add developer doc notes (#1201)

* add developer doc notes

* update version number

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 ---------------------------------------------------

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 <https://github.com/brain-score/result_caching>`_ 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 <https://brain-score.readthedocs.io/en/latest/modules/model_interface.html>`_  for additional notes.