logger.debug("DEBUGMODE: transfer initial values") _logger.debug("DEBUGMODE: transfer initial values")
# r_vals_initialized keeps track of the values that have # r_vals_initialized keeps track of the values that have
# actually been transferred from storage_map to r_vals # actually been transferred from storage_map to r_vals
...@@ -1803,17 +1830,20 @@ class _Linker(gof.link.LocalLinker): ...@@ -1803,17 +1830,20 @@ class _Linker(gof.link.LocalLinker):
# for a Generic object). We only want to raise # for a Generic object). We only want to raise
# an error if it is not valid. # an error if it is not valid.
if (storage_map[r][0] is None): if (storage_map[r][0] is None):
raise InvalidValueError(r, storage_map[r][0], raise InvalidValueError(
hint="Graph Input '%s' is missing" % str(r)) r, storage_map[r][0],
raise InvalidValueError(r, storage_map[r][0], hint=("Graph Input '%s' is missing" %
hint=("Graph Input '%s' has invalid value " str(r)))
"%s" % (r, storage_map[r][0]))) raise InvalidValueError(
r, storage_map[r][0],
hint=("Graph Input '%s' has invalid value "
"%s" % (r, storage_map[r][0])))
r_vals[r] = storage_map[r][0] r_vals[r] = storage_map[r][0]
storage_map[r][0] = None storage_map[r][0] = None
r_vals_initialized.append(r) r_vals_initialized.append(r)
# store preallocated outputs in another map, and test the thunks on # store preallocated outputs in another map, and test
# them as output storages. # the thunks on them as output storages.
init_outputs = {} init_outputs = {}
for r in storage_map: for r in storage_map:
if r in fgraph.outputs: if r in fgraph.outputs:
...@@ -1835,8 +1865,6 @@ class _Linker(gof.link.LocalLinker): ...@@ -1835,8 +1865,6 @@ class _Linker(gof.link.LocalLinker):
for i, (thunk_py, thunk_c, node) in enumerate(zip(thunks_py, for i, (thunk_py, thunk_c, node) in enumerate(zip(thunks_py,
thunks_c, thunks_c,
order)): order)):
this_node_destroyed_variables = set()
_logger.debug("%i - starting node %i %s", i, i, node) _logger.debug("%i - starting node %i %s", i, i, node)
# put a copy of each input into the storage_map # put a copy of each input into the storage_map
...@@ -1844,7 +1872,6 @@ class _Linker(gof.link.LocalLinker): ...@@ -1844,7 +1872,6 @@ class _Linker(gof.link.LocalLinker):
for r in node.inputs: for r in node.inputs:
assert isinstance(r, gof.Variable) assert isinstance(r, gof.Variable)
assert r in r_vals assert r in r_vals
# print >> sys.stderr,i, "DEBUGMODE: deepcopy input ", r
storage_map[r][0] = _lessbroken_deepcopy(r_vals[r]) storage_map[r][0] = _lessbroken_deepcopy(r_vals[r])
if not r.type.is_valid_value(storage_map[r][0]): if not r.type.is_valid_value(storage_map[r][0]):
raise InvalidValueError(r, storage_map[r][0], raise InvalidValueError(r, storage_map[r][0],
...@@ -1854,7 +1881,7 @@ class _Linker(gof.link.LocalLinker): ...@@ -1854,7 +1881,7 @@ class _Linker(gof.link.LocalLinker):
# storage will be None # storage will be None
if thunk_py: if thunk_py:
_logger.debug("%i - running thunk_py with None as " _logger.debug("%i - running thunk_py with None as "
"output storage", i) "output storage", i)
try: try:
thunk_py() thunk_py()
except utils.MethodNotDefined: except utils.MethodNotDefined:
...@@ -1872,10 +1899,12 @@ class _Linker(gof.link.LocalLinker): ...@@ -1872,10 +1899,12 @@ class _Linker(gof.link.LocalLinker):
raise raise
opt = str(reason[0][0]) opt = str(reason[0][0])
msg = ( msg = (
"An optimization (probably %s ) inserted an apply node that raise an error." % opt + "An optimization (probably %s) inserted an "
