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import math
def get_cosine_schedule_with_warmup_lr_lambda(
current_step: int,
*,
num_warmup_steps: int | float,
num_training_steps: int,
num_cycles: float = 0.5,
final_lr_ratio: float = 0.0,
):
if 0 < num_warmup_steps < 1: # float mode
num_warmup_steps = int(num_warmup_steps * num_training_steps)
if current_step < num_warmup_steps:
return float(current_step) / float(max(1, num_warmup_steps))
progress = float(current_step - num_warmup_steps) / float(
max(1, num_training_steps - num_warmup_steps)
)
return max(
final_lr_ratio,
0.5 * (1.0 + math.cos(math.pi * float(num_cycles) * 2.0 * progress)),
)
def get_constant_schedule_with_warmup_lr_lambda(
current_step: int,
*,
num_warmup_steps: int | float,
num_training_steps: int | None = None,
):
if 0 < num_warmup_steps < 1: # float mode
num_warmup_steps = int(num_warmup_steps * num_training_steps)
if current_step < num_warmup_steps:
return float(current_step) / float(max(1, num_warmup_steps))
return 1.0
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