from theano.gof.link import WrapLinker
from theano.compile.mode import (Mode, register_mode, predefined_modes,
predefined_linkers, predefined_optimizers)
from theano.gof.python25 import any
from theano import gof
from theano.configparser import config, AddConfigVar, IntParam, BoolParam
from theano.compile.function_module import FunctionMaker
run_cthunk = None # Will be imported only when needed.
from profiling import ProfileStats
import_time = time.time()
AddConfigVar('ProfileMode.n_apply_to_print',
"Number of apply instances to print by default",
IntParam(15, lambda i: i > 0),
in_c_key=False)
AddConfigVar('ProfileMode.n_ops_to_print',
"Number of ops to print by default",
IntParam(20, lambda i: i > 0),
in_c_key=False)
AddConfigVar('ProfileMode.min_memory_size',
"""For the memory profile, do not print apply nodes if the size
of their outputs (in bytes) is lower then this threshold""",
IntParam(1024, lambda i: i >= 0),
in_c_key=False)
AddConfigVar('ProfileMode.profile_memory',
"""Enable profiling of memory used by Theano functions""",
import logging
from contextlib import contextmanager
from theano import config
from theano.configparser import AddConfigVar, IntParam
_logger = logging.getLogger("theano.gof.compilelock")
# If the user provided a logging level, we don't want to override it.
if _logger.level == logging.NOTSET:
# INFO will show the "Refreshing lock" messages
_logger.setLevel(logging.INFO)
AddConfigVar('compile.wait',
"""Time to wait before retrying to aquire the compile lock.""",
IntParam(5, lambda i: i > 0, allow_override=False),
in_c_key=False)
def _timeout_default():
return config.compile.wait * 24
AddConfigVar('compile.timeout',
"""In seconds, time that a process will wait before deciding to
override an existing lock. An override only happens when the existing
lock is held by the same owner *and* has not been 'refreshed' by this
owner for more than this period. Refreshes are done every half timeout
period for running processes.""",
IntParam(_timeout_default, lambda i: i >= 0,
allow_override=False),
in_c_key=False)
AddConfigVar('on_unused_input',
"What to do if a variable in the 'inputs' list of "
" theano.function() is not used in the graph.",
EnumStr('raise', 'warn', 'ignore'),
in_c_key=False)
# This flag is used when we import Theano to initialize global variables.
# So changing it after import will not modify these global variables.
# This could be done differently... but for now we simply prevent it from being
# changed at runtime.
AddConfigVar(
'tensor.cmp_sloppy',
"Relax tensor._allclose (0) not at all, (1) a bit, (2) more",
IntParam(0, lambda i: i in (0, 1, 2), allow_override=False),
in_c_key=False)
AddConfigVar(
'tensor.local_elemwise_fusion',
("Enable or not in fast_run mode(fast_run optimization) the elemwise "
"fusion optimization"),
BoolParam(True),
in_c_key=False)
AddConfigVar(
'gpu.local_elemwise_fusion',
("Enable or not in fast_run mode(fast_run optimization) the gpu "
"elemwise fusion optimization"),
BoolParam(True),
in_c_key=False)