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applications/contrastive_phenotyping/contrastive_cli/fit_ctc_mps.yml
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| # See help here on how to configure hyper-parameters with config files: | ||
| # https://lightning.ai/docs/pytorch/stable/cli/lightning_cli_advanced.html | ||
| seed_everything: 42 | ||
| trainer: | ||
| accelerator: gpu | ||
| strategy: auto | ||
| devices: 1 | ||
| num_nodes: 1 | ||
| precision: 32-true | ||
| logger: | ||
| class_path: lightning.pytorch.loggers.TensorBoardLogger | ||
| # Nesting the logger config like this is equivalent to | ||
| # supplying the following argument to `lightning.pytorch.Trainer`: | ||
| # logger=TensorBoardLogger( | ||
| # "/hpc/projects/intracellular_dashboard/viral-sensor/infection_classification/models/contrastive_tune_augmentations", | ||
| # log_graph=True, | ||
| # version="vanilla", | ||
| # ) | ||
| init_args: | ||
| save_dir: /Users/ziwen.liu/Projects/test-time | ||
| # this is the name of the experiment. | ||
| # The logs will be saved in `save_dir/lightning_logs/version` | ||
| version: time_interval_1 | ||
| log_graph: True | ||
| callbacks: | ||
| - class_path: lightning.pytorch.callbacks.LearningRateMonitor | ||
| init_args: | ||
| logging_interval: step | ||
| - class_path: lightning.pytorch.callbacks.ModelCheckpoint | ||
| init_args: | ||
| monitor: loss/val | ||
| every_n_epochs: 1 | ||
| save_top_k: 4 | ||
| save_last: true | ||
| fast_dev_run: false | ||
| max_epochs: 100 | ||
| log_every_n_steps: 10 | ||
| enable_checkpointing: true | ||
| inference_mode: true | ||
| use_distributed_sampler: true | ||
| # synchronize batchnorm parameters across multiple GPUs. | ||
| # important for contrastive learning to normalize the tensors across the whole batch. | ||
| sync_batchnorm: true | ||
| model: | ||
| encoder: | ||
| class_path: viscy.representation.contrastive.ContrastiveEncoder | ||
| init_args: | ||
| backbone: convnext_tiny | ||
| in_channels: 1 | ||
| in_stack_depth: 1 | ||
| stem_kernel_size: [1, 4, 4] | ||
| stem_stride: [1, 4, 4] | ||
| embedding_dim: 768 | ||
| projection_dim: 32 | ||
| drop_path_rate: 0.0 | ||
| loss_function: | ||
| class_path: torch.nn.TripletMarginLoss | ||
| init_args: | ||
| margin: 0.5 | ||
| lr: 0.0002 | ||
| log_batches_per_epoch: 3 | ||
| log_samples_per_batch: 2 | ||
| example_input_array_shape: [1, 1, 1, 128, 128] | ||
| data: | ||
| data_path: /Users/ziwen.liu/Downloads/Hela_CTC.zarr | ||
| tracks_path: /Users/ziwen.liu/Downloads/Hela_CTC.zarr | ||
| source_channel: | ||
| - DIC | ||
| z_range: [0, 1] | ||
| batch_size: 16 | ||
| num_workers: 4 | ||
| initial_yx_patch_size: [256, 256] | ||
| final_yx_patch_size: [128, 128] | ||
| time_interval: 1 | ||
| normalizations: | ||
| - class_path: viscy.transforms.NormalizeSampled | ||
| init_args: | ||
| keys: [DIC] | ||
| level: fov_statistics | ||
| subtrahend: mean | ||
| divisor: std | ||
| augmentations: | ||
| - class_path: viscy.transforms.RandAffined | ||
| init_args: | ||
| keys: [DIC] | ||
| prob: 0.8 | ||
| scale_range: [0, 0.2, 0.2] | ||
| rotate_range: [3.14, 0.0, 0.0] | ||
| shear_range: [0.0, 0.01, 0.01] | ||
| padding_mode: zeros | ||
| - class_path: viscy.transforms.RandAdjustContrastd | ||
| init_args: | ||
| keys: [DIC] | ||
| prob: 0.5 | ||
| gamma: [0.8, 1.2] | ||
| - class_path: viscy.transforms.RandScaleIntensityd | ||
| init_args: | ||
| keys: [DIC] | ||
| prob: 0.5 | ||
| factors: 0.5 | ||
| - class_path: viscy.transforms.RandGaussianSmoothd | ||
| init_args: | ||
| keys: [DIC] | ||
| prob: 0.5 | ||
| sigma_x: [0.25, 0.75] | ||
| sigma_y: [0.25, 0.75] | ||
| sigma_z: [0.0, 0.0] | ||
| - class_path: viscy.transforms.RandGaussianNoised | ||
| init_args: | ||
| keys: [DIC] | ||
| prob: 0.5 | ||
| mean: 0.0 | ||
| std: 0.2 |
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applications/contrastive_phenotyping/contrastive_cli/predict_ctc_mps.yml
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| seed_everything: 42 | ||
| trainer: | ||
| accelerator: gpu | ||
| strategy: auto | ||
| devices: auto | ||
| num_nodes: 1 | ||
| precision: 32-true | ||
| callbacks: | ||
| - class_path: viscy.representation.embedding_writer.EmbeddingWriter | ||
| init_args: | ||
| output_path: /Users/ziwen.liu/Projects/test-time/predict/time_interval_1.zarr | ||
| inference_mode: true | ||
| model: | ||
| encoder: | ||
| class_path: viscy.representation.contrastive.ContrastiveEncoder | ||
| init_args: | ||
| backbone: convnext_tiny | ||
| in_channels: 1 | ||
| in_stack_depth: 1 | ||
| stem_kernel_size: [1, 4, 4] | ||
| stem_stride: [1, 4, 4] | ||
| embedding_dim: 768 | ||
| projection_dim: 32 | ||
| drop_path_rate: 0.0 | ||
| example_input_array_shape: [1, 1, 1, 128, 128] | ||
| data: | ||
| data_path: /Users/ziwen.liu/Downloads/Hela_CTC.zarr | ||
| tracks_path: /Users/ziwen.liu/Downloads/Hela_CTC.zarr | ||
| source_channel: DIC | ||
| z_range: [0, 1] | ||
| batch_size: 16 | ||
| num_workers: 4 | ||
| initial_yx_patch_size: [128, 128] | ||
| final_yx_patch_size: [128, 128] | ||
| time_interval: 1 | ||
| normalizations: | ||
| - class_path: viscy.transforms.NormalizeSampled | ||
| init_args: | ||
| keys: [DIC] | ||
| level: fov_statistics | ||
| subtrahend: mean | ||
| divisor: std | ||
| return_predictions: false | ||
| ckpt_path: /Users/ziwen.liu/Projects/test-time/lightning_logs/time_interval_1/checkpoints/last.ckpt |
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applications/contrastive_phenotyping/evaluation/figure.mplstyle
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| font.family: sans-serif | ||
| font.sans-serif: Arial | ||
| font.size: 10 | ||
| figure.titlesize: 12 | ||
| axes.titlesize: 10 | ||
| xtick.labelsize: 8 | ||
| ytick.labelsize: 8 | ||
| text.usetex: True |
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