本文整理匯總了Python中detectron.core.config.cfg.SOLVER屬性的典型用法代碼示例。如果您正苦於以下問題：Python cfg.SOLVER屬性的具體用法？Python cfg.SOLVER怎麽用？Python cfg.SOLVER使用的例子？那麽, 這裏精選的屬性代碼示例或許可以為您提供幫助。您也可以進一步了解該屬性所在類detectron.core.config.cfg的用法示例。
在下文中一共展示了cfg.SOLVER屬性的8個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: get_lr_at_iter
# 需要導入模塊: from detectron.core.config import cfg [as 別名]
# 或者: from detectron.core.config.cfg import SOLVER [as 別名]
def get_lr_at_iter(it):
"""Get the learning rate at iteration it according to the cfg.SOLVER
settings.
"""
lr = get_lr_func()(it)
if it < cfg.SOLVER.WARM_UP_ITERS:
method = cfg.SOLVER.WARM_UP_METHOD
if method == 'constant':
warmup_factor = cfg.SOLVER.WARM_UP_FACTOR
elif method == 'linear':
alpha = it / cfg.SOLVER.WARM_UP_ITERS
warmup_factor = cfg.SOLVER.WARM_UP_FACTOR * (1 - alpha) + alpha
else:
raise KeyError('Unknown SOLVER.WARM_UP_METHOD: {}'.format(method))
lr *= warmup_factor
return np.float32(lr)
# ---------------------------------------------------------------------------- #
# Learning rate policy functions
# ---------------------------------------------------------------------------- # 示例2: lr_func_steps_with_decay
# 需要導入模塊: from detectron.core.config import cfg [as 別名]
# 或者: from detectron.core.config.cfg import SOLVER [as 別名]
def lr_func_steps_with_decay(cur_iter):
"""For cfg.SOLVER.LR_POLICY = 'steps_with_decay'
Change the learning rate specified iterations based on the formula
lr = base_lr * gamma ** lr_step_count.
Example:
cfg.SOLVER.MAX_ITER: 90
cfg.SOLVER.STEPS: [0, 60, 80]
cfg.SOLVER.BASE_LR: 0.02
cfg.SOLVER.GAMMA: 0.1
for cur_iter in [0, 59] use 0.02 = 0.02 * 0.1 ** 0
in [60, 79] use 0.002 = 0.02 * 0.1 ** 1
in [80, inf] use 0.0002 = 0.02 * 0.1 ** 2
"""
ind = get_step_index(cur_iter)
return cfg.SOLVER.BASE_LR * cfg.SOLVER.GAMMA ** ind 示例3: lr_func_steps_with_lrs
# 需要導入模塊: from detectron.core.config import cfg [as 別名]
# 或者: from detectron.core.config.cfg import SOLVER [as 別名]
def lr_func_steps_with_lrs(cur_iter):
"""For cfg.SOLVER.LR_POLICY = 'steps_with_lrs'
Change the learning rate to specified values at specified iterations.
Example:
cfg.SOLVER.MAX_ITER: 90
cfg.SOLVER.STEPS: [0, 60, 80]
cfg.SOLVER.LRS: [0.02, 0.002, 0.0002]
for cur_iter in [0, 59] use 0.02
in [60, 79] use 0.002
in [80, inf] use 0.0002
"""
ind = get_step_index(cur_iter)
return cfg.SOLVER.LRS[ind] 示例4: lr_func_step
# 需要導入模塊: from detectron.core.config import cfg [as 別名]
# 或者: from detectron.core.config.cfg import SOLVER [as 別名]
def lr_func_step(cur_iter):
"""For cfg.SOLVER.LR_POLICY = 'step'
"""
return (
cfg.SOLVER.BASE_LR *
cfg.SOLVER.GAMMA ** (cur_iter // cfg.SOLVER.STEP_SIZE))
# ---------------------------------------------------------------------------- #
# Helpers
# ---------------------------------------------------------------------------- # 示例5: get_step_index
# 需要導入模塊: from detectron.core.config import cfg [as 別名]
# 或者: from detectron.core.config.cfg import SOLVER [as 別名]
def get_step_index(cur_iter):
"""Given an iteration, find which learning rate step we're at."""
assert cfg.SOLVER.STEPS[0] == 0, 'The first step should always start at 0.'
steps = cfg.SOLVER.STEPS + [cfg.SOLVER.MAX_ITER]
for ind, step in enumerate(steps): # NoQA
if cur_iter < step:
break
return ind - 1 示例6: lr_func_step
# 需要導入模塊: from detectron.core.config import cfg [as 別名]
# 或者: from detectron.core.config.cfg import SOLVER [as 別名]
def lr_func_step(cur_iter):
"""For cfg.SOLVER.LR_POLICY = 'step'
"""
return (
cfg.SOLVER.BASE_LR *
cfg.SOLVER.GAMMA ** (cur_iter // cfg.SOLVER.STEP_SIZE)) 示例7: lr_func_cosine_decay
# 需要導入模塊: from detectron.core.config import cfg [as 別名]
# 或者: from detectron.core.config.cfg import SOLVER [as 別名]
def lr_func_cosine_decay(cur_iter):
"""For cfg.SOLVER.LR_POLICY = 'cosine_decay'
"""
iter_frac = float(cur_iter) / cfg.SOLVER.MAX_ITER
cos_frac = 0.5 * (np.cos(np.pi * iter_frac) + 1)
return cfg.SOLVER.BASE_LR * cos_frac 示例8: get_lr_func
# 需要導入模塊: from detectron.core.config import cfg [as 別名]
# 或者: from detectron.core.config.cfg import SOLVER [as 別名]
def get_lr_func():
policy = 'lr_func_' + cfg.SOLVER.LR_POLICY
if policy not in globals():
raise NotImplementedError(
'Unknown LR policy: {}'.format(cfg.SOLVER.LR_POLICY))
else:
return globals()[policy]