From d9b971446c843b3a5e116e9740be763b338d7dc0 Mon Sep 17 00:00:00 2001 From: pollfly <75068813+pollfly@users.noreply.github.com> Date: Sun, 10 Dec 2023 14:51:48 +0200 Subject: [PATCH] Small edits (#727) --- docs/fundamentals/artifacts.md | 2 +- docs/integrations/pytorch.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/fundamentals/artifacts.md b/docs/fundamentals/artifacts.md index 40e9e983..d5ef2919 100644 --- a/docs/fundamentals/artifacts.md +++ b/docs/fundamentals/artifacts.md @@ -21,7 +21,7 @@ frameworks: * [Fast.ai](../integrations/fastai.md) * [MegEngine](../integrations/megengine.md) * [CatBoost](../integrations/catboost.md) -* [MONAI](../integrations/monai.md)) +* [MONAI](../integrations/monai.md) When a supported framework loads a weights file, the running task will be automatically updated, with its input model pointing directly to the original training task's model. diff --git a/docs/integrations/pytorch.md b/docs/integrations/pytorch.md index 8d931af1..585192c2 100644 --- a/docs/integrations/pytorch.md +++ b/docs/integrations/pytorch.md @@ -92,7 +92,7 @@ additional tools, like argparse, TensorBoard, and matplotlib: * [PyTorch TensorBoardX](../guides/frameworks/pytorch/pytorch_tensorboardx.md) - Demonstrates ClearML automatically logging PyTorch models, and scalars, debug samples, and text logged using TensorBoardX's `SummaryWriter` * [PyTorch Abseil](../guides/frameworks/pytorch/pytorch_abseil.md) - Demonstrates ClearML automatically logging PyTorch models and `absl.flags` parameters * [PyTorch Model Updating](../guides/frameworks/pytorch/model_updating.md) - Demonstrates training, logging, and updating a PyTorch model using ClearML's [OutputModel](../references/sdk/model_outputmodel.md) class -* [PyTorch Distributed](../guides/frameworks/pytorch/pytorch_distributed_example.md) - Demonstrates using ClearML with the [PyTorch Distributed Communications Package (torch.distributed)](https://pytorch.org/tutorials/beginner/dist_overview.html) +* [PyTorch Distributed](../guides/frameworks/pytorch/pytorch_distributed_example.md) - Demonstrates using ClearML with the [PyTorch Distributed Communications Package (`torch.distributed`)](https://pytorch.org/tutorials/beginner/dist_overview.html) ## Remote Execution ClearML logs all the information required to reproduce an experiment on a different machine (installed packages,