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save configs

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luni
2022-10-16 23:27:24 +00:00
parent 3a79508a8c
commit 8eaf090e4c
6 changed files with 77 additions and 44 deletions
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configs/config_ae_body.py
+1 -1
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@@ -1,6 +1,6 @@
from configs.config_base import config
config['gpu'] = '0'
config['gpu'] = '1'
config['lr'] = 0.0001
config['name'] = 'body_1'
configs/config_ae_curv.py
+5 -3
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@@ -1,10 +1,12 @@
from configs.config_base import config
config['gpu'] = '2'
config['gpu'] = '5'
config['lr'] = 0.001
config['name'] = 'curv_1_3' #'ae_curv_9'
config['name'] = 'curv_1_5' #'ae_curv_9'
config['notes'] = 'convnext + convnext, 16*8*32, ce loss. flattened latent dim of 128. trained on 100 garments. switched back to sparse CCE, normal one was giving NaN | \
try ssim loss'
try ssim loss | \
smaller model | \
'
config['cond_ae']['is_label'] = True
configs/config_ae_static.py
+9 -2
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@@ -1,10 +1,17 @@
from configs.config_base import config
config['gpu'] = '5'
config['gpu'] = '4'
config['lr'] = 0.0005
config['name'] = 'static_1'
config['name'] = 'static_1_5'
config['notes'] = 'convnext + convnext, add dense with tanh at the end of reverse convnext, | \
flattened latent dim to 128 | \
train on 100 garments | \
deeper model | \
larger batch size | \
'
config['cond_ae']['upscale_output'] = False
config['batch_size'] = 32
config['signature_dynamic'] = { 'id': (), }
configs/config_base.py
+24 -11
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@@ -4,6 +4,7 @@ config = dict()
config['batch_size'] = 4
config['train_dir'] = '/home/workspace/local-data/train'
config['valid_dir'] = '/home/workspace/local-data/valid'
config['test_dir'] = '/home/workspace/data/dataset/test_ready'
config['use_filled'] = False
config['resolution'] = 512
config['is_skirt'] = False
@@ -23,14 +24,26 @@ config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size']
config['cond_ae']['decoder_depths'] = [3, 3, 9, 3, 3]
config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 256, 128, 64, 16]
config['cond_ae_body'] = config['cond_ae']
# config['cond_ae_body'] = dict()
# config['cond_ae_body']['latent_dim'] = config['latent_dim']
# config['cond_ae_body']['kernel_size'] = 7
# config['cond_ae_body']['upscale_output'] = True
# config['cond_ae_body']['bottleneck_size'] = 512
# config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
# config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
# config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
# config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
# config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
# config['cond_ae'] = dict()
# config['cond_ae']['is_label'] = False
# config['cond_ae']['upscale_output'] = False
# config['cond_ae']['latent_dim'] = config['latent_dim']
# config['cond_ae']['kernel_size'] = 7
# config['cond_ae']['bottleneck_size'] = 64
# config['cond_ae']['encoder_depths'] = [3, 3, 3, 3, 3]
# config['cond_ae']['encoder_dims'] = [16, 32, 128, 128, config['cond_ae']['bottleneck_size']]
# config['cond_ae']['decoder_input'] = (8, 4, config['cond_ae']['bottleneck_size'])
# config['cond_ae']['decoder_depths'] = [3, 3, 3, 3, 3]
# config['cond_ae']['decoder_dims'] = [config['cond_ae']['bottleneck_size'], 128, 128, 32, 8]
# config['cond_ae_body'] = config['cond_ae']
config['cond_ae_body'] = dict()
