import logging

import theano
from theano.configparser import config, AddConfigVar, BoolParam
from theano.compile import optdb

_logger_name = 'theano.sandbox.gpuarray'
_logger = logging.getLogger(_logger_name)
_logger.setLevel(logging.WARNING)

error = _logger.error
info = _logger.info

pygpu_activated = False
try:
    import pygpu
    import pygpu.gpuarray
except ImportError:
    pygpu = None

AddConfigVar('gpuarray.sync',
             """If True, every op will make sure its work is done before
                returning.  Setting this to True will slow down execution,
                but give much more accurate results in profiling.""",
             BoolParam(False),
             in_c_key=True)

# This is for documentation not to depend on the availability of pygpu
from type import (GpuArrayType, GpuArrayVariable, GpuArrayConstant,
                  GpuArraySharedVariable, gpuarray_shared_constructor)
import opt


def init_dev(dev):
    global pygpu_activated
    context = pygpu.init(dev)
    pygpu.set_default_context(context)
    pygpu_activated = True

if pygpu:
    try:
        if (config.device.startswith('cuda') or
            config.device.startswith('opencl')):
            init_dev(config.device)
            import theano.compile
            theano.compile.shared_constructor(gpuarray_shared_constructor)
            optdb.add_tags('gpuarray_opt', 'fast_run', 'fast_compile', 'inplace')
        elif config.gpuarray.init_device != '':
            init_dev(config.gpuarray.init_device)
    except Exception:
        error("Could not initialize pygpu, support disabled", exc_info=True)
else:
    if (config.gpuarray.init_device != '' or
        config.device.startswith('opencl') or
        config.device.startswith('cuda')):
        error("pygpu was configured but could not be imported", exc_info=True)
