Testing

Test for Tensor Operations

Test for tensor operations (generally of the form: given this input, expect it match or approximate this output) are defined only in crates/burn-tensor/src/test/ops and not in the backends (with the exception of burn-autodiff). The tensor operation tests are added to the testgen_all macro rule in crates/burn-tensor/src/tests/mod.rs. This is then propagated to the existing backends without any additional work.

Test for Autodiff

Tests for autodiff go under burn-autodiff/src/tests and should verify backward pass correctness. For binary tensor operations, both the left and right sides need to be verified.

Here's an easy way to define tests for a new operation's backward pass:

1. Use small tensors with simple values.
2. Pop open a terminal, launch ipython and import numpy then do the calculations by hand. You can also use Google Colab so you don't have to install the packages on your system.
3. Compare the actual outputs to the expected output for left-hand side, right-hand side.

For float tensors, it is advised to use actual_output_tensor.into_data().assert_approx_eq::<FloatElem<TestBackend>>(&expected_tensor_data, Tolerance::default()) instead of assert_eq!(... due to occasional hiccups with floating point calculations. Other assertions should also always use FloatElem<TestBackend>, and use .elem() to convert any literals. Backends are tested for multiple precisions, and hardcoding to a fixed type causes tests to fail with alternate floating point precisions. For convenience, it might be worth aliasing the type like type FT = FloatElem<TestBackend>;.

For integers, tests should use IntElem<TestBackend>, and exit the test if the test values are unrepresentable (above max_value, below min_value). A minimum range of [0..127] (i8) can be assumed.