config['cond_ae_body']['latent_dim'] = config['latent_dim']
config['cond_ae_body']['kernel_size'] = 7
config['cond_ae_body']['upscale_output'] = True
config['cond_ae_body']['bottleneck_size'] = 512
config['cond_ae_body']['encoder_depths'] = [3, 3, 9, 9, 3, 3]
config['cond_ae_body']['encoder_dims'] = [32, 64, 128, 256, 256, config['cond_ae_body']['bottleneck_size']]
config['cond_ae_body']['decoder_input'] = (4, 2, config['cond_ae_body']['bottleneck_size'])
config['cond_ae_body']['decoder_depths'] = [3, 3, 9, 3]
config['cond_ae_body']['decoder_dims'] = [config['cond_ae_body']['bottleneck_size'], 128, 64, 16]
configs/config_cvae.py
+26 -18
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@@ -1,23 +1,31 @@
from configs.config_base import config
config['gpu'] = '2'
config['name'] = 'cvae_19_skirt'
config['gpu'] = '4'
config['name'] = 'v2_4'
config['notes'] = '\
offsets over average unposed garment. remove global orientation (in posed body input and in pose_shape parameters. \
retrained body encoder with deoriented bodies \
use mean l2 loss. small batch. l2 * 1000, balancing to 1 from 0.01\
fixed gender issue and retrained body encoder, FINAL\
remove shape from unposed garment\
training on 100 garments with offsets over the average of these\
fixed autoencoders!!!!!!!!!\
cvae only loads encoders instead AEs\
offsets over average unposed garment. remove global orientation (in posed body input and in pose_shape parameters. | \
retrained body encoder with deoriented bodies | \
use mean l2 loss. small batch. l2 * 1000, balancing to 1 from 0.01 | \
fixed gender issue and retrained body encoder, FINAL | \
remove shape from unposed garment | \
training on 100 garments with offsets over the average of these | \
fixed autoencoders!!!!!!!!! | \
cvae only loads encoders instead AEs | \
increase balancing coeff sooner | \
'
config['dataset_in_memory'] = True
config['dataset_in_memory'] = False
# DON'T FORGET TO RESET SSIM LOSS USAGE
# DON'T FORGET TO CHECK MODEL LOADING
# DON'T FORGET TO CHECK IF STORE IN MEMORY
# DON'T FORGET TO CHECK REG LOSS COEFF
# DON'T FORGET TO LOAD FINAL UPSCALER UNLESS HAVE LEVEL 512
config['resolution'] = 512
config['is_skirt'] = True
config['reg_loss_coeff'] = 0 # set to 0 if don't want to use edge+collision
config['is_skirt'] = False
config['reg_loss_coeff'] = 0.1 # set to 0 if don't want to use edge+collision
if config['resolution'] != 512:
config['notes'] += '\
@@ -50,14 +58,14 @@ if config['resolution'] != 512:
config['signature_static']['uv_mask' + res_modifier] = (config['resolution'], config['resolution']//2)
if config['resolution'] == 512:
config['avg_garment_path'] = 'custom_data/train_skirt_25_2_no_shape_avg_uv.npy'
config['avg_garment_path'] = 'custom_data/train_no_shape_avg_uv.npy'
else:
config['avg_garment_path'] = ''
config['static_model'] = 'checkpoints/ae_static_7_2_skirt_x'
config['body_model'] = 'checkpoints/ae_body_10_3_skirt_x'
config['curvature_model'] = 'checkpoints/ae_curv_9_skirt_x'
config['upscale_enhancer'] = 'checkpoints/up_2_3_skirt_x_d32'
config['static_model'] = 'checkpoints/static_1'
config['body_model'] = 'checkpoints/body_1'
config['curvature_model'] = 'checkpoints/curv_1'
config['upscale_enhancer'] = ''
