def test_deep_copy():
a = rand_gpuarray(20, dtype='float32')
g = GpuArrayType(dtype='float32', broadcastable=(False,))('g')
f = theano.function([g], g)
assert isinstance(f.maker.fgraph.toposort()[0].op, DeepCopyOp)
res = f(a)
assert GpuArrayType.values_eq(res, a)
def test_deep_copy():
a = rand_gpuarray(20, dtype='float32')
g = GpuArrayType(dtype='float32', broadcastable=(False, ))('g')
f = theano.function([g], g)
assert isinstance(f.maker.fgraph.toposort()[0].op, DeepCopyOp)
res = f(a)
assert GpuArrayType.values_eq(res, a)
def test_transfer_cpu_gpu():
a = T.fmatrix('a')
g = GpuArrayType(dtype='float32', broadcastable=(False, False))('g')
av = numpy.asarray(rng.rand(5, 4), dtype='float32')
gv = gpuarray.array(av)
f = theano.function([a], gpu_from_host(a))
fv = f(av)
assert GpuArrayType.values_eq(fv, gv)
f = theano.function([g], host_from_gpu(g))
fv = f(gv)
assert numpy.all(fv == av)
def test_transfer_cpu_gpu():
a = T.fmatrix('a')
g = GpuArrayType(dtype='float32', broadcastable=(False, False))('g')
av = numpy.asarray(rng.rand(5, 4), dtype='float32')
gv = gpuarray.array(av)
f = theano.function([a], gpu_from_host(a))
fv = f(av)
assert GpuArrayType.values_eq(fv, gv)
f = theano.function([g], host_from_gpu(g))
fv = f(gv)
assert numpy.all(fv == av)
def test_transfer_strided():
# This is just to ensure that it works in theano
# compyte has a much more comprehensive suit of tests to ensure correctness
a = T.fmatrix('a')
g = GpuArrayType(dtype='float32', broadcastable=(False, False))('g')
av = numpy.asarray(rng.rand(5, 8), dtype='float32')
gv = gpuarray.array(av)
av = av[:, ::2]
gv = gv[:, ::2]
f = theano.function([a], gpu_from_host(a))
fv = f(av)
assert GpuArrayType.values_eq(fv, gv)
f = theano.function([g], host_from_gpu(g))
fv = f(gv)
assert numpy.all(fv == av)
def test_transfer_strided():
# This is just to ensure that it works in theano
# compyte has a much more comprehensive suit of tests to ensure correctness
a = T.fmatrix('a')
g = GpuArrayType(dtype='float32', broadcastable=(False, False))('g')
av = numpy.asarray(rng.rand(5, 8), dtype='float32')
gv = gpuarray.array(av)
av = av[:,::2]
gv = gv[:,::2]
f = theano.function([a], gpu_from_host(a))
fv = f(av)
assert GpuArrayType.values_eq(fv, gv)
f = theano.function([g], host_from_gpu(g))
fv = f(gv)
assert numpy.all(fv == av)
