V good first issues

Vedrock is undergoing a significant architectural shift from a fixed server implementation to a flexible framework for building custom Minecraft: Bedrock Edition servers. This transition, primarily happening on the `dev2` branch, aims to empower developers to compose and extend their own servers using Vedrock's core runtime and APIs, moving away from a monolithic internal assembly of server components.

This issue proposes adding a new end-to-end example for transformer/attention mechanisms in the `examples/` directory. The example will demonstrate self-attention with positional encoding and include a README explaining the concept and how to run it.

This issue proposes adding a 1D convolutional layer (Conv1D) to the neural network library. The implementation should follow the existing Conv2D pattern, including separate files for the layer definition, internal CPU kernels, and autograd gate. Verification will involve comparing forward passes with PyTorch and performing gradient checks.

This issue proposes adding a Gated Recurrent Unit (GRU) layer to the neural network library, similar to the existing Long Short-Term Memory (LSTM) layer. The task involves defining the GRU layer, implementing its CPU kernels, adding autograd support, and creating a test case. A stretch goal includes GPU support.

This issue proposes adding three new loss functions (L1/MAE, Hinge, and Focal) to the existing library. The implementation should follow the pattern of existing loss functions and include comprehensive tests, verifying against PyTorch for accuracy and correctness of gradients.

This issue proposes adding two new popular Adam optimizer variants, NAdam and RAdam, to the existing optimizer library. The implementation should follow the established patterns for Adam and AdamW, including handling float32 and float64 precision, and require verification through unit tests on the XOR benchmark and comparison with reference implementations.

This issue proposes expanding the `datasets/imdb_test.v` file, which currently only tests the shape of the dataset. The goal is to add comprehensive tests for tokenization, subset loading, graceful skipping when the dataset is not downloaded, and vocabulary properties.

This issue proposes adding three new activation functions (Softplus, SELU, and HardSwish) to the neural network module. The implementation should follow existing patterns for activation functions and include corresponding gates and internal activation definitions. Verification will involve comparing outputs against PyTorch.

This issue proposes adding a test file for the CIFAR-10 dataset loader in the vtl/datasets module. The goal is to ensure the loader functions correctly under various configurations, including default and subset loading, and validates the expected data shapes and class counts.

This issue proposes expanding the `CONTRIBUTING.md` file to include crucial information missing from the current document. The additions will cover coding standards, test conventions, commit message formats, guidelines for adding new components, CI gate requirements, and the Hacktoberfest process. The goal is to create a more comprehensive guide for contributors, referencing VSL's `CONTRIBUTING.md` as a model.

This issue addresses an incomplete "Module overview" table in the project's README.md file. Several modules are missing from the table, and the task is to update it to include all modules with their descriptions and relevant links.

This issue requests the addition of README files for four user-facing modules: `la`, `stats`, `storage`, and `ml`. The READMEs should document the purpose and key features of each module, including specific details like backends, contracts, and limitations. The goal is to improve documentation for these modules, with links to tutorials and examples for verification.

This issue proposes adding comprehensive README files to the `nn` module and all its sub-modules within the project. The goal is to document the architecture, public APIs, mathematical formulas, update rules, and type definitions for various components like layers, loss functions, optimizers, and internal implementations.

This issue proposes adding a README file to the `autograd` module to document its functionality. The README should cover supported gate files and operations, core types, GPU support, and links to existing documentation. This aims to provide a concise, internal overview of the autograd module.

This issue requests the creation of a SECURITY.md file for the repository. The file should outline the project's security policy, including supported versions of native C libraries, the process for reporting vulnerabilities (via email or GitHub Security Advisory), and expected response timelines.

This issue proposes adding unit tests for the HDF5 input/output module within the `inout/` directory. The tests should create, write to, and read from an HDF5 file, and importantly, be designed to skip gracefully if the HDF5 library is not available on the system. This will ensure the module's functionality is verified and robust.

This issue proposes adding unit tests for the `errors` module in the V programming language. Specifically, it aims to create a new test file (`errors/errno_test.v`) to cover the `errors/errno.v`, `errors/errors.v`, and `errors/strerrno.v` files, ensuring that known errno integers map correctly to their string representations and that error code constants are consistent.

This issue requests the creation of a README file for the `compute/` module in the project's documentation. The README should explain the compute abstraction layer, its dispatch mechanism to backend modules (vcl, cuda, vulkan), supported operations, and provide a usage example. This aims to improve documentation consistency and user understanding of the GPU computing interface.

This issue requests the completion of three stub documentation articles in the `docs/advanced/` directory. The task involves writing detailed walkthroughs for MPI parallel programming, HDF5 I/O, and library integration, using existing examples as a guide. The goal is to bring these articles to the same depth as the OpenCL GPU article.

This issue requests an expansion of three README files within the `dist`, `noise`, and `roots` modules. The goal is to provide more comprehensive documentation, including module purpose, public API details with usage examples, and links to related resources, using `metrics/README.md` as a quality benchmark.

This issue proposes to refactor duplicate test code for FFT implementations. The shared logic in `fft_test.v` and `fft64_test.v` will be extracted into a common file, and both original files will import and parameterize this new common file. Additionally, a new cross-validation test will be added to ensure consistency between f32 and f64 FFT results.

This issue proposes adding unit tests for the geometry (gm) module in the vlang project. Specifically, it aims to cover the `basicgm.v` and `bins.v` files, which currently lack test coverage. The tests should include functionality like point creation, distance computation, bin operations, and handling edge cases.

This issue proposes adding a comprehensive unit test suite for the quaternion module in the V programming language. The goal is to cover various quaternion operations like rotations, interpolations (SLERP, NLERP), and basic arithmetic, ensuring the module's functionality is well-tested and reliable.

This issue requests the creation of a new documentation tutorial file for combining observables using operators like merge, concat, and zip. The tutorial should be located at `docs/tutorials/06-combining.md` and include code examples, potentially incorporating `combine_latest` once it's implemented.

This issue proposes adding unit tests for the `average_f64` and `sum_f64` operators. Currently, only `average_f64` has an example file, and neither operator has dedicated tests. The goal is to ensure the correctness of these aggregation operators, which are crucial for scientific computing, by adding a new test file with known inputs and expected outputs.

This issue proposes adding a new `ignore_elements` operator to the library. This operator will subscribe to a source observable, discard all emitted values, and complete when the source completes, making it useful for streams that only have side effects. A test case needs to be added to verify its functionality.

This issue proposes adding new functionality to the `combination` module to handle merging multiple observables. Specifically, it aims to introduce a variadic `merge` function that can accept any number of observables, a `merge_all` function for flattening observable-of-observables, and a `merge_map_` function that combines mapping and merging. The implementation will require adding new tests to ensure the functionality works as expected.

This issue requests the addition of test coverage for several implemented operators in the codebase that currently lack tests. The task involves creating new tests for operators like `take`, `timeout`, `interval`, `timer`, `defer_`, `from_channel`, `empty`, `throw`, and `range` to ensure their correct functionality.

This issue proposes the implementation of two new operators: `time_interval` which measures the time elapsed between emitted items, and `timestamp` which adds the current time to each emitted item. The implementation requires adding new tests in `timing_test.v` and ensuring all tests pass.

This issue proposes the implementation of two new RxJS operators: `on_error_resume_next` and `finally_`. The `on_error_resume_next` operator will allow a subscription to switch to a fallback observable when an error occurs, complementing the existing `catch_error` operator. The `finally_` operator will execute a provided function as a side effect when the source observable completes or errors.