update conformer

.gitignore

@@ -10,3 +10,5 @@
 *.pth
 *.npz
 *.zip
+*.txt
+*.trn
\ No newline at end of file

bert/bert4torch_cmcc/examples/sequence_labeling/bert_migraphx.bak.py

+#! -*- coding:utf-8 -*-
+# bert+crf用来做实体识别
+# 数据集：http://s3.bmio.net/kashgari/china-people-daily-ner-corpus.tar.gz
+# [valid_f1]  token_level: 97.06； entity_level: 95.90
+
+
+import numpy as np
+import torch
+from torch.utils.data import DataLoader
+from apex.optimizers import FusedLAMB
+import apex_C
+from apex import amp
+import migraphx
+import torch.nn as nn
+import torch.optim as optim
+# from bert4torch.snippets import sequence_padding, Callback, ListDataset, seed_everything
+from bert4torch.snippets import sequence_padding, ListDataset
+from bert4torch.layers import CRF
+from bert4torch.tokenizers import Tokenizer
+from bert4torch.models import build_transformer_model, BaseModel
+from tqdm import tqdm
+from bert4torch.models import BaseModelDDP
+import os
+import time
+import multiprocessing as mp
+from multiprocessing import Process, Queue, Manager
+
+
+categories = ['O', 'B-LOC', 'I-LOC', 'B-PER', 'I-PER', 'B-ORG', 'I-ORG']
+categories_id2label = {i: k for i, k in enumerate(categories)}
+categories_label2id = {k: i for i, k in enumerate(categories)}
+
+# BERT base
+maxlen = 256
+batch_size = 64
+config_path = '/datasets/bert-base-chinese/config.json'
+dict_path = '/datasets/bert-base-chinese/vocab.txt'
+gpuid = os.getenv('HIP_VISIBLE_DEVICES')
+labdir = os.path.join('results', gpuid, 'label')
+resultdir = os.path.join('results', gpuid, 'data')
+os.makedirs(resultdir, exist_ok=True)
+os.makedirs(labdir, exist_ok=True)
+
+def AllocateOutputMemory(model):
+    outputData={}
+    for key in model.get_outputs().keys():
+        outputData[key] = migraphx.allocate_gpu(s=model.get_outputs()[key])
+    return outputData
+
+# 加载数据集
+class MyDataset(ListDataset):
+    @staticmethod
+    def load_data(filename):
+        D = []
+        with open(filename, encoding='utf-8') as f:
+            f = f.read()
+            for l in f.split('\n\n'):
+                if not l:
+                    continue
+                d = ['']
+                for i, c in enumerate(l.split('\n')):
+                    char, flag = c.split(' ')
+                    d[0] += char
+                    if flag[0] == 'B':
+                        d.append([i, i, flag[2:]])
+                    elif flag[0] == 'I':
+                        d[-1][1] = i
+                D.append(d)
+        return D
+
+
+# 建立分词器
+tokenizer = Tokenizer(dict_path, do_lower_case=True)
+
+if os.path.isfile("/models/bert_best_fused.mxr"):
+    print("***********load mxr model******************")
+    model = migraphx.load("/models/bert_best_fused.mxr")
+else:
+    print("***********load onnx model******************")
+    # 加载模型
+    maxInput={"input":[64,256]}
+    model = migraphx.parse_onnx("/models/bert_best.onnx", map_input_dims=maxInput)
+    migraphx.quantize_fp16(model)
+
+    # 编译
+    model.compile(migraphx.get_target("gpu"), offload_copy=False, device_id=0)
+
+
+inputName=list(model.get_inputs().keys())[0]
+modelData=AllocateOutputMemory(model)
+
+
+
+def collate_fn(batch):
+    batch_token_ids, batch_labels = [], []
+    maxlen = 256
+    for d in batch:
+        tokens = tokenizer.tokenize(d[0], maxlen=maxlen)  # 截断到 maxlen
+        mapping = tokenizer.rematch(d[0], tokens)
+        start_mapping = {j[0]: i for i, j in enumerate(mapping) if j}
+        end_mapping = {j[-1]: i for i, j in enumerate(mapping) if j}
+        token_ids = tokenizer.tokens_to_ids(tokens)
+        
+        # 初始化 labels 为全 0（或根据你的设计，可能是 'O' 标签）
+        labels = np.zeros(len(token_ids), dtype=np.int64)
+        
+        for start, end, label in d[1:]:
+            if start in start_mapping and end in end_mapping:
+                start_idx = start_mapping[start]
+                end_idx = end_mapping[end]
+                labels[start_idx] = categories_label2id['B-' + label]
+                labels[start_idx + 1:end_idx + 1] = categories_label2id['I-' + label]
+        
+        batch_token_ids.append(token_ids)
+        batch_labels.append(labels)
+    batch_token_ids = torch.tensor(sequence_padding(batch_token_ids, length=maxlen, value=tokenizer._token_pad_id), 
+                                   dtype=torch.long, 
+                                   device="cuda:0")
+    batch_labels = torch.tensor(sequence_padding(batch_labels, length=maxlen, value=-100), 
+                                dtype=torch.long, 
+                                device="cuda:0")
+    return batch_token_ids, batch_labels
+
+# 转换数据集
+valid_dataloader = DataLoader(MyDataset('/datasets/bert-base-chinese/china-people-daily-ner-corpus/example.dev'), batch_size=batch_size, collate_fn=collate_fn) 
+
+
+def pad_data(data, seq=256):
+    if len(data.shape) == 1:
+        return np.pad(data, ((0, seq-data.shape[0])),
+                      "constant", constant_values=(0))
+    
+    elif len(data.shape) == 2:
+        return np.pad(data, ((0, 0), (0, seq-data.shape[1])),
+                      "constant", constant_values=(0))
+    
+    else:
+        # shape(bs, seq, len(categories))
+        return np.pad(data, ((0, 0), (0, seq-data.shape[1]), (0, 0)),
+                      "constant", constant_values=(0))
+
+
+def pad_data_bin(data, output, bs, seq=256, len_catagory=7):
+    if output == "emission_score":
+        data = data.reshape((bs, -1, len_catagory))
+    else:
+        data = data.reshape((bs, -1))
+    
+    return pad_data(data, seq)
+
+
+def evaluate(data):
+    X, Y, Z = 1e-10, 1e-10, 1e-10
+    X2, Y2, Z2 = 1e-10, 1e-10, 1e-10
+    end = 0
+    infer_times = []
+    total_infer_times = []
+    data_idx = 0
+    total_start = time.time()
+
+    # warmup
+    for token_ids, label in tqdm(data):
+        data_numpy=token_ids.detach().cpu().numpy()
+        img_data = np.zeros(data_numpy.shape).astype("int64")
+        for i in range(data_numpy.shape[0]):
+            img_data[i, :] = data_numpy[i, :]
+        modelData[inputName] = migraphx.to_gpu(migraphx.argument(img_data))
+        preds_dcu = model.run(modelData)
+        break
+
+
+    for token_ids, label in tqdm(data):
+        data_numpy=token_ids.detach().cpu().numpy()
+        # device = torch.device("cuda")
+
+        # 注意：这里需要执行赋值操作，否则会造成migraphx中输入数据步长不对
+        img_data = np.zeros(data_numpy.shape).astype("int64")
+        for i in range(data_numpy.shape[0]):
+            img_data[i, :] = data_numpy[i, :]
+        if img_data.shape[0] != 64:
+            break
+        modelData[inputName] = migraphx.to_gpu(migraphx.argument(img_data))
+
+        start = time.time()
+        # result = model.run({"input":img_data})
+        preds_dcu = model.run(modelData)
+        end += time.time() - start
+        infer_times.append(time.time() - start)
+        print(f"****infer time: {infer_times[-1]} s*****  fps: {64/infer_times[-1]}*********")
+        total_infer_times.append(time.time() - total_start)
+        result_1 = np.array(migraphx.from_gpu(preds_dcu[0]))
+        result_2 = np.array(migraphx.from_gpu(preds_dcu[1]))
+        emission_score = torch.from_numpy(np.array(result_1, copy=False))
+        attention_mask = torch.from_numpy(np.array(result_2, copy=False))
+        labels = label.cpu().numpy()
+        # emission_score = torch.from_numpy(np.array(result[0], copy=False))
+        # attention_mask = torch.from_numpy(np.array(result[1], copy=False))
+        
+
+        # 保存bin文件
+        labels = np.pad(labels, ((0, batch_size-labels.shape[0]), (0,0)), 'constant', constant_values=-1)
+        labels.tofile(f'{labdir}/{data_idx}.bin')
+        
+        emission_score = np.pad(emission_score, ((0, batch_size-emission_score.shape[0]), (0,0), (0,0)), 'constant')
+        attention_mask = np.pad(attention_mask, ((0, batch_size-attention_mask.shape[0]), (0,0)), 'constant')
+        emission_score.tofile(f'{resultdir}/{data_idx}_0.bin')
+        attention_mask.tofile(f'{resultdir}/{data_idx}_1.bin')
+
+        labels = pad_data_bin(labels, "labels", batch_size)
+        emission_score = pad_data_bin(emission_score, "emission_score", batch_size)
+        attention_mask = pad_data_bin(attention_mask, "attention_mask", batch_size)
+
+        labels = torch.Tensor(labels)
+        # mask last data
+        data_mask = labels[:, 0] >= 0
+        labels = labels[data_mask]
+        emission_score = torch.Tensor(emission_score)[data_mask]
+        attention_mask = torch.Tensor(attention_mask)[data_mask]
+
+        scores = crf.decode(emission_score, attention_mask)
+
+        true_label = []
+        for label in labels:
+            true_label += [categories_id2label[int(l)] for l in label if l != -100]
+        
+        attention_mask = labels.gt(0)
+        # token粒度
+        X += (scores.eq(labels) * attention_mask).sum().item()
+        Y += scores.gt(0).sum().item()
+        Z += labels.gt(0).sum().item()
+
+        # entity粒度
+        entity_pred = trans_entity2tuple(scores)
+        entity_true = trans_entity2tuple(labels)
+        X2 += len(entity_pred.intersection(entity_true))
+        Y2 += len(entity_pred)
+        Z2 += len(entity_true)
+
+        data_idx += 1
+        total_start = time.time()
+    print("total_sample_data:", (64 * data_idx))
+    avg_infer_fps = 64 * len(infer_times) / sum(infer_times)
+    print(f"total_infer_time: {end}s")
+    print(f'avg_infer_fps: {avg_infer_fps}samples/s')
+    load_data_infer_time = sum(total_infer_times)
+    load_data_avg_infer_fps = len(total_infer_times) * 64 / sum(total_infer_times)
+    print(f'load_data_total_infer_time: {load_data_infer_time}s')
+    print(f'load_data_avg_total_Infer_fps: {load_data_avg_infer_fps} samples/s')
+    
+
+    f1, precision, recall = 2 * X / (Y + Z), X / Y, X / Z
+    f2, precision2, recall2 = 2 * X2 / (Y2 + Z2), X2/ Y2, X2 / Z2
+    return f1, precision, recall, f2, precision2, recall2
+
+
+def trans_entity2tuple(scores):
+    '''把tensor转为(样本id, start, end, 实体类型)的tuple用于计算指标'''
+    batch_entity_ids = set()
+    for i, one_samp in enumerate(scores):
+        entity_ids = []
+        for j, item in enumerate(one_samp):
+            # 跳过 padding / ignore_index (-100)
+            if item == -100:
+                continue
+
+            # 安全地获取标签名（确保 key 是 int）
+            tag_id = int(item.item())  # 转为 int，避免 float key
+            flag_tag = categories_id2label[tag_id]
+
+            if flag_tag.startswith('B-'):  # B
+                entity_ids.append([i, j, j, flag_tag[2:]])
+            elif len(entity_ids) == 0:
+                continue
+            elif (len(entity_ids[-1]) > 0) and flag_tag.startswith('I-') and (flag_tag[2:] == entity_ids[-1][-1]):  # I
+                entity_ids[-1][-2] = j
+            elif len(entity_ids[-1]) > 0:
+                entity_ids.append([])
+
+        for ent in entity_ids:
+            if ent:  # 非空才加入
+                batch_entity_ids.add(tuple(ent))
+    return batch_entity_ids
+
+
+class Model(BaseModel):
+    def __init__(self, config_path):
+        super().__init__()
+        self.bert = build_transformer_model(config_path=config_path, checkpoint_path=None, segment_vocab_size=0)
+        # embedding_dims:768, len_categories: 7
+        self.fc = nn.Linear(768, 7)  # 包含首尾
+        self.crf = CRF(7)
+
+    def forward(self, token_ids):
+        sequence_output = self.bert([token_ids])  # [btz, seq_len, hdsz]
+        emission_score = self.fc(sequence_output)  # [btz, seq_len, tag_size]
+        attention_mask = token_ids.gt(0).long()
+        return emission_score, attention_mask
+
+
+def build_model(config_path, checkpoint_path):
+    model = Model(config_path).to("cpu")
+    model.load_weights(checkpoint_path, strict=False)
+    return model
+
+if __name__ == '__main__':
+
+    ptmodel = build_model("/datasets/bert-base-chinese/config.json", "/models/best_model.pt")
+    crf = ptmodel.crf
+
+    # time_fw为存储时间日志的文件对象，文件绝对路径为'log/time/time.txt'
+    time_fw = open(os.path.join('log/', f'time.txt'), 'a', encoding='utf-8')
+
+    # time_fw写入程序开始执行的时间
+    time_fw.write('Start Time: {:.6f}\n'.format(time.time()))
+
+    f1, precision, recall, f2, precision2, recall2 = evaluate(valid_dataloader)
+
+    print(f'[val-token  level] f1: {f1:.5f}, p: {precision:.5f} r: {recall:.5f}')
+    print(f'[val-entity level] f1: {f2:.5f}, p: {precision2:.5f} r: {recall2:.5f}\n')
+
+    # time_fw写入程序开始执行的时间
+    time_fw.write('End Time: {:.6f}\n'.format(time.time()))
+    time_fw.flush()
+    time_fw.close()

bert/bert4torch_cmcc/examples/sequence_labeling/bert_migraphx.py

@@ -72,9 +72,9 @@ class MyDataset(ListDataset):
 # 建立分词器
 tokenizer = Tokenizer(dict_path, do_lower_case=True)
 
