Ben_Kosytorz
3a67c0979c
- Updated stablediffusion crate path from "../stable-diffusion-burn" to "./crates/stable-diffusion-burn" for proper workspace resolution - Enhanced .gitignore to include generated model files (.mpk, .pt, .bin, .safetensors, .ckpt) and user_data directory - Added Cargo.lock to gitignore with appropriate comment - Reorganized IDE files section in gitignore for better clarity - Added newline at end of file for proper formatting
112 lines
3.6 KiB
Markdown
112 lines
3.6 KiB
Markdown
# Burn Backend Tests
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This crate provides a comprehensive suite of tests for Burn backends, covering:
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- Tensor operations: [tests/tensor/](./tests/tensor/)
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- Autodiff: [tests/autodiff/](./tests/autodiff/)
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- (Optional) CubeCL kernels correctness: [tests/cubecl/](./tests/cubecl/)
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## Running Tests
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The `TestBackend` is selected via feature flags. Use the provided shorthand commands for
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convenience:
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```sh
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# Cpu
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cargo test-cpu
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# Cuda
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cargo test-cuda
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# Rocm
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cargo test-rocm
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# Wgpu / WebGpu
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cargo test-wgpu
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# Vulkan
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cargo test-vulkan
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# Metal
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cargo test-metal
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# Router
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cargo test-router
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# NdArray
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cargo test-ndarray
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# LibTorch
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cargo test-tch
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```
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By default, `cargo test` fail-fast across integration test binaries. When one integration test
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binary fails, Cargo does not run the remaining test binaries. If you want to run all test binaries
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regardless of failures, pass `--no-fail-fast`, for example:
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```sh
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cargo test-cuda --no-fail-fast
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```
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## Structure
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- `tests/tensor.rs`: Tensor tests
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- `tests/autodiff.rs`: Autodiff tests
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- `tests/fusion.rs`: Fusion backend tests wrapping tensor and autodiff tests
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- `tests/cubecl.rs`: CubeCL kernel tests
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Each test module assumes exactly one `FloatElemType`, `IntElemType`, and `TestBackend` in scope.
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### Common Modules
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- `common/backend.rs`: Backend type definitions
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- `common/tensor.rs`: Reusable tensor test suite, split across float, int and bool tensor kinds
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- `common/autodiff.rs`: Reusable autodiff test suite, with and without checkpointing
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### Test Reusability
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This crate uses a pattern of parameterized test modules to run the same tests with different
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configurations (backends, dtypes, etc.):
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1. **Type aliases define the configuration**: Each test scope declares `FloatElemType`,
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`IntElemType`, and `TestBackend`
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1. **`#[path = "..."]` references shared modules**: Points to test files outside the normal module
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hierarchy, e.g. `"common/tensor.rs"`
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1. **`include!()` imports test code**: Test modules are included multiple times with different type
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configurations
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1. **`use super::*;`** propagates types down the module tree: Each level re-exports parent types so
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deeply nested tests have access to the configured types
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For example, `common/tensor.rs` can be included with `FloatElemType = f32` for base tests, then
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included again with `FloatElemType = f16` for half-precision tests, running the same test suite
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twice with different dtypes.
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## Adding New Tests
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Add test modules under `tests/tensor/`, `tests/autodiff/`, or `tests/cubecl` respectively. They will
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automatically run for all required configurations.
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For tensor tests, make sure to add the test to each relevant tensor kind:
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- `tensor/bool`: boolean tensor tests
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- `tensor/float`: float tensor tests
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- `tensor/int`: integer tensor tests
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**Guidelines:**
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Import types with `use super::*;` at the top of each module and use the types defined in
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`common/backend.rs`:
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```rust
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/// Collection of types used across tests
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pub use burn_autodiff::Autodiff;
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pub use burn_tensor::Tensor;
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pub type TestBackend = ...;
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pub type TestTensor<const D: usize> = Tensor<TestBackend, D>;
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pub type TestTensorInt<const D: usize> = Tensor<TestBackend, D, burn_tensor::Int>;
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pub type TestTensorBool<const D: usize> = Tensor<TestBackend, D, burn_tensor::Bool>;
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pub type FloatElem = burn_tensor::ops::FloatElem<TestBackend>;
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pub type IntElem = burn_tensor::ops::IntElem<TestBackend>;
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pub type TestAutodiffBackend = Autodiff<TestBackend>;
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pub type TestAutodiffTensor<const D: usize> = Tensor<TestAutodiffBackend, D>;
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```
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Tests will automatically run with default dtypes and any variants (f16, bf16, etc.) based on the
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backend configuration.
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