"\nThe information we have about this optimizations is:" + str(reason[0][1]) + "apply node that raise an error." % opt +
"\n" + reason[0][2] + "\nThe information we have about this "
"\n\nThe original exception: \n" + str(e)) "optimizations is:" + str(reason[0][1]) +
"\n" + reason[0][2] +
"\n\nThe original exception: \n" + str(e))
new_e = e.__class__(msg) new_e = e.__class__(msg)
exc_type, exc_value, exc_trace = sys.exc_info() exc_type, exc_value, exc_trace = sys.exc_info()
exc_value = new_e exc_value = new_e
...@@ -1891,45 +1920,42 @@ class _Linker(gof.link.LocalLinker): ...@@ -1891,45 +1920,42 @@ class _Linker(gof.link.LocalLinker):
raise InvalidValueError(r, storage_map[r][0], raise InvalidValueError(r, storage_map[r][0],
hint='perform output', hint='perform output',
specific_hint=hint2) specific_hint=hint2)
warn_inp = config.DebugMode.warn_input_not_reused
py_inplace_outs = _check_inputs( py_inplace_outs = _check_inputs(
node, storage_map, r_vals, dr_vals, node, storage_map, r_vals, dr_vals,
active_order_set, active_order_set,
clobber_dr_vals=True, perform='py', clobber_dr_vals=True, perform='py',
warn_input_not_reused=config.DebugMode.warn_input_not_reused) warn_input_not_reused=warn_inp)
_check_viewmap(node, storage_map) _check_viewmap(node, storage_map)
# Retrieve each output from the storage_map # Retrieve each output from the storage_map.
# The return values of this first run will be the reference ones # The return values of this first run will be
# the reference ones
for r in node.outputs: for r in node.outputs:
assert r not in r_vals assert r not in r_vals
# print >> sys.stderr, i, "DEBUGMODE storing reference output %x" % id(storage_map[r][0])
r_vals[r] = storage_map[r][0] r_vals[r] = storage_map[r][0]
# clear the storage_map of outputs for the thunk_c # clear the storage_map of outputs for the thunk_c
storage_map[r][0] = None storage_map[r][0] = None
if self.maker.mode.check_preallocated_output: if self.maker.mode.check_preallocated_output:
prealloc_modes = \ prealloc_modes = \
self.maker.mode.check_preallocated_output self.maker.mode.check_preallocated_output
_logger.debug( _logger.debug(
'%i - calling _check_preallocated_output ' '%i - calling _check_preallocated_output '
'with thunk_py', i) 'with thunk_py', i)
_check_preallocated_output( _check_preallocated_output(
node=node, node=node,
thunk=thunk_py, thunk=thunk_py,
prealloc_modes=prealloc_modes, prealloc_modes=prealloc_modes,
def_val=def_val, def_val=def_val,
storage_map=storage_map, storage_map=storage_map,
r_vals=r_vals, r_vals=r_vals,
dr_vals=dr_vals, dr_vals=dr_vals,
perform='py', perform='py',
active_order_set=active_order_set, active_order_set=active_order_set,
inplace_outs=py_inplace_outs, inplace_outs=py_inplace_outs,
init_outputs=init_outputs) init_outputs=init_outputs)
# print >> sys.stderr, i, "DEBUGMODE thunk_py %100s %50s %30s" % (node,
#[(id(o), numpy.asarray(storage_map[o][0])[0,0]) for o in node.inputs],
#[(id(o), numpy.asarray(storage_map[o][0])[0,0]) for o in node.outputs])
sys.stdout.flush() sys.stdout.flush()
if thunk_c: if thunk_c:
...@@ -1939,18 +1965,22 @@ class _Linker(gof.link.LocalLinker): ...@@ -1939,18 +1965,22 @@ class _Linker(gof.link.LocalLinker):
dmap = getattr(node.op, 'destroy_map', {}) dmap = getattr(node.op, 'destroy_map', {})
vmap = getattr(node.op, 'view_map', {}) vmap = getattr(node.op, 'view_map', {})
for i, r in enumerate(node.inputs): for i, r in enumerate(node.inputs):
