fix fastspeech2 multi speaker to static, test=tts

examples/aishell3/tts3/README.md

@@ -257,6 +257,7 @@ python3 ${BIN_DIR}/../synthesize_e2e.py \
   --output_dir=exp/default/test_e2e \
   --phones_dict=fastspeech2_nosil_aishell3_ckpt_0.4/phone_id_map.txt \
   --speaker_dict=fastspeech2_nosil_aishell3_ckpt_0.4/speaker_id_map.txt \
-  --spk_id=0
+  --spk_id=0 \
+  --inference_dir=exp/default/inference
 
 ```

examples/aishell3/tts3/local/synthesize_e2e.sh

@@ -20,4 +20,5 @@ python3 ${BIN_DIR}/../synthesize_e2e.py \
     --output_dir=${train_output_path}/test_e2e \
     --phones_dict=dump/phone_id_map.txt \
     --speaker_dict=dump/speaker_id_map.txt \
-    --spk_id=0
+    --spk_id=0 \
+    --inference_dir=${train_output_path}/inference

examples/vctk/tts3/README.md

@@ -240,13 +240,14 @@ python3 ${BIN_DIR}/../synthesize_e2e.py \
   --am_ckpt=fastspeech2_nosil_vctk_ckpt_0.5/snapshot_iter_66200.pdz \
   --am_stat=fastspeech2_nosil_vctk_ckpt_0.5/speech_stats.npy \
   --voc=pwgan_vctk \
-  --voc_config=pwg_vctk_ckpt_0.5/pwg_default.yaml  \
-  --voc_ckpt=pwg_vctk_ckpt_0.5/pwg_snapshot_iter_1000000.pdz \
-  --voc_stat=pwg_vctk_ckpt_0.5/pwg_stats.npy \
+  --voc_config=pwg_vctk_ckpt_0.1.1/default.yaml  \
+  --voc_ckpt=pwg_vctk_ckpt_0.1.1/snapshot_iter_1500000.pdz \
+  --voc_stat=pwg_vctk_ckpt_0.1.1/feats_stats.npy \
   --lang=en \
   --text=${BIN_DIR}/../sentences_en.txt \
   --output_dir=exp/default/test_e2e \
   --phones_dict=fastspeech2_nosil_vctk_ckpt_0.5/phone_id_map.txt \
   --speaker_dict=fastspeech2_nosil_vctk_ckpt_0.5/speaker_id_map.txt \
-  --spk_id=0
+  --spk_id=0 \
+  --inference_dir=exp/default/inference
 ```

examples/vctk/tts3/local/synthesize_e2e.sh

@@ -20,4 +20,5 @@ python3 ${BIN_DIR}/../synthesize_e2e.py \
     --output_dir=${train_output_path}/test_e2e \
     --phones_dict=dump/phone_id_map.txt \
     --speaker_dict=dump/speaker_id_map.txt \
-    --spk_id=0
+    --spk_id=0 \
+    --inference_dir=${train_output_path}/inference

paddlespeech/t2s/exps/inference.py

@@ -14,9 +14,11 @@
 import argparse
 from pathlib import Path
 
+import numpy
 import soundfile as sf
 from paddle import inference
 
+from paddlespeech.t2s.frontend import English
 from paddlespeech.t2s.frontend.zh_frontend import Frontend
 
 
@@ -29,20 +31,38 @@ def main():
         '--am',
         type=str,
         default='fastspeech2_csmsc',
-        choices=['speedyspeech_csmsc', 'fastspeech2_csmsc'],
+        choices=[
+            'speedyspeech_csmsc', 'fastspeech2_csmsc', 'fastspeech2_aishell3',
+            'fastspeech2_vctk'
+        ],
         help='Choose acoustic model type of tts task.')
     parser.add_argument(
         "--phones_dict", type=str, default=None, help="phone vocabulary file.")
     parser.add_argument(
         "--tones_dict", type=str, default=None, help="tone vocabulary file.")
+    parser.add_argument(
+        "--speaker_dict", type=str, default=None, help="speaker id map file.")
+    parser.add_argument(
+        '--spk_id',
+        type=int,
+        default=0,
+        help='spk id for multi speaker acoustic model')
     # voc
     parser.add_argument(
         '--voc',
         type=str,
         default='pwgan_csmsc',
-        choices=['pwgan_csmsc', 'mb_melgan_csmsc', 'hifigan_csmsc'],
+        choices=[
+            'pwgan_csmsc', 'mb_melgan_csmsc', 'hifigan_csmsc', 'pwgan_aishell3',
+            'pwgan_vctk'
+        ],
         help='Choose vocoder type of tts task.')
     # other
+    parser.add_argument(
+        '--lang',
+        type=str,
+        default='zh',
+        help='Choose model language. zh or en')
     parser.add_argument(
         "--text",
         type=str,
@@ -53,8 +73,12 @@ def main():
 
     args, _ = parser.parse_known_args()
 
