Merge branch '4980-get-wsi-at-mpp' of https://github.com/NikolasSchmitz/MONAI into 4980-get-wsi-at-mpp

Author: NikolasSchmitz

README.md

@@ -1,5 +1,5 @@
 <p align="center">
-  <img src="https://raw.githubusercontent.com/Project-MONAI/MONAI/dev/docs/images/MONAI-logo-color.png" width="50%" alt='project-monai'>
+<img src="https://raw.githubusercontent.com/Project-MONAI/MONAI/dev/docs/images/MONAI-logo-color.png" width="50%" alt='project-monai'>
 </p>
 
 **M**edical **O**pen **N**etwork for **AI**

monai/networks/schedulers/ddim.py

@@ -117,18 +117,14 @@ def set_timesteps(self, num_inference_steps: int, device: str | torch.device | N
             )
 
         self.num_inference_steps = num_inference_steps
-        step_ratio = self.num_train_timesteps // self.num_inference_steps
-        if self.steps_offset >= step_ratio:
-            raise ValueError(
-                f"`steps_offset`: {self.steps_offset} cannot be greater than or equal to "
-                f"`num_train_timesteps // num_inference_steps : {step_ratio}` as this will cause timesteps to exceed"
-                f" the max train timestep."
-            )
-
-        # creates integer timesteps by multiplying by ratio
-        # casting to int to avoid issues when num_inference_step is power of 3
-        timesteps = (np.arange(0, num_inference_steps) * step_ratio).round()[::-1].copy().astype(np.int64)
-        self.timesteps = torch.from_numpy(timesteps).to(device)
+        if self.steps_offset < 0 or self.steps_offset >= self.num_train_timesteps:
+            raise ValueError(f"`steps_offset`: {self.steps_offset} must be in range [0, {self.num_train_timesteps}).")
+
+        self.timesteps = (
+            torch.linspace((self.num_train_timesteps - 1) - self.steps_offset, 0, num_inference_steps, device=device)
+            .round()
+            .long()
+        )
         self.timesteps += self.steps_offset
 
     def _get_variance(self, timestep: int, prev_timestep: int) -> torch.Tensor:

monai/networks/schedulers/ddpm.py

@@ -31,7 +31,6 @@
 
 from __future__ import annotations
 
-import numpy as np
 import torch
 
 from monai.utils import StrEnum
@@ -122,11 +121,9 @@ def set_timesteps(self, num_inference_steps: int, device: str | torch.device | N
             )
 
         self.num_inference_steps = num_inference_steps
-        step_ratio = self.num_train_timesteps // self.num_inference_steps
-        # creates integer timesteps by multiplying by ratio
-        # casting to int to avoid issues when num_inference_step is power of 3
-        timesteps = (np.arange(0, num_inference_steps) * step_ratio).round()[::-1].astype(np.int64)
-        self.timesteps = torch.from_numpy(timesteps).to(device)
+        self.timesteps = (
+            torch.linspace(self.num_train_timesteps - 1, 0, self.num_inference_steps, device=device).round().long()
+        )
 
     def _get_mean(self, timestep: int, x_0: torch.Tensor, x_t: torch.Tensor) -> torch.Tensor:
         """

requirements-dev.txt

@@ -51,7 +51,7 @@ h5py
 nni==2.10.1; platform_system == "Linux" and "arm" not in platform_machine and "aarch" not in platform_machine
 optuna
 git+https://github.com/Project-MONAI/MetricsReloaded@monai-support#egg=MetricsReloaded
-onnx>=1.13.0
+onnx>=1.13.0, <1.19.1
 onnxruntime; python_version <= '3.10'
 typeguard<3  # https://github.com/microsoft/nni/issues/5457
 filelock<3.12.0  # https://github.com/microsoft/nni/issues/5523