Speedup meaning dataset build speed.
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b062cc9c94
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@ -85,6 +85,9 @@ class MeaningMap:
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ms_start[i] = index
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ms_end[i] = index + 1
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ms_len[i] = 1
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ms_level[i] = 0
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ms_rank_idx[i] = 0xFFFFFFF
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ms_rank_all[i] = 0xFFFFFFF
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ms_height[i] = 0
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ms_weight[i] = 1
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index = index + 1
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@ -95,8 +98,13 @@ class MeaningMap:
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m_len = len(m)
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m_list = m.tolist()
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assert m_list, "map list can not be empty list"
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ma = np.concatenate([ms_data[ms_start[newm] : ms_end[newm]] for newm in m_list])
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len_ma = len(ma)
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idx = np.concatenate([np.arange(ms_start[m], ms_end[m]) for m in m_list])
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idxidx = np.concatenate(
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[np.ones(l, dtype=np.uint32) * i for i, l in enumerate(ms_end[m_list] - ms_start[m_list])]
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)
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len_ma = len(idx)
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end = index + len_ma
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if ms_data.size < end:
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ms_data = np.concatenate([ms_data, np.zeros((268435456), dtype=np.int32)])
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@ -104,33 +112,16 @@ class MeaningMap:
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ms_rank_idx = np.concatenate([ms_rank_idx, np.zeros((268435456), dtype=np.uint32)])
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ms_rank_all = np.concatenate([ms_rank_all, np.zeros((268435456), dtype=np.uint32)])
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ms_data[index:end] = ma
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ms_level[index:end] = np.concatenate([ms_level[ms_start[newm] : ms_end[newm]] + 1 for newm in m_list])
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ms_rank_idx[index:end] = np.concatenate(
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[
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(
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[0xFFFFFFF0 + i]
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if newm < self.vocab_size
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else ms_rank_idx[ms_start[newm] : ms_end[newm]] * 16 + i
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)
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for i, newm in enumerate(m_list)
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]
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).astype(np.uint32)
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ms_rank_all[index:end] = np.concatenate(
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[
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(
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[0xFFFFFFF0 + m_len]
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if newm < self.vocab_size
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else ms_rank_all[ms_start[newm] : ms_end[newm]] * 16 + m_len
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)
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for i, newm in enumerate(m_list)
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]
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).astype(np.uint32)
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ms_data[index:end] = ms_data[idx]
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ms_level[index:end] = ms_level[idx] + 1
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ms_rank_idx[index:end] = (ms_rank_idx[idx] * 16 + idxidx).astype(np.uint32)
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ms_rank_all[index:end] = (ms_rank_all[idx] * 16 + m_len).astype(np.uint32)
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ms_start[i] = index
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ms_end[i] = end
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ms_len[i] = len_ma
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ms_height[i] = max([ms_height[sub_m] for sub_m in m_list]) + 1
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ms_weight[i] = sum(ms_weight[sub_m] for sub_m in m_list)
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ms_height[i] = max(ms_height[m_list]) + 1
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ms_weight[i] = sum(ms_weight[m_list])
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index = index + len_ma
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if i % 10000 == 0:
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print(i)
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@ -139,6 +130,7 @@ class MeaningMap:
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d = np.ones(ms_rank_idx.shape, dtype=np.uint32)
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d = ((d * 0xFFFFFFFF) << (ms_level * 4)).astype(np.uint32)
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shift = (8 - ms_level) * 4
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ms_rank_idx = (
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((ms_rank_idx & 0xF) << 28)
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+ ((ms_rank_idx & 0xF0) << 20)
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@ -149,7 +141,7 @@ class MeaningMap:
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+ ((ms_rank_idx & 0xF000000) >> 20)
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+ ((ms_rank_idx & 0xF0000000) >> 28)
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)
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ms_rank_idx = ((ms_rank_idx >> ((8 - ms_level) * 4)) + d).astype(np.uint32)
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ms_rank_idx = ((ms_rank_idx >> shift) + d).astype(np.uint32)
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ms_rank_all = (
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((ms_rank_all & 0xF) << 28)
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+ ((ms_rank_all & 0xF0) << 20)
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@ -160,7 +152,7 @@ class MeaningMap:
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+ ((ms_rank_all & 0xF000000) >> 20)
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+ ((ms_rank_all & 0xF0000000) >> 28)
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)
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ms_rank_all = ((ms_rank_all >> ((8 - ms_level) * 4)) + d).astype(np.uint32)
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ms_rank_all = ((ms_rank_all >> shift) + d).astype(np.uint32)
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ms_start = np.array(ms_start).astype(np.int32)
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ms_height = np.array(ms_height).astype(np.int32)
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