docs: documentation out of date/sync with inlined example code. (open…

…ai#1417)

Documentation text is out of sync with the codebase and provided inlined
code example.

`check_sampled_text` no longer exist and it looks like it has been
replaced by `record_and_check_match`

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docs/custom-eval.md

@@ -95,7 +95,7 @@ Generally, most `run` methods will follow the same pattern shown here: loading t
 
         evals.record_and_check_match(prompt=prompt, sampled=sampled, expected=test_sample["answer"])
 ```
-You'll notice that `eval_sample` doesn't take the `recorder` as an argument. This is because `eval_all_samples` sets it to be the default recorder before calling `eval_sample`, and the recording utilities defined in `evals/record.py` use the default recorder. In this example, the `eval_sample` method passes off a lot of the heavy lifting to the `evals.check_sampled_text` utility function, which is defined in `evals/api.py`. This utility function queries the model, defined by `self.model_spec`, with the given `prompt` and checks to see if the result matches the `expected` answer (or one of them, if given a list). It then records these matches (or non matches) using the default recorder.
+You'll notice that `eval_sample` doesn't take the `recorder` as an argument. This is because `eval_all_samples` sets it to be the default recorder before calling `eval_sample`, and the recording utilities defined in `evals/record.py` use the default recorder. In this example, the `eval_sample` method passes off a lot of the heavy lifting to the `evals.record_and_check_match` utility function, which is defined in `evals/api.py`. This utility function queries the model, defined by `self.model_spec`, with the given `prompt` and checks to see if the result matches the `expected` answer (or one of them, if given a list). It then records these matches (or non matches) using the default recorder.
 
 `eval_sample` methods may vary greatly based on your use case. If you are building custom evals, it is a good idea to be familiar with the functions available to you in `evals/record.py`, `evals/metrics.py`, and especially `evals/api.py`.