fix error in tts/st

paddlespeech/cli/st/infer.py

@@ -252,7 +252,7 @@ class STExecutor(BaseExecutor):
             norm_feat = dict(kaldiio.load_ark(process.stdout))[utt_name]
             self._inputs["audio"] = paddle.to_tensor(norm_feat).unsqueeze(0)
             self._inputs["audio_len"] = paddle.to_tensor(
-                self._inputs["audio"].shape[1], dtype="int64")
+                self._inputs["audio"].shape[1:2], dtype="int64")
         else:
             raise ValueError("Wrong model type.")
 

paddlespeech/cli/tts/infer.py

@@ -491,7 +491,7 @@ class TTSExecutor(BaseExecutor):
                 # multi speaker
                 if am_dataset in {'aishell3', 'vctk', 'mix', 'canton'}:
                     mel = self.am_inference(
-                        part_phone_ids, spk_id=paddle.to_tensor(spk_id))
+                        part_phone_ids, spk_id=paddle.to_tensor([spk_id]))
                 else:
                     mel = self.am_inference(part_phone_ids)
             self.am_time += (time.time() - am_st)

paddlespeech/t2s/models/fastspeech2/fastspeech2.py

@@ -783,7 +783,7 @@ class FastSpeech2(nn.Layer):
         x = paddle.cast(text, 'int64')
         d, p, e = durations, pitch, energy
         # setup batch axis
-        ilens = paddle.shape(x)[0]
+        ilens = paddle.shape(x)[0:1]
 
         xs = x.unsqueeze(0)
 

paddlespeech/t2s/modules/nets_utils.py

@@ -181,7 +181,7 @@ def make_pad_mask(lengths, xs=None, length_dim=-1):
     if length_dim == 0:
         raise ValueError("length_dim cannot be 0: {}".format(length_dim))
 
-    bs = paddle.shape(lengths)[0]
+    bs = paddle.shape(lengths)
     if xs is None:
         maxlen = paddle.cast(lengths.max(), dtype=bs.dtype)
     else: