backup

configs/config_pyramid.py

@@ -1,27 +1,38 @@
 from configs.config_base import config
 
-config['gpu'] = '1'
-config['name'] = 'cvae_pyr_4_4'
+config['gpu'] = '2'
+config['name'] = 'cvae_pyr_6_32_64_128_3_x'
 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!!!!!!!!!\
-common condition encoders for all levels, only run once\
-full res loss on each level\
-all higher levels are added to the output of first level\
-using custom MLP upscale enhancement\
-layers 32 and 512\
-try loading weights from previous trainings\
+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!!!!!!!!! | \
+common condition encoders for all levels, only run once | \
+full res loss on each level | \
+all higher levels are added to the output of first level | \
+using custom MLP upscale enhancement | \
+layers 32, 64, 128 | \
+testing plotting | \
+only train highest level, all other use from pretrained pyramids with one less level | \
+maybe upscale enhancer was not frozen? --> fixed pretrained approach | \
+upscale from level to level, not to final res, only at the end to final res  | \
+updated upscale enhancers | \
+try an old trained model as pretraining for new level | \
+ \
 '
-config['dataset_in_memory'] = False
+
+# DON'T FORGET TO RESET SSIM LOSS USAGE
+# DON'T FORGET TO CHECK MODEL LOADING
+
+config['dataset_in_memory'] = True
 config['resolution'] = None
 
 config['lr'] = 0.0001
 config['starting_balancing_coeff'] = 0.0001
+config['reg_loss_coeff'] = 0 # set to 0 if don't want to use edge+collision
 
 config['signature_dynamic'] = { 'id': (),
                           'pose_shape': (72 + 11,),
@@ -41,7 +52,9 @@ config['pyramid'] = dict()
 config['pyramid']['is_label'] = False
 config['pyramid']['latent_dim'] = config['latent_dim']
 
-config['pyramid']['resolutions'] = [32, 512]
+config['pyramid']['resolutions'] = [32, 64, 128]
+config['pyramid']['loss_weights'] = [1,1,1]
+config['pyramid']['pretrained_pyramid'] = 'checkpoints/cvae_pyr_6_32_64'
 
 for res in config['pyramid']['resolutions']:
   if res != 512:
@@ -53,12 +66,16 @@ for res in config['pyramid']['resolutions']:
       config['signature_static']['uv_mask' + res_modifier] = (res, res//2)
 
 
-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/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'] = ''
+config['pyramid']['body_model'] = ''
+config['pyramid']['curvature_model'] = ''
 config['pyramid']['freeze_encoders'] = True
 
 config['avg_garment_path'] = ''
+config['pyramid']['final_upscale_enhancer'] = 'checkpoints/up_3_d128_256'
 
 
 config['pyramid']['levels'] = []
@@ -87,7 +104,22 @@ 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_2_3_d128'
+    level['upscale_enhancer'] = ''
+    level['upscale_enhancer_freeze'] = True
+    config['pyramid']['levels'].append(level)
+  elif res == 64:
+    level = dict()
+    level['resolution'] = 64
+    level['latent_dim'] = config['latent_dim']
+    level['kernel_size'] = 5
+    level['encoder_depths'] = [27, 27, 16]
+    level['encoder_dims'] = [256, 256, 256]
+    level['decoder_input'] = (4, 2, 256)
+    level['decoder_depths'] = [27, 27, 16]
+    level['decoder_dims'] = [256, 256, 256]
+    level['avg_garment_path'] = ''
+    level['upscale_enhancer'] = 'checkpoints/up_3_d64_128'
+    level['upscale_enhancer_freeze'] = False
     config['pyramid']['levels'].append(level)
   elif res == 32:
     level = dict()
@@ -100,7 +132,8 @@ 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_2_3'
+    level['upscale_enhancer'] = 'checkpoints/up_3_d32_64'
+    level['upscale_enhancer_freeze'] = True
     config['pyramid']['levels'].append(level)
   else:
     raise NotImplementedError