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Merge branch 'master' of github.com:marcoyang1998/icefall into train_rnnlm

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This commit is contained in:
marcoyang 2023-09-22 17:11:20 +08:00
commit b984fb1b43
36 changed files with 81 additions and 2 deletions
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1
egs/aishell/ASR/pruned_transducer_stateless7/export-onnx.py
View File

@ -322,6 +322,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

3
egs/aishell/ASR/pruned_transducer_stateless7/onnx_pretrained.py
View File

@ -151,12 +151,14 @@ class OnnxModel:
self.encoder = ort.InferenceSession(
encoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
def init_decoder(self, decoder_model_filename: str):
self.decoder = ort.InferenceSession(
decoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
decoder_meta = self.decoder.get_modelmeta().custom_metadata_map
@ -170,6 +172,7 @@ class OnnxModel:
self.joiner = ort.InferenceSession(
joiner_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
joiner_meta = self.joiner.get_modelmeta().custom_metadata_map

1
egs/commonvoice/ASR/pruned_transducer_stateless7/export-onnx.py
View File

@ -330,6 +330,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

3
egs/commonvoice/ASR/pruned_transducer_stateless7/onnx_pretrained.py
View File

@ -152,12 +152,14 @@ class OnnxModel:
self.encoder = ort.InferenceSession(
encoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
def init_decoder(self, decoder_model_filename: str):
self.decoder = ort.InferenceSession(
decoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
decoder_meta = self.decoder.get_modelmeta().custom_metadata_map
@ -171,6 +173,7 @@ class OnnxModel:
self.joiner = ort.InferenceSession(
joiner_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
joiner_meta = self.joiner.get_modelmeta().custom_metadata_map

1
egs/librispeech/ASR/conv_emformer_transducer_stateless2/export-onnx.py
View File

@ -401,6 +401,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

3
egs/librispeech/ASR/conv_emformer_transducer_stateless2/onnx_pretrained.py
View File

@ -136,6 +136,7 @@ class OnnxModel:
self.encoder = ort.InferenceSession(
encoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
self.init_encoder_states()
@ -184,6 +185,7 @@ class OnnxModel:
self.decoder = ort.InferenceSession(
decoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
decoder_meta = self.decoder.get_modelmeta().custom_metadata_map
@ -197,6 +199,7 @@ class OnnxModel:
self.joiner = ort.InferenceSession(
joiner_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
joiner_meta = self.joiner.get_modelmeta().custom_metadata_map

1
egs/librispeech/ASR/lstm_transducer_stateless2/export-onnx-zh.py
View File

@ -359,6 +359,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

1
egs/librispeech/ASR/lstm_transducer_stateless2/export-onnx.py
View File

@ -356,6 +356,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

3
egs/librispeech/ASR/lstm_transducer_stateless2/onnx_pretrained.py
View File

@ -129,6 +129,7 @@ class OnnxModel:
self.encoder = ort.InferenceSession(
encoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
self.init_encoder_states()
@ -166,6 +167,7 @@ class OnnxModel:
self.decoder = ort.InferenceSession(
decoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
decoder_meta = self.decoder.get_modelmeta().custom_metadata_map
@ -179,6 +181,7 @@ class OnnxModel:
self.joiner = ort.InferenceSession(
joiner_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
joiner_meta = self.joiner.get_modelmeta().custom_metadata_map

5
egs/librispeech/ASR/lstm_transducer_stateless2/streaming-onnx-decode.py
View File

@ -172,30 +172,35 @@ class Model:
self.encoder = ort.InferenceSession(
args.encoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
def init_decoder(self, args):
self.decoder = ort.InferenceSession(
args.decoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
def init_joiner(self, args):
self.joiner = ort.InferenceSession(
args.joiner_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
def init_joiner_encoder_proj(self, args):
self.joiner_encoder_proj = ort.InferenceSession(
args.joiner_encoder_proj_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
def init_joiner_decoder_proj(self, args):
self.joiner_decoder_proj = ort.InferenceSession(
args.joiner_decoder_proj_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
def run_encoder(self, x, h0, c0) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:

