def test_gpu_merged_ksum(self):
with xdl.device("GPU"):
ksum = xdl.ksum(embeds, idx, values, segs, grps, sidx, sseg)
ksum = xdl.execute(ksum)
res = np.array([[0.03, 0.03], [0.04, 0.05], [0.05, 0.1]],
dtype=np.float)
self.assertTrue(np.allclose(ksum, res))
def test_gpu_kavg(self):
with xdl.device("GPU"):
grps = np.array([], dtype=np.int32)
ksum = xdl.ksum(embeds, idx, values, segs, grps, average=True)
ksum = xdl.execute(ksum)
res = np.array([[0.02], [0.03], [0.0375]], dtype=np.float)
self.assertTrue(np.allclose(ksum, res))
def test_gpu_ksum(self):
with xdl.device("GPU"):
grps = np.array([], dtype=np.int32)
ksum = xdl.ksum(embeds, idx, values, segs, grps, sidx, sseg)
ksum = xdl.execute(ksum)
res = np.array([[0.06], [0.09], [0.15]], dtype=np.float)
self.assertTrue(np.allclose(ksum, res))
def merged_ksum(embeddings,
idx,
values,
segments,
groups,
sidx,
sseg,
device='CPU',
**device_attrs):
with xdl.device(device, **device_attrs):
res = xdl.ksum(embeddings, idx, values, segments, groups, sidx, sseg)
return res
def ksum(embeddings,
idx,
values,
segments,
sidx,
sseg,
device='CPU',
**device_attrs):
groups = np.array([], dtype=dtype_xdl_2_np(segments.dtype))
with xdl.device(device, **device_attrs):
res = xdl.ksum(embeddings, idx, values, segments, groups, sidx, sseg)
return res
def test_cpu_merged_kavg(self):
ksum = xdl.ksum(embeds,
idx,
values,
segs,
grps,
sidx,
sseg,
average=True)
ksum = xdl.execute(ksum)
res = np.array([[0.015, 0.03], [0.04, 0.025], [0.05, 0.03333333]],
dtype=np.float)
self.assertTrue(np.allclose(ksum, res))
def merged_kmean(embeddings, idx, values, segments, groups):
return xdl.ksum(embeddings, idx, values, segments, groups, average=True)
def merged_ksum(embeddings, idx, values, segments, groups):
return xdl.ksum(embeddings, idx, values, segments, groups)
def kmean(embeddings, idx, values, segments):
groups = np.array([], dtype=dtype_xdl_2_np(segments.dtype))
return xdl.ksum(embeddings, idx, values, segments, groups, average=True)