size mismatch for seq2seq.encoder.embed_tokens.weight

[CathyW77]

Hi, when I run
python synthesis.py --preset=presets/20180505_deepvoice3_ljspeech.json pretrained_models/20180505_deepvoice3_checkpoint_step000640000.pth sentences.txt pretrained_output

error:
Command line args:
{'--checkpoint-postnet': None,
'--checkpoint-seq2seq': None,
'--file-name-suffix': '',
'--help': False,
'--hparams': '',
'--max-decoder-steps': '500',
'--output-html': False,
'--preset': 'presets/deepvoice3_vctk.json',
'--replace_pronunciation_prob': '0.0',
'--speaker_id': None,
'': 'pretrained_models/20171222_deepvoice3_vctk108_checkpoint_step000300000.pth',
'<dst_dir>': './pretrained_output',
'<text_list_file>': './sentences.txt'}
Traceback (most recent call last):
File "synthesis.py", line 130, in
model.load_state_dict(checkpoint["state_dict"])
File "/nfs/private/yanglu/zhrtvc/venv/lib/python3.6/site-packages/torch/nn/modules/module.py", line 769, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for MultiSpeakerTTSModel:
size mismatch for seq2seq.encoder.embed_tokens.weight: copying a param with shape torch.Size([149, 256]) from checkpoint, the shape in current model is torch.Size([159, 256]).

it also comes out when I run :
python synthesis.py --preset=presets/deepvoice3_vctk.json pretrained_models/20171222_deepvoice3_vctk108_checkpoint_step000300000.pth sentences.txt pretrained_output
Command line args:
{'--checkpoint-postnet': None,
'--checkpoint-seq2seq': None,
'--file-name-suffix': '',
'--help': False,
'--hparams': '',
'--max-decoder-steps': '500',
'--output-html': False,
'--preset': 'presets/deepvoice3_vctk.json',
'--replace_pronunciation_prob': '0.0',
'--speaker_id': None,
'': 'pretrained_models/20171222_deepvoice3_vctk108_checkpoint_step000300000.pth',
'<dst_dir>': 'pretrained_output',
'<text_list_file>': 'sentences.txt'}
Traceback (most recent call last):
File "synthesis.py", line 130, in
model.load_state_dict(checkpoint["state_dict"])
File "/nfs/private/yanglu/zhrtvc/venv/lib/python3.6/site-packages/torch/nn/modules/module.py", line 769, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for MultiSpeakerTTSModel:
size mismatch for seq2seq.encoder.embed_tokens.weight: copying a param with shape torch.Size([149, 256]) from checkpoint, the shape in current model is torch.Size([159, 256]).

[ymzlygw]

Hi, when I run
python synthesis.py --preset=presets/20180505_deepvoice3_ljspeech.json pretrained_models/20180505_deepvoice3_checkpoint_step000640000.pth sentences.txt pretrained_output

error:
Command line args:
{'--checkpoint-postnet': None,
'--checkpoint-seq2seq': None,
'--file-name-suffix': '',
'--help': False,
'--hparams': '',
'--max-decoder-steps': '500',
'--output-html': False,
'--preset': 'presets/deepvoice3_vctk.json',
'--replace_pronunciation_prob': '0.0',
'--speaker_id': None,
'': 'pretrained_models/20171222_deepvoice3_vctk108_checkpoint_step000300000.pth',
'<dst_dir>': './pretrained_output',
'<text_list_file>': './sentences.txt'}
Traceback (most recent call last):
File "synthesis.py", line 130, in
model.load_state_dict(checkpoint["state_dict"])
File "/nfs/private/yanglu/zhrtvc/venv/lib/python3.6/site-packages/torch/nn/modules/module.py", line 769, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for MultiSpeakerTTSModel:
size mismatch for seq2seq.encoder.embed_tokens.weight: copying a param with shape torch.Size([149, 256]) from checkpoint, the shape in current model is torch.Size([159, 256]).

it also comes out when I run :
python synthesis.py --preset=presets/deepvoice3_vctk.json pretrained_models/20171222_deepvoice3_vctk108_checkpoint_step000300000.pth sentences.txt pretrained_output
Command line args:
{'--checkpoint-postnet': None,
'--checkpoint-seq2seq': None,
'--file-name-suffix': '',
'--help': False,
'--hparams': '',
'--max-decoder-steps': '500',
'--output-html': False,
'--preset': 'presets/deepvoice3_vctk.json',
'--replace_pronunciation_prob': '0.0',
'--speaker_id': None,
'': 'pretrained_models/20171222_deepvoice3_vctk108_checkpoint_step000300000.pth',
'<dst_dir>': 'pretrained_output',
'<text_list_file>': 'sentences.txt'}
Traceback (most recent call last):
File "synthesis.py", line 130, in
model.load_state_dict(checkpoint["state_dict"])
File "/nfs/private/yanglu/zhrtvc/venv/lib/python3.6/site-packages/torch/nn/modules/module.py", line 769, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for MultiSpeakerTTSModel:
size mismatch for seq2seq.encoder.embed_tokens.weight: copying a param with shape torch.Size([149, 256]) from checkpoint, the shape in current model is torch.Size([159, 256]).

Hey, try don't use --preset params or change the correspond params in preset.

[CathyW77]

@ymzlygw Hi, I have tried
python synthesis.py pretrained_models/20180505_deepvoice3_checkpoint_step000640000.pth sentences.txt pretrained_output

still went error
File "synthesis.py", line 130, in
model.load_state_dict(checkpoint["state_dict"])
File "/nfs/private/yanglu/zhrtvc/venv/lib/python3.6/site-packages/torch/nn/modules/module.py", line 769, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for MultiSpeakerTTSModel:
size mismatch for seq2seq.encoder.embed_tokens.weight: copying a param with shape torch.Size([149, 128]) from checkpoint, the shape in current model is torch.Size([159, 128]).