# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

"""Logging utilities."""
# pylint: disable=unused-import
# pylint: disable=g-bad-import-order
# pylint: disable=invalid-name
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import logging as _logging
import os as _os
import sys as _sys
import time as _time
import traceback as _traceback
from logging import DEBUG
from logging import ERROR
from logging import FATAL
from logging import INFO
from logging import WARN
import threading

import six

from tensorflow.python.util.tf_export import tf_export

# Don't use this directly. Use get_logger() instead.
_logger = None
_logger_lock = threading.Lock()


def _get_caller(offset=3):
    """Returns a code and frame object for the lowest non-logging stack frame."""
    # Use sys._getframe().  This avoids creating a traceback object.
    # pylint: disable=protected-access
    f = _sys._getframe(offset)
    # pylint: enable=protected-access
    our_file = f.f_code.co_filename
    f = f.f_back
    while f:
        code = f.f_code
        if code.co_filename != our_file:
            return code, f
        f = f.f_back
    return None, None


# The definition of `findCaller` changed in Python 3.2
if _sys.version_info.major >= 3 and _sys.version_info.minor >= 8:

    def _logger_find_caller(
        stack_info=False, stacklevel=1
    ):  # pylint: disable=g-wrong-blank-lines
        code, frame = _get_caller(4)
        sinfo = None
        if stack_info:
            sinfo = "\n".join(_traceback.format_stack())
        if code:
            return (code.co_filename, frame.f_lineno, code.co_name, sinfo)
        else:
            return "(unknown file)", 0, "(unknown function)", sinfo


elif _sys.version_info.major >= 3 and _sys.version_info.minor >= 2:

    def _logger_find_caller(stack_info=False):  # pylint: disable=g-wrong-blank-lines
        code, frame = _get_caller(4)
        sinfo = None
        if stack_info:
            sinfo = "\n".join(_traceback.format_stack())
        if code:
            return (code.co_filename, frame.f_lineno, code.co_name, sinfo)
        else:
            return "(unknown file)", 0, "(unknown function)", sinfo


else:

    def _logger_find_caller():  # pylint: disable=g-wrong-blank-lines
        code, frame = _get_caller(4)
        if code:
            return (code.co_filename, frame.f_lineno, code.co_name)
        else:
            return "(unknown file)", 0, "(unknown function)"


@tf_export("get_logger")
def get_logger():
    """Return TF logger instance."""
    global _logger

    # Use double-checked locking to avoid taking lock unnecessarily.
    if _logger:
        return _logger

    _logger_lock.acquire()

    try:
        if _logger:
            return _logger

        # Scope the TensorFlow logger to not conflict with users' loggers.
        logger = _logging.getLogger("tensorflow")

        # Override findCaller on the logger to skip internal helper functions
        logger.findCaller = _logger_find_caller

        # Don't further configure the TensorFlow logger if the root logger is
        # already configured. This prevents double logging in those cases.
        if not _logging.getLogger().handlers:
            # Determine whether we are in an interactive environment
            _interactive = False
            try:
                # This is only defined in interactive shells.
                if _sys.ps1:
                    _interactive = True
            except AttributeError:
                # Even now, we may be in an interactive shell with `python -i`.
                _interactive = _sys.flags.interactive

            # If we are in an interactive environment (like Jupyter), set loglevel
            # to INFO and pipe the output to stdout.
            if _interactive:
                logger.setLevel(INFO)
                _logging_target = _sys.stdout
            else:
                _logging_target = _sys.stderr

            # Add the output handler.
            _handler = _logging.StreamHandler(_logging_target)
            _handler.setFormatter(_logging.Formatter(_logging.BASIC_FORMAT, None))
            logger.addHandler(_handler)

        _logger = logger
        return _logger

    finally:
        _logger_lock.release()


@tf_export(v1=["logging.log"])
def log(level, msg, *args, **kwargs):
    get_logger().log(level, msg, *args, **kwargs)


@tf_export(v1=["logging.debug"])
def debug(msg, *args, **kwargs):
    get_logger().debug(msg, *args, **kwargs)


@tf_export(v1=["logging.error"])
def error(msg, *args, **kwargs):
    get_logger().error(msg, *args, **kwargs)


@tf_export(v1=["logging.fatal"])
def fatal(msg, *args, **kwargs):
    get_logger().fatal(msg, *args, **kwargs)


@tf_export(v1=["logging.info"])
def info(msg, *args, **kwargs):
    get_logger().info(msg, *args, **kwargs)


@tf_export(v1=["logging.warn"])
def warn(msg, *args, **kwargs):
    get_logger().warning(msg, *args, **kwargs)


@tf_export(v1=["logging.warning"])
def warning(msg, *args, **kwargs):
    get_logger().warning(msg, *args, **kwargs)


