Merge remote-tracking branch 'b/add-trt-config' into add-trt-config

.pre-commit-config.yaml

@@ -9,7 +9,7 @@ ci:
 
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.6.0
+    rev: v5.0.0
     hooks:
       - id: end-of-file-fixer
       - id: trailing-whitespace
@@ -23,7 +23,7 @@ repos:
       - id: detect-private-key
 
   - repo: https://github.com/psf/black
-    rev: "24.4.2"
+    rev: "24.10.0"
     hooks:
       - id: black
       - id: black-jupyter

generation/README.md

@@ -43,7 +43,7 @@ Example shows the use cases of using MONAI to evaluate the performance of a gene
 ## [Training a 2D VQ-VAE + Autoregressive Transformers](./2d_vqvae_transformer/2d_vqvae_transformer_tutorial.ipynb):
 Example shows how to train a Vector-Quantized Variation Autoencoder + Transformers on the MedNIST dataset.
 
-## Training VQ-VAEs and VQ-GANs: [2D VAE](./2d_vqvae/2d_vqvae_tutorial.ipynb), [3D VAE](./3d_vqvae/3d_vqvae_tutorial.ipynb) and [2D GAN](./3d_autoencoderkl/2d_vqgan_tutorial.ipynb)
+## Training VQ-VAEs and VQ-GANs: [2D VAE](./2d_vqvae/2d_vqvae_tutorial.ipynb), [3D VAE](./3d_vqvae/3d_vqvae_tutorial.ipynb) and [2D GAN](./2d_vqgan/2d_vqgan_tutorial.ipynb)
 Examples show how to train Vector Quantized Variation Autoencoder on [2D](./2d_vqvae/2d_vqvae_tutorial.ipynb) and [3D](./3d_vqvae/3d_vqvae_tutorial.ipynb), and how to use the PatchDiscriminator class to train a [VQ-GAN](./2d_vqgan/2d_vqgan_tutorial.ipynb) and improve the quality of the generated images.
 
 ## [Training a 2D Denoising Diffusion Probabilistic Model](./2d_ddpm/2d_ddpm_tutorial.ipynb):

pathology/tumor_detection/ignite/profiling_camelyon_pipeline.ipynb

@@ -159,7 +159,7 @@
     "!nsys profile \\\n",
     "    --trace nvtx,osrt,cudnn,cuda, \\\n",
     "    --delay 5 \\\n",
-    "    --duration 10 \\\n",
+    "    --duration 20 \\\n",
     "    --show-output true \\\n",
     "    --force-overwrite true \\\n",
     "    --output profile_report.nsys-rep \\\n",