Run model visualization (weights, activations and model inputs) and visualize them on Tensorboard. Args: vis_loader (loader): video visualization loader. model (model): the video model to visualize. cfg (CfgNode): configs. Details can be found in slow
(vis_loader, model, cfg, writer=None)
| 26 | |
| 27 | |
| 28 | def run_visualization(vis_loader, model, cfg, writer=None): |
| 29 | """ |
| 30 | Run model visualization (weights, activations and model inputs) and visualize |
| 31 | them on Tensorboard. |
| 32 | Args: |
| 33 | vis_loader (loader): video visualization loader. |
| 34 | model (model): the video model to visualize. |
| 35 | cfg (CfgNode): configs. Details can be found in |
| 36 | slowfast/config/defaults.py |
| 37 | writer (TensorboardWriter, optional): TensorboardWriter object |
| 38 | to writer Tensorboard log. |
| 39 | """ |
| 40 | n_devices = cfg.NUM_GPUS * cfg.NUM_SHARDS |
| 41 | prefix = "module/" if n_devices > 1 else "" |
| 42 | # Get a list of selected layer names and indexing. |
| 43 | layer_ls, indexing_dict = process_layer_index_data( |
| 44 | cfg.TENSORBOARD.MODEL_VIS.LAYER_LIST, layer_name_prefix=prefix |
| 45 | ) |
| 46 | logger.info("Start Model Visualization.") |
| 47 | # Register hooks for activations. |
| 48 | model_vis = GetWeightAndActivation(model, layer_ls) |
| 49 | |
| 50 | if writer is not None and cfg.TENSORBOARD.MODEL_VIS.MODEL_WEIGHTS: |
| 51 | layer_weights = model_vis.get_weights() |
| 52 | writer.plot_weights_and_activations( |
| 53 | layer_weights, tag="Layer Weights/", heat_map=False |
| 54 | ) |
| 55 | |
| 56 | video_vis = VideoVisualizer( |
| 57 | cfg.MODEL.NUM_CLASSES, |
| 58 | cfg.TENSORBOARD.CLASS_NAMES_PATH, |
| 59 | cfg.TENSORBOARD.MODEL_VIS.TOPK_PREDS, |
| 60 | cfg.TENSORBOARD.MODEL_VIS.COLORMAP, |
| 61 | ) |
| 62 | if n_devices > 1: |
| 63 | grad_cam_layer_ls = [ |
| 64 | "module/" + layer |
| 65 | for layer in cfg.TENSORBOARD.MODEL_VIS.GRAD_CAM.LAYER_LIST |
| 66 | ] |
| 67 | else: |
| 68 | grad_cam_layer_ls = cfg.TENSORBOARD.MODEL_VIS.GRAD_CAM.LAYER_LIST |
| 69 | |
| 70 | if cfg.TENSORBOARD.MODEL_VIS.GRAD_CAM.ENABLE: |
| 71 | gradcam = GradCAM( |
| 72 | model, |
| 73 | target_layers=grad_cam_layer_ls, |
| 74 | data_mean=cfg.DATA.MEAN, |
| 75 | data_std=cfg.DATA.STD, |
| 76 | colormap=cfg.TENSORBOARD.MODEL_VIS.GRAD_CAM.COLORMAP, |
| 77 | ) |
| 78 | logger.info("Finish drawing weights.") |
| 79 | global_idx = -1 |
| 80 | for inputs, labels, _, meta in tqdm.tqdm(vis_loader): |
| 81 | if cfg.NUM_GPUS: |
| 82 | # Transfer the data to the current GPU device. |
| 83 | if isinstance(inputs, (list,)): |
| 84 | for i in range(len(inputs)): |
| 85 | inputs[i] = inputs[i].cuda(non_blocking=True) |
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