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)