# if thunk_py ran, and we still got this far, # if thunk_py ran, and we still got
# it means that the destroy_map of the Op (and view_map) are # this far, it means that the
# accurate # destroy_map of the Op (and view_map)
# so we can assume that inputs not marked as destroyed have in # are accurate so we can assume that
# fact not been destroyed. # inputs not marked as destroyed have
# Therefore... we only need to overwrite inputs that *have* # in fact not been destroyed.
# been marked as destroyed. # Therefore... we only need to
# Inputs marked as viewd are unsafe too, # overwrite inputs that *have* been
# because the corresponding output can # marked as destroyed. Inputs marked
# be destroyed. # as viewd are unsafe too, because the
if any(i in v for v in (dmap.values() + vmap.values())): # corresponding output can be
storage_map[r][0] = _lessbroken_deepcopy(r_vals[r]) # destroyed.
if any(i in v for v in (dmap.values() +
vmap.values())):
storage_map[r][0] = _lessbroken_deepcopy(
r_vals[r])
clobber = False clobber = False
...@@ -1969,10 +1999,12 @@ class _Linker(gof.link.LocalLinker): ...@@ -1969,10 +1999,12 @@ class _Linker(gof.link.LocalLinker):
raise raise
opt = str(reason[0][0]) opt = str(reason[0][0])
msg = ( msg = (
"An optimization (probably %s ) inserted an apply node that raise an error." % opt + "An optimization (probably %s) inserted "
"\nThe information we have about this optimizations is:" + str(reason[0][1]) + "an apply node that raise an error." % opt +
"\n" + reason[0][2] + "\nThe information we have about this "
"\n\nThe original exception: \n" + str(e)) "optimizations is:" + str(reason[0][1]) +
"\n" + reason[0][2] +
"\n\nThe original exception: \n" + str(e))
new_e = e.__class__(msg) new_e = e.__class__(msg)
exc_type, exc_value, exc_trace = sys.exc_info() exc_type, exc_value, exc_trace = sys.exc_info()
exc_value = new_e exc_value = new_e
...@@ -1982,21 +2014,26 @@ class _Linker(gof.link.LocalLinker): ...@@ -1982,21 +2014,26 @@ class _Linker(gof.link.LocalLinker):
for r in node.outputs: for r in node.outputs:
# check output values for type-correctness # check output values for type-correctness
if not r.type.is_valid_value(storage_map[r][0]): if not r.type.is_valid_value(storage_map[r][0]):
raise InvalidValueError(r, storage_map[r][0], hint='c output') raise InvalidValueError(r, storage_map[r][0],
hint='c output')
if thunk_py: if thunk_py:
assert r in r_vals # because we put it in during the thunk_py branch # because we put it in during the
# check for stride correctness (may raise exception) # thunk_py branch
_check_strides_match(r_vals[r], assert r in r_vals
storage_map[r][0], # check for stride correctness (may
# raise exception)
_check_strides_match(
r_vals[r], storage_map[r][0],
self.maker.mode.require_matching_strides, self.maker.mode.require_matching_strides,
node.op) node.op)
warn_inp = config.DebugMode.warn_input_not_reused
c_inplace_outs = _check_inputs( c_inplace_outs = _check_inputs(
node, storage_map, r_vals, node, storage_map, r_vals,
dr_vals, active_order_set, dr_vals, active_order_set,
