From 0dfb85dcaca03c86cab5aa3f6d87d25d8a7a230c Mon Sep 17 00:00:00 2001 From: Walter Hugo Lopez Pinaya Date: Mon, 6 Mar 2023 14:00:03 +0000 Subject: [PATCH 1/5] Add MIMIC pretrained model Signed-off-by: Walter Hugo Lopez Pinaya --- .../LICENSE | 201 ++++++++++++++++++ .../configs/inference.json | 108 ++++++++++ .../configs/logging.conf | 21 ++ .../configs/metadata.json | 60 ++++++ .../docs/README.md | 59 +++++ .../large_files.yml | 9 + .../scripts/__init__.py | 0 .../scripts/sampler.py | 43 ++++ .../scripts/saver.py | 17 ++ 9 files changed, 518 insertions(+) create mode 100644 model-zoo/models/cxr_image_synthesis_latent_diffusion_model/LICENSE create mode 100644 model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json create mode 100644 model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/logging.conf create mode 100644 model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json create mode 100644 model-zoo/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md create mode 100644 model-zoo/models/cxr_image_synthesis_latent_diffusion_model/large_files.yml create mode 100644 model-zoo/models/cxr_image_synthesis_latent_diffusion_model/scripts/__init__.py create mode 100644 model-zoo/models/cxr_image_synthesis_latent_diffusion_model/scripts/sampler.py create mode 100644 model-zoo/models/cxr_image_synthesis_latent_diffusion_model/scripts/saver.py diff --git a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/LICENSE b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/LICENSE new file mode 100644 index 00000000..261eeb9e --- /dev/null +++ b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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00000000..b120d939 --- /dev/null +++ b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json @@ -0,0 +1,108 @@ +{ + "imports": [ + "$import torch", + "$from datetime import datetime", + "$from pathlib import Path", + "$from transformers import CLIPTextModel", + "$from transformers import CLIPTokenizer" + ], + "//bundle_root": ".", + "bundle_root": "/media/walter/Storage/Projects/GenerativeModels/model-zoo/models/cxr_image_synthesis_latent_diffusion_model", + "model_dir": "$@bundle_root + '/models'", + "output_dir": "$@bundle_root + '/output'", + "create_output_dir": "$Path(@output_dir).mkdir(exist_ok=True)", + "prompt": "Big right-sided pleural effusion", + "prompt_list": "$['', @prompt]", + "guidance_scale": 7.0, + "device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')", + "tokenizer": "$CLIPTokenizer.from_pretrained(\"stabilityai/stable-diffusion-2-1-base\", subfolder=\"tokenizer\")", + "text_encoder": "$CLIPTextModel.from_pretrained(\"stabilityai/stable-diffusion-2-1-base\", subfolder=\"text_encoder\")", + "tokenized_prompt": "$@tokenizer(@prompt_list, padding=\"max_length\", max_length=@tokenizer.model_max_length, truncation=True,return_tensors=\"pt\")", + "prompt_embeds": "$@text_encoder(@tokenized_prompt.input_ids.squeeze(1))[0].to(@device)", + "out_file": "$datetime.now().strftime('sample_%H%M%S_%d%m%Y')", + "autoencoder_def": { + "_target_": "generative.networks.nets.AutoencoderKL", + "spatial_dims": 2, + "in_channels": 1, + "out_channels": 1, + "latent_channels": 3, + "num_channels": [ + 64, + 128, + 128, + 128 + ], + "num_res_blocks": 2, + "norm_num_groups": 32, + "norm_eps": 1e-06, + "attention_levels": [ + false, + false, + false, + false + ], + "with_encoder_nonlocal_attn": true, + "with_decoder_nonlocal_attn": true + }, + "load_autoencoder_path": "$@model_dir + '/autoencoder.pth'", + "load_autoencoder": "$@autoencoder_def.load_state_dict(torch.load(@load_autoencoder_path))", + "autoencoder": "$@autoencoder_def.to(@device)", + "diffusion_def": { + "_target_": "generative.networks.nets.DiffusionModelUNet", + "spatial_dims": 2, + "in_channels": 3, + "out_channels": 3, + "num_channels": [ + 256, + 512, + 768 + ], + "num_res_blocks": 2, + "attention_levels": [ + false, + true, + true + ], + "norm_num_groups": 32, + "norm_eps": 1e-06, + "resblock_updown": false, + "num_head_channels": [ + 0, + 512, + 768 + ], + "with_conditioning": true, + "transformer_num_layers": 1, + "cross_attention_dim": 1024 + }, + "load_diffusion_path": "$@model_dir + '/diffusion_model.pth'", + "load_diffusion": "$@diffusion_def.load_state_dict(torch.load(@load_diffusion_path))", + "diffusion": "$@diffusion_def.to(@device)", + "scheduler": { + "_target_": "generative.networks.schedulers.DDIMScheduler", + "_requires_": [ + "@load_diffusion", + "@load_autoencoder" + ], + "beta_start": 0.0015, + "beta_end": 0.0205, + "num_train_timesteps": 1000, + "beta_schedule": "scaled_linear", + "prediction_type": "v_prediction", + "clip_sample": false + }, + "noise": "$torch.randn((1, 3, 64, 64)).to(@device)", + "set_timesteps": "$@scheduler.set_timesteps(num_inference_steps=50)", + "sampler": { + "_target_": "scripts.sampler.Sampler", + "_requires_": "@set_timesteps" + }, + "sample": "$@sampler.sampling_fn(@noise, @autoencoder, @diffusion, @scheduler, @prompt_embeds)", + "saver": { + "_target_": "scripts.saver.JPGSaver", + "_requires_": "@create_output_dir", + "output_dir": "@output_dir" + }, + "save_nii": "$@saver.save(@sample, @out_file)", + "save": "$torch.save(@sample, @output_dir + '/' + @out_file + '.pt')" +} diff --git a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/logging.conf b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/logging.conf new file mode 100644 index 00000000..91c1a21c --- /dev/null +++ b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/logging.conf @@ -0,0 +1,21 @@ +[loggers] +keys=root + +[handlers] +keys=consoleHandler + +[formatters] +keys=fullFormatter + +[logger_root] +level=INFO +handlers=consoleHandler + +[handler_consoleHandler] +class=StreamHandler +level=INFO +formatter=fullFormatter +args=(sys.stdout,) + +[formatter_fullFormatter] +format=%(asctime)s - %(name)s - %(levelname)s - %(message)s diff --git a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json new file mode 100644 index 00000000..7097cb93 --- /dev/null +++ b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json @@ -0,0 +1,60 @@ +{ + "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json", + "version": "1.0.0", + "changelog": { + "0.1": "Initial release" + }, + "monai_version": "1.1.0", + "pytorch_version": "1.13.0", + "numpy_version": "1.22.4", + "optional_packages_version": { + "nibabel": "4.0.1", + "generative": "0.1.0", + "transformers": "4.26.1" + }, + "task": "Chest X-ray image synthesis", + "description": "A generative model for creating high-resolution Chest X-ray based on MIMIC dataset", + "copyright": "Copyright (c) MONAI Consortium", + "data_source": "https://physionet.org/content/mimic-cxr-jpg/2.0.0/", + "data_type": "image", + "image_classes": "X-ray with 512 x 512 pixels", + "intended_use": "This is a research tool/prototype and not to be used clinically", + "references": [ + "Pinaya, Walter HL, et al. \"Brain imaging generation with latent diffusion models.\" MICCAI Workshop on Deep Generative Models. Springer, Cham, 2022." + ], + "network_data_format": { + "inputs": { + "report": { + "type": "text", + "num_tokens": 77, + "dtype": "string" + }, + "guidance_scale": { + "type": "float", + "num_tokens": 77, + "dtype": "float32" + } + }, + "outputs": { + "pred": { + "type": "image", + "format": "magnitude", + "modality": "CXR", + "num_channels": 1, + "spatial_shape": [ + 512, + 512 + ], + "dtype": "float32", + "value_range": [ + 0, + 1 + ], + "is_patch_data": false, + "channel_def": { + "0": "X-ray" + } + } + } + } +} diff --git a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md new file mode 100644 index 00000000..d1c4ff77 --- /dev/null +++ b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md @@ -0,0 +1,59 @@ +# Chest X-ray with Latent Diffusion Models + +### **Authors** + +MONAI Generative Models + +### **Tags** +Synthetic data, Latent Diffusion Model, Generative model, Chest X-ray + +## **Model Description** +This model is trained from scratch using the Latent Diffusion Model architecture [1] and is used for the synthesis of +2D Chest X-ray conditioned on Radiological reports. The model