From 731bfcbc7e7c8fb797ddc9a0a73b84749d40ced7 Mon Sep 17 00:00:00 2001
From: 志浩 <neo.dzh@alibaba-inc.com>
Date: 星期一, 20 二月 2023 11:56:37 +0800
Subject: [PATCH] simu data
---
funasr/export/models/e2e_asr_paraformer.py | 12 +++++++++---
1 files changed, 9 insertions(+), 3 deletions(-)
diff --git a/funasr/export/models/e2e_asr_paraformer.py b/funasr/export/models/e2e_asr_paraformer.py
index dd87213..84dd9d2 100644
--- a/funasr/export/models/e2e_asr_paraformer.py
+++ b/funasr/export/models/e2e_asr_paraformer.py
@@ -63,17 +63,23 @@
decoder_out, _ = self.decoder(enc, enc_len, pre_acoustic_embeds, pre_token_length)
decoder_out = torch.log_softmax(decoder_out, dim=-1)
+ # sample_ids = decoder_out.argmax(dim=-1)
return decoder_out, pre_token_length
-
- # def get_output_size(self):
- # return self.model.encoders[0].size
def get_dummy_inputs(self):
speech = torch.randn(2, 30, self.feats_dim)
speech_lengths = torch.tensor([6, 30], dtype=torch.int32)
return (speech, speech_lengths)
+ def get_dummy_inputs_txt(self, txt_file: str = "/mnt/workspace/data_fbank/0207/12345.wav.fea.txt"):
+ import numpy as np
+ fbank = np.loadtxt(txt_file)
+ fbank_lengths = np.array([fbank.shape[0], ], dtype=np.int32)
+ speech = torch.from_numpy(fbank[None, :, :].astype(np.float32))
+ speech_lengths = torch.from_numpy(fbank_lengths.astype(np.int32))
+ return (speech, speech_lengths)
+
def get_input_names(self):
return ['speech', 'speech_lengths']
--
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