clobber_dr_vals=clobber, perform='c', clobber_dr_vals=clobber, perform='c',
warn_input_not_reused=config.DebugMode.warn_input_not_reused) warn_input_not_reused=warn_inp)
_check_viewmap(node, storage_map) _check_viewmap(node, storage_map)
...@@ -2006,11 +2043,14 @@ class _Linker(gof.link.LocalLinker): ...@@ -2006,11 +2043,14 @@ class _Linker(gof.link.LocalLinker):
# compares the version from thunk_py # compares the version from thunk_py
# (in r_vals) to the version produced # (in r_vals) to the version produced
# by thunk_c (in storage_map) # by thunk_c (in storage_map)
if not check_eq(r, r_vals[r], storage_map[r][0]): if not check_eq(r, r_vals[r],
inputs_val = [storage_map[inp][0] for inp in r.owner.inputs] storage_map[r][0]):
inputs_val = [storage_map[inp][0]
for inp in r.owner.inputs]
raise BadThunkOutput( raise BadThunkOutput(
r, thunk1='perform', val1=r_vals[r], r, thunk1='perform', val1=r_vals[r],
thunk2='c_code', val2=storage_map[r][0], thunk2='c_code',
val2=storage_map[r][0],
inputs_val=inputs_val) inputs_val=inputs_val)
else: else:
# retrieve each output from the storage_map # retrieve each output from the storage_map
...@@ -2020,37 +2060,34 @@ class _Linker(gof.link.LocalLinker): ...@@ -2020,37 +2060,34 @@ class _Linker(gof.link.LocalLinker):
if self.maker.mode.check_preallocated_output: if self.maker.mode.check_preallocated_output:
prealloc_modes = \ prealloc_modes = \
self.maker.mode.check_preallocated_output self.maker.mode.check_preallocated_output
def thunk(): def thunk():
try: try:
thunk_c() thunk_c()
except Exception: except Exception:
raise_with_op(node, thunk_c) raise_with_op(node, thunk_c)
_logger.debug( _logger.debug(
'%i - calling _check_preallocated_output ' '%i - calling _check_preallocated_output '
'with thunk_c', i) 'with thunk_c', i)
_check_preallocated_output( _check_preallocated_output(
node=node, node=node,
thunk=thunk, thunk=thunk,
prealloc_modes=prealloc_modes, prealloc_modes=prealloc_modes,
def_val=def_val, def_val=def_val,
storage_map=storage_map, storage_map=storage_map,
r_vals=r_vals, r_vals=r_vals,
dr_vals=dr_vals, dr_vals=dr_vals,
perform='c code', perform='c code',
active_order_set=active_order_set, active_order_set=active_order_set,
inplace_outs=c_inplace_outs, inplace_outs=c_inplace_outs,
init_outputs=init_outputs) init_outputs=init_outputs)
# print >> sys.stderr, i, "DEBUGMODE thunk_c %100s %50s %30s" % (node,
#[(id(o), numpy.asarray(storage_map[o][0])[0,0]) for o in node.inputs],
#[(id(o), numpy.asarray(storage_map[o][0])[0,0]) for o in node.outputs])
sys.stdout.flush() sys.stdout.flush()
# we're done with this thunk # we're done with this thunk
# clear everything out of the storage_map # clear everything out of the storage_map
for r in node.inputs: for r in node.inputs:
#print >> sys.stderr, i, "DEBUGMODE clearing input", r
storage_map[r][0] = None storage_map[r][0] = None
_logger.debug("%i - done with node", i) _logger.debug("%i - done with node", i)
...@@ -2059,7 +2096,8 @@ class _Linker(gof.link.LocalLinker): ...@@ -2059,7 +2096,8 @@ class _Linker(gof.link.LocalLinker):
