mvp

llama_stack/providers/impls/meta_reference/evals/tasks/__init__.py

@@ -0,0 +1,5 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.

llama_stack/providers/impls/meta_reference/evals/tasks/mmlu_task.py

@@ -0,0 +1,152 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+import re
+
+from .task import BaseTask
+
+QUERY_TEMPLATE_MULTICHOICE = """
+Answer the following multiple choice question and make the answer very simple. The last line of your response should be of the following format: 'Answer: $LETTER' (without quotes) where LETTER is one of ABCD.
+
+{Question}
+
+A) {A}
+B) {B}
+C) {C}
+D) {D}
+""".strip()
+
+MULTILINGUAL_ANSWER_REGEXES = [
+    r"Answer\s*:",
+    r"Answer\s*:​​​​​​",  # Korean invisible character
+    r"উত্তর\s*:",
+    r"उत्तर\s*:",
+    r"উত্তরঃ",
+    r"উত্তর\s*:",
+    r"Antwort\s*:",
+    r"답변\s*:",
+    r"정답\s*:",
+    r"답\s*:",
+    r"答案\s*：",
+    r"答案\s*:",
+    r"答\s*：",
+    r"答\s*:",
+    r"答复\s*：",
+    r"答曰\s*：",
+    r"الإجابة:",
+    r"الجواب:",
+    r"إجابة:",
+    r"الإجابة النهائية:",
+    r"الإجابة الصحيحة:",
+    r"الإجابة الصحيحة هي:",
+    r"الإجابة هي:",
+    r"Respuesta\s*:",
+    r"Risposta\s*:",
+    r"答え\s*:",
+    r"答え\s*：",
+    r"回答\s*:",
+    r"回答\s*：",
+    r"解答\s*:",
+    r"Jawaban\s*:",
+    r"Réponse\s*:",
+    r"Resposta\s*:",
+    r"Jibu\s*:",
+    r"Idahun\s*:",
+    r"Ìdáhùn\s*:",
+    r"Idáhùn\s*:",
+    r"Àmọ̀nà\s*:",
+    r"Àdáhùn\s*:",
+    r"Ànúgọ\s*:",
+    r"Àṣàyàn\s*:",
+]
+
+MULTILINGUAL_ANSWER_PATTERN_TEMPLATE = (
+    r"(?i){}\s*([A-D]|[أ-د]|[অ]|[ব]|[ড]|[ঢ]|[Ａ]|[Ｂ]|[Ｃ]|[Ｄ])"
+)
+
+
+def normalize_response(response: str) -> str:
+    """
+    Normalize the response by removing markdown and LaTeX formatting that may prevent a match.
+    """
+
+    return (
+        response.replace("**", "")
+        .replace("$\\boxed{", "")
+        .replace("}$", "")
+        .replace("\\$", "")
+        .replace("$\\text{", "")
+        .replace("$", "")
+        .replace("\\mathrm{", "")
+        .replace("\\{", "")
+        .replace("\\text", "")
+        .replace("\\(", "")
+        .replace("\\mathbf{", "")
+        .replace("{", "")
+        .replace("\\boxed", "")
+    )
+
+
+def normalize_extracted_answer(extracted_answer: str) -> str:
+    return (
+        # In arabic these are the letters used for A-D in multiple choice questions
+        extracted_answer.replace("أ", " A")
+        .replace("ب", " B")
+        .replace("ج", " C")
+        .replace("د", " D")
+        # In Bengali these are the letters used for A-D in multiple choice questions
+        .replace("অ", " A")
+        .replace("ব", " B")
+        .replace("ড", " C")
+        .replace("ঢ", " D")
+        # In Japanese these are the letters sometimes used for A-D in multiple choice questions
+        .replace("Ａ", " A")
+        .replace("Ｂ", " B")
+        .replace("Ｃ", " C")
+        .replace("Ｄ", " D")
+        .strip()
+    )
+
+
+class MMLUTask(BaseTask):
+    """
+    MMLU Task.
+    """
+
+    def __init__(self, dataset, *args, **kwargs):
+        super().__init__(dataset, *args, **kwargs)
+
+    def preprocess_sample(self, sample):
+        """
+        F1: preprocess sample
+        """
+        content = QUERY_TEMPLATE_MULTICHOICE.format(**sample)
+        return {
+            "role": "user",
+            "content": content,
+        }
+
+    def postprocess_sample(self, sample):
+        """
+        F2: postprocess sample
+        """
+        normalized = normalize_response(sample)
+        return normalized
+
+    def score_sample(self, sample, expected):
+        """
+        F3: score sample
+        """
+        extracted_answer = None
+        for answer_regex in MULTILINGUAL_ANSWER_REGEXES:
+            regex = MULTILINGUAL_ANSWER_PATTERN_TEMPLATE.format(answer_regex)
+            match = re.search(regex, sample)
+            if match:
+                extracted_answer = normalize_extracted_answer(match.group(1))
+                break
+        score = (
+            1.0 if extracted_answer and extracted_answer == expected["Answer"] else 0.0
+        )
+        return score

llama_stack/providers/impls/meta_reference/evals/tasks/task.py

@@ -8,8 +8,7 @@ from abc import ABC, abstractmethod
 
 class BaseTask(ABC):
     """
-    Base class for all evaluation tasks.
-    Each task needs to implement the following methods:
+    Base class for all evaluation tasks. Each task needs to implement the following methods:
     - F1: preprocess_sample(self)
     - F2: postprocess_sample(self)
     - F3: score_sample(self)
@@ -42,40 +41,13 @@ class BaseTask(ABC):
         raise NotImplementedError()
 
     def preprocess(self):
-        pass
+        return [self.preprocess_sample(sample) for sample in self.dataset]
 
-    def postprocess(self):
-        pass
+    def postprocess(self, generation):
+        return [self.postprocess_sample(sample) for sample in generation]
 
-    def score(self, generation):
-        pass
-
-
-class MMLUTask(BaseTask):
-    """
-    MMLU Task. Each task needs to implement the following methods:
-    - F1: preprocess_sample(self)
-    - F2: postprocess_sample(self)
-    - F3: score_sample(self)
-    """
-
-    def __init__(self, dataset, *args, **kwargs):
-        super().__init__(dataset, *args, **kwargs)
-
-    def preprocess_sample(self, sample):
-        """
-        F1: preprocess sample
-        """
-        pass
-
-    def postprocess_sample(self, sample):
-        """
-        F2: postprocess sample
-        """
-        pass
-
-    def score_sample(self, sample):
-        """
-        F3: score sample
-        """
-        pass
+    def score(self, postprocessed):
+        return [
+            self.score_sample(sample, ground_truth)
+            for sample, ground_truth in zip(postprocessed, self.dataset)
+        ]

llama_stack/providers/impls/meta_reference/evals/tasks/task_registry.py

@@ -3,7 +3,7 @@
 #
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
-from .tasks import *  # noqa: F403
+from .mmlu_task import MMLUTask
 
 # TODO: make this into a config based registry
 TASKS_REGISTRY = {