-if os.path.isfile("/models/bert_best_fp16_1.mxr"):
+if os.path.isfile("/models/bert_best_fused.mxr"):
     print("***********load mxr model******************")
-    model = migraphx.load("/models/bert_best_fp16_1.mxr")
+    model = migraphx.load("/models/bert_best_fused.mxr")
 else:
     print("***********load onnx model******************")
     # 加载模型
@@ -116,7 +116,7 @@ def collate_fn(batch):
     batch_token_ids = torch.tensor(sequence_padding(batch_token_ids, length=maxlen, value=tokenizer._token_pad_id), 
                                    dtype=torch.long, 
                                    device="cuda:0")
-    batch_labels = torch.tensor(sequence_padding(batch_labels, length=maxlen, value=-100), 
+    batch_labels = torch.tensor(sequence_padding(batch_labels, length=maxlen, value=0), 
                                 dtype=torch.long, 
                                 device="cuda:0")
     return batch_token_ids, batch_labels
@@ -221,7 +221,7 @@ def evaluate(data):
 
         true_label = []
         for label in labels:
-            true_label += [categories_id2label[int(l)] for l in label if l != -100]
+            true_label += [categories_id2label[int(l)] for l in label if l != 0]
         
         attention_mask = labels.gt(0)
         # token粒度
@@ -260,7 +260,7 @@ def trans_entity2tuple(scores):
         entity_ids = []
         for j, item in enumerate(one_samp):
             # 跳过 padding / ignore_index (-100)
-            if item == -100:
+            if item == 0:
                 continue
 
             # 安全地获取标签名（确保 key 是 int）

bert/bert4torch_cmcc/examples/sequence_labeling/gemm-softmax-gemm.py

+import onnx
+import onnxruntime as ort
+from onnxruntime.transformers import optimizer
+from onnxruntime.transformers.fusion_options import FusionOptions
+
+def fuse_gemm_softmax_gemm(model_path, output_path):
+    # 加载模型
+    model = onnx.load(model_path)
+    
+    # 创建优化选项
+    opt_options = FusionOptions('bert')
+    opt_options.enable_gemm_fast_gelu = True
+    opt_options.enable_layer_norm = False
+    opt_options.enable_attention = True  # 启用注意力融合
+    
+    # 优化模型
+    optimized_model = optimizer.optimize_model(
+        model_path,
+        model_type='bert',  # 也可以是 'gpt2', 'bert', 'bert_tf' 等
+        num_heads=12,       # 根据你的模型调整
+        hidden_size=768,    # 根据你的模型调整
+        optimization_options=opt_options
+    )
+    
+    # 保存优化后的模型
+    optimized_model.save_model_to_file(output_path)
+    return output_path
+
+model_path = "/models/bert_best.onnx"
+output_path = "/models/bert_best_fused.onnx"
+res = fuse_gemm_softmax_gemm(model_path, output_path)
+print(res)
+

bert/bert4torch_cmcc/examples/sequence_labeling/log/time.txt

@@ -207,3 +207,12 @@ Start Time: 1769494889.288779
 End Time: 1769494914.109688
 Start Time: 1769496150.433932
 End Time: 1769496173.504019
+Start Time: 1770033506.808056
+End Time: 1770033535.084920
+Start Time: 1770034180.143140
+Start Time: 1770034498.312319
+End Time: 1770034526.621981
+Start Time: 1770034739.525197
+End Time: 1770034762.796988
+Start Time: 1770035174.547607
+End Time: 1770035195.777491

conformer/34e9cabc2c29fd0e3a2917ffa525d98b/exp/asr_train_asr_conformer3_raw_char_batch_bins4000000_accum_grad4_sp/RESULTS.md

+<!-- Generated by scripts/utils/show_asr_result.sh -->
+# RESULTS
+## Environments
+- date: `Mon Oct 19 13:56:23 JST 2020`
+- python version: `3.7.3 (default, Mar 27 2019, 22:11:17)  [GCC 7.3.0]`
+- espnet version: `espnet 0.9.0`
+- pytorch version: `pytorch 1.6.0`
+- Git hash: `20b0c89369d9dd3e05780b65fdd00a9b4f4891e5`
+  - Commit date: `Mon Oct 12 09:28:20 2020 -0400`
+
+## asr_train_asr_conformer3_raw_char_batch_bins4000000_accum_grad4_sp
+### WER
+
+|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
+|---|---|---|---|---|---|---|---|---|
+|decode_asr_rnn_lm_lm_train_lm_char_valid.loss.ave_asr_model_valid.acc.ave/dev|14326|14326|64.8|35.2|0.0|0.0|35.2|35.2|
+|decode_asr_rnn_lm_lm_train_lm_char_valid.loss.ave_asr_model_valid.acc.ave/test|7176|7176|63.5|36.5|0.0|0.0|36.5|36.5|
+|decode_asr_rnn_lm_lm_train_lm_transformer_char_batch_bins2000000_valid.loss.ave_asr_model_valid.acc.ave/dev|14326|14326|66.3|33.7|0.0|0.0|33.7|33.7|
+|decode_asr_rnn_lm_lm_train_lm_transformer_char_batch_bins2000000_valid.loss.ave_asr_model_valid.acc.ave/test|7176|7176|65.0|35.0|0.0|0.0|35.0|35.0|
+
+### CER
+
+|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
+|---|---|---|---|---|---|---|---|---|
+|decode_asr_rnn_lm_lm_train_lm_char_valid.loss.ave_asr_model_valid.acc.ave/dev|14326|205341|95.5|4.4|0.1|0.1|4.6|35.2|
+|decode_asr_rnn_lm_lm_train_lm_char_valid.loss.ave_asr_model_valid.acc.ave/test|7176|104765|95.2|4.7|0.1|0.1|4.9|36.5|
+|decode_asr_rnn_lm_lm_train_lm_transformer_char_batch_bins2000000_valid.loss.ave_asr_model_valid.acc.ave/dev|14326|205341|95.7|4.2|0.1|0.1|4.4|33.7|
+|decode_asr_rnn_lm_lm_train_lm_transformer_char_batch_bins2000000_valid.loss.ave_asr_model_valid.acc.ave/test|7176|104765|95.4|4.5|0.1|0.1|4.7|35.0|
+

conformer/34e9cabc2c29fd0e3a2917ffa525d98b/exp/asr_train_asr_conformer3_raw_char_batch_bins4000000_accum_grad4_sp/config.yaml