config['freeze_encoders'] = True
config['cvae'] = dict()
configs/config_pyramid.py
+12 -9
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@@ -1,7 +1,7 @@
from configs.config_base import config
config['gpu'] = '1'
config['name'] = 'cvae_pyr_7_32_64_128_256_512'
config['gpu'] = '3'
config['name'] = 'pyr_1_32_64_128'
config['notes'] = '\
offsets over average unposed garment. remove global orientation (in posed body input and in pose_shape parameters. | \
retrained body encoder with deoriented bodies | \
@@ -56,9 +56,9 @@ config['pyramid'] = dict()
config['pyramid']['is_label'] = False
config['pyramid']['latent_dim'] = config['latent_dim']
config['pyramid']['resolutions'] = [32, 64, 128, 256, 512]
config['pyramid']['resolutions'] = [32, 64, 128]
config['pyramid']['loss_weights'] = [1,1,1,1,1]
config['pyramid']['pretrained_pyramid'] = 'checkpoints/cvae_pyr_7_32_64_128_256_50k'
config['pyramid']['pretrained_pyramid'] = 'checkpoints/pyr_1_32_64'
for res in config['pyramid']['resolutions']:
if res != 512:
@@ -73,13 +73,16 @@ for res in config['pyramid']['resolutions']:
# config['pyramid']['static_model'] = 'checkpoints/ae_static_7_2_x'
# config['pyramid']['body_model'] = 'checkpoints/ae_body_9_x'
# config['pyramid']['curvature_model'] = 'checkpoints/ae_curv_9_x'
# config['pyramid']['static_model'] = 'checkpoints/static_1'
# config['pyramid']['body_model'] = 'checkpoints/body_1'
# config['pyramid']['curvature_model'] = 'checkpoints/curv_1'
config['pyramid']['static_model'] = ''
config['pyramid']['body_model'] = ''
config['pyramid']['curvature_model'] = ''
config['pyramid']['freeze_encoders'] = True
config['avg_garment_path'] = ''
config['pyramid']['final_upscale_enhancer'] = ''
config['pyramid']['final_upscale_enhancer'] = 'checkpoints/128_512_3'
config['pyramid']['levels'] = []
@@ -108,7 +111,7 @@ for res in config['pyramid']['resolutions']:
level['decoder_depths'] = [9, 9, 9, 9]
level['decoder_dims'] = [256, 128, 64, 16]
level['avg_garment_path'] = ''
level['upscale_enhancer'] = 'checkpoints/up_3_d256_512_2'
level['upscale_enhancer'] = ''#'checkpoints/up_3_d256_512_2'
level['upscale_enhancer_freeze'] = True
config['pyramid']['levels'].append(level)
elif res == 128:
@@ -122,7 +125,7 @@ for res in config['pyramid']['resolutions']:
level['decoder_depths'] = [16, 16, 9, 9]
level['decoder_dims'] = [256, 256, 128, 64]
level['avg_garment_path'] = ''
level['upscale_enhancer'] = 'checkpoints/up_3_d128_256_2'
level['upscale_enhancer'] = ''#'checkpoints/up_3_d128_256_2'
level['upscale_enhancer_freeze'] = True
config['pyramid']['levels'].append(level)
elif res == 64:
@@ -136,7 +139,7 @@ for res in config['pyramid']['resolutions']:
level['decoder_depths'] = [27, 27, 16]
level['decoder_dims'] = [256, 256, 256]
level['avg_garment_path'] = ''
level['upscale_enhancer'] = 'checkpoints/up_3_d64_128_2'
level['upscale_enhancer'] = 'checkpoints/64_512_2'#checkpoints/up_3_d64_128_2'
level['upscale_enhancer_freeze'] = False
config['pyramid']['levels'].append(level)
elif res == 32:
@@ -150,7 +153,7 @@ for res in config['pyramid']['resolutions']:
level['decoder_depths'] = [27, 27]
level['decoder_dims'] = [256, 256]
level['avg_garment_path'] = ''
level['upscale_enhancer'] = 'checkpoints/up_3_d32_64_2'
level['upscale_enhancer'] = 'checkpoints/32_512_4'#'checkpoints/up_3_d32_64_2'
level['upscale_enhancer_freeze'] = True
config['pyramid']['levels'].append(level)
else: