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import ast
from typing import List, Tuple
from config.config import Config
class TrainConfig(Config):
RPN_PRE_NMS_TOP_N: int = 12000
RPN_POST_NMS_TOP_N: int = 2000
ANCHOR_SMOOTH_L1_LOSS_BETA: float = 1.0
PROPOSAL_SMOOTH_L1_LOSS_BETA: float = 1.0
BATCH_SIZE: int = 1
LEARNING_RATE: float = 0.001
MOMENTUM: float = 0.9
WEIGHT_DECAY: float = 0.0005
STEP_LR_SIZES: List[int] = [50000, 70000]
STEP_LR_GAMMA: float = 0.1
WARM_UP_FACTOR: float = 0.3333
WARM_UP_NUM_ITERS: int = 500
NUM_STEPS_TO_DISPLAY: int = 20
NUM_STEPS_TO_SNAPSHOT: int = 10000
NUM_STEPS_TO_FINISH: int = 90000
@classmethod
def setup(cls, image_min_side: float = None, image_max_side: float = None,
anchor_ratios: List[Tuple[int, int]] = None, anchor_sizes: List[int] = None, pooler_mode: str = None,
rpn_pre_nms_top_n: int = None, rpn_post_nms_top_n: int = None,
anchor_smooth_l1_loss_beta: float = None, proposal_smooth_l1_loss_beta: float = None,
batch_size: int = None, learning_rate: float = None, momentum: float = None, weight_decay: float = None,
step_lr_sizes: List[int] = None, step_lr_gamma: float = None,
warm_up_factor: float = None, warm_up_num_iters: int = None,
num_steps_to_display: int = None, num_steps_to_snapshot: int = None, num_steps_to_finish: int = None):
super().setup(image_min_side, image_max_side, anchor_ratios, anchor_sizes, pooler_mode)
if rpn_pre_nms_top_n is not None:
cls.RPN_PRE_NMS_TOP_N = rpn_pre_nms_top_n
if rpn_post_nms_top_n is not None:
cls.RPN_POST_NMS_TOP_N = rpn_post_nms_top_n
if anchor_smooth_l1_loss_beta is not None:
cls.ANCHOR_SMOOTH_L1_LOSS_BETA = anchor_smooth_l1_loss_beta
if proposal_smooth_l1_loss_beta is not None:
cls.PROPOSAL_SMOOTH_L1_LOSS_BETA = proposal_smooth_l1_loss_beta
if batch_size is not None:
cls.BATCH_SIZE = batch_size
if learning_rate is not None:
cls.LEARNING_RATE = learning_rate
if momentum is not None:
cls.MOMENTUM = momentum
if weight_decay is not None:
cls.WEIGHT_DECAY = weight_decay
if step_lr_sizes is not None:
cls.STEP_LR_SIZES = ast.literal_eval(step_lr_sizes)
if step_lr_gamma is not None:
cls.STEP_LR_GAMMA = step_lr_gamma
if warm_up_factor is not None:
cls.WARM_UP_FACTOR = warm_up_factor
if warm_up_num_iters is not None:
cls.WARM_UP_NUM_ITERS = warm_up_num_iters
if num_steps_to_display is not None:
cls.NUM_STEPS_TO_DISPLAY = num_steps_to_display
if num_steps_to_snapshot is not None:
cls.NUM_STEPS_TO_SNAPSHOT = num_steps_to_snapshot
if num_steps_to_finish is not None:
cls.NUM_STEPS_TO_FINISH = num_steps_to_finish
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