is divided into two parts: an autoencoder with a +KL-regularisation model that compresses data into a latent space and a diffusion model that learns to generate +conditioned synthetic latent representations. This model is conditioned on Findings and Impressions from radiological +reports. + +## **Data** +The model was trained on brain data from 90,000 participants from the MIMIC dataset [2] [3]. We downsampled the +original images to have a format of 512 x 512 pixels. + +#### **Preprocessing** +We resized the original images to make the smallest sides have 512 pixels. When inputting it to the network, we center +cropped the images to 512 x 512. The pixel intensity was normalised to be between [0, 1]. The text data was obtained +from associated radiological reports. We randoomly extracted sentences from the findings and impressions sections of the +reports, having a maximum of 5 sentences and 77 tokens. The text was tokenised using the CLIPTokenizer from +transformers package (https://github.com/huggingface/transformers) (pretrained model +"stabilityai/stable-diffusion-2-1-base") and then encoded using CLIPTextModel from the same package and pretrained +model. + + +## **commands example** +Execute sampling: +```shell +export PYTHONPATH=$PYTHONPATH:"" +$ python -m monai.bundle run save_nii --config_file configs/inference.json --prompt "Big right-sided pleural effusion" --guidance_scale 7.0 +``` + +```shell +$ python -m monai.bundle run save_nii --config_file configs/inference.json --prompt "Small right-sided pleural effusion" --guidance_scale 7.0 +``` + +```shell +$ python -m monai.bundle run save_nii --config_file configs/inference.json --prompt "Bilateral pleural effusion" --guidance_scale 7.0 +``` + +```shell +$ python -m monai.bundle run save_nii --config_file configs/inference.json --prompt "Cardiomegaly" --guidance_scale 7.0 +``` + + +## **References** + +Example: + +[1] Pinaya, Walter HL, et al. "Brain imaging generation with latent diffusion models." MICCAI Workshop on Deep Generative Models. Springer, Cham, 2022. + +[2] Johnson, A., Lungren, M., Peng, Y., Lu, Z., Mark, R., Berkowitz, S., & Horng, S. (2019). MIMIC-CXR-JPG - chest radiographs with structured labels (version 2.0.0). PhysioNet. https://doi.org/10.13026/8360-t248. + +[3] Johnson AE, Pollard TJ, Berkowitz S, Greenbaum NR, Lungren MP, Deng CY, Mark RG, Horng S. MIMIC-CXR: A large publicly available database of labeled chest radiographs. arXiv preprint arXiv:1901.07042. 2019 Jan 21. diff --git a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/large_files.yml b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/large_files.yml new file mode 100644 index 00000000..facfa840 --- /dev/null +++ b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/large_files.yml @@ -0,0 +1,9 @@ +large_files: + - path: "models/autoencoder.pth" + url: "https://drive.google.com/uc?export=download&id=11Em6qkEsqbFrtJau2mlZAvQZqQmiIEVe" + hash_val: "" + hash_type: "" + - path: "models/diffusion_model.pth" + url: "https://drive.google.com/uc?export=download&id=1PUqHb_0dKB7GAXA3P8l_3pIyorLudgrB" + hash_val: "" + hash_type: "" diff --git a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/scripts/__init__.py b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/scripts/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/scripts/sampler.py b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/scripts/sampler.py new file mode 100644 index 00000000..c0e602e3 --- /dev/null +++ b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/scripts/sampler.py @@ -0,0 +1,43 @@ +from __future__ import annotations + +import torch +import torch.nn as nn +from monai.utils import optional_import +from torch.cuda.amp import autocast + +tqdm, has_tqdm = optional_import("tqdm", name="tqdm") + + +class Sampler: + def __init__(self) -> None: + super().