+accum_grad: 4
+allow_variable_data_keys: false
+batch_bins: 4000000
+batch_size: 20
+batch_type: numel
+best_model_criterion:
+- - valid
+  - acc
+  - max
+bpemodel: null
+chunk_length: 500
+chunk_shift_ratio: 0.5
+cleaner: null
+collect_stats: false
+config: ./conf/train_asr_conformer3.yaml
+ctc_conf:
+  ctc_type: builtin
+  dropout_rate: 0.0
+  reduce: true
+cudnn_benchmark: false
+cudnn_deterministic: true
+cudnn_enabled: true
+decoder: transformer
+decoder_conf:
+  attention_heads: 4
+  dropout_rate: 0.1
+  linear_units: 2048
+  num_blocks: 6
+  positional_dropout_rate: 0.1
+  self_attention_dropout_rate: 0.0
+  src_attention_dropout_rate: 0.0
+dist_backend: nccl
+dist_init_method: env://
+dist_launcher: null
+dist_master_addr: null
+dist_master_port: null
+dist_rank: null
+dist_world_size: null
+distributed: false
+dry_run: false
+early_stopping_criterion:
+- valid
+- loss
+- min
+encoder: conformer
+encoder_conf:
+  activation_type: swish
+  attention_dropout_rate: 0.0
+  attention_heads: 4
+  cnn_module_kernel: 15
+  dropout_rate: 0.1
+  input_layer: conv2d
+  linear_units: 2048
+  macaron_style: true
+  normalize_before: true
+  num_blocks: 12
+  output_size: 256
+  pos_enc_layer_type: rel_pos
+  positional_dropout_rate: 0.1
+  selfattention_layer_type: rel_selfattn
+  use_cnn_module: true
+fold_length:
+- 51200
+- 150
+frontend: default
+frontend_conf:
+  fs: 16k
+g2p: null
+grad_clip: 5
+grad_clip_type: 2.0
+grad_noise: false
+init: null
+input_size: null
+iterator_type: sequence
+keep_nbest_models: 10
+local_rank: 0
+log_interval: null
+log_level: INFO
+max_cache_fd: 32
+max_cache_size: 0.0
+max_epoch: 50
+model_conf:
+  ctc_weight: 0.3
+  length_normalized_loss: false
+  lsm_weight: 0.1
+multiple_iterator: false
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+- "\u5267"
+- "\u9646"
+- "\u7ADF"
+- "\u7B7E"
+- "\u6B27"
+- "\u4EAB"
+- "\u6625"
+- "\u5FBD"
+- "\u88C1"
+- "\u507F"
+- "\u542F"
+- "\u827A"
+- "\u5B97"
+- "\u5473"
+- "\u5BDF"
+- "\u4F30"
+- "\u51C0"
+- "\u52DF"
+- "\u62E5"
+- "\u91CA"
+- "\u559C"
+- "\u987A"
+- "\u52B1"
+- "\u9760"
+- "\u6E10"
+- "\u5170"
+- "\u6CB9"
+- "\u4F73"
+- "\u56F0"
+- "\u9488"
+- "\u8FF7"
+- "\u5199"
+- "\u6750"
+- "\u786C"
+- "\u6865"
+- "\u575A"
+- "\u8BA2"
+- "\u62F3"
+- "\u7D2F"
+- "\u76D6"
+- "\u5BA4"
+- "\u675F"
+- "\u622A"
+- "\u8DDD"
+- "\u9A76"
+- "\u65EC"
+- "\u6B4C"
+- "\u6089"
+- "\u70C8"
+- "\u5E8F"
+- "\u60A3"
+- "\u5E72"
+- "\u6C61"
+- "\u5708"
+- "\u6770"
+- "\u9876"
+- "\u8D25"
+- "\u4F34"
+- "\u5F52"
+- "\u63A2"
+- "\u66DD"
+- "\u6000"
+- "\u6025"
+- "\u6C60"
+- "\u7EC7"
+- "\u79C0"
+- "\u59D0"
+- "\u5CF0"
+- "\u987E"
+- "\u8BEF"
+- "\u952E"
+- "\u4E30"
+- "\u73A9"
+- "\u6C49"
+- "\u53E4"
+- "\u5F69"
+- "\u8BA8"
+- "\u670B"
+- "\u6297"
+- "\u523A"
+- "\u6311"
+- "\u8840"
+- "\u51CC"
+- "\u65E7"
+- "\u62DF"
+- "\u6652"
+- "\u9644"
+- "\u60CA"
+- "\u6B22"
+- "\u52B3"
+- "\u4E08"
+- "\u64AD"
+- "\u5F90"
+- "\u5417"
+- "\u6E56"
+- "\u7B11"
+- "\u9986"
+- "\u97F3"
+- "\u9635"
+- "\u5750"
+- "\u8C37"
+- "\u5F02"
+- "\u600E"
+- "\u590F"
+- "\u9F84"
+- "\u719F"
+- "\u82E5"
+- "\u60E0"
+- "\u4F11"
+- "\u6C38"
+- "\u54EA"
+- "\u6682"
+- "\u8F93"
+- "\u7ECD"
+- "\u5370"
+- "\u51B0"
+- "\u7F13"
+- "\u6696"
+- "\u542C"
+- "\u907F"
+- "\u5609"
+- "\u5BFB"
+- "\u57F9"
+- "\u7B79"
+- "\u4F26"
+- "\u96EA"
+- "\u8D26"
+- "\u66B4"
+- "\u7B80"
+- "\u4E88"
+- "\u4E3D"
+- "\u6CFD"
+- "\u523B"
+- "\u91CE"
+- "\u5A01"
+- "\u5BBD"
+- "\u7B14"
+- "\u8BED"
+- "\u6B66"
+- "\u7092"
+- "\u865A"
+- "\u67B6"
+- "\u5947"
+- "\u54E5"
+- "\u5C24"
+- "\u5EA7"
+- "\u8FC5"
+- "\u7C89"
+- "\u500D"
+- "\u6731"
+- "\u5C4B"
+- "\u822C"
+- "\u9519"
+- "\u6D25"
+- "\u5F1F"
+- "\u6C47"
+- "\u6982"
+- "\u9F13"
+- "\u6389"
+- "\u90D1"
+- "\u949F"
+- "\u53EC"
+- "\u793C"
+- "\u7981"
+- "\u6298"
+- "\u7F29"
+- "\u9501"
+- "\u6D9B"
+- "\u4E61"
+- "\u80A5"
+- "\u5E78"
+- "\u96E8"
+- "\u68A6"
+- "\u8089"
+- "\u653B"
+- "\u51AC"
+- "\u547C"
+- "\u84DD"
+- "\u7EFC"
+- "\u7801"
+- "\u676F"
+- "\u6620"
+- "\u5200"
+- "\u8C22"
+- "\u7F16"
+- "\u811A"
+- "\u6653"
+- "\u904D"
+- "\u671D"
+- "\u5409"
+- "\u6D17"
+- "\u76D7"
+- "\u4E39"
+- "\u5C4F"
+- "\u76DB"
+- "\u79D8"
+- "\u62D8"
+- "\u67D3"
+- "\u6E20"
+- "\u6263"
+- "\u6D0B"
+- "\u68AF"
+- "\u67AA"
+- "\u4E45"
+- "\u8BC8"
+- "\u5DDD"
+- "\u6469"
+- "\u4FC4"
+- "\u8FEA"
+- "\u6BDB"
+- "\u8D5E"
+- "\u7B26"
+- "\u753B"
+- "\u7FFB"
+- "\u59B9"
+- "\u7B51"
+- "\u805A"
+- "\u54C8"
+- "\u5175"
+- "\u80AF"
+- "\u80CE"
+- "\u6F6E"
+- "\u82E6"
+- "\u9003"
+- "\u8BB2"
+- "\u6388"
+- "\u6162"
+- "\u987F"
+- "\u9057"
+- "\u4E1D"
+- "\u5448"
+- "\u63ED"
+- "\u6302"
+- "\u5C01"
+- "\u6167"
+- "\u8DE8"
+- "\u8BE2"
+- "\u62C6"
+- "\u68EE"
+- "\u5B55"
+- "\u8131"
+- "\u8BFB"
+- "\u679A"
+- "\u6350"
+- "\u6869"
+- "\u8DC3"
+- "\u5237"
+- "\u82AF"
+- "\u6597"
+- "\u6606"
+- "\u50A8"
+- "\u5B88"
+- "\u89E6"
+- "\u6728"
+- "\u76AE"
+- "\u996D"
+- "\u6DFB"
+- "\u839E"
+- "\u9707"
+- "\u8F7D"
+- "\u8D35"
+- "\u4FB5"
+- "\u6491"
+- "\u7238"
+- "\u518C"
+- "\u821E"
+- "\u4E01"
+- "\u8D38"
+- "\u5976"
+- "\u9690"
+- "\u5987"
+- "\u699C"
+- "\u7761"
+- "\u9677"
+- "\u8349"
+- "\u626C"
+- "\u88AD"
+- "\u5077"
+- "\u7763"
+- "\u4E8F"
+- "\u5415"
+- "\u73E0"
+- "\u8D76"
+- "\u6276"
+- "\u76C8"
+- "\u6863"
+- "\u8BFA"
+- "\u8FD4"
+- "\u65E2"
+- "\u672B"
+- "\u6C99"
+- "\u8C01"
+- "\u5B8F"
+- "\u6458"
+- "\u5178"
+- "\u5E8A"
+- "\u95ED"
+- "\u5F03"
+- "\u96F7"
+- "\u6BD5"
+- "\u90ED"
+- "\u73B2"
+- "\u90CE"
+- "\u829D"
+- "\u80E1"
+- "\u745E"
+- "\u76DF"
+- "\u5385"
+- "\u62B1"
+- "\u71C3"
+- "\u94DC"
+- "\u65D7"
+- "\u8363"
+- "\u9910"
+- "\u7259"
+- "\u7237"
+- "\u8FF9"
+- "\u5B87"
+- "\u9014"
+- "\u6F5C"
+- "\u62B5"
+- "\u9AA8"
+- "\u63F4"
+- "\u6D6A"
+- "\u7389"
+- "\u7956"
+- "\u632F"
+- "\u8679"
+- "\u6563"
+- "\u7126"
+- "\u52C7"
+- "\u52AA"
+- "\u5A46"
+- "\u62D2"
+- "\u5F39"
+- "\u6881"
+- "\u575B"
+- "\u542B"
+- "\u574F"
+- "\u7EAF"
+- "\u70DF"
+- "\u51B7"
+- "\u955C"
+- "\u53EB"
+- "\u8D75"
+- "\u9759"
+- "\u4EEA"
+- "\u85CF"
+- "\u6742"
+- "\u75DB"
+- "\u614E"
+- "\u6811"
+- "\u7AE0"
+- "\u585E"
+- "\u94A2"
+- "\u72C2"
+- "\u5462"
+- "\u96C5"
+- "\u5BFF"
+- "\u6069"
+- "\u56FA"
+- "\u72D7"
+- "\u83DC"
+- "\u6C9F"
+- "\u732E"
+- "\u53F6"
+- "\u6CF0"
+- "\u8D62"
+- "\u5269"
+- "\u7A83"
+- "\u504F"
+- "\u638C"
+- "\u5B9C"
+- "\u8BFE"
+- "\u8DA3"
+- "\u559D"
+- "\u7EA0"
+- "\u7C4D"
+- "\u66FF"
+- "\u70B8"
+- "\u9694"
+- "\u7838"
+- "\u642D"
+- "\u8BDA"
+- "\u65CF"
+- "\u6D59"
+- "\u9F50"
+- "\u6746"
+- "\u664B"
+- "\u6076"
+- "\u594B"
+- "\u79CB"
+- "\u9C9C"
+- "\u9C81"
+- "\u5192"
+- "\u8D5A"
+- "\u5F31"
+- "\u817F"
+- "\u795D"
+- "\u6DF7"
+- "\u7F34"
+- "\u75BE"
+- "\u63E1"
+- "\u6C6A"
+- "\u8F89"
+- "\u5954"
+- "\u9192"
+- "\u6355"
+- "\u9A91"
+- "\u9E1F"
+- "\u6446"
+- "\u7075"
+- "\u654F"
+- "\u725B"
+- "\u5C9B"
+- "\u604B"
+- "\u8017"
+- "\u74E6"
+- "\u62FC"
+- "\u6050"
+- "\u68D2"
+- "\u5766"
+- "\u539A"
+- "\u4FA7"
+- "\u5C1D"
+- "\u85AA"
+- "\u5802"
+- "\u66F2"
+- "\u7B54"
+- "\u96C4"
+- "\u5F92"
+- "\u788D"
+- "\u62D3"
+- "\u7FD4"
+- "\u4F5B"
+- "\u4F50"
+- "\u6EF4"
+- "\u676D"
+- "\u6B8B"
+- "\u6BEB"
+- "\u5C04"
+- "\u62D6"
+- "\u963B"
+- "\u8F91"
+- "\u8E2A"
+- "\u75C7"
+- "\u59D3"
+- "\u6B32"
+- "\u9C7C"
+- "\u8239"
+- "\u6062"
+- "\u8861"
+- "\u6DE1"
+- "\u552F"
+- "\u4E4F"
+- "\u8FDF"
+- "\u742A"
+- "\u70E7"
