Initial commit: FunASR Speech Recognition Toolkit

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

funasr/utils/misc.py

@@ -0,0 +1,166 @@
+import os
+import io
+import shutil
+import logging
+from collections import OrderedDict
+import numpy as np
+from omegaconf import DictConfig, OmegaConf
+
+
+def statistic_model_parameters(model, prefix=None):
+    """Statistic model parameters.
+    
+        Args:
+            model: Model instance or model name.
+            prefix: TODO.
+        """
+    var_dict = model.state_dict()
+    numel = 0
+    for i, key in enumerate(
+        sorted(list([x for x in var_dict.keys() if "num_batches_tracked" not in x]))
+    ):
+        if prefix is None or key.startswith(prefix):
+            numel += var_dict[key].numel()
+    return numel
+
+
+def int2vec(x, vec_dim=8, dtype=np.int32):
+    """Int2vec.
+    
+        Args:
+            x: TODO.
+            vec_dim: Size/dimension parameter.
+            dtype: TODO.
+        """
+    b = ("{:0" + str(vec_dim) + "b}").format(x)
+    # little-endian order: lower bit first
+    return (np.array(list(b)[::-1]) == "1").astype(dtype)
+
+
+def seq2arr(seq, vec_dim=8):
+    """Seq2arr.
+    
+        Args:
+            seq: TODO.
+            vec_dim: Size/dimension parameter.
+        """
+    return np.row_stack([int2vec(int(x), vec_dim) for x in seq])
+
+
+def load_scp_as_dict(scp_path, value_type="str", kv_sep=" "):
+    """Load scp as dict.
+    
+        Args:
+            scp_path: TODO.
+            value_type: TODO.
+            kv_sep: TODO.
+        """
+    with io.open(scp_path, "r", encoding="utf-8") as f:
+        ret_dict = OrderedDict()
+        for one_line in f.readlines():
+            one_line = one_line.strip()
+            pos = one_line.find(kv_sep)
+            key, value = one_line[:pos], one_line[pos + 1 :]
+            if value_type == "list":
+                value = value.split(" ")
+            ret_dict[key] = value
+        return ret_dict
+
+
+def load_scp_as_list(scp_path, value_type="str", kv_sep=" "):
+    """Load scp as list.
+    
+        Args:
+            scp_path: TODO.
+            value_type: TODO.
+            kv_sep: TODO.
+        """
+    with io.open(scp_path, "r", encoding="utf8") as f:
+        ret_dict = []
+        for one_line in f.readlines():
+            one_line = one_line.strip()
+            pos = one_line.find(kv_sep)
+            key, value = one_line[:pos], one_line[pos + 1 :]
+            if value_type == "list":
+                value = value.split(" ")
+            ret_dict.append((key, value))
+        return ret_dict
+
+
+def deep_update(original, update):
+
+    """Recursively merge update dict into original dict (in-place).
+
+    For nested dicts, merges recursively. For other types, overwrites.
+
+    Args:
+        original (dict): Target dict to be updated in-place.
+        update (dict): Source dict with new values.
+    """
+    for key, value in update.items():
+        if isinstance(value, dict) and key in original:
+            if len(value) == 0:
+                original[key] = value
+            deep_update(original[key], value)
+        else:
+            original[key] = value
+
+
+def prepare_model_dir(**kwargs):
+
+    """Prepare model dir.
+    
+        Args:
+            **kwargs: Additional keyword arguments.
+        """
+    os.makedirs(kwargs.get("output_dir", "./"), exist_ok=True)
+
+    yaml_file = os.path.join(kwargs.get("output_dir", "./"), "config.yaml")
+    OmegaConf.save(config=kwargs, f=yaml_file)
+    logging.info(f"kwargs: {kwargs}")
+    logging.info("config.yaml is saved to: %s", yaml_file)
+
+    model_path = kwargs.get("model_path", None)
+    if model_path is not None:
+        config_json = os.path.join(model_path, "configuration.json")
+        if os.path.exists(config_json):
+            shutil.copy(
+                config_json, os.path.join(kwargs.get("output_dir", "./"), "configuration.json")
+            )
+
+
+def extract_filename_without_extension(file_path):
+    """
+    从给定的文件路径中提取文件名（不包含路径和扩展名）
+    :param file_path: 完整的文件路径
+    :return: 文件名（不含路径和扩展名）
+    """
+    # 首先，使用os.path.basename获取路径中的文件名部分（含扩展名）
+    filename_with_extension = os.path.basename(file_path)
+    # 然后，使用os.path.splitext分离文件名和扩展名
+    filename, extension = os.path.splitext(filename_with_extension)
+    # 返回不包含扩展名的文件名
+    return filename
+
+
+def smart_remove(path):
+    """Intelligently removes files, empty directories, and non-empty directories recursively."""
+    # Check if the provided path exists
+    if not os.path.exists(path):
+        print(f"{path} does not exist.")
+        return
+
+    # If the path is a file, delete it
+    if os.path.isfile(path):
+        os.remove(path)
+        print(f"File {path} has been deleted.")
+    # If the path is a directory
+    elif os.path.isdir(path):
+        try:
+            # Attempt to remove an empty directory
+            os.rmdir(path)
+            print(f"Empty directory {path} has been deleted.")
+        except OSError:
+            # If the directory is not empty, remove it along with all its contents
+            shutil.rmtree(path)
+            print(f"Non-empty directory {path} has been recursively deleted.")