Configurations for executing code with the PPMI dataset

[DayrisRM]

Hi! I'm trying to run Stage1 with the PPMI dataset but I ge the error:

Traceback (most recent call last): File "/content/DDM2_test/train_noise_model.py", line 98, in <module> trainer.optimize_parameters() File "/content/DDM2_test/model/model_stage1.py", line 69, in optimize_parameters outputs = self.netG(self.data) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl return forward_call(*args, **kwargs) File "/content/DDM2_test/model/mri_modules/noise_model.py", line 44, in forward return self.p_losses(x, *args, **kwargs) File "/content/DDM2_test/model/mri_modules/noise_model.py", line 36, in p_losses x_recon = self.denoise_fn(x_in['condition']) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl return forward_call(*args, **kwargs) File "/content/DDM2_test/model/mri_modules/unet.py", line 286, in forward x = layer(x) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl return self._call_impl(*args, **kwargs) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl return forward_call(*args, **kwargs) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/conv.py", line 460, in forward return self._conv_forward(input, self.weight, self.bias) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/conv.py", line 456, in _conv_forward return F.conv2d(input, weight, bias, self.stride, RuntimeError: Input type (double) and bias type (float) should be the same

It's the same dataset that you use in your article. I have added a new config file as follows:

 {
    "name": "ppmi64",
    "phase": "train", // always set to train in the config
    "gpu_ids": [
        0
    ],
    "path": { //set the path
        "log": "logs",
        "tb_logger": "tb_logger",
        "results": "results",
        "checkpoint": "checkpoint",
        "resume_state": null // UPDATE THIS FOR RESUMING TRAINING
    },
    "datasets": {
        "train": {
            "name": "ppmi",
            "dataroot": "/PPMI/noisy.nii.gz",
            "valid_mask": [10,64],
            "phase": "train",
            "padding": 3,
            "val_volume_idx": 40, // the volume to visualize for validation
            "val_slice_idx": 40, // the slice to visualize for validation
            "batch_size": 32,
            "in_channel": 1,
            "num_workers": 0,
            "use_shuffle": true
        },
        "val": {
            "name": "ppmi",
            "dataroot": "/PPMI/noisy.nii.gz",
            "valid_mask": [10,64],
            "phase": "val",
            "padding": 3,
            "val_volume_idx": 40, // the volume to visualize for validation
            "val_slice_idx": 40, // the slice to visualize for validation
            "batch_size": 1,
            "in_channel": 1,
            "num_workers": 0
        }
    },
    "model": {
        "which_model_G": "mri",
        "finetune_norm": false,
        "drop_rate": 0.0,
        "unet": {
            "in_channel": 1,
            "out_channel": 1,
            "inner_channel": 32,
            "norm_groups": 32,
            "channel_multiplier": [
                1,
                2,
                4,
                8,
                8
            ],
            "attn_res": [
                16
            ],
            "res_blocks": 2,
            "dropout": 0.0,
            "version": "v1"
        },
        "beta_schedule": { // use munual beta_schedule for acceleration
            "train": {
                "schedule": "rev_warmup70",
                "n_timestep": 1000,
                "linear_start": 5e-5,
                "linear_end": 1e-2
            },
            "val": {
                "schedule": "rev_warmup70",
                "n_timestep": 1000,
                "linear_start": 5e-5,
                "linear_end": 1e-2
            }
        },
        "diffusion": {
            "image_size": 128,
            "channels": 3, //sample channel
            "conditional": true // not used for DDM2
        }
    },
    "train": {
        "n_iter": 100000, //150000,
        "val_freq": 1e3,
        "save_checkpoint_freq": 1e4,
        "print_freq": 1e2,
        "optimizer": {
            "type": "adam",
            "lr": 1e-4
        },
        "ema_scheduler": { // not used now
            "step_start_ema": 5000,
            "update_ema_every": 1,
            "ema_decay": 0.9999
        }
    },
    // for Phase1
    "noise_model": {
        "resume_state": null,
        "drop_rate": 0.0,
        "unet": {
            "in_channel": 2,
            "out_channel": 1,
            "inner_channel": 32,
            "norm_groups": 32,
            "channel_multiplier": [
                1,
                2,
                4,
                8,
                8
            ],
            "attn_res": [
                16
            ],
            "res_blocks": 2,
            "dropout": 0.0,
            "version": "v1"
        },
        "beta_schedule": { // use munual beta_schedule for accelerationß
            "linear_start": 5e-5,
            "linear_end": 1e-2
        },
        "n_iter": 10000,
        "val_freq": 2e3,
        "save_checkpoint_freq": 1e4,
        "print_freq": 1e3,
        "optimizer": {
            "type": "adam",
            "lr": 1e-4
        }
    },
    "stage2_file": "" // **UPDATE THIS TO THE PATH OF PHASE2 MATCHED FILE** 
}

Do we need to change anything else in the config file? Can you share the configuration files you have used for the other datasets?

[tiangexiang]

Hi, sorry for the bug. It is due to data type mismatch between MRI tensor and convolution kernel. I have just updated the code, please pull the latest code and try again :) Your configuration for PPMI looks good to me, it should work for Stage1. Remember to update the configuration after each stage, as described in README.

[DayrisRM]

It's working now! Thanks!