From ee7cc946e37fa9330d7906de4670fbcafe260232 Mon Sep 17 00:00:00 2001 From: Walter Hugo Lopez Pinaya Date: Wed, 8 Mar 2023 12:19:32 +0000 Subject: [PATCH] Fix val_data Signed-off-by: Walter Hugo Lopez Pinaya --- .../2d_autoencoderkl_tutorial.ipynb | 2 +- .../2d_autoencoderkl_tutorial.py | 2 +- .../2d_ddpm/2d_ddpm_compare_schedulers.ipynb | 4 ++-- .../2d_ddpm/2d_ddpm_compare_schedulers.py | 4 ++-- .../generative/2d_ldm/2d_ldm_tutorial.ipynb | 22 ++++--------------- .../generative/2d_ldm/2d_ldm_tutorial.py | 2 +- ...stable_diffusion_v2_super_resolution.ipynb | 2 +- ...2d_stable_diffusion_v2_super_resolution.py | 2 +- .../2d_vqgan/2d_vqgan_tutorial.ipynb | 2 +- .../generative/2d_vqgan/2d_vqgan_tutorial.py | 2 +- .../2d_vqvae/2d_vqvae_tutorial.ipynb | 2 +- .../generative/2d_vqvae/2d_vqvae_tutorial.py | 2 +- .../2d_vqvae_transformer_tutorial.ipynb | 3 +-- .../2d_vqvae_transformer_tutorial.py | 3 +-- 14 files changed, 19 insertions(+), 35 deletions(-) diff --git a/tutorials/generative/2d_autoencoderkl/2d_autoencoderkl_tutorial.ipynb b/tutorials/generative/2d_autoencoderkl/2d_autoencoderkl_tutorial.ipynb index ff2f9f14..965b1350 100644 --- a/tutorials/generative/2d_autoencoderkl/2d_autoencoderkl_tutorial.ipynb +++ b/tutorials/generative/2d_autoencoderkl/2d_autoencoderkl_tutorial.ipynb @@ -316,7 +316,7 @@ ], "source": [ "val_data = MedNISTDataset(root_dir=root_dir, section=\"validation\", download=True, seed=0)\n", - "val_datalist = [{\"image\": item[\"image\"]} for item in train_data.data if item[\"class_name\"] == \"Hand\"]\n", + "val_datalist = [{\"image\": item[\"image\"]} for item in val_data.data if item[\"class_name\"] == \"Hand\"]\n", "val_transforms = transforms.Compose(\n", " [\n", " transforms.LoadImaged(keys=[\"image\"]),\n", diff --git a/tutorials/generative/2d_autoencoderkl/2d_autoencoderkl_tutorial.py b/tutorials/generative/2d_autoencoderkl/2d_autoencoderkl_tutorial.py index 9c56c2b4..0ecb5acf 100644 --- a/tutorials/generative/2d_autoencoderkl/2d_autoencoderkl_tutorial.py +++ b/tutorials/generative/2d_autoencoderkl/2d_autoencoderkl_tutorial.py @@ -101,7 +101,7 @@ # ### Download the validation set val_data = MedNISTDataset(root_dir=root_dir, section="validation", download=True, seed=0) -val_datalist = [{"image": item["image"]} for item in train_data.data if item["class_name"] == "Hand"] +val_datalist = [{"image": item["image"]} for item in val_data.data if item["class_name"] == "Hand"] val_transforms = transforms.Compose( [ transforms.LoadImaged(keys=["image"]), diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.ipynb b/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.ipynb index 1cadad2c..4595b4d3 100644 --- a/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.ipynb +++ b/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.ipynb @@ -301,7 +301,7 @@ ], "source": [ "val_data = MedNISTDataset(root_dir=root_dir, section=\"validation\", download=True, seed=0)\n", - "val_datalist = [{\"image\": item[\"image\"]} for item in train_data.data if item[\"class_name\"] == \"Hand\"]\n", + "val_datalist = [{\"image\": item[\"image\"]} for item in val_data.data if item[\"class_name\"] == \"Hand\"]\n", "val_transforms = transforms.Compose(\n", " [\n", " transforms.LoadImaged(keys=[\"image\"]),\n", @@ -1096,7 +1096,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.13" + "version": "3.10.6" } }, "nbformat": 4, diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.py b/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.py index dee1bed2..f9409bfe 100644 --- a/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.py +++ b/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.py @@ -6,7 +6,7 @@ # extension: .py # format_name: percent # format_version: '1.3' -# jupytext_version: 1.14.1 +# jupytext_version: 1.14.4 # kernelspec: # display_name: Python 3 (ipykernel) # language: python @@ -131,7 +131,7 @@ # %% val_data = MedNISTDataset(root_dir=root_dir, section="validation", download=True, seed=0) -val_datalist = [{"image": item["image"]} for item in train_data.data if item["class_name"] == "Hand"] +val_datalist = [{"image": item["image"]} for item in val_data.data if item["class_name"] == "Hand"] val_transforms = transforms.Compose( [ transforms.LoadImaged(keys=["image"]), diff --git a/tutorials/generative/2d_ldm/2d_ldm_tutorial.ipynb b/tutorials/generative/2d_ldm/2d_ldm_tutorial.ipynb index d0d56f5e..64cd2746 100644 --- a/tutorials/generative/2d_ldm/2d_ldm_tutorial.ipynb +++ b/tutorials/generative/2d_ldm/2d_ldm_tutorial.ipynb @@ -309,7 +309,7 @@ ], "source": [ "val_data = MedNISTDataset(root_dir=root_dir, section=\"validation\", download=True, seed=0)\n", - "val_datalist = [{\"image\": item[\"image\"]} for item in train_data.data if item[\"class_name\"] == \"Hand\"]\n", + "val_datalist = [{\"image\": item[\"image\"]} for item in val_data.data if item[\"class_name\"] == \"Hand\"]\n", "val_transforms = transforms.Compose(\n", " [\n", " transforms.LoadImaged(keys=[\"image\"]),\n", @@ -425,20 +425,10 @@ ], "source": [ "unet = DiffusionModelUNet(\n", - " spatial_dims=2,\n", - " in_channels=3,\n", - " out_channels=3,\n", - " num_res_blocks=1,\n", - " num_channels=(128, 256, 256),\n", - " num_head_channels=256,\n", + " spatial_dims=2, in_channels=3, out_channels=3, num_res_blocks=1, num_channels=(128, 256, 256), num_head_channels=256\n", ")\n", "\n", - "scheduler = DDPMScheduler(\n", - " num_train_timesteps=1000,\n", - " beta_schedule=\"linear\",\n", - " beta_start=0.0015,\n", - " beta_end=0.0195,\n", - ")\n", + "scheduler = DDPMScheduler(num_train_timesteps=1000, beta_schedule=\"linear\", beta_start=0.0015, beta_end=0.0195)\n", "\n", "discriminator = PatchDiscriminator(\n", " spatial_dims=2,\n", @@ -1433,11 +1423,7 @@ "\n", " epoch_loss += loss.item()\n", "\n", - " progress_bar.set_postfix(\n", - " {\n", - " \"loss\": epoch_loss / (step + 1),\n", - " }\n", - " )\n", + " progress_bar.set_postfix({\"loss\": epoch_loss / (step + 1)})\n", " epoch_loss_list.append(epoch_loss / (step + 1))\n", "\n", " if (epoch + 1) % val_interval == 0:\n", diff --git a/tutorials/generative/2d_ldm/2d_ldm_tutorial.py b/tutorials/generative/2d_ldm/2d_ldm_tutorial.py index bc464a99..7b555345 100644 --- a/tutorials/generative/2d_ldm/2d_ldm_tutorial.py +++ b/tutorials/generative/2d_ldm/2d_ldm_tutorial.py @@ -104,7 +104,7 @@ # ## Download the validation set val_data = MedNISTDataset(root_dir=root_dir, section="validation", download=True, seed=0) -val_datalist = [{"image": item["image"]} for item in train_data.data if item["class_name"] == "Hand"] +val_datalist = [{"image": item["image"]} for item in val_data.data if item["class_name"] == "Hand"] val_transforms = transforms.Compose( [ transforms.LoadImaged(keys=["image"]), diff --git a/tutorials/generative/2d_super_resolution/2d_stable_diffusion_v2_super_resolution.ipynb b/tutorials/generative/2d_super_resolution/2d_stable_diffusion_v2_super_resolution.ipynb index 8cf094d3..2a383dc9 100644 --- a/tutorials/generative/2d_super_resolution/2d_stable_diffusion_v2_super_resolution.ipynb +++ b/tutorials/generative/2d_super_resolution/2d_stable_diffusion_v2_super_resolution.ipynb @@ -368,7 +368,7 @@ ], "source": [ "val_data = MedNISTDataset(root_dir=root_dir, section=\"validation\", download=True, seed=0)\n", - "val_datalist = [{\"image\": item[\"image\"]} for item in train_data.data if item[\"class_name\"] == \"HeadCT\"]\n", + "val_datalist = [{\"image\": item[\"image\"]} for item in val_data.data if item[\"class_name\"] == \"HeadCT\"]\n", "val_transforms = transforms.Compose(\n", " [\n", " transforms.LoadImaged(keys=[\"image\"]),\n", diff --git a/tutorials/generative/2d_super_resolution/2d_stable_diffusion_v2_super_resolution.py b/tutorials/generative/2d_super_resolution/2d_stable_diffusion_v2_super_resolution.py index d2365a0d..9c3a9afd 100644 --- a/tutorials/generative/2d_super_resolution/2d_stable_diffusion_v2_super_resolution.py +++ b/tutorials/generative/2d_super_resolution/2d_stable_diffusion_v2_super_resolution.py @@ -139,7 +139,7 @@ # %% val_data = MedNISTDataset(root_dir=root_dir, section="validation", download=True, seed=0) -val_datalist = [{"image": item["image"]} for item in train_data.data if item["class_name"] == "HeadCT"] +val_datalist = [{"image": item["image"]} for item in val_data.data if item["class_name"] == "HeadCT"] val_transforms = transforms.Compose( [ transforms.LoadImaged(keys=["image"]), diff --git a/tutorials/generative/2d_vqgan/2d_vqgan_tutorial.ipynb b/tutorials/generative/2d_vqgan/2d_vqgan_tutorial.ipynb index d1089644..2566d397 100644 --- a/tutorials/generative/2d_vqgan/2d_vqgan_tutorial.ipynb +++ b/tutorials/generative/2d_vqgan/2d_vqgan_tutorial.ipynb @@ -266,7 +266,7 @@ ], "source": [ "val_data = MedNISTDataset(root_dir=root_dir, section=\"validation\", download=True, progress=False, seed=0)\n", - "val_datalist = [{\"image\": item[\"image\"]} for item in train_data.data if item[\"class_name\"] == \"HeadCT\"]\n", + "val_datalist = [{\"image\": item[\"image\"]} for item in val_data.data if item[\"class_name\"] == \"HeadCT\"]\n", "val_transforms = transforms.Compose(\n", " [\n", " transforms.LoadImaged(keys=[\"image\"]),\n", diff --git a/tutorials/generative/2d_vqgan/2d_vqgan_tutorial.py b/tutorials/generative/2d_vqgan/2d_vqgan_tutorial.py index 242750c0..fd347f20 100644 --- a/tutorials/generative/2d_vqgan/2d_vqgan_tutorial.py +++ b/tutorials/generative/2d_vqgan/2d_vqgan_tutorial.py @@ -124,7 +124,7 @@ # %% val_data = MedNISTDataset(root_dir=root_dir, section="validation", download=True, progress=False, seed=0) -val_datalist = [{"image": item["image"]} for item in train_data.data if item["class_name"] == "HeadCT"] +val_datalist = [{"image": item["image"]} for item in val_data.data if item["class_name"] == "HeadCT"] val_transforms = transforms.Compose( [ transforms.LoadImaged(keys=["image"]), diff --git a/tutorials/generative/2d_vqvae/2d_vqvae_tutorial.ipynb b/tutorials/generative/2d_vqvae/2d_vqvae_tutorial.ipynb index 714ba358..78c0e6a1 100644 --- a/tutorials/generative/2d_vqvae/2d_vqvae_tutorial.ipynb +++ b/tutorials/generative/2d_vqvae/2d_vqvae_tutorial.ipynb @@ -315,7 +315,7 @@ ], "source": [ "val_data = MedNISTDataset(root_dir=root_dir, section=\"validation\", download=True, seed=0)\n", - "val_datalist = [{\"image\": item[\"image\"]} for item in train_data.data if item[\"class_name\"] == \"HeadCT\"]\n", + "val_datalist = [{\"image\": item[\"image\"]} for item in val_data.data if item[\"class_name\"] == \"HeadCT\"]\n", "val_transforms = transforms.Compose(\n", " [\n", " transforms.LoadImaged(keys=[\"image\"]),\n", diff --git a/tutorials/generative/2d_vqvae/2d_vqvae_tutorial.py b/tutorials/generative/2d_vqvae/2d_vqvae_tutorial.py index 2aae29fb..3a73d3c4 100644 --- a/tutorials/generative/2d_vqvae/2d_vqvae_tutorial.py +++ b/tutorials/generative/2d_vqvae/2d_vqvae_tutorial.py @@ -99,7 +99,7 @@ # ### Download the validation set val_data = MedNISTDataset(root_dir=root_dir, section="validation", download=True, seed=0) -val_datalist = [{"image": item["image"]} for item in train_data.data if item["class_name"] == "HeadCT"] +val_datalist = [{"image": item["image"]} for item in val_data.data if item["class_name"] == "HeadCT"] val_transforms = transforms.Compose( [ transforms.LoadImaged(keys=["image"]), diff --git a/tutorials/generative/2d_vqvae_transformer/2d_vqvae_transformer_tutorial.ipynb b/tutorials/generative/2d_vqvae_transformer/2d_vqvae_transformer_tutorial.ipynb index 7f43bae2..8f2d9ba3 100644 --- a/tutorials/generative/2d_vqvae_transformer/2d_vqvae_transformer_tutorial.ipynb +++ b/tutorials/generative/2d_vqvae_transformer/2d_vqvae_transformer_tutorial.ipynb @@ -294,7 +294,7 @@ ], "source": [ "val_data = MedNISTDataset(root_dir=root_dir, section=\"validation\", download=True, seed=0)\n", - "val_datalist = [{\"image\": item[\"image\"]} for item in train_data.data if item[\"class_name\"] == \"HeadCT\"]\n", + "val_datalist = [{\"image\": item[\"image\"]} for item in val_data.data if item[\"class_name\"] == \"HeadCT\"]\n", "val_transforms = transforms.Compose(\n", " [\n", " transforms.LoadImaged(keys=[\"image\"]),\n", @@ -490,7 +490,6 @@ " in_channels=1,\n", " out_channels=1,\n", " num_res_layers=2,\n", - " num_levels=2,\n", " downsample_parameters=((2, 4, 1, 1), (2, 4, 1, 1)),\n", " upsample_parameters=((2, 4, 1, 1, 0), (2, 4, 1, 1, 0)),\n", " num_channels=(256, 256),\n", diff --git a/tutorials/generative/2d_vqvae_transformer/2d_vqvae_transformer_tutorial.py b/tutorials/generative/2d_vqvae_transformer/2d_vqvae_transformer_tutorial.py index bcd38b91..c1890939 100644 --- a/tutorials/generative/2d_vqvae_transformer/2d_vqvae_transformer_tutorial.py +++ b/tutorials/generative/2d_vqvae_transformer/2d_vqvae_transformer_tutorial.py @@ -123,7 +123,7 @@ # %% val_data = MedNISTDataset(root_dir=root_dir, section="validation", download=True, seed=0) -val_datalist = [{"image": item["image"]} for item in train_data.data if item["class_name"] == "HeadCT"] +val_datalist = [{"image": item["image"]} for item in val_data.data if item["class_name"] == "HeadCT"] val_transforms = transforms.Compose( [ transforms.LoadImaged(keys=["image"]), @@ -149,7 +149,6 @@ in_channels=1, out_channels=1, num_res_layers=2, - num_levels=2, downsample_parameters=((2, 4, 1, 1), (2, 4, 1, 1)), upsample_parameters=((2, 4, 1, 1, 0), (2, 4, 1, 1, 0)), num_channels=(256, 256),