Initial commit: FunASR Speech Recognition Toolkit

Add complete FunASR codebase including models, runtime, and documentation.

funasr/datasets/openai_datasets/index_ds.py

@@ -0,0 +1,138 @@
+import os
+import json
+import torch
+import logging
+
+import librosa
+import random
+import torch.distributed as dist
+
+from funasr.register import tables
+
+
+@tables.register("index_ds_classes", "OpenAIIndexDSJsonl")
+class OpenAIIndexDSJsonl(torch.utils.data.Dataset):  # torch.utils.data.Dataset
+
+    def __init__(self, path: str, **kwargs):
+        """Initialize OpenAIIndexDSJsonl.
+        
+            Args:
+                path: TODO.
+                **kwargs: Additional keyword arguments.
+            """
+        super().__init__()
+
+        self.max_source_length = kwargs.get("max_source_length", 3000)
+        self.min_source_length = kwargs.get("min_source_length", 0)
+        self.max_target_length = kwargs.get("max_target_length", 2048)
+        self.min_target_length = kwargs.get("min_target_length", 0)
+        self.max_token_length = kwargs.get("max_token_length", 2200)
+
+        is_training = kwargs.get("is_training", True)
+        if not (path.endswith(".jsonl") or path.endswith(".json")):
+            # jsonl list file
+            data_split_num = kwargs.get("data_split_num", 1)
+            data_split_i = kwargs.get("data_split_i", 0)
+
+            if not is_training:
+                data_split_num = 1
+                data_split_i = 0
+            with open(path, encoding="utf-8") as fin:
+                file_list_all = fin.readlines()
+
+                num_per_slice = (len(file_list_all) - 1) // data_split_num + 1  # 16
+                file_list = file_list_all[
+                    data_split_i * num_per_slice : (data_split_i + 1) * num_per_slice
+                ]
+                logging.info(
+                    f"is_training: {is_training}, data_split_num: {data_split_num}, data_split_i: {data_split_i}, \nfile_list: {file_list}, \nfile_list_all: {file_list_all}"
+                )
+
+        else:
+            file_list = [path]
+
+        contents = []
+        for file_json in file_list:
+            with open(file_json.strip(), encoding="utf-8") as fin:
+                for line in fin:
+                    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)
+                    if speech_length > self.max_source_length:
+                        logging.info(
+                            "speech_length: {speech_length} > {self.max_source_length}, drop it"
+                        )
+                        continue
+                    if text_length > self.max_target_length:
+                        continue
+
+                    self.max_target_length = kwargs.get("max_target_length", 2048)
+
+                    system, user, assistant = [], [], []
+                    for i, item in enumerate(data):
+                        role = item["role"]
+                        content = item["content"]
+                        if role == "system":
+                            system.append(content)
+                        elif role == "user":
+                            user.append(content)
+                        elif role == "assistant":
+                            assistant.append(content)
+
+                    system = system * len(user)
+
+                    contents_i = {
+                        "system": system,
+                        "user": user,
+                        "assistant": assistant,
+                        "source_len": speech_length + text_length,
+                    }
+                    contents.append(contents_i)
+
+        self.contents = contents
+
+        logging.info("total_num of samplers: {}, {}".format(len(self.contents), path))
+
+    def __len__(self):
+        """Internal: len  ."""
+        return len(self.contents)
+
+    def __getitem__(self, index):
+
+        """Internal: getitem  .
+        
+            Args:
+                index: TODO.
+            """
+        data = self.contents[index]
+
+        return data
+
+    def get_source_len(self, data_dict):
+        """Get source len.
+        
+            Args:
+                data_dict: TODO.
+            """
+        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):
+
+        """Get target len.
+        
+            Args:
+                data_dict: TODO.
+            """
+        return 0
+
+
+if __name__ == "__main__":
+    index_ds = OpenAIIndexDSJsonl(
+        path="/Users/zhifu/funasr1.0/test_local/data_tmp/tmp_wav_10.jsonl"
+    )
+    print(index_ds.contents)
+    pass