| --- |
| language: en |
| library_name: pytorch |
| tags: |
| - pytorch |
| - gan |
| - week06-caa |
| - conditional-gan |
| --- |
| |
| # mnist-conditional-gan |
|
|
| **Local run name:** `gan_run` |
|
|
| Generator weights exported from the Week 6 GAN lab training codebase. |
|
|
| ## Repository files |
|
|
| | Key | Value | |
| | --- | --- | |
| | `mnist_cgan_generator.pth` | Generator `state_dict` (PyTorch) | |
| | `generator_training_config.json` | Training hyperparameters / layout (JSON) | |
| | `README.md` | This model card (auto-generated on upload) | |
|
|
| ## Export provenance |
|
|
| | Key | Value | |
| | --- | --- | |
| | Checkpoint path | `/home/ucloud/caa-andre/complements-ml-labs-andreribeiro87/week-06/outputs/runs/gan_run__20260322T142324Z__9e0ad9f4/checkpoints/latest.pt` | |
| | Run directory JSON | `config.json`, `run_meta.json` | |
|
|
| ## Run metadata (`run_meta.json`) |
| |
| | Key | Value | |
| | --- | --- | |
| | config_fingerprint | 9e0ad9f4 | |
| | created_utc | 20260322T142324Z | |
| | run_name | gan_run | |
| |
| ## Training configuration (summary) |
| |
| | Key | Value | |
| | --- | --- | |
| | run_name | gan_run | |
| | task | mnist | |
| | image_size | 64 | |
| | nz | 100 | |
| | ngf | 64 | |
| | ndf | 64 | |
| | num_classes | 10 | |
| | adversarial_loss | hinge | |
| | use_gradient_penalty | False | |
| | lambda_fm | 0.0 | |
| | lambda_perc | 0.0 | |
| | epochs | 25 | |
| | max_steps | None | |
| | batch_size | 32 | |
| | lr_g | 0.0002 | |
| | lr_d | 0.0002 | |
| | n_critic | 1 | |
| | seed | 42 | |
| | spectral_norm_d | True | |
| |
| ## Source JSON (run directory) |
| |
| Verbatim JSON files from the run folder root (next to `checkpoints/`). |
| |
| ### `config.json` |
| |
| ```json |
| { |
| "adversarial_loss": "hinge", |
| "batch_size": 32, |
| "beta1": 0.5, |
| "beta2": 0.999, |
| "checkpoint_every": 1000, |
| "data_cache_dir": null, |
| "device": "cuda", |
| "epochs": 25, |
| "eval_at_end": true, |
| "eval_batch_size": 32, |
| "eval_every": 1000, |
| "eval_num_fake": 2048, |
| "eval_num_real": 2048, |
| "image_size": 64, |
| "lambda_fm": 0.0, |
| "lambda_gp": 10.0, |
| "lambda_perc": 0.0, |
| "log_every": 50, |
| "lr_d": 0.0002, |
| "lr_g": 0.0002, |
| "max_steps": null, |
| "metrics_device": null, |
| "n_critic": 1, |
| "n_samples_grid": 64, |
| "ndf": 64, |
| "ngf": 64, |
| "num_classes": 10, |
| "num_workers": 2, |
| "nz": 100, |
| "output_root": "outputs", |
| "run_name": "gan_run", |
| "sample_every": 500, |
| "seed": 42, |
| "spectral_norm_d": true, |
| "tags": {}, |
| "task": "mnist", |
| "use_bf16": true, |
| "use_gradient_penalty": false, |
| "use_wandb": true, |
| "wandb_entity": null, |
| "wandb_mode": "online", |
| "wandb_project": "week06-gan" |
| } |
| ``` |
| |
| ### `run_meta.json` |
| |
| ```json |
| { |
| "config": { |
| "adversarial_loss": "hinge", |
| "batch_size": 32, |
| "beta1": 0.5, |
| "beta2": 0.999, |
| "checkpoint_every": 1000, |
| "data_cache_dir": null, |
| "device": "cuda", |
| "epochs": 25, |
| "eval_at_end": true, |
| "eval_batch_size": 32, |
| "eval_every": 1000, |
| "eval_num_fake": 2048, |
| "eval_num_real": 2048, |
| "image_size": 64, |
| "lambda_fm": 0.0, |
| "lambda_gp": 10.0, |
| "lambda_perc": 0.0, |
| "log_every": 50, |
| "lr_d": 0.0002, |
| "lr_g": 0.0002, |
| "max_steps": null, |
| "metrics_device": null, |
| "n_critic": 1, |
| "n_samples_grid": 64, |
| "ndf": 64, |
| "ngf": 64, |
| "num_classes": 10, |
| "num_workers": 2, |
| "nz": 100, |
| "output_root": "outputs", |
| "run_name": "gan_run", |
| "sample_every": 500, |
| "seed": 42, |
| "spectral_norm_d": true, |
| "tags": {}, |
| "task": "mnist", |
| "use_bf16": true, |
| "use_gradient_penalty": false, |
| "use_wandb": true, |
| "wandb_entity": null, |
| "wandb_mode": "online", |
| "wandb_project": "week06-gan" |
| }, |
| "config_fingerprint": "9e0ad9f4", |
| "created_utc": "20260322T142324Z", |
| "run_name": "gan_run" |
| } |
| ``` |
| |