# But it is very slow and it is not sure it will help. # But it is very slow and it is not sure it will help.
gc.collect() gc.collect()
_find_bad_optimizations(order, fgraph.equivalence_tracker.reasons, _find_bad_optimizations(order,
fgraph.equivalence_tracker.reasons,
r_vals) r_vals)
##### #####
...@@ -2081,18 +2119,24 @@ class _Linker(gof.link.LocalLinker): ...@@ -2081,18 +2119,24 @@ class _Linker(gof.link.LocalLinker):
for r in r_vals: for r in r_vals:
if r.owner is None: if r.owner is None:
if r in fgraph.inputs: if r in fgraph.inputs:
assert storage_map[r] is input_storage[fgraph.inputs.index(r)] assert (storage_map[r] is
input_storage[fgraph.inputs.index(r)])
storage_map[r][0] = r_vals[r] storage_map[r][0] = r_vals[r]
# if an input was destroyed, the destroyed value should be returned # if an input was destroyed, the destroyed value
# should be returned
for r in dr_vals: for r in dr_vals:
assert dr_vals[r][0] is not None assert dr_vals[r][0] is not None
if r.owner is None: if r.owner is None:
assert r in fgraph.inputs assert r in fgraph.inputs
# HACK TO LOOK LIKE A REAL DESTRUCTIVE ACTION TOOK PLACE # HACK TO LOOK LIKE A REAL DESTRUCTIVE ACTION
if type(dr_vals[r][0]) in (numpy.ndarray, numpy.memmap) \ # TOOK PLACE
and dr_vals[r][0].dtype == storage_map[r][0].dtype \ if ((type(dr_vals[r][0]) in
and dr_vals[r][0].shape == storage_map[r][0].shape: (numpy.ndarray, numpy.memmap)) and
(dr_vals[r][0].dtype ==
storage_map[r][0].dtype) and
(dr_vals[r][0].shape ==
storage_map[r][0].shape)):
if len(dr_vals[r][0].shape): if len(dr_vals[r][0].shape):
storage_map[r][0][:] = dr_vals[r][0] storage_map[r][0][:] = dr_vals[r][0]
else: else:
...@@ -2111,10 +2155,6 @@ class _Linker(gof.link.LocalLinker): ...@@ -2111,10 +2155,6 @@ class _Linker(gof.link.LocalLinker):
storage_map[r][0] = None storage_map[r][0] = None
raise raise
# print ""
# print output_storage
# print dr_vals
# print storage_map
for r in storage_map: for r in storage_map:
if (r.owner is None): if (r.owner is None):
if not r.type.is_valid_value(None): if not r.type.is_valid_value(None):
...@@ -2130,12 +2170,14 @@ class _Linker(gof.link.LocalLinker): ...@@ -2130,12 +2170,14 @@ class _Linker(gof.link.LocalLinker):
# so it will screw up if we are trying to use # so it will screw up if we are trying to use
# multiple modes at once. # multiple modes at once.
old_filter_checks_isfinite = TensorType.filter_checks_isfinite old_filter_checks_isfinite = TensorType.filter_checks_isfinite
TensorType.filter_checks_isfinite = self.maker.mode.check_isfinite TensorType.filter_checks_isfinite = \
self.maker.mode.check_isfinite
try: try:
return f() return f()
finally: finally:
# put back the filter_checks_isfinite # put back the filter_checks_isfinite
TensorType.filter_checks_isfinite = old_filter_checks_isfinite TensorType.filter_checks_isfinite = \
old_filter_checks_isfinite
return deco return deco
f = run_with_tensortype_filter_check(f) f = run_with_tensortype_filter_check(f)
...@@ -2143,12 +2185,12 @@ class _Linker(gof.link.LocalLinker): ...@@ -2143,12 +2185,12 @@ class _Linker(gof.link.LocalLinker):
f.allow_gc = True f.allow_gc = True
assert len(fgraph.inputs) == len(input_storage) assert len(fgraph.inputs) == len(input_storage)
assert len(fgraph.outputs) == len(output_storage) assert len(fgraph.outputs) == len(output_storage)
# print 'make_all returning output', [id(z) for z in output_storage] return (f,
return f, [link.Container(input, storage, readonly=False) [link.Container(input, storage, readonly=False)
for input, storage in zip(fgraph.inputs, input_storage)], \ for input, storage in zip(fgraph.inputs, input_storage)],
[link.Container(output, storage, readonly=True) [link.Container(output, storage, readonly=True)
