Open codeant-ai[bot] opened 6 months ago
Seems you are using me but didn't get OPENAI_API_KEY seted in Variables/Secrets for this repo. you could follow readme for more information
Processing PR updates...
Unable to locate .performanceTestingBot config file
Thanks @codeant-ai[bot] for opening this PR!
For COLLABORATOR only :
To add labels, comment on the issue
/label add label1,label2,label3
To remove labels, comment on the issue
/label remove label1,label2,label3
PR Details of @codeant-ai[bot] in torchdiffeq : | OPEN | CLOSED | TOTAL |
---|---|---|---|
2 | 1 | 3 |
Description has been updated!
Check out the playback for this Pull Request here.
[!IMPORTANT]
Auto Review Skipped
Bot user detected.
To trigger a single review, invoke the
@coderabbitai review
command.
Thank you for using CodeRabbit. We offer it for free to the OSS community and would appreciate your support in helping us grow. If you find it useful, would you consider giving us a shout-out on your favorite social media?
Description
This pull request modifies the
torchdiffeq/_impl/misc.py
file. Here is a summary of the changes made:_handle_unused_kwargs
that warns if there are any unexpected arguments passed to the solver._linf_norm
that calculates the L-infinity norm of a given tensor._rms_norm
that calculates the root mean square (RMS) norm of a given tensor._zero_norm
that returns 0 as the norm for any input tensor._mixed_norm
that calculates the maximum RMS norm among multiple tensor inputs._select_initial_step
that selects the initial step size for numerical integration._compute_error_ratio
that computes the error ratio for adaptive step size control._optimal_step_size
that determines the optimal step size based on error ratio and other parameters._decreasing
that checks if a sequence is strictly decreasing._assert_one_dimensional
that asserts that a tensor is one-dimensional._assert_increasing
that asserts that a sequence is strictly increasing._assert_floating
that asserts that a tensor is of floating point type._tuple_tol
that handles error tolerances when multiple tolerances are provided as a tuple._flat_to_shape
that converts a flat tensor to a tensor with the specified shape._TupleFunc
that wraps a function to accept and return tensors with multiple shapes._TupleInputOnlyFunc
that wraps a function to accept only the input tensor with multiple shapes._ReverseFunc
that reverses the time variable and multiplies the output of a base function by a constant factor.Perturb
as an enumeration for different perturbation modes._PerturbFunc
that wraps a base function and provides a perturbation mode argument.These changes provide additional utility functions and classes for the solver implementation.