+- "\u5510"
+- "\u5377"
+- "\u966A"
+- "\u4F0F"
+- "\u52B5"
+- "\u7E41"
+- "\u9006"
+- "\u8FC1"
+- "\u8BCA"
+- "\u4E71"
+- "\u4EA6"
+- "\u8C13"
+- "\u77FF"
+- "\u8FEB"
+- "\u5FE7"
+- "\u626E"
+- "\u5DE2"
+- "\u624E"
+- "\u5353"
+- "\u6052"
+- "\u5E84"
+- "\u9012"
+- "\u707E"
+- "\u83B1"
+- "\u8D74"
+- "\u7164"
+- "\u640F"
+- "\u5242"
+- "\u6885"
+- "\u5427"
+- "\u64A4"
+- "\u54F2"
+- "\u70B3"
+- "\u5C3E"
+- "\u8A89"
+- "\u6D1B"
+- "\u8F68"
+- "\u7F72"
+- "\u515A"
+- "\u60EF"
+- "\u5E7C"
+- "\u7F18"
+- "\u58A8"
+- "\u83AB"
+- "\u8F9E"
+- "\u594F"
+- "\u6562"
+- "\u5784"
+- "\u65C1"
+- "\u8499"
+- "\u7BB1"
+- "\u5428"
+- "\u6CDB"
+- "\u6015"
+- "\u95F9"
+- "\u6B20"
+- "\u52AB"
+- "\u7EB8"
+- "\u5CB8"
+- "\u6DD8"
+- "\u8D4C"
+- "\u7A97"
+- "\u6D01"
+- "\u5C97"
+- "\u5A18"
+- "\u6676"
+- "\u52B2"
+- "\u51ED"
+- "\u65A4"
+- "\u6D2A"
+- "\u6DB2"
+- "\u69DB"
+- "\u517C"
+- "\u6454"
+- "\u695A"
+- "\u660C"
+- "\u83F2"
+- "\u840C"
+- "\u4F0D"
+- "\u6CBF"
+- "\u54A8"
+- "\u996E"
+- "\u5899"
+- "\u6C88"
+- "\u5761"
+- "\u5BF8"
+- "\u6EA2"
+- "\u4ED3"
+- "\u9274"
+- "\u6148"
+- "\u67EF"
+- "\u65E6"
+- "\u6B8A"
+- "\u5760"
+- "\u8BF8"
+- "\u641E"
+- "\u4F0A"
+- "\u9738"
+- "\u7ED1"
+- "\u6C27"
+- "\u5885"
+- "\u8F7F"
+- "\u86CB"
+- "\u5FD9"
+- "\u6EE8"
+- "\u4E95"
+- "\u903C"
+- "\u4F2F"
+- "\u764C"
+- "\u71D5"
+- "\u8D56"
+- "\u6D66"
+- "\u6F0F"
+- "\u643A"
+- "\u582A"
+- "\u9605"
+- "\u8BD7"
+- "\u8D29"
+- "\u8150"
+- "\u503E"
+- "\u94FA"
+- "\u65FA"
+- "\u6A2A"
+- "\u900A"
+- "\u5141"
+- "\u7A84"
+- "\u9E21"
+- "\u5531"
+- "\u8D3F"
+- "\u62E8"
+- "\u780D"
+- "\u731B"
+- "\u78B3"
+- "\u5835"
+- "\u9080"
+- "\u5195"
+- "\u680F"
+- "\u59C6"
+- "\u8033"
+- "\u7ED5"
+- "\u89C8"
+- "\u8058"
+- "\u7433"
+- "\u971E"
+- "\u6316"
+- "\u5E9E"
+- "\u5F7B"
+- "\u9881"
+- "\u633A"
+- "\u6C89"
+- "\u6284"
+- "\u5BAB"
+- "\u6BB4"
+- "\u5783"
+- "\u573E"
+- "\u5C38"
+- "\u6DB5"
+- "\u5A03"
+- "\u5A77"
+- "\u7275"
+- "\u817E"
+- "\u5367"
+- "\u5076"
+- "\u6270"
+- "\u6FB3"
+- "\u8FC8"
+- "\u864E"
+- "\u8D21"
+- "\u8BCD"
+- "\u58C1"
+- "\u5BBE"
+- "\u6377"
+- "\u5FCD"
+- "\u4F69"
+- "\u558A"
+- "\u62BD"
+- "\u690D"
+- "\u70BC"
+- "\u5978"
+- "\u5410"
+- "\u629B"
+- "\u7965"
+- "\u8389"
+- "\u6CC4"
+- "\u68B0"
+- "\u4E52"
+- "\u8F9B"
+- "\u75AF"
+- "\u51EF"
+- "\u626B"
+- "\u706F"
+- "\u6DC0"
+- "\u6BC1"
+- "\u9B3C"
+- "\u5A74"
+- "\u6DEB"
+- "\u51BB"
+- "\u7BEE"
+- "\u804A"
+- "\u5E05"
+- "\u4E54"
+- "\u6CAA"
+- "\u7FBD"
+- "\u820D"
+- "\u88C2"
+- "\u5FFD"
+- "\u5706"
+- "\u62D4"
+- "\u6717"
+- "\u5BBF"
+- "\u9EBB"
+- "\u7720"
+- "\u73AE"
+- "\u5854"
+- "\u78B0"
+- "\u602A"
+- "\u62BC"
+- "\u6500"
+- "\u9A70"
+- "\u6B23"
+- "\u8E0F"
+- "\u5DE9"
+- "\u5E9F"
+- "\u8270"
+- "\u4E73"
+- "\u53E5"
+- "\u4FA6"
+- "\u5144"
+- "\u8350"
+- "\u5BD3"
+- "\u53A6"
+- "\u8D1D"
+- "\u7EB5"
+- "\u8096"
+- "\u675C"
+- "\u5FD8"
+- "\u4E22"
+- "\u642C"
+- "\u66FC"
+- "\u74F6"
+- "\u9E4F"
+- "\u9ED8"
+- "\u60E8"
+- "\u6CE1"
+- "\u6108"
+- "\u6566"
+- "\u6D1E"
+- "\u529D"
+- "\u9896"
+- "\u9177"
+- "\u989C"
+- "\u5DE1"
+- "\u810F"
+- "\u4EFF"
+- "\u7F8A"
+- "\u6324"
+- "\u5EC9"
+- "\u9EA6"
+- "\u584C"
+- "\u541B"
+- "\u654C"
+- "\u4E4C"
+- "\u4FE9"
+- "\u6A0A"
+- "\u90AE"
+- "\u70EF"
+- "\u8BE6"
+- "\u8212"
+- "\u5951"
+- "\u6F2B"
+- "\u80DE"
+- "\u9B54"
+- "\u5B8B"
+- "\u4F10"
+- "\u8C28"
+- "\u59FF"
+- "\u59D1"
+- "\u9686"
+- "\u7EB9"
+- "\u5085"
+- "\u8336"
+- "\u8457"
+- "\u8C0B"
+- "\u656C"
+- "\u90C1"
+- "\u9A71"
+- "\u83CC"
+- "\u60AC"
+- "\u5FAA"
+- "\u644A"
+- "\u95EA"
+- "\u4F2A"
+- "\u9E3F"
+- "\u5A1C"
+- "\u6F8E"
+- "\u6E43"
+- "\u7089"
+- "\u6697"
+- "\u95EF"
+- "\u7EEA"
+- "\u6C70"
+- "\u7A3F"
+- "\u54AC"
+- "\u5362"
+- "\u6CC9"
+- "\u6D8C"
+- "\u857E"
+- "\u59FB"
+- "\u718A"
+- "\u7A00"
+- "\u6447"
+- "\u540A"
+- "\u684C"
+- "\u4FCA"
+- "\u54ED"
+- "\u8D60"
+- "\u9038"
+- "\u5413"
+- "\u8D6B"
+- "\u51E1"
+- "\u4FF1"
+- "\u51AF"
+- "\u5DE7"
+- "\u6DAF"
+- "\u5566"
+- "\u8BBC"
+- "\u6070"
+- "\u629A"
+- "\u8087"
+- "\u950B"
+- "\u51F6"
+- "\u8D2F"
+- "\u6084"
+- "\u706D"
+- "\u5180"
+- "\u7CD5"
+- "\u4F38"
+- "\u80D6"
+- "\u8179"
+- "\u90CA"
+- "\u658C"
+- "\u946B"
+- "\u5389"
+- "\u80A9"
+- "\u5723"
+- "\u6D6E"
+- "\u5999"
+- "\u9970"
+- "\u5C16"
+- "\u5C0A"
+- "\u90B1"
+- "\u8BDE"
+- "\u5C61"
+- "\u6478"
+- "\u916C"
+- "\u95F2"
+- "\u6670"
+- "\u5339"
+- "\u953B"
+- "\u7532"
+- "\u6572"
+- "\u9065"
+- "\u52D2"
+- "\u5151"
+- "\u7199"
+- "\u7A3D"
+- "\u8521"
+- "\u60DC"
+- "\u732B"
+- "\u6012"
+- "\u9A7B"
+- "\u9887"
+- "\u6D53"
+- "\u5BB4"
+- "\u4EC1"
+- "\u8D4F"
+- "\u78E8"
+- "\u60B2"
+- "\u9A82"
+- "\u8F74"
+- "\u59DC"
+- "\u732A"
+- "\u5272"
+- "\u6B49"
+- "\u73BB"
+- "\u6D69"
+- "\u756A"
+- "\u6E21"
+- "\u808C"
+- "\u8DF5"
+- "\u76FE"
+- "\u751C"
+- "\u6EBA"
+- "\u5C3A"
+- "\u5FC6"
+- "\u76D0"
+- "\u6CE5"
+- "\u8584"
+- "\u77DB"
+- "\u7545"
+- "\u6291"
+- "\u9897"
+- "\u848B"
+- "\u7A0D"
+- "\u788E"
+- "\u5E1D"
+- "\u7483"
+- "\u6380"
+- "\u62D0"
+- "\u7262"
+- "\u5E7B"
+- "\u4ED4"
+- "\u7CAE"
+- "\u827E"
+- "\u626D"
+- "\u5C3F"
+- "\u520A"
+- "\u4ED1"
+- "\u9ECE"
+- "\u57C3"
+- "\u81C2"
+- "\u90BB"
+- "\u82D7"
+- "\u8854"
+- "\u6842"
+- "\u6F6D"
+- "\u5C65"
+- "\u8D3E"
+- "\u997C"
+- "\u60E9"
+- "\u8BF1"
+- "\u65CB"
+- "\u7BC7"
+- "\u8FBD"
+- "\u65ED"
+- "\u903E"
+- "\u8C46"
+- "\u6F58"
+- "\u5806"
+- "\u7518"
+- "\u90A6"
+- "\u6C0F"
+- "\u62E6"
+- "\u7855"
+- "\u68CB"
+- "\u88E4"
+- "\u4E53"
+- "\u59DA"
+- "\u5398"
+- "\u9093"
+- "\u9676"
+- "\u8428"
+- "\u5F17"
+- "\u8F85"
+- "\u5EF7"
+- "\u5401"
+- "\u6760"
+- "\u7EEE"
+- "\u7444"
+- "\u5939"
+- "\u69FD"
+- "\u7978"
+- "\u8881"
+- "\u52FE"
+- "\u8D41"
+- "\u5E16"
+- "\u8170"
+- "\u6F02"
+- "\u88D5"
+- "\u5634"
+- "\u58EE"
+- "\u5F2F"
+- "\u554A"
+- "\u6C64"
+- "\u57AB"
+- "\u9B4F"
+- "\u5021"
+- "\u680B"
+- "\u7891"
+- "\u9888"
+- "\u6691"
+- "\u9B45"
+- "\u88F8"
+- "\u758F"
+- "\u96C7"
+- "\u6BC5"
+- "\u5FE0"
+- "\u7586"
+- "\u845B"
+- "\u51E4"
+- "\u5C48"
+- "\u60A6"
+- "\u9988"
+- "\u6321"
+- "\u95EB"
+- "\u6C2E"
+- "\u5146"
+- "\u8C8C"
+- "\u5395"
+- "\u8C23"
+- "\u98A0"
+- "\u731C"
+- "\u75B2"
+- "\u6846"
+- "\u63FD"
+- "\u80C1"
+- "\u61BE"
+- "\u79E9"
+- "\u8273"
+- "\u5E3D"
+- "\u6C1B"
+- "\u8377"
+- "\u6CEA"
+- "\u5251"
+- "\u61C2"
+- "\u94BB"
+- "\u9075"
+- "\u8D2A"
+- "\u8D3C"
+- "\u72F1"
+- "\u59E3"
+- "\u5BFA"
+- "\u80F6"
+- "\u5435"
+- "\u50AC"
+- "\u524A"
+- "\u4E11"
+- "\u6B3A"
+- "\u8083"
+- "\u59A5"
+- "\u70E6"
+- "\u7070"
+- "\u64C5"
+- "\u4F63"
+- "\u8427"
+- "\u867E"
+- "\u978B"
+- "\u6367"
+- "\u901D"
+- "\u7325"
+- "\u74DC"
+- "\u9178"
+- "\u5948"
+- "\u53A8"
+- "\u7D2B"
+- "\u4FA0"
+- "\u5851"
+- "\u5A07"
+- "\u8F96"
+- "\u8206"
+- "\u64E6"
+- "\u67CF"
+- "\u6F84"
+- "\u78CA"
+- "\u8650"
+- "\u8F70"
+- "\u66F9"
+- "\u5220"
+- "\u9F3B"
+- "\u67F3"
+- "\u5C6F"
+- "\u7B3C"
+- "\u7687"
+- "\u7CD6"
+- "\u73CD"
+- "\u75BC"
+- "\u67DC"
+- "\u6361"
+- "\u5740"
+- "\u80A0"
+- "\u635E"
+- "\u62DC"
+- "\u5CFB"
+- "\u5439"
+- "\u4E43"
+- "\u7626"
+- "\u809A"
+- "\u8D24"
+- "\u5E15"
+- "\u5CB3"
+- "\u52E4"
+- "\u745C"
+- "\u9505"
+- "\u6CAB"
+- "\u4FD7"
+- "\u6615"
+- "\u5E06"
+- "\u8302"
+- "\u9189"
+- "\u586B"
+- "\u9971"
+- "\u722C"
+- "\u8F69"
+- "\u6EDE"
+- "\u871C"
+- "\u6C57"
+- "\u98D9"
+- "\u8010"
+- "\u4EA8"
+- "\u5AB3"
+- "\u5F6D"
+- "\u84C4"
+- "\u8776"
+- "\u70AE"
+- "\u9F20"
+- "\u5496"
+- "\u7434"
+- "\u5BA0"
+- "\u68CD"
