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# Copyright 2025 The HuggingFace Team. 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.

import copy
import json
import os
from dataclasses import dataclass
from typing import Any, Union


@dataclass
class DistributedConfig:
    """
    Base class for distributed configs
    """

    enable_expert_parallel: bool = False
    # TODO: add tp_plan, pp_plan, device_mesh etc..

    @classmethod
    def from_dict(cls, config_dict, **kwargs):
        """
        Constructs a DistributedConfig instance from a dictionary of parameters.
        Args:
            config_dict (Dict[str, Any]): Dictionary containing configuration parameters.
            **kwargs: Additional keyword arguments to override dictionary values.
        Returns:
            DistributedConfig: Instance of DistributedConfig constructed from the dictionary.
        """
        config = cls(**config_dict)
        to_remove = []
        for key, value in kwargs.items():
            if hasattr(config, key):
                setattr(config, key, value)
                to_remove.append(key)
        for key in to_remove:
            kwargs.pop(key, None)
        return config

    # Copied from transformers.utils.quantization_config.QuantizationConfigMixin.to_json_file
    def to_json_file(self, json_file_path: Union[str, os.PathLike]):
        """
        Save this instance to a JSON file.
        Args:
            json_file_path (`str` or `os.PathLike`):
                Path to the JSON file in which this configuration instance's parameters will be saved.
            use_diff (`bool`, *optional*, defaults to `True`):
                If set to `True`, only the difference between the config instance and the default
                `QuantizationConfig()` is serialized to JSON file.
        """
        with open(json_file_path, "w", encoding="utf-8") as writer:
            config_dict = self.to_dict()
            json_string = json.dumps(config_dict, indent=2, sort_keys=True) + "\n"

            writer.write(json_string)

    def to_dict(self) -> dict[str, Any]:
        """
        Serializes this instance to a Python dictionary. Returns:
            `Dict[str, Any]`: Dictionary of all the attributes that make up this configuration instance.
        """
        return copy.deepcopy(self.__dict__)

    # Copied from transformers.utils.quantization_config.QuantizationConfigMixin.__iter__
    def __iter__(self):
        """allows `dict(obj)` for situations where obj may be a dict or QuantizationConfigMixin"""
        for attr, value in copy.deepcopy(self.__dict__).items():
            yield attr, value

    # Copied from transformers.utils.quantization_config.QuantizationConfigMixin.__repr__
    def __repr__(self):
        return f"{self.__class__.__name__} {self.to_json_string()}"

    def to_json_string(self):
        """
        Serializes this instance to a JSON formatted string.
        Returns:
            str: JSON formatted string representing the configuration instance.
        """
        return json.dumps(self.__dict__, indent=2) + "\n"

    def update(self, **kwargs):
        """
        Updates attributes of this class instance with attributes from `kwargs` if they match existing attributes,
        returning all the unused kwargs.
        Args:
            kwargs (`Dict[str, Any]`):
                Dictionary of attributes to tentatively update this class.
        Returns:
            `Dict[str, Any]`: Dictionary containing all the key-value pairs that were not used to update the instance.
        """
        to_remove = []
        for key, value in kwargs.items():
            if hasattr(self, key):
                setattr(self, key, value)
                to_remove.append(key)

        # Remove all the attributes that were updated, without modifying the input dict
        unused_kwargs = {key: value for key, value in kwargs.items() if key not in to_remove}
        return unused_kwargs

	# Copyright 2025 The HuggingFace Team. 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.

	import copy
	import json
	import os
	from dataclasses import dataclass
	from typing import Any, Union


	@dataclass
	class DistributedConfig:
	"""
	Base class for distributed configs
	"""

	enable_expert_parallel: bool = False
	# TODO: add tp_plan, pp_plan, device_mesh etc..

	@classmethod
	def from_dict(cls, config_dict, **kwargs):
	"""
	Constructs a DistributedConfig instance from a dictionary of parameters.
	Args:
	config_dict (Dict[str, Any]): Dictionary containing configuration parameters.
	**kwargs: Additional keyword arguments to override dictionary values.
	Returns:
	DistributedConfig: Instance of DistributedConfig constructed from the dictionary.
	"""
	config = cls(**config_dict)
	to_remove = []
	for key, value in kwargs.items():
	if hasattr(config, key):
	setattr(config, key, value)
	to_remove.append(key)
	for key in to_remove:
	kwargs.pop(key, None)
	return config

	# Copied from transformers.utils.quantization_config.QuantizationConfigMixin.to_json_file
	def to_json_file(self, json_file_path: Union[str, os.PathLike]):
	"""
	Save this instance to a JSON file.
	Args:
	json_file_path (`str` or `os.PathLike`):
	Path to the JSON file in which this configuration instance's parameters will be saved.
	use_diff (`bool`, optional, defaults to `True`):
	If set to `True`, only the difference between the config instance and the default
	`QuantizationConfig()` is serialized to JSON file.
	"""
	with open(json_file_path, "w", encoding="utf-8") as writer:
	config_dict = self.to_dict()
	json_string = json.dumps(config_dict, indent=2, sort_keys=True) + "\n"

	writer.write(json_string)

	def to_dict(self) -> dict[str, Any]:
	"""
	Serializes this instance to a Python dictionary. Returns:
	`Dict[str, Any]`: Dictionary of all the attributes that make up this configuration instance.
	"""
	return copy.deepcopy(self.__dict__)

	# Copied from transformers.utils.quantization_config.QuantizationConfigMixin.__iter__
	def __iter__(self):
	"""allows `dict(obj)` for situations where obj may be a dict or QuantizationConfigMixin"""
	for attr, value in copy.deepcopy(self.__dict__).items():
	yield attr, value

	# Copied from transformers.utils.quantization_config.QuantizationConfigMixin.__repr__
	def __repr__(self):
	return f"{self.__class__.__name__} {self.to_json_string()}"

	def to_json_string(self):
	"""
	Serializes this instance to a JSON formatted string.
	Returns:
	str: JSON formatted string representing the configuration instance.
	"""
	return json.dumps(self.__dict__, indent=2) + "\n"

	def update(self, **kwargs):
	"""
	Updates attributes of this class instance with attributes from `kwargs` if they match existing attributes,
	returning all the unused kwargs.
	Args:
	kwargs (`Dict[str, Any]`):
	Dictionary of attributes to tentatively update this class.
	Returns:
	`Dict[str, Any]`: Dictionary containing all the key-value pairs that were not used to update the instance.
	"""
	to_remove = []
	for key, value in kwargs.items():
	if hasattr(self, key):
	setattr(self, key, value)
	to_remove.append(key)

	# Remove all the attributes that were updated, without modifying the input dict
	unused_kwargs = {key: value for key, value in kwargs.items() if key not in to_remove}
	return unused_kwargs