def test_gemm_vector_vector():
a = theano._asarray(numpy.random.rand(5,1), dtype='float32')
_a = cuda_ndarray.CudaNdarray(a)
b = theano._asarray(numpy.random.rand(1,5), dtype='float32')
_b = cuda_ndarray.CudaNdarray(b)
_c = cuda_ndarray.dot(_a,_b)
assert _c.shape == (5,5)
assert numpy.allclose(_c, numpy.dot(a, b))
_c = cuda_ndarray.dot(_b,_a)
assert _c.shape == (1,1)
assert numpy.allclose(_c, numpy.dot(b, a))
def test_dot():
print >>sys.stdout, 'starting test_dot'
utt.seed_rng()
rng = numpy.random.RandomState(utt.fetch_seed())
a0 = theano._asarray(rng.randn(4, 7), dtype='float32')
a1 = theano._asarray(rng.randn(7, 6), dtype='float32')
b0 = cuda_ndarray.CudaNdarray(a0)
b1 = cuda_ndarray.CudaNdarray(a1)
assert _allclose(numpy.dot(a0, a1), cuda_ndarray.dot(b0, b1))
a1 = theano._asarray(rng.randn(6, 7), dtype='float32')
b1 = cuda_ndarray.CudaNdarray(a1)
numpy_version = numpy.dot(a0, a1.T)
transposed = cuda_ndarray.dimshuffle(b1,(1,0))
cuda_version = cuda_ndarray.dot(b0, transposed)
assert _allclose(numpy_version, cuda_version)
a1 = theano._asarray(rng.randn(7, 6), dtype='float32')
b1 = cuda_ndarray.CudaNdarray(a1)
a0 = theano._asarray(rng.randn(7, 4), dtype='float32')
b0 = cuda_ndarray.CudaNdarray(a0)
assert _allclose(numpy.dot(a0.T, a1),
cuda_ndarray.dot(cuda_ndarray.dimshuffle(b0,(1,0)), b1))
a1 = theano._asarray(rng.randn(6, 7), dtype='float32')
b1 = cuda_ndarray.CudaNdarray(a1)
assert _allclose(numpy.dot(a0.T, a1.T),
cuda_ndarray.dot(cuda_ndarray.dimshuffle(b0,(1,0)),
cuda_ndarray.dimshuffle(b1,(1,0))))