1
egs/librispeech/ASR/pruned_transducer_stateless/export-onnx.py
View File

@ -307,6 +307,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

1
egs/librispeech/ASR/pruned_transducer_stateless3/export-onnx.py
View File

@ -312,6 +312,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

3
egs/librispeech/ASR/pruned_transducer_stateless3/onnx_pretrained.py
View File

@ -150,12 +150,14 @@ class OnnxModel:
self.encoder = ort.InferenceSession(
encoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
def init_decoder(self, decoder_model_filename: str):
self.decoder = ort.InferenceSession(
decoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
decoder_meta = self.decoder.get_modelmeta().custom_metadata_map
@ -169,6 +171,7 @@ class OnnxModel:
self.joiner = ort.InferenceSession(
joiner_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
joiner_meta = self.joiner.get_modelmeta().custom_metadata_map

5
egs/librispeech/ASR/pruned_transducer_stateless3/test_onnx.py
View File

@ -78,6 +78,7 @@ def test_conv2d_subsampling():
session = ort.InferenceSession(
filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
input_nodes = session.get_inputs()
@ -133,6 +134,7 @@ def test_rel_pos():
session = ort.InferenceSession(
filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
input_nodes = session.get_inputs()
@ -220,6 +222,7 @@ def test_conformer_encoder_layer():
session = ort.InferenceSession(
filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
input_nodes = session.get_inputs()
@ -304,6 +307,7 @@ def test_conformer_encoder():
session = ort.InferenceSession(
filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
input_nodes = session.get_inputs()
@ -359,6 +363,7 @@ def test_conformer():
session = ort.InferenceSession(
filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
input_nodes = session.get_inputs()

1
egs/librispeech/ASR/pruned_transducer_stateless5/export-onnx-streaming.py
View File

@ -404,6 +404,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

1
egs/librispeech/ASR/pruned_transducer_stateless5/export-onnx.py
View File

@ -335,6 +335,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

3
egs/librispeech/ASR/pruned_transducer_stateless5/onnx_pretrained-streaming.py
View File

@ -138,6 +138,7 @@ class OnnxModel:
self.encoder = ort.InferenceSession(
encoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
self.init_encoder_states()
@ -185,6 +186,7 @@ class OnnxModel:
self.decoder = ort.InferenceSession(
decoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
decoder_meta = self.decoder.get_modelmeta().custom_metadata_map
@ -198,6 +200,7 @@ class OnnxModel:
self.joiner = ort.InferenceSession(
joiner_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
joiner_meta = self.joiner.get_modelmeta().custom_metadata_map

1
egs/librispeech/ASR/pruned_transducer_stateless7/export-onnx.py
View File

@ -329,6 +329,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

5
egs/librispeech/ASR/pruned_transducer_stateless7/test_onnx.py
View File

@ -74,6 +74,7 @@ def test_conv2d_subsampling():
session = ort.InferenceSession(
filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
input_nodes = session.get_inputs()
@ -128,6 +129,7 @@ def test_rel_pos():
session = ort.InferenceSession(
filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
input_nodes = session.get_inputs()
@ -204,6 +206,7 @@ def test_zipformer_encoder_layer():
session = ort.InferenceSession(
filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
input_nodes = session.get_inputs()
@ -284,6 +287,7 @@ def test_zipformer_encoder():
session = ort.InferenceSession(
filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
input_nodes = session.get_inputs()
@ -338,6 +342,7 @@ def test_zipformer():
session = ort.InferenceSession(
filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
input_nodes = session.get_inputs()

8
egs/librispeech/ASR/pruned_transducer_stateless7_ctc_bs/onnx_pretrained.py
View File

