[debug] support flow cache, for sharper tts_mel output

cosyvoice/flow/flow.py

@@ -109,7 +109,9 @@ class MaskedDiffWithXvec(torch.nn.Module):
                   prompt_token_len,
                   prompt_feat,
                   prompt_feat_len,
-                  embedding):
+                  embedding,
+                  required_cache_size=0,
+                  flow_cache=None):
         assert token.shape[0] == 1
         # xvec projection
         embedding = F.normalize(embedding, dim=1)
@@ -133,13 +135,15 @@ class MaskedDiffWithXvec(torch.nn.Module):
         conds = conds.transpose(1, 2)
 
         mask = (~make_pad_mask(torch.tensor([mel_len1 + mel_len2]))).to(h)
-        feat = self.decoder(
+        feat, flow_cache = self.decoder(
             mu=h.transpose(1, 2).contiguous(),
             mask=mask.unsqueeze(1),
             spks=embedding,
             cond=conds,
-            n_timesteps=10
+            n_timesteps=10,
+            required_cache_size=required_cache_size,
+            flow_cache=flow_cache
         )
         feat = feat[:, :, mel_len1:]
         assert feat.shape[2] == mel_len2
-        return feat
+        return feat, flow_cache