+- "\u6398"
+- "\u8328"
+- "\u5751"
+- "\u6E58"
+- "\u5B5F"
+- "\u52A3"
+- "\u707F"
+- "\u866B"
+- "\u5F66"
+- "\u55B7"
+- "\u63CF"
+- "\u8FA9"
+- "\u5C34"
+- "\u5C2C"
+- "\u5F25"
+- "\u5B64"
+- "\u5CE1"
+- "\u51F8"
+- "\u903B"
+- "\u8FB0"
+- "\u5B54"
+- "\u62AC"
+- "\u99A8"
+- "\u851A"
+- "\u6021"
+- "\u96EF"
+- "\u7816"
+- "\u5D07"
+- "\u80A2"
+- "\u67F1"
+- "\u9614"
+- "\u5F7C"
+- "\u8352"
+- "\u6EDA"
+- "\u8461"
+- "\u8404"
+- "\u6602"
+- "\u76C6"
+- "\u6028"
+- "\u77AC"
+- "\u659C"
+- "\u65A9"
+- "\u775B"
+- "\u526A"
+- "\u63D2"
+- "\u68DA"
+- "\u4E32"
+- "\u6C83"
+- "\u67D4"
+- "\u80A4"
+- "\u58F3"
+- "\u80F8"
+- "\u9655"
+- "\u51C9"
+- "\u5D1B"
+- "\u9E23"
+- "\u7F55"
+- "\u8877"
+- "\u9634"
+- "\u76F2"
+- "\u4F1E"
+- "\u6212"
+- "\u8E22"
+- "\u72FC"
+- "\u57CB"
+- "\u917F"
+- "\u65E8"
+- "\u6208"
+- "\u6349"
+- "\u8DEA"
+- "\u8D3A"
+- "\u8C2D"
+- "\u6D82"
+- "\u840E"
+- "\u6ECB"
+- "\u660F"
+- "\u6247"
+- "\u9F0E"
+- "\u6960"
+- "\u9A73"
+- "\u6EAA"
+- "\u6851"
+- "\u94A7"
+- "\u8361"
+- "\u75D5"
+- "\u739B"
+- "\u8EB2"
+- "\u8C10"
+- "\u60A8"
+- "\u53F9"
+- "\u6876"
+- "\u6655"
+- "\u4E19"
+- "\u7487"
+- "\u549A"
+- "\u70C2"
+- "\u6749"
+- "\u6323"
+- "\u7A9D"
+- "\u4EB5"
+- "\u82B8"
+- "\u6E1D"
+- "\u82B3"
+- "\u5986"
+- "\u819C"
+- "\u714C"
+- "\u5C18"
+- "\u4FAF"
+- "\u8D4B"
+- "\u6E23"
+- "\u8D2B"
+- "\u6843"
+- "\u9875"
+- "\u541E"
+- "\u80C0"
+- "\u7AF9"
+- "\u809D"
+- "\u96FE"
+- "\u5AC1"
+- "\u8F88"
+- "\u6124"
+- "\u7410"
+- "\u6B96"
+- "\u5A9B"
+- "\u5BC4"
+- "\u50F5"
+- "\u902E"
+- "\u806A"
+- "\u7C97"
+- "\u5BD2"
+- "\u5F04"
+- "\u5893"
+- "\u8C0C"
+- "\u6254"
+- "\u5F79"
+- "\u5446"
+- "\u9756"
+- "\u8482"
+- "\u82AC"
+- "\u7FFC"
+- "\u5582"
+- "\u5B75"
+- "\u8C0E"
+- "\u7845"
+- "\u74A8"
+- "\u5580"
+- "\u76FC"
+- "\u76D2"
+- "\u614C"
+- "\u70EB"
+- "\u79E6"
+- "\u68B3"
+- "\u97E6"
+- "\u888B"
+- "\u9493"
+- "\u5915"
+- "\u7897"
+- "\u5BE8"
+- "\u5858"
+- "\u884D"
+- "\u5792"
+- "\u537F"
+- "\u6EE9"
+- "\u6251"
+- "\u7ED8"
+- "\u8FB1"
+- "\u708E"
+- "\u94C5"
+- "\u80BF"
+- "\u8870"
+- "\u53A2"
+- "\u8EBA"
+- "\u7EBD"
+- "\u786B"
+- "\u7750"
+- "\u7FC1"
+- "\u6170"
+- "\u800D"
+- "\u7F20"
+- "\u72E0"
+- "\u8109"
+- "\u65A5"
+- "\u8102"
+- "\u8DB4"
+- "\u94A9"
+- "\u6B67"
+- "\u6905"
+- "\u8E29"
+- "\u63B7"
+- "\u633D"
+- "\u9510"
+- "\u52D8"
+- "\u9022"
+- "\u90DD"
+- "\u5BAA"
+- "\u80C3"
+- "\u7C92"
+- "\u77A9"
+- "\u8F9F"
+- "\u7686"
+- "\u4EF0"
+- "\u8155"
+- "\u532A"
+- "\u9675"
+- "\u94A5"
+- "\u7F1D"
+- "\u95F8"
+- "\u72AC"
+- "\u9521"
+- "\u5F0A"
+- "\u51DD"
+- "\u81ED"
+- "\u8D81"
+- "\u62FE"
+- "\u5938"
+- "\u63A9"
+- "\u8000"
+- "\u70AD"
+- "\u94EC"
+- "\u53E0"
+- "\u574A"
+- "\u632A"
+- "\u87F9"
+- "\u88F9"
+- "\u72EE"
+- "\u8F90"
+- "\u964C"
+- "\u6345"
+- "\u75AB"
+- "\u5179"
+- "\u970D"
+- "\u9508"
+- "\u5A1F"
+- "\u8681"
+- "\u5962"
+- "\u543B"
+- "\u4F83"
+- "\u6656"
+- "\u6273"
+- "\u51A4"
+- "\u5F70"
+- "\u8E48"
+- "\u7574"
+- "\u86C7"
+- "\u6FE0"
+- "\u5561"
+- "\u5821"
+- "\u4FA3"
+- "\u6492"
+- "\u94ED"
+- "\u638F"
+- "\u594E"
+- "\u8702"
+- "\u54B8"
+- "\u7A77"
+- "\u7784"
+- "\u9042"
+- "\u78BE"
+- "\u533F"
+- "\u74F7"
+- "\u8231"
+- "\u5239"
+- "\u67C4"
+- "\u502A"
+- "\u7779"
+- "\u8BD1"
+- "\u6DC7"
+- "\u731D"
+- "\u6D45"
+- "\u80BA"
+- "\u6E7F"
+- "\u987D"
+- "\u7F69"
+- "\u80C6"
+- "\u5319"
+- "\u6E34"
+- "\u59AE"
+- "\u7F9E"
+- "\u8106"
+- "\u9B44"
+- "\u9502"
+- "\u7EA4"
+- "\u70AB"
+- "\u88D9"
+- "\u80BE"
+- "\u50B2"
+- "\u819D"
+- "\u53D4"
+- "\u5565"
+- "\u6495"
+- "\u7272"
+- "\u7334"
+- "\u8FA8"
+- "\u915D"
+- "\u522E"
+- "\u60D1"
+- "\u6E17"
+- "\u55BB"
+- "\u6674"
+- "\u6DD1"
+- "\u7FA1"
+- "\u6155"
+- "\u64C2"
+- "\u9A9A"
+- "\u7EBA"
+- "\u5495"
+- "\u50E7"
+- "\u6094"
+- "\u5782"
+- "\u762B"
+- "\u5265"
+- "\u8230"
+- "\u6D4F"
+- "\u9C8D"
+- "\u8DFB"
+- "\u4EAD"
+- "\u64B0"
+- "\u5378"
+- "\u83B2"
+- "\u7EB1"
+- "\u7CCA"
+- "\u6735"
+- "\u5CA9"
+- "\u7709"
+- "\u51FD"
+- "\u7CDF"
+- "\u4ED7"
+- "\u60F9"
+- "\u7426"
+- "\u8D1E"
+- "\u6C22"
+- "\u6977"
+- "\u8393"
+- "\u7792"
+- "\u5960"
+- "\u52C3"
+- "\u9524"
+- "\u59A8"
+- "\u5E37"
+- "\u6D3D"
+- "\u4E5E"
+- "\u727A"
+- "\u4EA9"
+- "\u7C3F"
+- "\u6591"
+- "\u7FD8"
+- "\u7948"
+- "\u5507"
+- "\u8015"
+- "\u626F"
+- "\u598D"
+- "\u574E"
+- "\u8C31"
+- "\u76EF"
+- "\u6CFC"
+- "\u608D"
+- "\u838E"
+- "\u6C41"
+- "\u56CA"
+- "\u7529"
+- "\u8FA3"
+- "\u6D78"
+- "\u607C"
+- "\u76D4"
+- "\u70E4"
+- "\u575D"
+- "\u5DC5"
+- "\u6CB8"
+- "\u62B9"
+- "\u90B9"
+- "\u973E"
+- "\u6016"
+- "\u72B9"
+- "\u64CE"
+- "\u8FC4"
+- "\u6068"
+- "\u4E27"
+- "\u575E"
+- "\u8896"
+- "\u8D64"
+- "\u840D"
+- "\u723D"
+- "\u7A46"
+- "\u5A36"
+- "\u95F7"
+- "\u634D"
+- "\u8180"
+- "\u4F88"
+- "\u7B4B"
+- "\u901B"
+- "\u5029"
+- "\u7EB2"
+- "\u906E"
+- "\u5FA1"
+- "\u59E8"
+- "\u6DEE"
+- "\u5BB0"
+- "\u53C9"
+- "\u7EF5"
+- "\u60E7"
+- "\u94A6"
+- "\u5ECA"
+- "\u9CC4"
+- "\u7802"
+- "\u6D46"
+- "\u79BD"
+- "\u548F"
+- "\u763E"
+- "\u997F"
+- "\u75F4"
+- "\u7EF3"
+- "\u789F"
+- "\u97F5"
+- "\u7693"
+- "\u5ED6"
+- "\u5CAD"
+- "\u86D9"
+- "\u5154"
+- "\u82BD"
+- "\u5256"
+- "\u5AD6"
+- "\u6614"
+- "\u54C0"
+- "\u8513"
+- "\u8C26"
+- "\u6EE5"
+- "\u8D42"
+- "\u6E0A"
+- "\u6363"
+- "\u4F51"
+- "\u5F08"
+- "\u4ED9"
+- "\u6FA1"
+- "\u9AA4"
+- "\u4FA8"
+- "\u5949"
+- "\u78C5"
+- "\u6168"
+- "\u7B5B"
+- "\u5632"
+- "\u7AE3"
+- "\u7BAD"
+- "\u8367"
+- "\u8116"
+- "\u5F64"
+- "\u8C6B"
+- "\u8E81"
+- "\u79C9"
+- "\u9E64"
+- "\u5E7A"
+- "\u6E14"
+- "\u7F62"
+- "\u8D2C"
+- "\u94F2"
+- "\u5375"
+- "\u9017"
+- "\u7267"
+- "\u852C"
+- "\u82D1"
+- "\u6CA6"
+- "\u904F"
+- "\u67F4"
+- "\u5E99"
+- "\u517D"
+- "\u8036"
+- "\u9B42"
+- "\u6E9C"
+- "\u7F09"
+- "\u4FCF"
+- "\u8574"
+- "\u82DB"
+- "\u51D1"
+- "\u5A7F"
+- "\u94F8"
+- "\u515C"
+- "\u8E6D"
+- "\u9E2D"
+- "\u6734"
+- "\u808B"
+- "\u566A"
+- "\u711A"
+- "\u574D"
+- "\u5564"
+- "\u9489"
+- "\u621A"
+- "\u8C0D"
+- "\u632B"
+- "\u8247"
+- "\u4F59"
+- "\u5DF7"
+- "\u5C60"
+- "\u548B"
+- "\u8A79"
+- "\u886B"
+- "\u6D74"
+- "\u7239"
+- "\u5B5D"
+- "\u7624"
+- "\u9716"
+- "\u5D29"
+- "\u7538"
+- "\u60BC"
+- "\u64D2"
+- "\u6D47"
+- "\u96D5"
+- "\u7AD6"
+- "\u5E10"
+- "\u8424"
+- "\u9761"
+- "\u6F20"
+- "\u50BB"
+- "\u64BC"
+- "\u5D14"
+- "\u7B52"
+- "\u810A"
+- "\u561B"
+- "\u81E3"
+- "\u79BE"
+- "\u9F9F"
+- "\u5524"
+- "\u5440"
+- "\u58E4"
+- "\u704C"
+- "\u90B5"
+- "\u7A3B"
+- "\u5DFE"
+- "\u8469"
+- "\u9965"
+- "\u7F14"
+- "\u820C"
+- "\u7A9C"
+- "\u79FD"
+- "\u8305"
+- "\u9753"
+- "\u9631"
+- "\u949E"
+- "\u6F7C"
+- "\u785D"
+- "\u58A9"
+- "\u8759"
+- "\u8760"
+- "\u5AC2"
+- "\u8258"
+- "\u56A3"
+- "\u94C3"
+- "\u6252"
+- "\u4F6C"
+- "\u7AED"
+- "\u8D4E"
+- "\u508D"
+- "\u71AC"
+- "\u60A0"
+- "\u6328"
+- "\u6CCA"
+- "\u6512"
+- "\u576A"
+- "\u7130"
+- "\u87BA"
+- "\u8587"
+- "\u86DB"
+- "\u725F"
+- "\u5FCC"
+- "\u6127"
+- "\u9175"
+- "\u8FED"
+- "\u9976"
+- "\u60DF"
+- "\u94AE"
+- "\u95F5"
+- "\u78A7"
+- "\u5F98"
+- "\u5F8A"
+- "\u6EAF"
+- "\u68C9"
+- "\u6B6A"
+- "\u6342"
+- "\u868A"
+- "\u9530"
+- "\u5C41"
+- "\u7578"
+- "\u80AA"
+- "\u8E72"
+- "\u5254"
+- "\u6986"
+- "\u6487"
+- "\u745F"
+- "\u8BB6"
+- "\u98D8"
+- "\u84B8"
+- "\u8BE0"
+- "\u5BC2"
+- "\u7F44"
+- "\u83B9"
+- "\u9E45"
+- "\u6CE3"
+- "\u5D16"
+- "\u73CA"
+- "\u8BB3"
+- "\u7FF0"
+- "\u8718"
+- "\u4EF2"
+- "\u71E5"
+- "\u83F1"
+- "\u6EE2"
+- "\u714E"
+- "\u86EE"
+- "\u77BB"
+- "\u8611"
+- "\u83C7"
+- "\u9699"
+- "\u6346"
+- "\u8549"
+- "\u9063"
+- "\u5B9B"
+- "\u8086"
+- "\u4E38"
+- "\u78C1"
+- "\u73A5"
+- "\u5D4C"
+- "\u97F6"
+- "\u679D"
+- "\u54AA"
+- "\u6109"
+- "\u5455"
+- "\u6DE4"
+- "\u8A93"
+- "\u8F84"
+- "\u4FEF"
+- "\u6850"
+- "\u8205"
+- "\u84C9"
+- "\u6E2D"
+- "\u6C2F"
+- "\u6E85"
+- "\u96C1"
+- "\u9F9A"
+- "\u607A"
+- "\u5996"
+- "\u997D"
+- "\u8346"
+- "\u67AF"
+- "\u4EC7"
+- "\u575F"
+- "\u6F9C"
+- "\u9E9F"
+- "\u85E4"
+- "\u730E"
+- "\u6D12"
+- "\u8339"
+- "\u788C"
+- "\u754F"
+- "\u6DA4"
+- "\u4FDE"
+- "\u52FF"
+- "\u853D"
+- "\u7F50"
+- "\u5C39"
+- "\u5830"
+- "\u5112"
+- "\u82AE"
+- "\u5B5A"
+- "\u54D7"
+- "\u6390"
+- "\u77F6"
+- "\u690E"
+- "\u9610"
+- "\u9A74"
+- "\u8749"
+- "\u7115"
+- "\u9102"
+- "\u803B"
+- "\u70AF"
+- "\u886C"
+- "\u5A49"
+- "\u6101"
+- "\u68A8"
+- "\u4E1B"
+- "\u8C05"
+- "\u81A8"
+- "\u66D9"
+- "\u9E7F"
+- "\u9A84"
+- "\u7F05"
+- "\u5306"
+- "\u8D43"
+- "\u84B2"
+- "\u7741"
+- "\u7131"
+- "\u707C"
+- "\u5203"
+- "\u8783"
+- "\u7455"
+- "\u8BB9"
+- "\u7985"
+- "\u81C0"
+- "\u59D7"
+- "\u5A9A"
+- "\u545B"
+- "\u51F0"
+- "\u701A"
+- "\u57D4"
+- "\u5F13"
+- "\u961A"
+- "\u6E5B"
+- "\u5955"
+- "\u625B"
+- "\u9F7F"
+- "\u631F"
+- "\u9AD3"
+- "\u72ED"
+- "\u6808"
+- "\u9A8F"
+- "\u5D2D"
+- "\u6151"
+- "\u6BBF"
+- "\u796D"
+- "\u50FB"
+- "\u8E6C"
+- "\u5BE1"
+- "\u5466"
+- "\u97A0"
+- "\u9171"
+- "\u7470"
+- "\u9992"
+- "\u5764"
+- "\u8D9F"
+- "\u81FB"
+- "\u5492"
+- "\u8C79"
+- "\u755C"
+- "\u5189"
+- "\u7ECE"
+- "\u5C8C"
+- "\u7504"
+- "\u7EDE"
+- "\u5BB5"
+- "\u5EB8"
+- "\u6B47"
+- "\u6320"
+- "\u6C28"
+- "\u4E59"
+- "\u8335"
+- "\u5C94"
+- "\u6DC4"
+- "\u7898"
+- "\u6DCB"
+- "\u84EC"
+- "\u9885"
+- "\u7FB9"
+- "\u6D51"
+- "\u6627"
+- "\u7FE0"
+- "\u5CE5"
+- "\u60D5"
+- "\u777F"
+- "\u82A6"
+- "\u8680"
+- "\u9893"
+- "\u971C"
+- "\u94B0"
+- "\u6A58"
+- "\u5824"
+- "\u51F3"
+- "\u6EB6"
+- "\u952F"
+- "\u5E42"
+- "\u69B4"
+- "\u5A3C"
+- "\u6C79"
+- "\u832B"
+- "\u538C"
+- "\u7EF0"
+- "\u5D0E"
+- "\u6E83"
+- "\u64AC"
+- "\u6CBE"
+- "\u62C7"
+- "\u75B5"
+- "\u54E6"
+- "\u5F27"
+- "\u5F18"
+- "\u54BD"
+- "\u846C"
+- "\u9601"
+- "\u7AFF"
+- "\u7BE1"
+- "\u96B6"
+- "\u8BDF"
+- "\u716E"
+- "\u4E18"
+- "\u803F"
+- "\u5F6C"
+- "\u655E"
+- "\u6CFB"
+- "\u5937"
+- "\u9685"
+- "\u6E0E"
+- "\u6DF9"
+- "\u9A86"
+- "\u918B"
+- "\u9706"
+- "\u6DA9"
+- "\u9640"
+- "\u53D9"
+- "\u6897"
+- "\u51B6"
+- "\u655B"
+- "\u75EA"
+- "\u8BBD"
+- "\u75A4"
+- "\u8782"
+- "\u8292"
+- "\u5E62"
+- "\u709C"
+- "\u6BEF"
+- "\u6A59"
+- "\u62E2"
+- "\u4FE8"
+- "\u4ED5"
+- "\u6C30"
+- "\u94BE"
+- "\u5450"
+- "\u682A"
+- "\u813E"
+- "\u70E8"
+- "\u78D5"
+- "\u859B"
+- "\u7A96"
+- "\u82B7"
+- "\u8715"
+- "\u8845"
+- "\u6B79"
+- "\u54D2"
+- "\u8BE1"
+- "\u6467"
+- "\u6F06"
+- "\u87D1"
+- "\u5288"
+- "\u5475"
+- "\u7D6E"
+- "\u6296"
+- "\u5A05"
+- "\u94DD"
+- "\u9709"
+- "\u82AD"
+- "\u8F9C"
+- "\u660A"
+- "\u5618"
+- "\u54D1"
+- "\u67A2"
+- "\u8110"
+- "\u5E90"
+- "\u94A0"
+- "\u9CCC"
+- "\u77E9"
+- "\u9506"
+- "\u5A67"
+- "\u6C9B"
+- "\u9972"
+- "\u7184"
+- "\u7FE1"
+- "\u5C79"
+- "\u818F"
+- "\u9619"
+- "\u6402"
+- "\u9523"
+- "\u5E4C"
+- "\u6A44"
+- "\u6984"
+- "\u6756"
+- "\u65F7"
+- "\u77EB"
+- "\u5188"
+- "\u821F"
+- "\u814A"
+- "\u8042"
+- "\u62E3"
+- "\u905B"
+- "\u52CB"
+- "\u7A98"
+- "\u97E7"
+- "\u54B1"
+- "\u62CE"
+- "\u6912"
+- "\u63E3"
+- "\u6BB7"
+- "\u63EA"
+- "\u4F3D"
+- "\u8D31"
+- "\u743C"
+- "\u83E1"
+- "\u95FA"
+- "\u662D"
+- "\u96CF"
+- "\u8E4A"
+- "\u9EDB"
+- "\u79B9"
+- "\u978D"
+- "\u4E56"
+- "\u6C5D"
+- "\u752B"
+- "\u5F5D"
+- "\u6CF8"
+- "\u8BEC"
+- "\u62FD"
+- "\u6BFD"
+- "\u6405"
+- "\u8475"
+- "\u65F1"
+- "\u52C9"
+- "\u8DF7"
+- "\u7554"
+- "\u8098"
+- "\u5742"
+- "\u6F29"
+- "\u6DA1"
+- "\u5018"
+- "\u919B"
+- "\u66E6"
+- "\u94C0"
+- "\u674F"
+- "\u68D5"
+- "\u5E7D"
+- "\u88F4"
+- "\u962E"
+- "\u6577"
+- "\u8304"
+- "\u6CA7"
+- "\u527D"
+- "\u6073"
+- "\u6DF3"
+- "\u8431"
+- "\u88B1"
+- "\u4EA5"
+- "\u75F1"
+- "\u8154"
+- "\u5AC9"
+- "\u7CB9"
+- "\u710A"
+- "\u8BC0"
+- "\u7CAA"
+- "\u6714"
+- "\u9EEF"
+- "\u8C1C"
+- "\u7728"
+- "\u7941"
+- "\u66A7"
+- "\u9B41"
+- "\u8F97"
+- "\u7A57"
+- "\u5026"
+- "\u527F"
+- "\u888D"
+- "\u606D"
+- "\u7099"
+- "\u5A34"
+- "\u73AB"
+- "\u950F"
+- "\u718F"
+- "\u7AA5"
+- "\u5815"
+- "\u609F"
+- "\u6643"
+- "\u7F2A"
+- "\u9A7F"
+- "\u6CF7"
+- "\u96C0"
+- "\u60EB"
+- "\u73BA"
+- "\u5243"
+- "\u6590"
+- "\u8882"
+- "\u68AD"
+- "\u54C4"
+- "\u90AA"
+- "\u5C82"
+- "\u817B"
+- "\u5AE9"
+- "\u6995"
+- "\u8C34"
+- "\u6F47"
+- "\u7EAC"
+- "\u4FAE"
+- "\u7FC5"
+- "\u9576"
+- "\u5777"
+- "\u5F6A"
+- "\u7977"
+- "\u531D"
+- "\u803D"
+- "\u841D"
+- "\u7A91"
+- "\u747E"
+- "\u6EE4"
+- "\u62F1"
+- "\u54E8"
+- "\u8822"
+- "\u90A2"
+- "\u6D9E"
+- "\u6064"
+- "\u6CFE"
+- "\u8C24"
+- "\u7011"
+- "\u8236"
+- "\u61C8"
+- "\u5FF1"
+- "\u70F9"
+- "\u665F"
+- "\u8E1E"
+- "\u5241"
+- "\u73C9"
+- "\u5E9A"
+- "\u6664"
+- "\u58F6"
+- "\u783E"
+- "\u55C5"
+- "\u5992"
+- "\u5308"
+- "\u80F0"
+- "\u7EEF"
+- "\u837C"
+- "\u722A"
+- "\u831C"
+- "\u6866"
+- "\u8707"
+- "\u829C"
+- "\u7384"
+- "\u846B"
+- "\u8682"
+- "\u7ECA"
+- "\u6401"
+- "\u970F"
+- "\u7C98"
+- "\u4F5F"
+- "\u96CD"
+- "\u57AE"
+- "\u7F81"
+- "\u5A25"
+- "\u78B1"
+- "\u78F7"
+- "\u948A"
+- "\u6BD9"
+- "\u8BFF"
+- "\u7EF8"
+- "\u634F"
+- "\u9074"
+- "\u754A"
+- "\u53AE"
+- "\u5DEB"
+- "\u7316"
+- "\u7357"
+- "\u63B4"
+- "\u8F8D"
+- "\u8721"
+- "\u8D63"
+- "\u7B75"
+- "\u8299"
+- "\u849C"
+- "\u7F06"
+- "\u4FEA"
+- "\u9E70"
+- "\u7B0B"
+- "\u6BCB"
+- "\u5586"
+- "\u9E6D"
+- "\u8774"
+- "\u6C40"
+- "\u8BFD"
+- "\u6854"
+- "\u7BF7"
+- "\u83BD"
+- "\u6816"
+- "\u996A"
+- "\u4F3A"
+- "\u6233"
+- "\u8C0A"
+- "\u9704"
+- "\u4F84"
+- "\u6ED4"
+- "\u778E"
+- "\u76B1"
+- "\u86DF"
+- "\u88D4"
+- "\u70FD"
+- "\u733F"
+- "\u53EE"
+- "\u7EF7"
+- "\u817A"
+- "\u66A8"
+- "\u6CA5"
+- "\u55A7"
+- "\u56E4"
+- "\u63A0"
+- "\u9661"
+- "\u81BA"
+- "\u75D2"
+- "\u9975"
+- "\u620E"
+- "\u891A"
+- "\u4E10"
+- "\u6E24"
+- "\u5E1C"
+- "\u5A04"
+- "\u6D3C"
+- "\u7984"
+- "\u5A75"
+- "\u7422"
+- "\u8EAF"
+- "\u79BA"
+- "\u5CD9"
+- "\u8E39"
+- "\u601C"
+- "\u7096"
+- "\u5250"
+- "\u7F1A"
+- "\u8944"
+- "\u67AB"
+- "\u7EFD"
+- "\u5EBE"
+- "\u65A7"
+- "\u7A74"
+- "\u5BC7"
+- "\u8747"
+- "\u97AD"
+- "\u960E"
+- "\u77E2"
+- "\u7CD9"
+- "\u5DCD"
+- "\u84BF"
+- "\u6B92"
+- "\u86F0"
+- "\u56E7"
+- "\u535C"
+- "\u5B99"
+- "\u73EE"
+- "\u9E26"
+- "\u749E"
+- "\u7FDF"
+- "\u9157"
+- "\u8912"
+- "\u8C41"
+- "\u9551"
+- "\u8037"
+- "\u68E0"
+- "\u57A6"
+- "\u97EC"
+- "\u836B"
+- "\u7AA8"
+- "\u9E3D"
+- "\u7FB2"
+- "\u61D2"
+- "\u8EAC"
+- "\u5315"
+- "\u7280"
+- "\u543C"
+- "\u73C0"
+- "\u6619"
+- "\u6A31"
+- "\u8E7F"
+- "\u6289"
+- "\u82CD"
+- "\u6C5B"
+- "\u94C9"
+- "\u9549"
+- "\u5594"
+- "\u90AF"
+- "\u90F8"
+- "\u5671"
+- "\u74EF"
+- "\u6CBC"
+- "\u637B"
+- "\u82EF"
+- "\u8E7C"
+- "\u9E8B"
+- "\u9600"
+- "\u715E"
+- "\u8E1D"
+- "\u7F2D"
+- "\u83CA"
+- "\u7AFA"
+- "\u5CED"
+- "\u6525"
+- "\u7656"
+- "\u809B"
+- "\u6CD4"
+- "\u62EF"
+- "\u7A9F"
+- "\u9773"
+- "\u8235"
+- "\u5631"
+- "\u6631"
+- "\u52FA"
+- "\u543E"
+- "\u4E2B"
+- "\u89C5"
+- "\u9187"
+- "\u78CB"
+- "\u5F99"
+- "\u9668"
+- "\u60FA"
+- "\u6E0D"
+- "\u70AC"
+- "\u683D"
+- "\u664F"
+- "\u9882"
+- "\u5974"
+- "\u6994"
+- "\u9A6D"
+- "\u56BC"
+- "\u8D61"
+- "\u8C5A"
+- "\u8537"
+- "\u6893"
+- "\u68A7"
+- "\u54FD"
+- "\u6657"
+- "\u6C5E"
+- "\u5AE3"
+- "\u854A"
+- "\u797A"
+- "\u75B9"
+- "\u58F9"
+- "\u566C"
+- "\u7682"
+- "\u77D7"
+- "\u609A"
+- "\u61A7"
+- "\u61AC"
+- "\u62F7"
+- "\u6241"
+- "\u5ED3"
+- "\u8E74"
+- "\u5C9A"
+- "\u745B"
+- "\u5D34"
+- "\u6817"
+- "\u56DA"
+- "\u6DBF"
+- "\u7901"
+- "\u6654"
+- "\u6BA1"
+- "\u7480"
+- "\u6DDE"
+- "\u968B"
+- "\u8E35"
+- "\u94B5"
+- "\u714A"
+- "\u8D58"
+- "\u77A7"
+- "\u5BDE"
+- "\u964B"
+- "\u9AB7"
+- "\u9AC5"
+- "\u79F8"
+- "\u79C6"
+- "\u592F"
+- "\u8354"
+- "\u8941"
+- "\u8913"
+- "\u7B28"
+- "\u6CAE"
+- "\u7785"
+- "\u6002"
+- "\u8317"
+- "\u7525"
+- "\u4E9F"
+- "\u6773"
+- "\u7166"
+- "\u631A"
+- "\u68F5"
+- "\u7960"
+- "\u55EF"
+- "\u6795"
+- "\u7C9F"
+- "\u6CCC"
+- "\u8700"
+- "\u5BE5"
+- "\u9050"
+- "\u6D9D"
+- "\u8FAB"
+- "\u7C41"
+- "\u7A8D"
+- "\u804B"
+- "\u900D"
+- "\u8DE4"
+- "\u51F9"
+- "\u91DC"
+- "\u5600"
+- "\u55D2"
+- "\u6DDD"
+- "\u85DC"
+- "\u7FF1"
+- "\u785A"
+- "\u53FC"
+- "\u75F9"
+- "\u817C"
+- "\u8146"
+- "\u4F0E"
+- "\u9A8B"
+- "\u6115"
+- "\u8165"
+- "\u62EE"
+- "\u8F67"
+- "\u766B"
+- "\u6A61"
+- "\u818A"
+- "\u89D1"
+- "\u5BC5"
+- "\u7812"
+- "\u8DBE"
+- "\u9890"
+- "\u6F33"
+- "\u5CE8"
+- "\u545C"
+- "\u6DC6"
+- "\u51FF"
+- "\u58D5"
+- "\u94E8"
+- "\u8386"
+- "\u7B77"
+- "\u74A7"
+- "\u8B6C"
+- "\u5C96"
+- "\u62A0"
+- "\u7B1B"
+- "\u53A5"
+- "\u783A"
+- "\u5589"
+- "\u914C"
+- "\u7C27"
+- "\u9CB8"
+- "\u8E0A"
+- "\u7261"
+- "\u5B1B"
+- "\u7F1C"
+- "\u5942"
+- "\u71B9"
+- "\u95FD"
+- "\u998A"
+- "\u80EF"
+- "\u5587"
+- "\u4F36"
+- "\u589F"
+- "\u715C"
+- "\u8018"
+- "\u69B7"
+- "\u9A81"
+- "\u7329"
+- "\u8F99"
+- "\u72F8"
+- "\u6ED5"
+- "\u8BF5"
+- "\u7A92"
+- "\u604D"
+- "\u9AE6"
+- "\u8BEB"
+- "\u69A8"
+- "\u71A0"
+- "\u853A"
+- "\u85AF"
+- "\u6B46"
+- "\u7CA4"
+- "\u592D"
+- "\u62CC"
+- "\u550F"
+- "\u5384"
+- "\u541D"
+- "\u7737"
+- "\u5CEA"
+- "\u62D9"
+- "\u548E"
+- "\u7CA5"
+- "\u75F0"
+- "\u7405"
+- "\u7F9A"
+- "\u8398"
+- "\u61A8"
+- "\u77B0"
+- "\u7085"
+- "\u5B5C"
+- "\u4EA2"
+- "\u7F2E"
+- "\u712F"
+- "\u5484"
+- "\u6687"
+- "\u77EE"
+- "\u6C72"
+- "\u7076"
+- "\u95F0"
+- "\u595A"
+- "\u6C76"
+- "\u73F2"
+- "\u9E93"
+- "\u618B"
+- "\u5D02"
+- "\u9573"
+- "\u6B83"
+- "\u5349"
+- "\u8BE7"
+- "\u77E3"
+- "\u5C4E"
+- "\u8046"
+- "\u828B"
+- "\u5C51"
+- "\u7F42"
+- "\u7C7D"
+- "\u7EDA"
+- "\u535E"
+- "\u6789"
+- "\u6C55"
+- "\u61CB"
+- "\u5AB2"
+- "\u5567"
+- "\u63A3"
+- "\u5B09"
+- "\u4EE8"
+- "\u59EC"
+- "\u61FF"
+- "\u9985"
+- "\u80FA"
+- "\u6482"
+- "\u776B"
+- "\u86D0"
+- "\u8403"
+- "\u7708"
+- "\u98DA"
+- "\u6BD3"
+- "\u6D85"
+- "\u663C"
+- "\u6A71"
+- "\u9A7C"
+- "\u6DA0"
+- "\u8C29"
+- "\u5A76"
+- "\u819B"
+- "\u62C4"
+- "\u7EE3"
+- "\u6805"
+- "\u90AC"
+- "\u6020"
+- "\u9119"
+- "\u54C9"
+- "\u8DFA"
+- "\u5E18"
+- "\u6C93"
+- "\u6400"
+- "\u814C"
+- "\u7FBF"
+- "\u6CF5"
+- "\u911E"
+- "\u90E1"
+- "\u70C3"
+- "\u611A"
+- "\u8559"
+- "\u57A4"
+- "\u950C"
+- "\u67E0"
+- "\u6AAC"
+- "\u8471"
+- "\u57A2"
+- "\u532E"
+- "\u5366"
+- "\u61CA"
+- "\u63BA"
+- "\u53F1"
+- "\u576F"
+- "\u7CEF"
+- "\u8986"
+- "\u94C6"
+- "\u742C"
+- "\u62A1"
+- "\u6F62"
+- "\u68FA"
+- "\u587E"
+- "\u98D3"
+- "\u8BC5"
+- "\u7FE9"
+- "\u63CD"
+- "\u6A80"
+- "\u9CDD"
+- "\u8BAA"
+- "\u7194"
+- "\u675E"
+- "\u5543"
+- "\u6600"
+- "\u7D0A"
+- "\u6556"
+- "\u7490"
+- "\u8517"
+- "\u69CC"
+- "\u94D0"
+- "\u6421"
+- "\u78D0"
+- "\u5B95"
+- "\u6813"
+- "\u53ED"
+- "\u621F"
+- "\u9877"
+- "\u6FD2"
+- "\u7AA6"
+- "\u6441"
+- "\u4FD0"
+- "\u77B3"
+- "\u8695"
+- "\u9E4A"
+- "\u8FC2"
+- "\u757F"
+- "\u74E3"
+- "\u5A9E"
+- "\u5BDD"
+- "\u8E66"
+- "\u55D1"
+- "\u8892"
+- "\u6B89"
+- "\u7A1A"
+- "\u4FD8"
+- "\u642A"
+- "\u6CBD"
+- "\u5983"
+- "\u55D3"
+- "\u80EB"
+- "\u753A"
+- "\u83B4"
+- "\u82E3"
+- "\u75D8"
+- "\u8511"
+- "\u7696"
+- "\u679E"
+- "\u5FD0"
+- "\u5FD1"
+- "\u9774"
+- "\u83C1"
+- "\u59E5"
+- "\u8BD9"
+- "\u56B7"
+- "\u7109"
+- "\u6CA3"
+- "\u9739"
+- "\u96F3"
+- "\u50DA"
+- "\u5C27"
+- "\u560E"
+- "\u8BE9"
+- "\u54AB"
+- "\u67EC"
+- "\u60EE"
+- "\u72C4"
+- "\u5300"
+- "\u88C6"
+- "\u9ECF"
+- "\u91C9"
+- "\u81B3"
+- "\u6E3A"
+- "\u82DF"
+- "\u7476"
+- "\u553E"
+- "\u7620"
+- "\u8BA7"
+- "\u7766"
+- "\u5F26"
+- "\u5E87"
+- "\u8884"
+- "\u5669"
+- "\u627C"
+- "\u621B"
+- "\u7980"
+- "\u607F"
+- "\u6EC1"
+- "\u9EBE"
+- "\u7B71"
+- "\u7600"
+- "\u892A"
+- "\u69DF"
+- "\u7F28"
+- "\u7ED2"
+- "\u72B7"
+- "\u8338"
+- "\u60CB"
+- "\u55E4"
+- "\u5BEE"
+- "\u8902"
+- "\u54B3"
+- "\u7F00"
+- "\u8C19"
+- "\u6DA7"
+- "\u70BD"
+- "\u7F04"
+- "\u9E5C"
+- "\u780C"
+- "\u8D2E"
+- "\u5EB5"
+- "\u96A7"
+- "\u5364"
+- "\u8DC6"
+- "\u768B"
+- "\u8757"
+- "\u6D31"
+- "\u572A"
+- "\u9091"
+- "\u9504"
+- "\u835F"
+- "\u6E1A"
+- "\u82C7"
+- "\u5B70"
+- "\u9E43"
+- "\u54FC"
+- "\u5443"
+- "\u741B"
+- "\u75E3"
+- "\u6479"
+- "\u75FC"
+- "\u956F"
+- "\u5201"
+- "\u79E7"
+- "\u8169"
+- "\u9CDE"
+- "\u4E4D"
+- "\u989A"
+- "\u6177"
+- "\u6C13"
+- "\u60E6"
+- "\u5351"
+- "\u631D"
+- "\u71A8"
+- "\u6FEE"
+- "\u80F3"
+- "\u74E2"
+- "\u7830"
+- "\u6EA7"
+- "\u9537"
+- "\u9E20"
+- "\u7292"
+- "\u59DD"
+- "\u8E44"
+- "\u5BB8"
+- "\u4FA5"
+- "\u952D"
+- "\u4F76"
+- "\u6D4A"
+- "\u5A6A"
+- "\u78FA"
+- "\u54A4"
+- "\u8FE2"
+- "\u6A90"
+- "\u90BA"
+- "\u6382"
+- "\u6E32"
+- "\u568E"
+- "\u795B"
+- "\u4F22"
+- "\u53DB"
+- "\u64AE"
+- "\u752C"
+- "\u6DCC"
+- "\u701B"
+- "\u673D"
+- "\u9642"
+- "\u5E3C"
+- "\u94FF"
+- "\u9535"
+- "\u6F13"
+- "\u9A6F"
+- "\u9CA8"
+- "\u6292"
+- "\u8301"
+- "\u67FF"
+- "\u8C94"
+- "\u8C85"
+- "\u949D"
+- "\u9CC5"
+- "\u568F"
+- "\u66AE"
+- "\u745A"
+- "\u8364"
+- "\u8713"
+- "\u57A3"
+- "\u98A4"
+- "\u6EA5"
+- "\u81C3"
+- "\u622E"
+- "\u67A3"
+- "\u4F7C"
+- "\u62D7"
+- "\u54C6"
+- "\u55E6"
+- "\u60DA"
+- "\u9E25"
+- "\u501A"
+- "\u55E8"
+- "\u8238"
+- "\u8D50"
+- "\u59CA"
+- "\u6194"
+- "\u60B4"
+- "\u94F0"
+- "\u9EDD"
+- "\u5C7F"
+- "\u79C3"
+- "\u563B"
+- "\u695E"
+- "\u68F1"
+- "\u8888"
+- "\u88DF"
+- "\u6C74"
+- "\u63C9"
+- "\u9ACB"
+- "\u60B8"
+- "\u69BB"
+- "\u901E"
+- "\u667E"
+- "\u5C4C"
+- "\u95F3"
+- "\u75CA"
+- "\u889C"
+- "\u6249"
+- "\u7436"
+- "\u6452"
+- "\u637A"
+- "\u5320"
+- "\u7A88"
+- "\u7A95"
+- "\u98D2"
+- "\u732C"
+- "\u871A"
+- "\u840B"
+- "\u86AF"
+- "\u8693"
+- "\u9C9F"
+- "\u6F88"
+- "\u6A1F"
+- "\u6096"
+- "\u7396"
+- "\u4FFE"
+- "\u62BF"
+- "\u5F77"
+- "\u5F7F"
+- "\u8671"
+- "\u72D9"
+- "\u9CB6"
+- "\u69FF"
+- "\u70D8"
+- "\u630E"
+- "\u72F0"
+- "\u72DE"
+- "\u9083"
+- "\u77AA"
+- "\u4FDA"
+- "\u6D95"
+- "\u8C2C"
+- "\u776C"
+- "\u8737"
+- "\u5162"
+- "\u954D"
+- "\u7837"
+- "\u83E0"
+- "\u6026"
+- "\u51C4"
+- "\u536F"
+- "\u7352"
+- "\u6E00"
+- "\u8F98"
+- "\u6EC7"
+- "\u71CE"
+- "\u564E"
+- "\u874E"
+- "\u7DA6"
+- "\u9122"
+- "\u634E"
+- "\u77BF"
+- "\u873F"
+- "\u8712"
+- "\u79A7"
+- "\u6988"
+- "\u9539"
+- "\u6BAD"
+- "\u7235"
+- "\u76F9"
+- "\u6DD6"
+- "\u557C"
+- "\u74EE"
+- "\u9CD6"
+- "\u9556"
+- "\u73D1"
+- "\u7F79"
+- "\u6B86"
+- "\u6396"
+- "\u67DE"
+- "\u7F38"
+- "\u7EC5"
+- "\u68D8"
+- "\u7949"
+- "\u80F1"
+- "\u6B93"
+- "\u55E1"
+- "\u55F7"
+- "\u7B8D"
+- "\u5729"
+- "\u8012"
+- "\u5A55"
+- "\u8151"
+- "\u8426"
+- "\u9E5E"
+- "\u73DC"
+- "\u5575"
+- "\u7459"
+- "\u8446"
+- "\u9021"
+- "\u55FD"
+- "\u9955"
+- "\u992E"
+- "\u96BC"
+- "\u599E"
+- "\u997A"
+- "\u53E8"
+- "\u914B"
+- "\u6059"
+- "\u6CD7"
+- "\u5F29"
+- "\u9A9C"
+- "\u94CE"
+- "\u9176"
+- "\u869D"
+- "\u70C1"
+- "\u533E"
+- "\u4FAC"
+- "\u85FB"