_level_names = {
    FATAL: "FATAL",
    ERROR: "ERROR",
    WARN: "WARN",
    INFO: "INFO",
    DEBUG: "DEBUG",
}

# Mask to convert integer thread ids to unsigned quantities for logging
# purposes
_THREAD_ID_MASK = 2 * _sys.maxsize + 1

_log_prefix = None  # later set to google2_log_prefix

# Counter to keep track of number of log entries per token.
_log_counter_per_token = {}


@tf_export(v1=["logging.TaskLevelStatusMessage"])
def TaskLevelStatusMessage(msg):
    error(msg)


@tf_export(v1=["logging.flush"])
def flush():
    raise NotImplementedError()


# Code below is taken from pyglib/logging
@tf_export(v1=["logging.vlog"])
def vlog(level, msg, *args, **kwargs):
    get_logger().log(level, msg, *args, **kwargs)


def _GetNextLogCountPerToken(token):
    """Wrapper for _log_counter_per_token.

    Args:
      token: The token for which to look up the count.

    Returns:
      The number of times this function has been called with
      *token* as an argument (starting at 0)
    """
    global _log_counter_per_token  # pylint: disable=global-variable-not-assigned
    _log_counter_per_token[token] = 1 + _log_counter_per_token.get(token, -1)
    return _log_counter_per_token[token]


@tf_export(v1=["logging.log_every_n"])
def log_every_n(level, msg, n, *args):
    """Log 'msg % args' at level 'level' once per 'n' times.

    Logs the 1st call, (N+1)st call, (2N+1)st call,  etc.
    Not threadsafe.

    Args:
      level: The level at which to log.
      msg: The message to be logged.
      n: The number of times this should be called before it is logged.
      *args: The args to be substituted into the msg.
    """
    count = _GetNextLogCountPerToken(_GetFileAndLine())
    log_if(level, msg, not (count % n), *args)


@tf_export(v1=["logging.log_first_n"])
def log_first_n(level, msg, n, *args):  # pylint: disable=g-bad-name
    """Log 'msg % args' at level 'level' only first 'n' times.

    Not threadsafe.

    Args:
      level: The level at which to log.
      msg: The message to be logged.
      n: The number of times this should be called before it is logged.
      *args: The args to be substituted into the msg.
    """
    count = _GetNextLogCountPerToken(_GetFileAndLine())
    log_if(level, msg, count < n, *args)


@tf_export(v1=["logging.log_if"])
def log_if(level, msg, condition, *args):
    """Log 'msg % args' at level 'level' only if condition is fulfilled."""
    if condition:
        vlog(level, msg, *args)


def _GetFileAndLine():
    """Returns (filename, linenumber) for the stack frame."""
    code, f = _get_caller()
    if not code:
        return ("<unknown>", 0)
    return (code.co_filename, f.f_lineno)


def google2_log_prefix(level, timestamp=None, file_and_line=None):
    """Assemble a logline prefix using the google2 format."""
    # pylint: disable=global-variable-not-assigned
    global _level_names
    # pylint: enable=global-variable-not-assigned

    # Record current time
    now = timestamp or _time.time()
    now_tuple = _time.localtime(now)
    now_microsecond = int(1e6 * (now % 1.0))

    (filename, line) = file_and_line or _GetFileAndLine()
    basename = _os.path.basename(filename)

    # Severity string
    severity = "I"
    if level in _level_names:
        severity = _level_names[level][0]

    s = "%c%02d%02d %02d:%02d:%02d.%06d %5d %s:%d] " % (
        severity,
        now_tuple[1],  # month
        now_tuple[2],  # day
        now_tuple[3],  # hour
        now_tuple[4],  # min
        now_tuple[5],  # sec
        now_microsecond,
        _get_thread_id(),
        basename,
        line,
    )

    return s


@tf_export(v1=["logging.get_verbosity"])
def get_verbosity():
    """Return how much logging output will be produced."""
    return get_logger().getEffectiveLevel()


@tf_export(v1=["logging.set_verbosity"])
def set_verbosity(v):
    """Sets the threshold for what messages will be logged."""
    get_logger().setLevel(v)


def _get_thread_id():
    """Get id of current thread, suitable for logging as an unsigned quantity."""
    # pylint: disable=protected-access
    thread_id = six.moves._thread.get_ident()
    # pylint:enable=protected-access
    return thread_id & _THREAD_ID_MASK


_log_prefix = google2_log_prefix

tf_export(v1=["logging.DEBUG"]).export_constant(__name__, "DEBUG")
tf_export(v1=["logging.ERROR"]).export_constant(__name__, "ERROR")
tf_export(v1=["logging.FATAL"]).export_constant(__name__, "FATAL")
tf_export(v1=["logging.INFO"]).export_constant(__name__, "INFO")
tf_export(v1=["logging.WARN"]).export_constant(__name__, "WARN")