@ -326,41 +326,49 @@ def main():
encoder = ort.InferenceSession(
args.encoder_model_filename,
sess_options=session_opts,
providers=["CPUExecutionProvider"],
)
decoder = ort.InferenceSession(
args.decoder_model_filename,
sess_options=session_opts,
providers=["CPUExecutionProvider"],
)
joiner = ort.InferenceSession(
args.joiner_model_filename,
sess_options=session_opts,
providers=["CPUExecutionProvider"],
)
joiner_encoder_proj = ort.InferenceSession(
args.joiner_encoder_proj_model_filename,
sess_options=session_opts,
providers=["CPUExecutionProvider"],
)
joiner_decoder_proj = ort.InferenceSession(
args.joiner_decoder_proj_model_filename,
sess_options=session_opts,
providers=["CPUExecutionProvider"],
)
lconv = ort.InferenceSession(
args.lconv_filename,
sess_options=session_opts,
providers=["CPUExecutionProvider"],
)
frame_reducer = ort.InferenceSession(
args.frame_reducer_filename,
sess_options=session_opts,
providers=["CPUExecutionProvider"],
)
ctc_output = ort.InferenceSession(
args.ctc_output_filename,
sess_options=session_opts,
providers=["CPUExecutionProvider"],
)
sp = spm.SentencePieceProcessor()

1
egs/librispeech/ASR/pruned_transducer_stateless7_streaming/export-onnx-zh.py
View File

@ -413,6 +413,7 @@ def export_decoder_model_onnx(
context_size = decoder_model.decoder.context_size
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

1
egs/librispeech/ASR/pruned_transducer_stateless7_streaming/export-onnx.py
View File

@ -401,6 +401,7 @@ def export_decoder_model_onnx(
context_size = decoder_model.decoder.context_size
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

3
egs/librispeech/ASR/pruned_transducer_stateless7_streaming/onnx_pretrained.py
View File

@ -130,6 +130,7 @@ class OnnxModel:
self.encoder = ort.InferenceSession(
encoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
self.init_encoder_states()
@ -229,6 +230,7 @@ class OnnxModel:
self.decoder = ort.InferenceSession(
decoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
decoder_meta = self.decoder.get_modelmeta().custom_metadata_map
@ -242,6 +244,7 @@ class OnnxModel:
self.joiner = ort.InferenceSession(
joiner_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
joiner_meta = self.joiner.get_modelmeta().custom_metadata_map

2
egs/librispeech/ASR/pruned_transducer_stateless7_streaming/zipformer.py
View File

@ -865,7 +865,7 @@ class ZipformerEncoderLayer(nn.Module):
return final_dropout_rate
else:
return initial_dropout_rate - (
initial_dropout_rate * final_dropout_rate
initial_dropout_rate - final_dropout_rate
) * (self.batch_count / warmup_period)
def forward(

2
egs/librispeech/ASR/streaming_conformer_ctc/conformer.py
View File

@ -230,7 +230,7 @@ class Conformer(Transformer):
x, pos_emb, mask=mask, src_key_padding_mask=src_key_padding_mask
) # (T, B, F)
else:
x = self.encoder(x, pos_emb, src_key_padding_mask=mask) # (T, B, F)
x = self.encoder(x, pos_emb, src_key_padding_mask=src_key_padding_mask) # (T, B, F)
if self.normalize_before:
x = self.after_norm(x)

1
egs/librispeech/ASR/zipformer/export-onnx-streaming.py
View File

@ -506,6 +506,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

1
egs/librispeech/ASR/zipformer/export-onnx.py
View File

@ -353,6 +353,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

3
egs/librispeech/ASR/zipformer/onnx_pretrained-streaming.py
View File

@ -146,6 +146,7 @@ class OnnxModel:
self.encoder = ort.InferenceSession(
encoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
self.init_encoder_states()
@ -236,6 +237,7 @@ class OnnxModel:
self.decoder = ort.InferenceSession(
decoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
decoder_meta = self.decoder.get_modelmeta().custom_metadata_map
@ -249,6 +251,7 @@ class OnnxModel:
self.joiner = ort.InferenceSession(
joiner_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
joiner_meta = self.joiner.get_modelmeta().custom_metadata_map