for output, storage in zip(fgraph.outputs, output_storage)], \ for output, storage in zip(fgraph.outputs, output_storage)],
thunks_py, order thunks_py, order)
_NODEFAULT = ['NODEFAULT'] _NODEFAULT = ['NODEFAULT']
...@@ -2162,33 +2204,37 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions ...@@ -2162,33 +2204,37 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions
0: silent)""" 0: silent)"""
def __init__(self, inputs, outputs, optimizer, mode, def __init__(self, inputs, outputs, optimizer, mode,
accept_inplace=False, accept_inplace=False,
function_builder=Function, function_builder=Function,
profile=None, profile=None,
on_unused_input=None, on_unused_input=None,
output_keys=None): output_keys=None):
""" """
:type inputs: a list of SymbolicInput instances :type inputs: a list of SymbolicInput instances
:type outputs: a list of SymbolicOutput instances :type outputs: a list of SymbolicOutput instances outputs may
outputs may also be a single Variable (not a list), in which also be a single Variable (not a list), in
case the functions produced by FunctionMaker will return which case the functions produced by
their output value directly FunctionMaker will return their output value
directly
:param accept_inplace: True iff it is acceptable to have :param accept_inplace: True iff it is acceptable to have
inplace operations in the graph from the inputs to inplace operations in the graph from the inputs to
the outputs the outputs
:param on_unused_input: What to do if a variable in the 'inputs' list is :param on_unused_input: What to do if a variable in the
not used in the graph. Possible values are 'raise', 'warn', and 'ignore'. 'inputs' list is not used in the
graph. Possible values are 'raise',
'warn', and 'ignore'.
:param output_keys: If the outputs argument for theano.function was a :param output_keys: If the outputs argument for
list, then output_keys is None. If the outputs argument was a dict, theano.function was a list, then
then output_keys is a sorted list of the keys from that dict. output_keys is None. If the outputs
argument was a dict, then output_keys is a
sorted list of the keys from that dict.
:note: this function sets TensorType.filter_checks_isfinite :note: this function sets TensorType.filter_checks_isfinite
when `mode.check_isfinite` is True when `mode.check_isfinite` is True
""" """
self.profile = profile self.profile = profile
# Handle the case where inputs and/or outputs is a single # Handle the case where inputs and/or outputs is a single
...@@ -2205,7 +2251,8 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions ...@@ -2205,7 +2251,8 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions
inputs = [inputs] inputs = [inputs]
# Wrap them in In or Out instances if needed. # Wrap them in In or Out instances if needed.
inputs, outputs = map(self.wrap_in, inputs), map(self.wrap_out, outputs) inputs = map(self.wrap_in, inputs),
outputs = map(self.wrap_out, outputs)
_inputs = gof.graph.inputs([o.variable for o in outputs] + _inputs = gof.graph.inputs([o.variable for o in outputs] +
[i.update for i in inputs [i.update for i in inputs
if getattr(i, 'update', False)]) if getattr(i, 'update', False)])
...@@ -2213,9 +2260,11 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions ...@@ -2213,9 +2260,11 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions
# Check if some input variables are unused # Check if some input variables are unused
self._check_unused_inputs(inputs, outputs, on_unused_input) self._check_unused_inputs(inputs, outputs, on_unused_input)
# Make a list of (SymbolicInput|SymblicInputKits, indices, [SymbolicInput,...]), one # Make a list of (SymbolicInput|SymblicInputKits, indices,
# tuple for each input. (See Function.indices for more details) # [SymbolicInput,...]), one tuple for each input. (See
indices = [[input] + self.expand_in(input, _inputs) for input in inputs] # Function.indices for more details)