+- "\u99A5"
+- "\u9AA5"
+- "\u69D0"
+- "\u7F15"
+- "\u693F"
+- "\u8886"
+- "\u740A"
+- "\u7A23"
+- "\u85E9"
+- "\u8FF8"
+- "\u8E42"
+- "\u8E8F"
+- "\u96BD"
+- "\u4FF8"
+- "\u90EB"
+- "\u7C38"
+- "\u7825"
+- "\u9AB8"
+- "\u63AE"
+- "\u659B"
+- "\u5578"
+- "\u748B"
+- "\u579B"
+- "\u672D"
+- "\u908B"
+- "\u9062"
+- "\u8572"
+- "\u54C7"
+- "\u78B4"
+- "\u909B"
+- "\u5D03"
+- "\u89D0"
+- "\u7B19"
+- "\u88F3"
+- "\u6CDE"
+- "\u868C"
+- "\u918D"
+- "\u9190"
+- "\u62F4"
+- "\u821C"
+- "\u6C85"
+- "\u61F5"
+- "\u8C15"
+- "\u5E1A"
+- "\u87B3"
+- "\u567C"
+- "\u556A"
+- "\u6F31"
+- "\u90DC"
+- "\u7889"
+- "\u572D"
+- "\u8C00"
+- "\u8F76"
+- "\u8200"
+- "\u5472"
+- "\u5576"
+- "\u6C1F"
+- "\u740F"
+- "\u5785"
+- "\u5A29"
+- "\u4E7E"
+- "\u93D6"
+- "\u727E"
+- "\u80AE"
+- "\u5555"
+- "\u540F"
+- "\u6D93"
+- "\u6C26"
+- "\u9525"
+- "\u684E"
+- "\u543F"
+- "\u70CA"
+- "\u659F"
+- "\u6C7E"
+- "\u5C90"
+- "\u8004"
+- "\u800B"
+- "\u55F2"
+- "\u80DB"
+- "\u759A"
+- "\u9A87"
+- "\u7663"
+- "\u78E1"
+- "\u4F91"
+- "\u6F3E"
+- "\u789A"
+- "\u7409"
+- "\u60EC"
+- "\u9041"
+- "\u8038"
+- "\u5CB1"
+- "\u7CD7"
+- "\u7F19"
+- "\u80B4"
+- "\u68B5"
+- "\u50EE"
+- "\u9E35"
+- "\u60AF"
+- "\u5B6A"
+- "\u8385"
+- "\u622C"
+- "\u9701"
+- "\u7C07"
+- "\u9035"
+- "\u501C"
+- "\u50A5"
+- "\u998B"
+- "\u84C1"
+- "\u8859"
+- "\u86C0"
+- "\u852B"
+- "\u5D27"
+- "\u541F"
+- "\u7430"
+- "\u552C"
+- "\u6E25"
+- "\u5CB7"
+- "\u4EE1"
+- "\u6D8E"
+- "\u9E33"
+- "\u9E2F"
+- "\u954A"
+- "\u59A7"
+- "\u5B37"
+- "\u5AE6"
+- "\u5AD4"
+- "\u6C90"
+- "\u4F09"
+- "\u5D9D"
+- "\u9522"
+- "\u7B50"
+- "\u8725"
+- "\u8734"
+- "\u6CF1"
+- "\u9A85"
+- "\u5406"
+- "\u64A9"
+- "\u602F"
+- "\u53E9"
+- "\u54DF"
+- "\u556C"
+- "\u5CAC"
+- "\u7B03"
+- "\u73B3"
+- "\u7441"
+- "\u909D"
+- "\u54A3"
+- "\u77DC"
+- "\u562D"
+- "\u9997"
+- "\u5A40"
+- "\u9ED4"
+- "\u951F"
+- "\u5570"
+- "\u7FCC"
+- "\u94E0"
+- "\u8C89"
+- "\u737E"
+- "\u9163"
+- "\u6963"
+- "\u4F43"
+- "\u7435"
+- "\u8306"
+- "\u7699"
+- "\u51CB"
+- "\u655D"
+- "\u5323"
+- "\u5D58"
+- "\u5B93"
+- "\u830E"
+- "\u6942"
+- "\u7AF2"
+- "\u762A"
+- "\u4F97"
+- "\u94E3"
+- "\u85B0"
+- "\u7832"
+- "\u7FA3"
+- "\u6DFC"
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+- "\u5A20"
+- "\u7F61"
+- "\u7601"
+- "\u6930"
+- "\u70D9"
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+- "\u6B9A"
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+- "\u8153"
+- "\u69AD"
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+- "\u5509"
+- "\u94EE"
+- "\u72E9"
+- "\u62A8"
+- "\u5CC1"
+- "\u7CB1"
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+- "\u53A9"
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+- "\u5429"
+- "\u5490"
+- "\u778C"
+- "\u870A"
+- "\u606C"
+- "\u8191"
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+- "\u8DC4"
+- "\u988D"
+- "\u6710"
+- "\u759D"
+- "\u6BC2"
+- "\u79E3"
+- "\u821B"
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+- "\u6F2F"
+- "\u6CE0"
+- "\u5598"
+- "\u64B5"
+- "\u72E1"
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+- "\u94C2"
+- "\u949B"
+- "\u835E"
+- "\u62ED"
+- "\u4E1E"
+- "\u6F2D"
+- "\u7ECC"
+- "\u57DC"
+- "\u63B0"
+- "\u72C8"
+- "\u951C"
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+- "\u5F1B"
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+- "\u79E4"
+- "\u705E"
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+- "\u5D5B"
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+- "\u5E44"
+- "\u988A"
+- "\u7F24"
+- "\u6726"
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+- "\u51A5"
+- "\u781D"
+- "\u9540"
+- "\u5919"
+- "\u71CA"
+- "\u835A"
+- "\u6D48"
+- "\u82E1"
+- "\u773A"
+- "\u966C"
+- "\u5BD0"
+- "\u4F58"
+- "\u6FD1"
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+- "\u6954"
+- "\u80DA"
+- "\u5D69"
+- "\u6D19"
+- "\u8BD3"
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+- "\u6D5A"
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+- "\u66F0"
+- "\u6035"
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+- "\u7A20"
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+- "\u739F"
+- "\u8934"
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+- "\u55B1"
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+- "\u561F"
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+- "\u728A"
+- "\u54CE"
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+- "\u4FFA"
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+- "\u59AF"
+- "\u5A0C"
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+- "\u86A3"
+- "\u6063"
+- "\u6C8F"
+- "\u78F4"
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+- "\u6C81"
+- "\u7583"
+- "\u6078"
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+- "\u6684"
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+- "\u60F0"
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+- "\u70B7"
+- "\u73FA"
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+- "\u8C11"
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+- "\u55EC"
+- "\u7F30"
+- "\u5372"
+- "\u58D1"
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+- "\u968D"
+- "\u5520"
+- "\u6FE1"
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+- "\u9A8A"
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+- "\u62E7"
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+- "\u690B"
+- "\u9F3E"
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+- "\u9082"
+- "\u9005"
+- "\u5984"
+- "\u9A90"
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+- "\u55B5"
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+- "\u772C"
+- "\u7EA3"
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+- "\u8983"
+- "\u5B40"
+- "\u828A"
+- "\u5B62"
+- "\u60F6"
+- "\u8FE5"
+- "\u7EB0"
+- "\u5480"
+- "\u9E3E"
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+- "\u6666"
+- "\u6CEF"
+- "\u781A"
+- "\u542D"
+- "\u7962"
+- "\u63E9"
+- "\u5228"
+- "\u73CF"
+- "\u64B8"
+- "\u5140"
+- "\u75C9"
+- "\u631B"
+- "\u80E4"
+- "\u5DFF"
+- "\u7EB6"
+- "\u9541"
+- "\u54FA"
+- "\u5494"
+- "\u5693"
+- "\u7A3C"
+- "\u7116"
+- "\u59A4"
+- "\u59A9"
+- "\u6F5E"
+- "\u96CC"
+- "\u683E"
+- "\u4F8D"
+- "\u7172"
+- "\u5ADA"
+- "\u7AFD"
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+- "\u9708"
+- "\u8D5D"
+- "\u83BA"
+- "\u7736"
+- "\u6853"
+- "\u69CE"
+- "\u9991"
+- "\u6DAE"
+- "\u67AD"
+- "\u5F87"
+- "\u6D35"
+- "\u578C"
+- "\u6635"
+- "\u8936"
+- "\u55BD"
+- "\u812F"
+- "\u5B71"
+- "\u9068"
+- "\u8C1A"
+- "\u70F7"
+- "\u643D"
+- "\u916F"
+- "\u67B7"
+- "\u6849"
+- "\u54A7"
+- "\u7ABF"
+- "\u62C8"
+- "\u6593"
+- "\u8DDB"
+- "\u8E76"
+- "\u761F"
+- "\u4FED"
+- "\u975B"
+- "\u810D"
+- <sos/eos>
+token_type: char
+train_data_path_and_name_and_type:
+- - dump/raw/train_sp/wav.scp
+  - speech
+  - kaldi_ark
+- - dump/raw/train_sp/text
+  - text
+  - text
+train_dtype: float32
+train_shape_file:
+- exp/asr_stats_raw_sp/train/speech_shape
+- exp/asr_stats_raw_sp/train/text_shape.char
+use_amp: false
+use_preprocessor: true
+val_scheduler_criterion:
+- valid
+- acc
+valid_batch_bins: null
+valid_batch_size: null
+valid_batch_type: null
+valid_data_path_and_name_and_type:
+- - dump/raw/dev/wav.scp
+  - speech
+  - kaldi_ark
+- - dump/raw/dev/text
+  - text
+  - text
+valid_max_cache_size: null
+valid_shape_file:
+- exp/asr_stats_raw_sp/valid/speech_shape
+- exp/asr_stats_raw_sp/valid/text_shape.char
+write_collected_feats: false