Spaces:
Runtime error
Runtime error
| # Copyright 2024 EPFL and Apple Inc. | |
| # | |
| # 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. | |
| # -------------------------------------------------------- | |
| # Based on DINO code base | |
| # https://github.com/facebookresearch/dino | |
| # -------------------------------------------------------- | |
| import numpy as np | |
| import math | |
| def cosine_scheduler(base_value, final_value, epochs, niter_per_ep, warmup_epochs=0, | |
| start_warmup_value=0, warmup_steps=-1): | |
| warmup_schedule = np.array([]) | |
| warmup_iters = warmup_epochs * niter_per_ep | |
| if warmup_steps > 0: | |
| warmup_iters = warmup_steps | |
| print("Set warmup steps = %d" % warmup_iters) | |
| if warmup_epochs > 0 or warmup_steps > 0: | |
| warmup_schedule = np.linspace(start_warmup_value, base_value, warmup_iters) | |
| iters = np.arange(epochs * niter_per_ep - warmup_iters) | |
| schedule = np.array( | |
| [final_value + 0.5 * (base_value - final_value) * (1 + math.cos(math.pi * i / (len(iters)))) for i in iters]) | |
| schedule = np.concatenate((warmup_schedule, schedule)) | |
| assert len(schedule) == epochs * niter_per_ep | |
| return schedule | |
| def constant_scheduler(base_value, epochs, niter_per_ep): | |
| return base_value * np.ones(epochs*niter_per_ep) | |
| def inverse_sqrt_scheduler(base_value, final_value, epochs, niter_per_ep, warmup_epochs=0, | |
| start_warmup_value=0, warmup_steps=-1, | |
| cooldown_epochs=0, cooldown_steps=-1, | |
| timescale=10_000): | |
| warmup_iters = warmup_epochs * niter_per_ep | |
| if warmup_steps > 0: | |
| warmup_iters = warmup_steps | |
| print("Set warmup steps = %d" % warmup_iters) | |
| cooldown_iters = cooldown_epochs * niter_per_ep | |
| if cooldown_steps > 0: | |
| cooldown_iters = cooldown_steps | |
| print("Set cooldown steps = %d" % cooldown_iters) | |
| # Warmup schedule | |
| if warmup_epochs > 0 or warmup_steps > 0: | |
| warmup_schedule = np.linspace(start_warmup_value, base_value, warmup_iters) | |
| else: | |
| warmup_schedule = np.array([]) | |
| # Inverse square-root LR schedule | |
| iters = np.arange(epochs * niter_per_ep - warmup_iters - cooldown_iters) | |
| if base_value == final_value: | |
| schedule = base_value * np.ones(len(iters)) | |
| else: | |
| schedule = base_value / np.sqrt((iters + timescale) / timescale) | |
| # Cooldown schedule | |
| if cooldown_epochs > 0 or cooldown_steps > 0: | |
| cooldown_schedule = np.linspace(schedule[-1], final_value, cooldown_iters) | |
| else: | |
| cooldown_schedule = np.array([]) | |
| schedule = np.concatenate((warmup_schedule, schedule, cooldown_schedule)) | |
| assert len(schedule) == epochs * niter_per_ep | |
| return schedule |