text stringlengths 1 93.6k |
|---|
's_two_hop_feat': s_two_hop_feat,
|
't_self_feat': t_self_feat,
|
't_one_hop_feat': t_one_hop_feat,
|
't_two_hop_feat': t_two_hop_feat,
|
'neg_his_times_list': neg_his_times_list,
|
'neg_his_his_times_list': neg_his_his_times_list,
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'neg_self_feat': neg_self_feat,
|
'neg_one_hop_feat': neg_one_hop_feat,
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'neg_two_hop_feat': neg_two_hop_feat,
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's_edge_rate': s_edge_rate,
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}
|
if self.transform:
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sample = self.transform(sample)
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return sample
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def negative_sampling(self):
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rand_idx = np.random.randint(0, self.neg_table_size, (self.neg_size,))
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sampled_nodes = self.neg_table[rand_idx]
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return sampled_nodes
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# <FILESEP>
|
import os
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import argparse
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from tqdm import tqdm
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from random import shuffle
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import json
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config_template = {
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"train": {
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"log_interval": 200,
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"eval_interval": 1000,
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"seed": 1234,
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"epochs": 10000,
|
"learning_rate": 1e-4,
|
"betas": [0.8, 0.99],
|
"eps": 1e-9,
|
"batch_size": 12,
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"fp16_run": False,
|
"lr_decay": 0.999875,
|
"segment_size": 17920,
|
"init_lr_ratio": 1,
|
"warmup_epochs": 0,
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"c_mel": 45,
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"c_kl": 1.0,
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"use_sr": True,
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"max_speclen": 384,
|
"port": "8001"
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},
|
"data": {
|
"training_files":"filelists/train.txt",
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"validation_files":"filelists/val.txt",
|
"max_wav_value": 32768.0,
|
"sampling_rate": 32000,
|
"filter_length": 1280,
|
"hop_length": 320,
|
"win_length": 1280,
|
"n_mel_channels": 80,
|
"mel_fmin": 0.0,
|
"mel_fmax": None
|
},
|
"model": {
|
"inter_channels": 192,
|
"hidden_channels": 192,
|
"filter_channels": 768,
|
"n_heads": 2,
|
"n_layers": 6,
|
"kernel_size": 3,
|
"p_dropout": 0.1,
|
"resblock": "1",
|
"resblock_kernel_sizes": [3,7,11],
|
"resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]],
|
"upsample_rates": [10,8,2,2],
|
"upsample_initial_channel": 512,
|
"upsample_kernel_sizes": [16,16,4,4],
|
"n_layers_q": 3,
|
"use_spectral_norm": False,
|
"gin_channels": 256,
|
"ssl_dim": 256,
|
"n_speakers": 0,
|
},
|
"spk":{
|
"nen": 0,
|
"paimon": 1,
|
"yunhao": 2
|
}
|
}
|
if __name__ == "__main__":
|
parser = argparse.ArgumentParser()
|
parser.add_argument("--train_list", type=str, default="./filelists/train.txt", help="path to train list")
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parser.add_argument("--val_list", type=str, default="./filelists/val.txt", help="path to val list")
|
parser.add_argument("--test_list", type=str, default="./filelists/test.txt", help="path to test list")
|
parser.add_argument("--source_dir", type=str, default="./dataset/32k", help="path to source dir")
|
args = parser.parse_args()
|
train = []
|
val = []
|
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