__init__() + + @torch.no_grad() + def sampling_fn( + self, + noise: torch.Tensor, + autoencoder_model: nn.Module, + diffusion_model: nn.Module, + scheduler: nn.Module, + prompt_embeds: torch.Tensor, + guidance_scale: float = 7.0, + scale_factor: float = 0.3, + ) -> torch.Tensor: + if has_tqdm: + progress_bar = tqdm(scheduler.timesteps) + else: + progress_bar = iter(scheduler.timesteps) + + for t in progress_bar: + noise_input = torch.cat([noise] * 2) + model_output = diffusion_model( + noise_input, timesteps=torch.Tensor((t,)).to(noise.device).long(), context=prompt_embeds + ) + noise_pred_uncond, noise_pred_text = model_output.chunk(2) + noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond) + noise, _ = scheduler.step(noise_pred, t, noise) + + with autocast(): + sample = autoencoder_model.decode_stage_2_outputs(noise / scale_factor) + + return sample diff --git a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/scripts/saver.py b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/scripts/saver.py new file mode 100644 index 00000000..b945ceec --- /dev/null +++ b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/scripts/saver.py @@ -0,0 +1,17 @@ +from __future__ import annotations + +import numpy as np +import torch +from PIL import Image + + +class JPGSaver: + def __init__(self, output_dir: str) -> None: + super().__init__() + self.output_dir = output_dir + + def save(self, image_data: torch.Tensor, file_name: str) -> None: + image_data = image_data.cpu().numpy() + image_data = (image_data * 255).astype(np.uint8) + im = Image.fromarray(image_data[0, 0]) + im.save(self.output_dir + "/" + file_name + ".jpg") From 5afef998393b3c453728e925c05d4b84fc26e987 Mon Sep 17 00:00:00 2001 From: Walter Hugo Lopez Pinaya Date: Mon, 6 Mar 2023 14:36:13 +0000 Subject: [PATCH 2/5] Fix bundle_root Signed-off-by: Walter Hugo Lopez Pinaya --- .../configs/inference.json | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json index b120d939..951e5b3a 100644 --- a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json +++ b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json @@ -6,8 +6,7 @@ "$from transformers import CLIPTextModel", "$from transformers import CLIPTokenizer" ], - "//bundle_root": ".", - "bundle_root": "/media/walter/Storage/Projects/GenerativeModels/model-zoo/models/cxr_image_synthesis_latent_diffusion_model", + "bundle_root": ".", "model_dir": "$@bundle_root + '/models'", "output_dir": "$@bundle_root + '/output'", "create_output_dir": "$Path(@output_dir).mkdir(exist_ok=True)", From 2f266bbd06ff8d67d2455245717fab9dd5231572 Mon Sep 17 00:00:00 2001 From: Walter Hugo Lopez Pinaya Date: Mon, 6 Mar 2023 15:46:06 +0000 Subject: [PATCH 3/5] Apply suggestions from code review Co-authored-by: Eric Kerfoot <17726042+ericspod@users.noreply.github.com> --- .../cxr_image_synthesis_latent_diffusion_model/docs/README.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md index d1c4ff77..858b2c14 100644 --- a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md +++ b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md @@ -28,7 +28,7 @@ transformers package (https://github.com/huggingface/transformers) (pretrained m model. -## **commands example** +## **Commands Example** Execute sampling: ```shell export PYTHONPATH=$PYTHONPATH:"" @@ -50,7 +50,6 @@ $ python -m monai.bundle run save_nii --config_file configs/inference.json --pro ## **References** -Example: [1] Pinaya, Walter HL, et al. "Brain imaging generation with latent diffusion models." MICCAI Workshop on Deep Generative Models. Springer, Cham, 2022. From 10fe25118c3af3c23f4bb42d37209604f72ea68e Mon Sep 17 00:00:00 2001 From: Walter Hugo Lopez Pinaya Date: Mon, 6 Mar 2023 15:56:55 +0000 Subject: [PATCH 4/5] Add more information about the arguments Signed-off-by: Walter Hugo Lopez Pinaya --- .../configs/inference.json | 2 +- .../docs/README.md | 19 ++++++++++++++----- 2 files changed, 15 insertions(+), 6 deletions(-) diff --git a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json index 951e5b3a..c5e5bf60 100644 --- a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json +++ b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/inference.json @@ -102,6 +102,6 @@ "_requires_": "@create_output_dir", "output_dir": "@output_dir" }, - "save_nii": "$@saver.save(@sample, @out_file)", + "save_jpg": "$@saver.save(@sample, @out_file)", "save": "$torch.save(@sample, @output_dir + '/' + @out_file + '.pt')" } diff --git a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md index 858b2c14..68bceeae 100644 --- a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md +++ b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/docs/README.md @@ -29,22 +29,31 @@ model. ## **Commands Example** -Execute sampling: +Here we included a few examples of commands to sample images from the model and save them as .jpg files. The available +arguments for this task are: "--prompt" (str) text prompt to condition the model on; "--guidance_scale" (float), the +parameter that controls how much the image generation process follows the text prompt. The higher the value, the more +the image sticks to a given text input (the common range is between 1-21). + +Examples: + ```shell export PYTHONPATH=$PYTHONPATH:"" -$ python -m monai.bundle run save_nii --config_file configs/inference.json --prompt "Big right-sided pleural effusion" --guidance_scale 7.0 +$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Big right-sided pleural effusion" --guidance_scale 7.0 ``` ```shell -$ python -m monai.bundle run save_nii --config_file configs/inference.json --prompt "Small right-sided pleural effusion" --guidance_scale 7.0 +export PYTHONPATH=$PYTHONPATH:"" +$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Small right-sided pleural effusion" --guidance_scale 7.0 ``` ```shell -$ python -m monai.bundle run save_nii --config_file configs/inference.json --prompt "Bilateral pleural effusion" --guidance_scale 7.0 +export PYTHONPATH=$PYTHONPATH:"" +$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Bilateral pleural effusion" --guidance_scale 7.0 ``` ```shell -$ python -m monai.bundle run save_nii --config_file configs/inference.json --prompt "Cardiomegaly" --guidance_scale 7.0 +export PYTHONPATH=$PYTHONPATH:"" +$ python -m monai.bundle run save_jpg --config_file configs/inference.json --prompt "Cardiomegaly" --guidance_scale 7.0 ``` From 97070f637dd94140c4495924538f78d6e181932a Mon Sep 17 00:00:00 2001 From: Walter Hugo Lopez Pinaya Date: Wed, 8 Mar 2023 12:06:50 +0000 Subject: [PATCH 5/5] Fix metadata.json Signed-off-by: Walter Hugo Lopez Pinaya --- .../configs/metadata.json | 37 +++++++++++++------ 1 file changed, 25 insertions(+), 12 deletions(-) diff --git a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json index 7097cb93..36ded665 100644 --- a/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json +++ b/model-zoo/models/cxr_image_synthesis_latent_diffusion_model/configs/metadata.json @@ -13,25 +13,38 @@ "transformers": "4.26.1" }, "task": "Chest X-ray image synthesis", - "description": "A generative model for creating high-resolution Chest X-ray based on MIMIC dataset", + "description": "A generative model for creating high-resolution chest X-ray based on MIMIC dataset", "copyright": "Copyright (c) MONAI Consortium", "data_source": "https://physionet.org/content/mimic-cxr-jpg/2.0.0/", "data_type": "image", - "image_classes": "X-ray with 512 x 512 pixels", + "image_classes": "Radiography (X-ray) with 512 x 512 pixels", "intended_use": "This is a research tool/prototype and not to be used clinically", - "references": [ - "Pinaya, Walter HL, et al. \"Brain imaging generation with latent diffusion models.\" MICCAI Workshop on Deep Generative Models. Springer, Cham, 2022." - ], "network_data_format": { "inputs": { - "report": { - "type": "text", - "num_tokens": 77, - "dtype": "string" + "latent_representation": { + "type": "image", + "format": "magnitude", + "modality": "CXR", + "num_channels": 3, + "spatial_shape": [ + 64, + 64 + ], + "dtype": "float32", + "value_range": [], + "is_patch_data": false + }, + "timesteps": { + "type": "vector", + "value_range": [ + 0, + 1000 + ], + "dtype": "long" }, - "guidance_scale": { - "type": "float", - "num_tokens": 77, + "context": { + "type": "vector", + "value_range": [], "dtype": "float32" } },