add submodule

cosyvoice/bin/train.py

@@ -75,8 +75,7 @@ def get_args():
     parser.add_argument('--timeout',
                         default=30,
                         type=int,
-                        help='timeout (in seconds) of cosyvoice_join. ' +
-                        '30s for aishell & 300s for wenetspeech')
+                        help='timeout (in seconds) of cosyvoice_join.')
     parser = deepspeed.add_config_arguments(parser)
     args = parser.parse_args()
     return args

cosyvoice/transformer/attention.py

@@ -152,7 +152,7 @@ class MultiHeadedAttention(nn.Module):
                 4.If the different position in decoder see different block
                 of the encoder, such as Mocha, the passed in mask could be
                 in (#batch, L, T) shape. But there is no such case in current
-                Wenet.
+                CosyVoice.
             cache (torch.Tensor): Cache tensor (1, head, cache_t, d_k * 2),
                 where `cache_t == chunk_size * num_decoding_left_chunks`
                 and `head * d_k == size`