Merge branch 'main' into comma

lm_eval/tasks/afrobench/masakhapos/utils.py

@@ -4,7 +4,7 @@ from lm_eval.utils import weighted_f1_score
 def doc_to_text(doc):
     output = """Please provide the POS tags for each word in the input sentence. The input will be a list of words in
     the sentence. The output format should be a list of tuples, where each tuple consists of a word from the input text
-    and its corresponding POS tag label from the tag label set: ["ADJ", "ADP", "ADV", "AUX", "CCONJ, "DET", "INTJ",
+    and its corresponding POS tag label from the tag label set: ["ADJ", "ADP", "ADV", "AUX", "CCONJ", "DET", "INTJ",
     "NOUN", "NUM", "PART", "PRON", "PROPN", "PUNCT" "SCONJ", "SYM", "VERB", "X"]. \nYour response should include only a
     list of tuples, in the order that the words appear in the input sentence, with each tuple containing the
     corresponding POS tag label for a word.

lm_eval/tasks/afrobench/nollysenti/prompt_1/nollysenti

@@ -2,7 +2,6 @@ tag:
     - afrobench_sentiment_tasks
     - nollysenti_prompt_1
 dataset_path: Davlan/nollysenti
-dataset_kwargs: {trust_remote_code: True}
 output_type: multiple_choice
 validation_split: validation
 test_split: test

lm_eval/tasks/afrobench/nollysenti/prompt_2/nollysenti

@@ -2,7 +2,6 @@ tag:
     - afrobench_sentiment_tasks
     - nollysenti_prompt_2
 dataset_path: Davlan/nollysenti
-dataset_kwargs: {trust_remote_code: True}
 output_type: multiple_choice
 validation_split: validation
 test_split: test

lm_eval/tasks/afrobench/nollysenti/prompt_3/nollysenti

@@ -2,7 +2,6 @@ tag:
     - afrobench_sentiment_tasks
     - nollysenti_prompt_3
 dataset_path: Davlan/nollysenti
-dataset_kwargs: {trust_remote_code: True}
 output_type: multiple_choice
 validation_split: validation
 test_split: test

lm_eval/tasks/afrobench/nollysenti/prompt_4/nollysenti

@@ -2,7 +2,6 @@ tag:
     - afrobench_sentiment_tasks
     - nollysenti_prompt_4
 dataset_path: Davlan/nollysenti
-dataset_kwargs: {trust_remote_code: True}
 output_type: multiple_choice
 validation_split: validation
 test_split: test

lm_eval/tasks/afrobench/nollysenti/prompt_5/nollysenti

@@ -2,7 +2,6 @@ tag:
     - afrobench_sentiment_tasks
     - nollysenti_prompt_5
 dataset_path: Davlan/nollysenti
-dataset_kwargs: {trust_remote_code: True}
 output_type: multiple_choice
 validation_split: validation
 test_split: test

lm_eval/tasks/afrobench/ntrex/prompt_1/african-english/ntrex

@@ -4,7 +4,6 @@ tag:
 - ntrex_afr-eng_prompt_1
 - afrobench_MT_tasks
 dataset_path: masakhane/ntrex_african
-dataset_kwargs: {trust_remote_code: True}
 output_type: generate_until
 validation_split: test
 fewshot_split: test

lm_eval/tasks/afrobench/ntrex/prompt_1/english-african/ntrex

@@ -4,7 +4,6 @@ tag:
 - ntrex_eng-afr_prompt_1
 - afrobench_MT_tasks
 dataset_path: masakhane/ntrex_african
-dataset_kwargs: {trust_remote_code: True}
 output_type: generate_until
 validation_split: test
 fewshot_split: test

lm_eval/tasks/afrobench/ntrex/prompt_2/african-english/ntrex

@@ -3,7 +3,6 @@ tag:
 - ntrex_afr-eng_prompt_2
 - afrobench_MT_tasks
 dataset_path: masakhane/ntrex_african
-dataset_kwargs: {trust_remote_code: True}
 output_type: generate_until
 validation_split: test
 fewshot_split: test

lm_eval/tasks/afrobench/ntrex/prompt_2/english-african/ntrex

@@ -3,7 +3,6 @@ tag:
 - ntrex_eng-afr_prompt_2
 - afrobench_MT_tasks
 dataset_path: masakhane/ntrex_african
-dataset_kwargs: {trust_remote_code: True}
 output_type: generate_until
 validation_split: test
 fewshot_split: test

lm_eval/tasks/afrobench/ntrex/prompt_3/african-english/ntrex

@@ -3,7 +3,6 @@ tag:
 - ntrex_afr-eng_prompt_3
 - afrobench_MT_tasks
 dataset_path: masakhane/ntrex_african
-dataset_kwargs: {trust_remote_code: True}
 output_type: generate_until
 validation_split: test
 fewshot_split: test

