diff --git a/beginner_source/hyperparameter_tuning_tutorial.py b/beginner_source/hyperparameter_tuning_tutorial.py index 2680d1a23c3..aa84069f7be 100644 --- a/beginner_source/hyperparameter_tuning_tutorial.py +++ b/beginner_source/hyperparameter_tuning_tutorial.py @@ -10,7 +10,7 @@ Fortunately, there are tools that help with finding the best combination of parameters. `Ray Tune `_ is an industry standard tool for distributed hyperparameter tuning. Ray Tune includes the latest hyperparameter search -algorithms, integrates with TensorBoard and other analysis libraries, and natively +algorithms, integrates with various analysis libraries, and natively supports distributed training through `Ray's distributed machine learning engine `_. diff --git a/en-wordlist.txt b/en-wordlist.txt index 79545a9ff03..8a118b941b2 100644 --- a/en-wordlist.txt +++ b/en-wordlist.txt @@ -1,4 +1,3 @@ - ACL ADI AOT @@ -188,6 +187,7 @@ PIL's PPO PatchPredictor PennFudan +Perfetto Pixman Plotly Pohjonen diff --git a/intermediate_source/tensorboard_profiler_tutorial.py b/intermediate_source/tensorboard_profiler_tutorial.py index 00bdcfbf079..3782ced18d9 100644 --- a/intermediate_source/tensorboard_profiler_tutorial.py +++ b/intermediate_source/tensorboard_profiler_tutorial.py @@ -4,6 +4,14 @@ This tutorial demonstrates how to use TensorBoard plugin with PyTorch Profiler to detect performance bottlenecks of the model. +.. warning:: + The TensorBoard integration with the PyTorch profiler is now + deprecated. Instead, use Perfetto or the Chrome trace to + view ``trace.json`` files. After + `generating a trace `__, + simply drag the ``trace.json`` into `Perfetto UI `__ + or ``chrome://tracing`` to visualize your profile. + Introduction ------------ PyTorch 1.8 includes an updated profiler API capable of diff --git a/recipes_source/recipes/profiler_recipe.py b/recipes_source/recipes/profiler_recipe.py index b2d28192bd2..4d43726e71f 100644 --- a/recipes_source/recipes/profiler_recipe.py +++ b/recipes_source/recipes/profiler_recipe.py @@ -459,7 +459,6 @@ def trace_handler(p): # # Take a look at the following recipes/tutorials to continue your learning: # -# - `PyTorch Benchmark `_ -# - `PyTorch Profiler with TensorBoard `_ tutorial -# - `Visualizing models, data, and training with TensorBoard `_ tutorial +# - `PyTorch Benchmark `_ +# - `Visualizing models, data, and training with TensorBoard `_ tutorial #