<jupyter_start><jupyter_text>MLP with IC, 2 class gender<jupyter_code>config_path = "./training-results/gender-add-residual-true-add-ic-true/training/imdb-wiki-adience/models/ResMLP/0806_111344/config.json"
config = read_json(config_path)

model = ResMLP(**config["arch"]["args"])
pprint(sum(p.numel() for p in model.parameters()))
pprint(config["arch"]["args"])
model<jupyter_output>877602
{'add_IC': True,
 'add_residual': True,
 'dropout': 0.05,
 'num_blocks': 4,
 'num_classes': 2,
 'num_initial_features': 512,
 'num_residuals_per_block': 1}<jupyter_text>plain MLP, 2 class gender<jupyter_code>config_path = "./training-results/gender-add-residual-false-add-ic-false/training/imdb-wiki-adience/models/ResMLP/0806_143330/config.json"
config = read_json(config_path)

model = ResMLP(**config["arch"]["args"])
pprint(sum(p.numel() for p in model.parameters()))
pprint(config["arch"]["args"])
model<jupyter_output>872866
{'add_IC': False,
 'add_residual': False,
 'dropout': 0.05,
 'num_blocks': 4,
 'num_classes': 2,
 'num_initial_features': 512,
 'num_residuals_per_block': 1}<jupyter_text>MLP with IC, 8 class age<jupyter_code>config_path = "./training-results/age-8-add-residual-true-add-ic-true/training/imdb-wiki-adience/models/ResMLP/0806_102733/config.json"
config = read_json(config_path)

model = ResMLP(**config["arch"]["args"])
pprint(sum(p.numel() for p in model.parameters()))
pprint(config["arch"]["args"])
model<jupyter_output>825736
{'add_IC': True,
 'add_residual': True,
 'dropout': 0.05,
 'num_blocks': 2,
 'num_classes': 8,
 'num_initial_features': 512,
 'num_residuals_per_block': 1}<jupyter_text>plain MLP, 8 class age<jupyter_code>config_path = "./training-results/age-8-add-residual-false-add-ic-false/training/imdb-wiki-adience/models/ResMLP/0805_164830/config.json"
config = read_json(config_path)

model = ResMLP(**config["arch"]["args"])
pprint(sum(p.numel() for p in model.parameters()))
pprint(config["arch"]["args"])
model<jupyter_output>822152
{'add_IC': False,
 'add_residual': False,
 'dropout': 0.05,
 'num_blocks': 2,
 'num_classes': 8,
 'num_initial_features': 512,
 'num_residuals_per_block': 1}<jupyter_text>MLP with IC, 101 class age<jupyter_code>config_path = "./training-results/age-101-add-residual-true-add-ic-true/training/imdb-wiki-adience/models/ResMLP/0804_130630/config.json"
config = read_json(config_path)

model = ResMLP(**config["arch"]["args"])
pprint(sum(p.numel() for p in model.parameters()))
pprint(config["arch"]["args"])
model<jupyter_output>837733
{'add_IC': True,
 'add_residual': True,
 'dropout': 0.05,
 'num_blocks': 2,
 'num_classes': 101,
 'num_initial_features': 512,
 'num_residuals_per_block': 1}<jupyter_text>plain MLP, 101 class age<jupyter_code>config_path = "./training-results/age-101-add-residual-false-add-ic-false/training/imdb-wiki-adience/models/ResMLP/0804_225547/config.json"
config = read_json(config_path)

model = ResMLP(**config["arch"]["args"])
pprint(sum(p.numel() for p in model.parameters()))
pprint(config["arch"]["args"])
model<jupyter_output>834149
{'add_IC': False,
 'add_residual': False,
 'dropout': 0.05,
 'num_blocks': 2,
 'num_classes': 101,
 'num_initial_features': 512,
 'num_residuals_per_block': 1}
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