diff --git a/docs/source/conf.py b/docs/source/conf.py index 295f247a9..d0c56d306 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -17,11 +17,11 @@ # -- Project information ----------------------------------------------------- project = 'Brain-Score' -copyright = '2022, Brain-Score Team' +copyright = '2024, Brain-Score Team' author = 'Brain-Score Team' # The full version, including alpha/beta/rc tags -release = '1.3' +release = '2.0.0' # -- General configuration --------------------------------------------------- diff --git a/docs/source/modules/developer_clarifications.rst b/docs/source/modules/developer_clarifications.rst new file mode 100644 index 000000000..6e63f2008 --- /dev/null +++ b/docs/source/modules/developer_clarifications.rst @@ -0,0 +1,36 @@ +.. _interface: + +************************ +Developer Clarifications +************************ + +The Following documentation stores commonly-asked developer questions. We hope this will be useful to +anyone interested in contributing to Brain-Score's codebase or scientific workings. + + + +1. **For a given model, are activations different on each benchmark? How?** + + + Activations per model are generated based on benchmark stimuli; not every benchmark has unique stimuli. For most + model-benchmark pairs, activations will be different because stimuli will be different. The exceptions to this + are the benchmarks that use the same stimuli, such as the `MajajHong20215` family of benchmarks. + +2. **Result Caching** + + Result Caching is a Brain-Score `repo `_ that allows model activations (and other functions) to be cached + to disk, in order to speed up the process of rescoring models. It contains a decorator that can be attached to a function + right before it is defined. On the first run of that function, `result_caching` will save to disk the result of tha function + and will load that result from disk in future calls with the same parameters. All files are saved in the user's `~/result_caching` + folder, and they are persistent, as there is no garbage collection built in. You can deactivate + `result_caching` by simply setting the environment flag `RESULTCACHING_DISABLE` to `1`. Please see the link above + for more detailed documentation. + +3. **Model Mapping Procedure** + + In general, there are different methods that are used in the Brain-Score code to instruct the model to "begin recording", + observe stimuli, and to generate scores. Models follow the `ModelCommitment` to conform to the `BrainModel` API. A + `BrainModel` is any model that has a `region_layer_map`. This allows the layers in the model to be mapped to layers in + the ventral visual stream, and is chosen by scoring models on the public version of a benchmark (the private + benchmark data is heldout for the BrainModel to be scored on). See the more technical docs + `here `_ for additional notes.