# Copyright 2021 cstsunfu. 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.
from typing import Dict
import torch.nn as nn
import torch.optim as optim
from dlk.utils.config import BaseConfig
from . import optimizer_register, optimizer_config_register, BaseOptimizer
[docs]@optimizer_config_register("sgd")
class SGDOptimizerConfig(BaseConfig):
"""Config for SGDOptimizer
Config Example:
>>> {
>>> "config": {
>>> "lr": 1e-3,
>>> "momentum": 0.9,
>>> "dampening": 0,
>>> "weight_decay": 0,
>>> "nesterov":false,
>>> "optimizer_special_groups": {
>>> // "order": ['decoder', 'bias'], // the group order, if the para is in decoder & is in bias, set to decoder. The order name is set to the group name
>>> // "bias": {
>>> // "config": {
>>> // "weight_decay": 0
>>> // },
>>> // "pattern": ["bias", "LayerNorm.bias", "LayerNorm.weight"]
>>> // },
>>> // "decoder": {
>>> // "config": {
>>> // "lr": 1e-3
>>> // },
>>> // "pattern": ["decoder"]
>>> // },
>>> }
>>> "name": "default" // default group name
>>> },
>>> "_name": "sgd",
>>> }
"""
def __init__(self, config: Dict):
super(SGDOptimizerConfig, self).__init__(config)
self.config = config['config']
self.post_check(self.config, used=[
"lr",
"momentum",
"dampening",
"weight_decay",
"nesterov",
"optimizer_special_groups",
])
[docs]@optimizer_register("sgd")
class SGDOptimizer(BaseOptimizer):
"""wrap for optim.SGD"""
def __init__(self, model: nn.Module, config: SGDOptimizerConfig):
super(SGDOptimizer, self).__init__()
self.config = config.config
self.model = model
self.optimizer = optim.SGD
[docs] def get_optimizer(self)->optim.SGD:
"""return the initialized SGD optimizer
Returns:
SGD Optimizer
"""
return self.init_optimizer(optim.SGD, self.model, self.config)