import os
import subprocess
import logging

from theano.configparser import TheanoConfigParser, AddConfigVar, EnumStr, StrParam, IntParam, FloatParam, BoolParam

_logger = logging.getLogger('theano.configdefaults')

config = TheanoConfigParser()

AddConfigVar('floatX',
        "Default floating-point precision for python casts",
        EnumStr('float64', 'float32'),
        )

AddConfigVar('cast_policy',
        "Rules for implicit type casting",
        EnumStr('custom', 'numpy+floatX',
                # The 'numpy' policy was originally planned to provide a smooth
                # transition from numpy. It was meant to behave the same as
                # numpy+floatX, but keeping float64 when numpy would. However
                # the current implementation of some cast mechanisms makes it
                # a bit more complex to add than what was expected, so it is
                # currently not available.
                #numpy,
               ),
        )

AddConfigVar('int_division',
        "What to do when one computes x / y, where both x and y are of "
        "integer types",
        EnumStr('int', 'raise', 'floatX'),
        in_c_key=False)

#gpu mean let the driver select the gpu. Needed in case of gpu in exclusive mode.
#gpuX mean use the gpu number X.
AddConfigVar('device',
        "Default device for computations. If gpu*, change the default to try to move computation to it and to put shared variable of float32 on it.",
        EnumStr('cpu', 'gpu',
            'gpu0', 'gpu1', 'gpu2', 'gpu3',
            'gpu4', 'gpu5', 'gpu6', 'gpu7',
            'gpu8', 'gpu9', 'gpu10', 'gpu11',
            'gpu12', 'gpu13', 'gpu14', 'gpu15',
                allow_override=False),
        in_c_key=False,
        )

AddConfigVar('init_gpu_device',
        ("Initialize the gpu device to use, works only if device=cpu. "
         "Unlike 'device', setting this option will NOT move computations, "
         "nor shared variables, to the specified GPU. "
         "It can be used to run GPU-specific tests on a particular GPU."),
        EnumStr('', 'gpu',
            'gpu0', 'gpu1', 'gpu2', 'gpu3',
            'gpu4', 'gpu5', 'gpu6', 'gpu7',
            'gpu8', 'gpu9', 'gpu10', 'gpu11',
            'gpu12', 'gpu13', 'gpu14', 'gpu15',
                allow_override=False),
        in_c_key=False)

AddConfigVar('force_device',
        "Raise an error if we can't use the specified device",
        BoolParam(False, allow_override=False),
        in_c_key=False)

# Do not add FAST_RUN_NOGC to this list (nor any other ALL CAPS shortcut).
# The way to get FAST_RUN_NOGC is with the flag 'linker=c|py_nogc'.
# The old all capital letter way of working is deprecated as it is not
# scalable.
# Also, please be careful not to modify the first item in the enum when adding
# new modes, since it is the default mode.
AddConfigVar('mode',
        "Default compilation mode",
        EnumStr('Mode', 'ProfileMode', 'DebugMode', 'FAST_RUN',
                'FAST_COMPILE', 'PROFILE_MODE', 'DEBUG_MODE'),
        in_c_key=False)

# Test whether or not gcc is present: disable C code if it is not.
# Using the dummy file descriptor below is a workaround for a crash experienced
# in an unusual Python 2.4.4 Windows environment with the default stdin=None.
dummy_stdin = open(os.devnull)
try:
    subprocess.Popen('gcc', stdout=subprocess.PIPE, stderr=subprocess.PIPE,
                     stdin=dummy_stdin.fileno())
    # Keep the default linker the same as the one for the mode FAST_RUN
    AddConfigVar('linker',
                 "Default linker used if the theano flags mode is Mode or ProfileMode",
                 EnumStr('c|py', 'py', 'c', 'c|py_nogc', 'c&py',
                     'vm', 'cvm', 'vm_nogc', 'cvm_nogc'),
                 in_c_key=False)
except OSError:
    # gcc is not present, linker should default to python only
    AddConfigVar('linker',
                 "Default linker used if the theano flags mode is Mode or ProfileMode",
                 EnumStr('py', 'c|py', 'c', 'c|py_nogc', 'c&py',
                     'vm', 'cvm', 'vm_nogc', 'cvm_nogc'),
                 in_c_key=False)
    _logger.warning('GCC not detected ! Theano will be unable to execute '
            'optimized C-implementations (for both CPU and GPU) and will '
            'default to Python implementations. Performance will be severely '
            'degraded.')

del dummy_stdin

#Keep the default optimizer the same as the one for the mode FAST_RUN
AddConfigVar('optimizer',
        "Default optimizer. If not None, will use this linker with the Mode object(not ProfileMode or DebugMode)",
        EnumStr('fast_run', 'merge', 'fast_compile', 'None'),
        in_c_key=False)

AddConfigVar('on_opt_error',
        "What to do when an optimization crashes: warn and skip it, or raise the exception",
        EnumStr('warn', 'raise'),
        in_c_key=False)

def get_home_dir():
    home = os.getenv('HOME')
    if home is None:
        # This expanduser usually works on Windows (see discussion on
        # theano-users, July 13 2010).
        home = os.path.expanduser('~')
        if home == '~':
            # This might happen when expanduser fails. Although the cause of
            # failure is a mystery, it has been seen on some Windows system.
            home = os.getenv('USERPROFILE')
    assert home is not None
    return home

AddConfigVar('home',
        "User home directory",
        StrParam(get_home_dir()),
        in_c_key=False)

AddConfigVar('nocleanup',
        "Suppress the deletion of code files that did not compile cleanly",
        BoolParam(False),
        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)

#http://developer.amd.com/CPU/LIBRARIES/LIBM/Pages/default.aspx
AddConfigVar('lib.amdlibm',
        "Use amd's amdlibm numerical library",
        BoolParam(False))

