import cPickle
import os.path
import sys

from nose.tools import assert_raises
import numpy

from theano import config
from theano.sandbox.cuda import cuda_available

if cuda_available:
    from theano.sandbox.cuda import CudaNdarray

# testfile created on cuda enabled machine using
# >>> with open('CudaNdarray.pkl', 'wb') as fp:
# >>> cPickle.dump(theano.sandbox.cuda.CudaNdarray(np.array([-42.0], dtype=np.float32)), fp)


def test_unpickle_flag_is_false_by_default():
    assert not config.experimental.unpickle_gpu_on_cpu, (
        "Config flag experimental.unpickle_gpu_on_cpu is "
        "set to true. Make sure the default value stays false "
        "and that you have not set the flag manually.")


def test_unpickle_cudandarray_as_numpy_ndarray_flag0():
    oldflag = config.experimental.unpickle_gpu_on_cpu
    config.experimental.unpickle_gpu_on_cpu = False

    try:
        testfile_dir = os.path.dirname(os.path.realpath(__file__))
        fname = 'CudaNdarray.pkl'
        if sys.version_info[0] == 3:
            fname = 'CudaNdarray_py3.pkl'

        with open(os.path.join(testfile_dir, fname), 'rb') as fp:
            if cuda_available:
                mat = cPickle.load(fp)
            else:
                assert_raises(ImportError, cPickle.load, fp)

        if cuda_available:
            assert isinstance(mat, CudaNdarray)
            assert numpy.asarray(mat)[0] == -42.0

    finally:
        config.experimental.unpickle_gpu_on_cpu = oldflag


def test_unpickle_cudandarray_as_numpy_ndarray_flag1():
    oldflag = config.experimental.unpickle_gpu_on_cpu
    config.experimental.unpickle_gpu_on_cpu = True

    try:
        testfile_dir = os.path.dirname(os.path.realpath(__file__))

        with open(os.path.join(testfile_dir, 'CudaNdarray.pkl')) as fp:
            mat = cPickle.load(fp)

        assert isinstance(mat, numpy.ndarray)
        assert mat[0] == -42.0

    finally:
        config.experimental.unpickle_gpu_on_cpu = oldflag
