fix(core): Fix fschat and alembic log conflict (#919)

Co-authored-by: chengfangyin2 <chengfangyin3@jd.com>

dbgpt/util/__init__.py

@@ -1,8 +1,5 @@
 from .utils import (
     get_gpu_memory,
-    StreamToLogger,
-    disable_torch_init,
-    pretty_print_semaphore,
     server_error_msg,
     get_or_create_event_loop,
 )

dbgpt/util/utils.py

@@ -111,58 +111,6 @@ def _build_logger(logger_name, logging_level=None, logger_filename: str = None):
     return logger
 
 
-class StreamToLogger(object):
-    """
-    Fake file-like stream object that redirects writes to a logger instance.
-    """
-
-    def __init__(self, logger, log_level=logging.INFO):
-        self.terminal = sys.stdout
-        self.logger = logger
-        self.log_level = log_level
-        self.linebuf = ""
-
-    def __getattr__(self, attr):
-        return getattr(self.terminal, attr)
-
-    def write(self, buf):
-        temp_linebuf = self.linebuf + buf
-        self.linebuf = ""
-        for line in temp_linebuf.splitlines(True):
-            # From the io.TextIOWrapper docs:
-            #   On output, if newline is None, any '\n' characters written
-            #   are translated to the system default line separator.
-            # By default sys.stdout.write() expects '\n' newlines and then
-            # translates them so this is still cross platform.
-            if line[-1] == "\n":
-                encoded_message = line.encode("utf-8", "ignore").decode("utf-8")
-                self.logger.log(self.log_level, encoded_message.rstrip())
-            else:
-                self.linebuf += line
-
-    def flush(self):
-        if self.linebuf != "":
-            encoded_message = self.linebuf.encode("utf-8", "ignore").decode("utf-8")
-            self.logger.log(self.log_level, encoded_message.rstrip())
-        self.linebuf = ""
-
-
-def disable_torch_init():
-    """
-    Disable the redundant torch default initialization to accelerate model creation.
-    """
-    import torch
-
-    setattr(torch.nn.Linear, "reset_parameters", lambda self: None)
-    setattr(torch.nn.LayerNorm, "reset_parameters", lambda self: None)
-
-
-def pretty_print_semaphore(semaphore):
-    if semaphore is None:
-        return "None"
-    return f"Semaphore(value={semaphore._value}, locked={semaphore.locked()})"
-
-
 def get_or_create_event_loop() -> asyncio.BaseEventLoop:
     loop = None
     try: