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73 lines
2.9 KiB
73 lines
2.9 KiB
# Copyright (c) ByteDance, Inc. and its affiliates. |
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# All rights reserved. |
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# |
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# This source code is licensed under the license found in the |
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# LICENSE file in the root directory of this source tree. |
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import math |
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from pprint import pformat |
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def lr_wd_annealing(optimizer, peak_lr, wd, wd_end, cur_it, wp_it, max_it): |
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wp_it = round(wp_it) |
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if cur_it < wp_it: |
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cur_lr = 0.005 * peak_lr + 0.995 * peak_lr * cur_it / wp_it |
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else: |
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ratio = (cur_it - wp_it) / (max_it-1 - wp_it) |
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cur_lr = 0.001 * peak_lr + 0.999 * peak_lr * (0.5 + 0.5 * math.cos(math.pi * ratio)) |
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ratio = cur_it / (max_it-1) |
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cur_wd = wd_end + (wd - wd_end) * (0.5 + 0.5 * math.cos(math.pi * ratio)) |
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inf = 1e6 |
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min_lr, max_lr = inf, -1 |
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min_wd, max_wd = inf, -1 |
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for param_group in optimizer.param_groups: |
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param_group['lr'] = cur_lr * param_group.get('lr_scale', 1) # 'lr_scale' could be assigned |
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max_lr = max(max_lr, param_group['lr']) |
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min_lr = min(min_lr, param_group['lr']) |
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param_group['weight_decay'] = cur_wd * param_group.get('weight_decay_scale', 1) |
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max_wd = max(max_wd, param_group['weight_decay']) |
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if param_group['weight_decay'] > 0: |
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min_wd = min(min_wd, param_group['weight_decay']) |
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if min_lr == inf: min_lr = -1 |
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if min_wd == inf: min_wd = -1 |
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return min_lr, max_lr, min_wd, max_wd |
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def get_param_groups(model, nowd_keys=(), lr_scale=0.0): |
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with_lr_scale = hasattr(model, 'get_layer_id_and_scale_exp') and 0 < lr_scale < 1 |
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print(f'[get_ft_param_groups][lr decay] with_lr_scale={with_lr_scale}, ft_lr_scale={lr_scale}') |
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para_groups, para_groups_dbg = {}, {} |
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for name, para in model.named_parameters(): |
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if not para.requires_grad: |
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continue # frozen weights |
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if len(para.shape) == 1 or name.endswith('.bias') or any(k in name for k in nowd_keys): |
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wd_scale, group_name = 0., 'no_decay' |
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else: |
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wd_scale, group_name = 1., 'decay' |
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if with_lr_scale: |
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layer_id, scale_exp = model.get_layer_id_and_scale_exp(name) |
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group_name = f'layer{layer_id}_' + group_name |
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cur_lr_scale = lr_scale ** scale_exp |
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dbg = f'[layer {layer_id}][sc = {lr_scale} ** {scale_exp}]' |
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else: |
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cur_lr_scale = 1 |
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dbg = f'[no scale]' |
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if group_name not in para_groups: |
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para_groups[group_name] = {'params': [], 'weight_decay_scale': wd_scale, 'lr_scale': cur_lr_scale} |
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para_groups_dbg[group_name] = {'params': [], 'weight_decay_scale': wd_scale, 'lr_scale': dbg} |
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para_groups[group_name]['params'].append(para) |
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para_groups_dbg[group_name]['params'].append(name) |
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for g in para_groups_dbg.values(): |
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g['params'] = pformat(', '.join(g['params']), width=200) |
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print(f'[get_ft_param_groups] param groups = \n{pformat(para_groups_dbg, indent=2, width=250)}\n') |
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return list(para_groups.values())
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