+    # frontend
+    if args.lang == 'zh':
         frontend = Frontend(
             phone_vocab_path=args.phones_dict, tone_vocab_path=args.tones_dict)
+    elif args.lang == 'en':
+        frontend = English(phone_vocab_path=args.phones_dict)
     print("frontend done!")
 
     # model: {model_name}_{dataset}
@@ -83,30 +107,52 @@ def main():
 
     print("in new inference")
 
+    # construct dataset for evaluation
+    sentences = []
     with open(args.text, 'rt') as f:
         for line in f:
             items = line.strip().split()
             utt_id = items[0]
+            if args.lang == 'zh':
                 sentence = "".join(items[1:])
+            elif args.lang == 'en':
+                sentence = " ".join(items[1:])
             sentences.append((utt_id, sentence))
 
     get_tone_ids = False
     if am_name == 'speedyspeech':
         get_tone_ids = True
+    if am_dataset in {"aishell3", "vctk"} and args.speaker_dict:
+        get_spk_id = True
+        spk_id = numpy.array([args.spk_id])
 
     am_input_names = am_predictor.get_input_names()
-
+    print("am_input_names:", am_input_names)
+    merge_sentences = True
     for utt_id, sentence in sentences:
+        if args.lang == 'zh':
+            input_ids = frontend.get_input_ids(
+                sentence,
+                merge_sentences=merge_sentences,
+                get_tone_ids=get_tone_ids)
+            phone_ids = input_ids["phone_ids"]
+        elif args.lang == 'en':
             input_ids = frontend.get_input_ids(
-            sentence, merge_sentences=True, get_tone_ids=get_tone_ids)
+                sentence, merge_sentences=merge_sentences)
             phone_ids = input_ids["phone_ids"]
+        else:
+            print("lang should in {'zh', 'en'}!")
+
         if get_tone_ids:
             tone_ids = input_ids["tone_ids"]
             tones = tone_ids[0].numpy()
             tones_handle = am_predictor.get_input_handle(am_input_names[1])
             tones_handle.reshape(tones.shape)
             tones_handle.copy_from_cpu(tones)
-
+        if get_spk_id:
+            spk_id_handle = am_predictor.get_input_handle(am_input_names[1])
+            spk_id_handle.reshape(spk_id.shape)
+            spk_id_handle.copy_from_cpu(spk_id)
         phones = phone_ids[0].numpy()
         phones_handle = am_predictor.get_input_handle(am_input_names[0])
         phones_handle.reshape(phones.shape)

paddlespeech/t2s/exps/synthesize_e2e.py

@@ -159,9 +159,16 @@ def evaluate(args):
         # acoustic model
         if am_name == 'fastspeech2':
             if am_dataset in {"aishell3", "vctk"} and args.speaker_dict:
-                print(
-                    "Haven't test dygraph to static for multi speaker fastspeech2 now!"
-                )
+                am_inference = jit.to_static(
+                    am_inference,
+                    input_spec=[
+                        InputSpec([-1], dtype=paddle.int64),
+                        InputSpec([1], dtype=paddle.int64)
+                    ])
+                paddle.jit.save(am_inference,
+                                os.path.join(args.inference_dir, args.am))
+                am_inference = paddle.jit.load(
+                    os.path.join(args.inference_dir, args.am))
             else:
                 am_inference = jit.to_static(
                     am_inference,

paddlespeech/t2s/models/fastspeech2/fastspeech2.py

@@ -781,7 +781,7 @@ class FastSpeech2(nn.Layer):
         elif self.spk_embed_integration_type == "concat":
             # concat hidden states with spk embeds and then apply projection
             spk_emb = F.normalize(spk_emb).unsqueeze(1).expand(
-                shape=[-1, hs.shape[1], -1])
+                shape=[-1, paddle.shape(hs)[1], -1])
             hs = self.spk_projection(paddle.concat([hs, spk_emb], axis=-1))
         else:
             raise NotImplementedError("support only add or concat.")