AddConfigVar('op.set_flops',
        "currently used only in ConvOp. The profile mode will print the flops/s for the op.",
        BoolParam(False),
        in_c_key=False)

AddConfigVar('gpuelemwise.sync',
        "when true, wait that the gpu fct finished and check it error code.",
        BoolParam(True))

AddConfigVar('traceback.limit',
             "The number of stack to trace. -1 mean all.",
             IntParam(5),
             in_c_key=False)

AddConfigVar('experimental.mrg',
             "Another random number generator that work on the gpu",
             BoolParam(False))

AddConfigVar('numpy.seterr_all',
             ("Sets numpy's behaviour for floating-point errors, ",
              "see numpy.seterr. "
              "'None' means not to change numpy's default, which can be "
              "different for different numpy releases. "
              "This flag sets the default behaviour for all kinds of floating-"
              "point errors, its effect can be overriden for specific errors "
              "by the following flags: seterr_divide, seterr_over, "
              "seterr_under and seterr_invalid."),
             EnumStr('ignore', 'warn', 'raise', 'call', 'print', 'log', 'None',
                 allow_override=False),
             in_c_key=False)

AddConfigVar('numpy.seterr_divide',
             ("Sets numpy's behavior for division by zero, see numpy.seterr. "
              "'None' means using the default, defined by numpy.seterr_all."),
             EnumStr('None', 'ignore', 'warn', 'raise', 'call', 'print', 'log',
                 allow_override=False),
             in_c_key=False)

AddConfigVar('numpy.seterr_over',
             ("Sets numpy's behavior for floating-point overflow, "
              "see numpy.seterr. "
              "'None' means using the default, defined by numpy.seterr_all."),
             EnumStr('None', 'ignore', 'warn', 'raise', 'call', 'print', 'log',
                 allow_override=False),
             in_c_key=False)

AddConfigVar('numpy.seterr_under',
             ("Sets numpy's behavior for floating-point underflow, "
              "see numpy.seterr. "
              "'None' means using the default, defined by numpy.seterr_all."),
             EnumStr('None', 'ignore', 'warn', 'raise', 'call', 'print', 'log',
                 allow_override=False),
             in_c_key=False)

AddConfigVar('numpy.seterr_invalid',
             ("Sets numpy's behavior for invalid floating-point operation, "
              "see numpy.seterr. "
              "'None' means using the default, defined by numpy.seterr_all."),
             EnumStr('None', 'ignore', 'warn', 'raise', 'call', 'print', 'log',
                 allow_override=False),
             in_c_key=False)

###
### To disable some warning about old bug that are fixed now.
###
AddConfigVar('warn.ignore_bug_before',
             "If 'None', we warn about all Theano bugs found by default. If 'all', we don't warn about Theano bugs found by default. If a version, we print only the warnings relative to Theano bugs found after that version. Warning for specific bugs can be configured with specific [warn] flags.",
             EnumStr('None', 'all', '0.3','0.4', '0.4.1',allow_override=False),
             in_c_key=False)

default_0_3 = True
if config.warn.ignore_bug_before == 'None':
    default_0_3 = True
elif config.warn.ignore_bug_before == 'all':
    default_0_3 = False
elif config.warn.ignore_bug_before >= '0.3':
    # Disable 0.3 warnings for 0.3 and all subsequent versions
    default_0_3 = False

AddConfigVar('warn.argmax_pushdown_bug',
             "Warn if in past version of Theano we generated a bug with the optimisation theano.tensor.nnet.nnet.local_argmax_pushdown optimization. Was fixed 27 may 2010",
             BoolParam(default_0_3),
             in_c_key=False)

AddConfigVar('warn.gpusum_01_011_0111_bug',
             "Warn if we are in a case where old version of Theano had a silent bug with GpuSum pattern 01,011 and 0111 when the first dimensions was bigger then 4096. Was fixed 31 may 2010",
             BoolParam(default_0_3),
             in_c_key=False)

AddConfigVar('warn.sum_sum_bug',
             "Warn if we are in a case where Theano version between version 9923a40c7b7a and the 2 august 2010(fixed date), generated an error in that case. This happen when their is 2 consecutive sum in the graph, bad code was generated. Was fixed 2 August 2010",
             BoolParam(default_0_3),
             in_c_key=False)

AddConfigVar('warn.sum_div_dimshuffle_bug',
             "Warn if previous versions of Theano (between rev. 3bd9b789f5e8, 2010-06-16, and cfc6322e5ad4, 2010-08-03) would have given incorrect result. This bug was triggered by sum of division of dimshuffled tensors.",
             BoolParam(default_0_3),
             in_c_key=False)

AddConfigVar('compute_test_value',
        "If 'True', Theano will run each op at graph build time, using Constants, SharedVariables and the tag 'test_value' as inputs to the function. This helps the user track down problems in the graph before it gets optimized.",
        EnumStr('off', 'ignore', 'warn', 'raise'),
        in_c_key=False)


"""Note to developers:
    Generally your exceptions should use an apply node's __str__
    method when exception_verbosity == 'low'. When exception_verbosity
    == 'high', you should include a call to printing.min_informative_str
    on all important apply nodes.
"""
AddConfigVar('exception_verbosity',
        "If 'low', the text of exceptions will generally refer " \
        + "to apply nodes with short names such as " \
        + "Elemwise{add_no_inplace}. If 'high', some exceptions " \
        + "will also refer to apply nodes with long descriptions " \
        + """ like:
        A. Elemwise{add_no_inplace}
                B. log_likelihood_v_given_h
                C. log_likelihood_h""",
        EnumStr('low','high'),
        in_c_key=False)
