def test_concatenate():
ac, ag = gen_gpuarray((2, 2), 'float32', ctx=context)
bc, bg = gen_gpuarray((1, 2), 'float32', ctx=context)
rc = numpy.concatenate((ac, bc), axis=0)
rg = pygpu.concatenate((ag, bg), axis=0)
numpy.testing.assert_allclose(rc, numpy.asarray(rg))
rc = numpy.concatenate((ac, bc.T), axis=1)
rg = pygpu.concatenate((ag, bg.T), axis=1)
numpy.testing.assert_allclose(rc, numpy.asarray(rg))
def test_concatenate():
ac, ag = gen_gpuarray((2, 2), 'float32', ctx=context)
bc, bg = gen_gpuarray((1, 2), 'float32', ctx=context)
rc = numpy.concatenate((ac, bc), axis=0)
rg = pygpu.concatenate((ag, bg), axis=0)
numpy.testing.assert_allclose(rc, numpy.asarray(rg))
rc = numpy.concatenate((ac, bc.T), axis=1)
rg = pygpu.concatenate((ag, bg.T), axis=1)
numpy.testing.assert_allclose(rc, numpy.asarray(rg))
def perform(self, node, axis_and_tensors, out_, ctx):
out, = out_
axis = int(axis_and_tensors[0])
if axis < 0:
axis += axis_and_tensors[1].ndim
tensors = axis_and_tensors[1:]
out[0] = pygpu.concatenate(tensors, axis=axis, context=ctx).astype(
node.outputs[0].dtype)
def perform(self, node, axis_and_tensors, out_, ctx):
out, = out_
axis = int(axis_and_tensors[0])
if axis < 0:
axis += axis_and_tensors[1].ndim
tensors = axis_and_tensors[1:]
out[0] = pygpu.concatenate(tensors, axis=axis,
context=ctx).astype(node.outputs[0].dtype)
def perform(self, node, axis_and_tensors, out_, ctx):
out, = out_
view = self.view
axis = int(axis_and_tensors[0])
tensors = axis_and_tensors[1:]
if axis < -axis_and_tensors[1].ndim:
raise IndexError
if axis < 0:
axis += axis_and_tensors[1].ndim
# we check these tensors for being empty.
if (view != -1) and numpy.all(
[tensor.shape[axis] == 0 for tensor in
tensors[0:view] + tensors[view + 1:]]):
out[0] = tensors[view]
else:
out[0] = pygpu.concatenate(tensors, axis=axis, context=ctx).astype(
node.outputs[0].dtype)
def perform(self, node, axis_and_tensors, out_, ctx):
out, = out_
view = self.view
axis = int(axis_and_tensors[0])
tensors = axis_and_tensors[1:]
if axis < -axis_and_tensors[1].ndim:
raise IndexError
if axis < 0:
axis += axis_and_tensors[1].ndim
# we check these tensors for being empty.
if (view != -1) and np.all(
[tensor.shape[axis] == 0 for tensor in
tensors[0:view] + tensors[view + 1:]]):
out[0] = tensors[view]
else:
out[0] = pygpu.concatenate(tensors, axis=axis, context=ctx).astype(
node.outputs[0].dtype)
def perform(self, node, axis_and_tensors, out_):
out, = out_
axis = int(axis_and_tensors[0])
tensors = axis_and_tensors[1:]
out[0] = pygpu.concatenate(tensors, axis=axis).astype(
node.outputs[0].dtype)
def perform(self, node, axis_and_tensors, out_):
out, = out_
axis = int(axis_and_tensors[0])
tensors = axis_and_tensors[1:]
out[0] = pygpu.concatenate(tensors, axis=axis).astype(
node.outputs[0].dtype)
