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fix bug

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This commit is contained in:
游雁 2024-06-09 22:40:49 +08:00
parent 1d27a1507b
commit 7fc17b1aaf
3 changed files with 29 additions and 16 deletions
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1
examples/industrial_data_pretraining/llm_asr/demo_speech2text.py
View File

@ -15,6 +15,7 @@ jsonl = (
"/nfs/beinian.lzr/workspace/GPT-4o/Data/Speech2Text/TestData/aishell1_test_speech2text.jsonl"
)
output_dir = f"{os.path.join(ckpt_dir, ckpt_id)}"
device = "cuda:0"
ckpt_dir = sys.argv[1]
ckpt_id = sys.argv[2]

28
examples/industrial_data_pretraining/llm_asr/demo_speech2text.sh
View File

@ -1,10 +1,10 @@
ckpt_dir="/nfs/zhifu.gzf/ckpt/saves/qwen_1.5_7b/full/sft/asr_tts_text_exp1_ds_z3/checkpoint-11000"
ckpt_dir="/nfs/beinian.lzr/workspace/GPT-4o/Exp/exp6/5m-8gpu/exp6_speech2text_linear_ddp_0609"
ckpt_id="model.pt.ep0.90000"
jsonl_dir="/nfs/beinian.lzr/workspace/GPT-4o/Data/Speech2Text/TestData"
out_dir="${ckpt_dir}/asr"
out_dir="${ckpt_dir}/inference-${ckpt_id}"
mkdir -p ${out_dir}
device="cuda:0"
@ -12,9 +12,9 @@ device="cuda:0"
for data_set in "librispeech_test_clean_speech2text.jsonl" "librispeech_test_other_speech2text.jsonl"; do
jsonl=${jsonl_dir}/${data_set}
output_dir=${out_dir}/${data_set}
pred_file=${out_dir}/${data_set}/1best_recog/text_tn
ref_file=${out_dir}/${data_set}/1best_recog/label
mkdir -p ${output_dir}
pred_file=${output_dir}/${data_set}/1best_recog/text_tn
ref_file=${output_dir}/${data_set}/1best_recog/label
python ./demo_speech2text.py ${ckpt_dir} ${ckpt_id} ${jsonl} ${output_dir} ${device}
@ -26,9 +26,9 @@ done
for data_set in "aishell1_test_speech2text.jsonl" "aishell2_ios_test_speech2text.jsonl" "librispeech_test_other_speech2text.jsonl"; do
jsonl=${jsonl_dir}/${data_set}
output_dir=${out_dir}/${data_set}
pred_file=${out_dir}/${data_set}/1best_recog/text_tn
ref_file=${out_dir}/${data_set}/1best_recog/label
mkdir -p ${output_dir}
pred_file=${output_dir}/${data_set}/1best_recog/text_tn
ref_file=${output_dir}/${data_set}/1best_recog/label
python ./demo_speech2text.py ${ckpt_dir} ${ckpt_id} ${jsonl} ${output_dir}
@ -39,9 +39,9 @@ done
for data_set in "s2tt_en2zh.v20240605.test.jsonl"; do
jsonl=${jsonl_dir}/${data_set}
output_dir=${out_dir}/${data_set}
pred_file=${out_dir}/${data_set}/1best_recog/text_tn
ref_file=${out_dir}/${data_set}/1best_recog/label
mkdir -p ${output_dir}
pred_file=${output_dir}/${data_set}/1best_recog/text_tn
ref_file=${output_dir}/${data_set}/1best_recog/label
python ./demo_speech2text.py ${ckpt_dir} ${ckpt_id} ${jsonl} ${output_dir}
@ -52,9 +52,9 @@ done
for data_set in "s2tt_zh2en.v20240605.test.jsonl"; do
jsonl=${jsonl_dir}/${data_set}
output_dir=${out_dir}/${data_set}
pred_file=${out_dir}/${data_set}/1best_recog/text_tn
ref_file=${out_dir}/${data_set}/1best_recog/label
mkdir -p ${output_dir}
pred_file=${output_dir}/${data_set}/1best_recog/text_tn
ref_file=${output_dir}/${data_set}/1best_recog/label
python ./demo_speech2text.py ${ckpt_dir} ${ckpt_id} ${jsonl} ${output_dir}

16
funasr/models/llm_asr/model.py
View File

@ -556,7 +556,7 @@ class LLMASR2(nn.Module):
return contents
def data_load_speech(self, contents: dict, tokenizer, frontend, **kwargs):
def data_load_speech(self, contents: dict, tokenizer, frontend, meta_data={}, **kwargs):
system = contents["system"]
user = contents["user"]
@ -594,7 +594,10 @@ class LLMASR2(nn.Module):
)
if sub_str.startswith("!"):
try:
time1 = time.perf_counter()
data_src = load_audio_text_image_video(sub_str[1:], fs=frontend.fs)
time2 = time.perf_counter()
meta_data["load_data"] = f"{time2 - time1:0.3f}"
except Exception as e:
logging.error(f"Loading wav failed! {str(e)}, {traceback.format_exc()}")
@ -605,6 +608,15 @@ class LLMASR2(nn.Module):
is_final=True,
) # speech: [b, T, d]
time3 = time.perf_counter()
meta_data["extract_feat"] = f"{time3 - time2:0.3f}"
meta_data["batch_data_time"] = (
speech_lengths.sum().item()
* frontend.frame_shift
* frontend.lfr_n
/ 1000
)
if kwargs.get("permute", True):
speech = speech.permute(0, 2, 1)
@ -666,7 +678,7 @@ class LLMASR2(nn.Module):
raise NotImplementedError("batch decoding is not implemented")
contents = self.data_template(data_in[0])
output = self.data_load_speech(contents, tokenizer, frontend, **kwargs)
output = self.data_load_speech(contents, tokenizer, frontend, meta_data=meta_data, **kwargs)
batch = to_device(output, kwargs["device"])
# audio encoder