3
egs/librispeech/ASR/zipformer/onnx_pretrained.py
View File

@ -151,12 +151,14 @@ class OnnxModel:
self.encoder = ort.InferenceSession(
encoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
def init_decoder(self, decoder_model_filename: str):
self.decoder = ort.InferenceSession(
decoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
decoder_meta = self.decoder.get_modelmeta().custom_metadata_map
@ -170,6 +172,7 @@ class OnnxModel:
self.joiner = ort.InferenceSession(
joiner_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
joiner_meta = self.joiner.get_modelmeta().custom_metadata_map

1
egs/wenetspeech/ASR/pruned_transducer_stateless2/export-onnx.py
View File

@ -315,6 +315,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

5
egs/wenetspeech/ASR/pruned_transducer_stateless2/onnx_check.py
View File

@ -258,6 +258,7 @@ def main():
encoder_session = ort.InferenceSession(
args.onnx_encoder_filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
test_encoder(model, encoder_session)
@ -265,6 +266,7 @@ def main():
decoder_session = ort.InferenceSession(
args.onnx_decoder_filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
test_decoder(model, decoder_session)
@ -272,14 +274,17 @@ def main():
joiner_session = ort.InferenceSession(
args.onnx_joiner_filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
joiner_encoder_proj_session = ort.InferenceSession(
args.onnx_joiner_encoder_proj_filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
joiner_decoder_proj_session = ort.InferenceSession(
args.onnx_joiner_decoder_proj_filename,
sess_options=options,
providers=["CPUExecutionProvider"],
)
test_joiner(
model,

1
egs/wenetspeech/ASR/pruned_transducer_stateless5/export-onnx-streaming.py
View File

@ -404,6 +404,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

1
egs/wenetspeech/ASR/pruned_transducer_stateless5/export-onnx.py
View File

@ -335,6 +335,7 @@ def export_decoder_model_onnx(
vocab_size = decoder_model.decoder.vocab_size
y = torch.zeros(10, context_size, dtype=torch.int64)
decoder_model = torch.jit.script(decoder_model)
torch.onnx.export(
decoder_model,
y,

3
egs/wenetspeech/ASR/pruned_transducer_stateless5/onnx_pretrained-streaming.py
View File

@ -139,6 +139,7 @@ class OnnxModel:
self.encoder = ort.InferenceSession(
encoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
self.init_encoder_states()
@ -186,6 +187,7 @@ class OnnxModel:
self.decoder = ort.InferenceSession(
decoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
decoder_meta = self.decoder.get_modelmeta().custom_metadata_map
@ -199,6 +201,7 @@ class OnnxModel:
self.joiner = ort.InferenceSession(
joiner_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
joiner_meta = self.joiner.get_modelmeta().custom_metadata_map

3
egs/wenetspeech/ASR/pruned_transducer_stateless5/onnx_pretrained.py
View File

@ -158,12 +158,14 @@ class OnnxModel:
self.encoder = ort.InferenceSession(
encoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
def init_decoder(self, decoder_model_filename: str):
self.decoder = ort.InferenceSession(
decoder_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
decoder_meta = self.decoder.get_modelmeta().custom_metadata_map
@ -177,6 +179,7 @@ class OnnxModel:
self.joiner = ort.InferenceSession(
joiner_model_filename,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
joiner_meta = self.joiner.get_modelmeta().custom_metadata_map

1
egs/yesno/ASR/tdnn/onnx_pretrained.py
View File

@ -54,6 +54,7 @@ class OnnxModel:
self.model = ort.InferenceSession(
nn_model,
sess_options=self.session_opts,
providers=["CPUExecutionProvider"],
)
meta = self.model.get_modelmeta().custom_metadata_map