From 4a99b828a834d1d3870abbe3ee477518470f3dd9 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期五, 07 六月 2024 01:58:14 +0800
Subject: [PATCH] auto frontend
---
funasr/datasets/openai_datasets/datasets.py | 29 ++++++++++++++++++++++-------
funasr/datasets/openai_datasets/index_ds.py | 19 +++++++++++++++----
funasr/datasets/audio_datasets/samplers.py | 12 +++++++++---
3 files changed, 46 insertions(+), 14 deletions(-)
diff --git a/funasr/datasets/audio_datasets/samplers.py b/funasr/datasets/audio_datasets/samplers.py
index 18f8f91..7195add 100644
--- a/funasr/datasets/audio_datasets/samplers.py
+++ b/funasr/datasets/audio_datasets/samplers.py
@@ -364,6 +364,8 @@
self.sort_size = sort_size * num_replicas
self.max_token_length = kwargs.get("max_token_length", 2048)
self.length_scale_source = kwargs.get("length_scale_source", 1.0)
+ self.start_step = kwargs.get("start_step", 2048)
+
super().__init__(
dataset, num_replicas=num_replicas, rank=rank, shuffle=shuffle, drop_last=drop_last
)
@@ -415,13 +417,17 @@
rank_batches[i % self.num_replicas].append(batch)
# Assign all batches for the current rank directly
- final_batches = rank_batches[self.rank]
+ final_batches = rank_batches[self.rank][self.start_step :]
+ self.batch_num = len(final_batches)
+ logging.info(
+ f"rank: {self.rank}, dataloader start from step: {self.start_step}, batch_num: {self.batch_num}"
+ )
return iter(final_batches)
def __len__(self):
-
- return 1
+ # Calculate the number of batches per epoch for the current rank
+ return self.batch_num
def set_epoch(self, epoch):
self.epoch = epoch
diff --git a/funasr/datasets/openai_datasets/datasets.py b/funasr/datasets/openai_datasets/datasets.py
index 9bd0698..5813c3b 100644
--- a/funasr/datasets/openai_datasets/datasets.py
+++ b/funasr/datasets/openai_datasets/datasets.py
@@ -51,7 +51,7 @@
self.batch_size = kwargs.get("batch_size")
self.batch_type = kwargs.get("batch_type")
self.prompt_ids_len = 0
- self.retry = kwargs.get("retry", 5)
+ self.retry = kwargs.get("retry", 10)
self.permute = False
from funasr.frontends.whisper_frontend import WhisperFrontend
@@ -60,6 +60,8 @@
self.permute = True
self.pattern = re.compile(r"(<\|startofspeech\|>.*?<\|endofspeech\|>)")
+ # self.kwargs = kwargs
+ self.max_token_length = kwargs.get("max_token_length", 1024)
def get_source_len(self, index):
item = self.index_ds[index]
@@ -77,7 +79,9 @@
# pdb.set_trace()
output = None
+
for idx in range(self.retry):
+ badcase_flag = False
if idx == 0:
index_cur = index
else:
@@ -112,9 +116,14 @@
"<|endofspeech|>", ""
)
if sub_str.startswith("!"):
-
- data_src = load_audio_text_image_video(sub_str[1:], fs=self.fs)
-
+ try:
+ data_src = load_audio_text_image_video(sub_str[1:], fs=self.fs)
+ except Exception as e:
+ logging.error(
+ f"Loading wav failed! {str(e)}, {traceback.format_exc()}"
+ )
+ badcase_flag = True
+ continue
speech, speech_lengths = extract_fbank(
data_src,
data_type=self.data_type,
@@ -134,6 +143,8 @@
source_ids += sub_token
fbank_mask_i += [1] * len(sub_token)
+ if badcase_flag:
+ continue
source_mask = [-100] * len(source_ids)
target_out = f"{target_out}<|im_end|>"
target_ids = self.tokenizer.encode(target_out)
@@ -142,6 +153,10 @@
fbank_mask += fbank_mask_i
fbank_beg.append(fbank_beg_i)
+ if len(input_ids) > self.max_token_length:
+ badcase_flag = True
+ if badcase_flag:
+ continue
input_ids = torch.tensor(input_ids, dtype=torch.int64)
attention_mask = torch.tensor([len(input_ids)], dtype=torch.int32)
labels = torch.tensor(labels, dtype=torch.int64)
@@ -186,9 +201,9 @@
data_list, batch_first=True, padding_value=pad_value
)
- if self.batch_type != "example":
- for i in range(10):
- outputs = self._filter_badcase(outputs, i=i)
+ # if self.batch_type != "example":
+ # for i in range(10):
+ # outputs = self._filter_badcase(outputs, i=i)
return outputs
diff --git a/funasr/datasets/openai_datasets/index_ds.py b/funasr/datasets/openai_datasets/index_ds.py
index 1c48cd2..cc518f8 100644
--- a/funasr/datasets/openai_datasets/index_ds.py
+++ b/funasr/datasets/openai_datasets/index_ds.py
@@ -48,7 +48,10 @@
for file_json in file_list:
with open(file_json.strip(), encoding="utf-8") as fin:
for line in fin:
- data = json.loads(line.strip())["messages"]
+ data_dict = json.loads(line.strip())
+ data = data_dict["messages"]
+ speech_length = data_dict.get("speech_length", -1) // 8
+ text_length = data_dict.get("text_length", 0)
system, user, assistant = [], [], []
for i, item in enumerate(data):
@@ -63,7 +66,12 @@
system = system * len(user)
- contents_i = {"system": system, "user": user, "assistant": assistant}
+ contents_i = {
+ "system": system,
+ "user": user,
+ "assistant": assistant,
+ "source_len": speech_length + text_length,
+ }
contents.append(contents_i)
self.contents = contents
@@ -80,11 +88,14 @@
return data
def get_source_len(self, data_dict):
- return len(data_dict["system"]) + len(data_dict["user"])
+ source_len = data_dict.get("source_len", -1)
+ if source_len < 0:
+ source_len = len(data_dict["system"]) + len(data_dict["user"])
+ return source_len
def get_target_len(self, data_dict):
- return len(data_dict["assistant"])
+ return 0
if __name__ == "__main__":
--
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