You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
115 lines
3.5 KiB
115 lines
3.5 KiB
2 years ago
|
"""
|
||
|
|
@Time : 2021-01-21 10:37:36
|
||
|
|
@File : defaults.py
|
||
|
|
@Author : Abtion
|
||
|
|
@Email : abtion{at}outlook.com
|
||
|
|
"""
|
||
|
|
from yacs.config import CfgNode as CN
|
||
|
|
|
||
|
|
# -----------------------------------------------------------------------------
|
||
|
|
# Convention about Training / Test specific parameters
|
||
|
|
# -----------------------------------------------------------------------------
|
||
|
|
# Whenever an argument can be either used for training or for testing, the
|
||
|
|
# corresponding name will be post-fixed by a _TRAIN for a training parameter,
|
||
|
|
# or _TEST for a test-specific parameter.
|
||
|
|
# For example, the number of images during training will be
|
||
|
|
# IMAGES_PER_BATCH_TRAIN, while the number of images for testing will be
|
||
|
|
# IMAGES_PER_BATCH_TEST
|
||
|
|
|
||
|
|
# -----------------------------------------------------------------------------
|
||
|
|
# Config definition
|
||
|
|
# -----------------------------------------------------------------------------
|
||
|
|
|
||
|
|
_C = CN()
|
||
|
|
|
||
|
|
_C.MODEL = CN()
|
||
|
|
_C.MODEL.DEVICE = "cpu"
|
||
|
|
_C.MODEL.GPU_IDS = [0]
|
||
|
|
_C.MODEL.NUM_CLASSES = 10
|
||
|
|
_C.MODEL.BERT_CKPT = 'bert-base-chinese'
|
||
|
|
_C.MODEL.NAME = ''
|
||
|
|
_C.MODEL.WEIGHTS = ''
|
||
|
|
_C.MODEL.HYPER_PARAMS = []
|
||
|
|
|
||
|
|
# -----------------------------------------------------------------------------
|
||
|
|
# INPUT
|
||
|
|
# -----------------------------------------------------------------------------
|
||
|
|
_C.INPUT = CN()
|
||
|
|
# Max length of input text.
|
||
|
|
_C.INPUT.MAX_LEN = 512
|
||
|
|
|
||
|
|
|
||
|
|
# -----------------------------------------------------------------------------
|
||
|
|
# Dataset
|
||
|
|
# -----------------------------------------------------------------------------
|
||
|
|
_C.DATASETS = CN()
|
||
|
|
# List of the dataset names for training, as present in paths_catalog.py
|
||
|
|
_C.DATASETS.TRAIN = ""
|
||
|
|
# List of the dataset names for validation, as present in paths_catalog.py
|
||
|
|
_C.DATASETS.VALID = ""
|
||
|
|
# List of the dataset names for testing, as present in paths_catalog.py
|
||
|
|
_C.DATASETS.TEST = ""
|
||
|
|
|
||
|
|
# -----------------------------------------------------------------------------
|
||
|
|
# DataLoader
|
||
|
|
# -----------------------------------------------------------------------------
|
||
|
|
_C.DATALOADER = CN()
|
||
|
|
# Number of data loading threads
|
||
|
|
_C.DATALOADER.NUM_WORKERS = 4
|
||
|
|
|
||
|
|
# ---------------------------------------------------------------------------- #
|
||
|
|
# Solver
|
||
|
|
# ---------------------------------------------------------------------------- #
|
||
|
|
_C.SOLVER = CN()
|
||
|
|
_C.SOLVER.OPTIMIZER_NAME = "AdamW"
|
||
|
|
|
||
|
|
_C.SOLVER.MAX_EPOCHS = 50
|
||
|
|
|
||
|
|
_C.SOLVER.BASE_LR = 0.001
|
||
|
|
_C.SOLVER.BIAS_LR_FACTOR = 2
|
||
|
|
|
||
|
|
_C.SOLVER.MOMENTUM = 0.9
|
||
|
|
|
||
|
|
_C.SOLVER.WEIGHT_DECAY = 0.0005
|
||
|
|
_C.SOLVER.WEIGHT_DECAY_BIAS = 0
|
||
|
|
|
||
|
|
_C.SOLVER.GAMMA = 0.9999
|
||
|
|
_C.SOLVER.STEPS = (10,)
|
||
|
|
_C.SOLVER.SCHED = "WarmupExponentialLR"
|
||
|
|
_C.SOLVER.WARMUP_FACTOR = 0.01
|
||
|
|
_C.SOLVER.WARMUP_ITERS = 2
|
||
|
|
_C.SOLVER.WARMUP_EPOCHS = 1024
|
||
|
|
_C.SOLVER.WARMUP_METHOD = "linear"
|
||
|
|
_C.SOLVER.DELAY_ITERS = 0
|
||
|
|
_C.SOLVER.ETA_MIN_LR = 3e-7
|
||
|
|
_C.SOLVER.MAX_ITER = 10
|
||
|
|
_C.SOLVER.INTERVAL = 'step'
|
||
|
|
|
||
|
|
_C.SOLVER.CHECKPOINT_PERIOD = 10
|
||
|
|
_C.SOLVER.LOG_PERIOD = 100
|
||
|
|
_C.SOLVER.ACCUMULATE_GRAD_BATCHES = 1
|
||
|
|
# Number of images per batch
|
||
|
|
# This is global, so if we have 8 GPUs and IMS_PER_BATCH = 16, each GPU will
|
||
|
|
# see 2 images per batch
|
||
|
|
_C.SOLVER.BATCH_SIZE = 16
|
||
|
|
|
||
|
|
|
||
|
|
_C.TEST = CN()
|
||
|
|
_C.TEST.BATCH_SIZE = 8
|
||
|
|
_C.TEST.CKPT_FN = ""
|
||
|
|
|
||
|
|
# ---------------------------------------------------------------------------- #
|
||
|
|
# Task specific
|
||
|
|
# ---------------------------------------------------------------------------- #
|
||
|
|
_C.TASK = CN()
|
||
|
|
_C.TASK.NAME = "CSC"
|
||
|
|
|
||
|
|
|
||
|
|
# ---------------------------------------------------------------------------- #
|
||
|
|
# Misc options
|
||
|
|
# ---------------------------------------------------------------------------- #
|
||
|
|
_C.OUTPUT_DIR = ""
|
||
|
|
_C.MODE = ['train', 'test']
|
||
|
|
|
||
|
|
|