indices = [[input] + self.expand_in(input, _inputs)
for input in inputs]
# make the fgraph # make the fgraph
for i in xrange(mode.stability_patience): for i in xrange(mode.stability_patience):
...@@ -2226,58 +2275,53 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions ...@@ -2226,58 +2275,53 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions
# optimize the fgraph # optimize the fgraph
compute_test_value_orig = theano.config.compute_test_value compute_test_value_orig = theano.config.compute_test_value
try: try:
theano.config.compute_test_value = theano.config.compute_test_value_opt theano.config.compute_test_value = \
theano.config.compute_test_value_opt
optimizer(fgraph) optimizer(fgraph)
theano.compile.function_module.insert_deepcopy(fgraph, inputs, theano.compile.function_module.insert_deepcopy(
outputs + additional_outputs) fgraph, inputs, outputs + additional_outputs)
finally: finally:
theano.config.compute_test_value = compute_test_value_orig theano.config.compute_test_value = compute_test_value_orig
if i: if i == 0:
fgraph0 = fgraph
else:
li = fgraph.equivalence_tracker.event_list li = fgraph.equivalence_tracker.event_list
l0 = fgraph0.equivalence_tracker.event_list l0 = fgraph0.equivalence_tracker.event_list
if li != l0 : if li != l0:
infolog = StringIO() infolog = StringIO()
print("WARNING: Optimization process is unstable...", file=infolog) print("WARNING: Optimization process is unstable...",
print(" (HINT: Ops that the nodes point to must compare equal)", file=infolog) file=infolog)
print("(event index) (one event trace) (other event trace)", file=infolog) print(" (HINT: Ops that the nodes point to must compare "
print("-----------------------------------------------------", file=infolog) "equal)", file=infolog)
print("(event index) (one event trace) (other event "
"trace)", file=infolog)
print("-------------------------------------------------"
"----", file=infolog)
for j in xrange(max(len(li), len(l0))): for j in xrange(max(len(li), len(l0))):
if j >= len(li): if j >= len(li):
print('trailing event in optimization 0 :', j, file=infolog) print('trailing event in optimization 0 :', j,
file=infolog)
print(' ', str(l0[j]), file=infolog) print(' ', str(l0[j]), file=infolog)
elif j >= len(l0): elif j >= len(l0):
print('trailing event in optimization', i, ':', j, file=infolog) print('trailing event in optimization', i, ':',
j, file=infolog)
print(' ', str(li[j]), file=infolog) print(' ', str(li[j]), file=infolog)
elif li[j] != l0[j]: elif li[j] != l0[j]:
print('non-equal optimization events', i, ':', j, file=infolog) print('non-equal optimization events', i, ':',
j, file=infolog)
print(' ', str(l0[j]), file=infolog) print(' ', str(l0[j]), file=infolog)
print(' ', str(li[j]), file=infolog) print(' ', str(li[j]), file=infolog)
#print >> infolog, "* ", j,
# if j < len(li):
# msg = str(li[j])
# else:
# msg = '-'
#print >> infolog, " ", msg
# if j < len(l0):
# msg = str(l0[j])
# else:
# msg = '-'
#print >> infolog, " ", msg
else: else:
pass pass
raise StochasticOrder(infolog.getvalue()) raise StochasticOrder(infolog.getvalue())
else: else:
if self.verbose: if self.verbose:
print("OPTCHECK: optimization", i, \ print("OPTCHECK: optimization", i,
"of", len(li), "events was stable.", file=sys.stderr) "of", len(li), "events was stable.",
else: file=sys.stderr)
fgraph0 = fgraph
del fgraph0
self.fgraph = fgraph self.fgraph = fgraph
# equivalence_tracker.printstuff()
linker = _Linker(self) linker = _Linker(self)
...@@ -2285,14 +2329,14 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions ...@@ -2285,14 +2329,14 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions
# the internal storage pointer. # the internal storage pointer.
no_borrow = [ no_borrow = [
output output
for output, spec in izip(fgraph.outputs, for output, spec in izip(fgraph.outputs,
outputs + additional_outputs) outputs + additional_outputs)
if not spec.borrow] if not spec.borrow]
if no_borrow: if no_borrow:
self.linker = linker.accept( self.linker = linker.accept(
fgraph, fgraph,
no_recycling=infer_reuse_pattern(fgraph, no_borrow)) no_recycling=infer_reuse_pattern(fgraph, no_borrow))
else: else:
self.linker = linker.accept(fgraph) self.linker = linker.accept(fgraph)
...@@ -2351,8 +2395,8 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions ...@@ -2351,8 +2395,8 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions
input_storage += [default[i].storage for i in indices] input_storage += [default[i].storage for i in indices]
else: else:
raise ValueError( raise ValueError(
'Not enough storage for SymbolicInputKit', 'Not enough storage for SymbolicInputKit',
input, indices, default) input, indices, default)
default = _NODEFAULT default = _NODEFAULT
else: else:
input_storage += [[None] for i in indices] input_storage += [[None] for i in indices]
...@@ -2389,8 +2433,8 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions ...@@ -2389,8 +2433,8 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions
else: else:
# This might catch some bugs early # This might catch some bugs early
raise ValueError( raise ValueError(
"A default (initial) value is required for an " "A default (initial) value is required for an "
"input which can update itself.", input) "input which can update itself.", input)
else: else:
_defaults.append((False, False, default)) _defaults.append((False, False, default))
else: else:
...@@ -2512,14 +2556,14 @@ class DebugMode(Mode): ...@@ -2512,14 +2556,14 @@ class DebugMode(Mode):
return _Maker(i, o, self.optimizer, self, *args, **kwargs) return _Maker(i, o, self.optimizer, self, *args, **kwargs)
def __init__(self, def __init__(self,
optimizer='fast_run', optimizer='fast_run',
stability_patience=None, stability_patience=None,
check_c_code=None, check_c_code=None,
check_py_code=None, check_py_code=None,
check_isfinite=None, check_isfinite=None,
check_preallocated_output=None, check_preallocated_output=None,
require_matching_strides=None, require_matching_strides=None,
linker=_DummyLinker()): linker=_DummyLinker()):
"""Initialize member variables. """Initialize member variables.
If any of these arguments (except optimizer) is not None, it overrides If any of these arguments (except optimizer) is not None, it overrides
...@@ -2532,9 +2576,8 @@ class DebugMode(Mode): ...@@ -2532,9 +2576,8 @@ class DebugMode(Mode):
raise Exception("DebugMode can only use its own linker! You " raise Exception("DebugMode can only use its own linker! You "
"should not provide one.", linker) "should not provide one.", linker)
super(DebugMode, self).__init__( super(DebugMode, self).__init__(optimizer=optimizer,
optimizer=optimizer, linker=linker)
linker=linker)
if stability_patience is not None: if stability_patience is not None:
self.stability_patience = stability_patience self.stability_patience = stability_patience
...@@ -2561,6 +2604,6 @@ class DebugMode(Mode): ...@@ -2561,6 +2604,6 @@ class DebugMode(Mode):
def __str__(self): def __str__(self):
return "DebugMode(linker=%s, optimizer=%s)" % ( return "DebugMode(linker=%s, optimizer=%s)" % (
self.provided_linker, self.provided_optimizer) self.provided_linker, self.provided_optimizer)
register_mode('DEBUG_MODE', DebugMode(optimizer='fast_run')) register_mode('DEBUG_MODE', DebugMode(optimizer='fast_run'))
theano/tests/test_flake8.py
浏览文件 @ 3578c80c
...@@ -38,7 +38,6 @@ whitelist_flake8 = [ ...@@ -38,7 +38,6 @@ whitelist_flake8 = [
"tests/test_tutorial.py", "tests/test_tutorial.py",
"tests/disturb_mem.py", "tests/disturb_mem.py",
"tests/unittest_tools.py", "tests/unittest_tools.py",
"compile/debugmode.py",
"compile/function.py", "compile/function.py",
"compile/pfunc.py", "compile/pfunc.py",
"compile/mode.py", "compile/mode.py",
......
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