# Copyright 2020 Huawei Technologies Co., Ltd
#
# 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.
# ============================================================================
"""
network config setting, will be used in train.py and eval.py
"""
from easydict import EasyDict as edict

# config for vgg16, cifar10
cifar_cfg = edict({
    'num_classes': 10,
    "lr": 0.01,
    'lr_init': 0.01,
    'lr_max': 0.1,
    "lr_epochs": '30,60,90,120',
    "lr_scheduler": "step",
    'warmup_epochs': 5,
    'batch_size': 64,
    'max_epoch': 70,
    'momentum': 0.9,
    'weight_decay': 5e-4,
    "loss_scale": 1.0,
    "label_smooth": 0,
    "label_smooth_factor": 0,
    'buffer_size': 10,
    "image_size": '224,224',
    'pad_mode': 'same',
    'padding': 0,
    'has_bias': False,
    "batch_norm": True,
    'keep_checkpoint_max': 10
})

# config for vgg16, imagenet2012
imagenet_cfg = edict({
    'num_classes': 1000,
    "lr": 0.01,
    'lr_init': 0.01,
    'lr_max': 0.1,
    "lr_epochs": '30,60,90,120',
    "lr_scheduler": 'cosine_annealing',
    'warmup_epochs': 0,
    'batch_size': 32,
    'max_epoch': 150,
    'momentum': 0.9,
    'weight_decay': 1e-4,
    "loss_scale": 1024,
    "label_smooth": 1,
    "label_smooth_factor": 0.1,
    'buffer_size': 10,
    "image_size": '224,224',
    'pad_mode': 'pad',
    'padding': 1,
    'has_bias': True,
    "batch_norm": False,
    'keep_checkpoint_max': 10
})