lm_eval/tasks/afrobench/ntrex/prompt_3/english-african/ntrex

@@ -3,7 +3,6 @@ tag:
 - ntrex_eng-afr_prompt_3
 - afrobench_MT_tasks
 dataset_path: masakhane/ntrex_african
-dataset_kwargs: {trust_remote_code: True}
 output_type: generate_until
 validation_split: test
 fewshot_split: test

lm_eval/tasks/afrobench/salt/prompt_1/salt

@@ -3,7 +3,6 @@ tag:
 - salt_prompt_1
 - afrobench_MT_tasks
 dataset_path: Sunbird/salt
-dataset_kwargs: {trust_remote_code: True}
 output_type: generate_until
 validation_split: dev
 fewshot_split: dev

lm_eval/tasks/afrobench/salt/prompt_2/salt

@@ -3,7 +3,6 @@ tag:
 - salt_prompt_2
 - afrobench_MT_tasks
 dataset_path: Sunbird/salt
-dataset_kwargs: {trust_remote_code: True}
 output_type: generate_until
 validation_split: dev
 fewshot_split: dev

lm_eval/tasks/afrobench/salt/prompt_3/salt

@@ -3,7 +3,6 @@ tag:
 - salt_prompt_3
 - afrobench_MT_tasks
 dataset_path: Sunbird/salt
-dataset_kwargs: {trust_remote_code: True}
 output_type: generate_until
 validation_split: dev
 fewshot_split: dev

lm_eval/tasks/aime/README.md

+# AIME
+
+### Citation
+
+```text
+@dataset{aime_1983_2024,
+  author = {Hemish Veeraboina},
+  title = {AIME Problem Set 1983-2024},
+  year = {2024},
+  publisher = {Kaggle},
+  url = {https://www.kaggle.com/datasets/hemishveeraboina/aime-problem-set-1983-2024}
+}
+
+@dataset{aime_2024,
+  author = {Maxwell Jia},
+  title = {AIME Problem Set 2024},
+  year = {2024},
+  publisher = {Huggingface},
+  url = {https://huggingface.co/datasets/Maxwell-Jia/AIME_2024}
+}
+
+@dataset{aime_2025,
+  author = {math-ai},
+  title = {AIME Problem Set 2025},
+  year = {2025},
+  publisher = {Huggingface},
+  url = {https://huggingface.co/datasets/math-ai/aime25}
+}
+```
+
+### Groups, Tags, and Tasks
+
+#### Groups
+
+* `math_word_problems`
+
+#### Tasks
+
+* `aime`: `AIME 1983-2024 problems`
+* `aime24`: `AIME 2024 problems`
+* `aime25`: `AIME 2025 problems`
+
+### Checklist
+
+For adding novel benchmarks/datasets to the library:
+
+* [x] Is the task an existing benchmark in the literature?
+  * [x] Have you referenced the original paper that introduced the task?
+  * [ ] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?
+
+If other tasks on this dataset are already supported:
+
+* [ ] Is the "Main" variant of this task clearly denoted?
+* [ ] Have you provided a short sentence in a README on what each new variant adds / evaluates?
+* [ ] Have you noted which, if any, published evaluation setups are matched by this variant?

lm_eval/tasks/aime/aime.yaml

+tag:
+  - math_word_problems
+task: aime
+dataset_path: gneubig/aime-1983-2024
+# dataset_name: null
+output_type: generate_until
+training_split: train
+fewshot_split: train
+test_split: train
+doc_to_text: "Question: {{Question}}\nAnswer:"
+doc_to_target: "{{Answer}}"
+metric_list:
+  - metric: exact_match
+    aggregation: mean
+    higher_is_better: true
+generation_kwargs:
+  until:
+    - "Question:"
+    - "</s>"
+    - "<|im_end|>"
+    - "<|eot_id|>"
+  do_sample: false
+  temperature: 0.0
+  max_gen_toks: 32768
+repeats: 1
+num_fewshot: 0
+metadata:
+  version: 0.0

lm_eval/tasks/aime/aime24.yaml

+tag:
+  - math_word_problems
+task: aime24
+dataset_path: Maxwell-Jia/AIME_2024
+# dataset_name: null
+output_type: generate_until
+training_split: train
+fewshot_split: train
+test_split: train
+doc_to_text: "Question: {{Problem}}\nAnswer:"
+doc_to_target: "{{Answer}}"
+process_results: !function utils.process_results
+metric_list:
+  - metric: exact_match
+    aggregation: mean
+    higher_is_better: true
+generation_kwargs:
+  until:
+    - "Question:"
+    - "</s>"
+    - "<|im_end|>"
+    - "<|eot_id|>"
+  do_sample: false
+  temperature: 0.0
+  max_gen_toks: 32768
+repeats: 1
+num_fewshot: 0
+metadata:
+  version: 0.0

lm_eval/tasks/aime/aime25.yaml

+tag:
+  - math_word_problems
+task: aime25
+dataset_path: math-ai/aime25
+# dataset_name: null
+output_type: generate_until
+training_split: test
+fewshot_split: test
+test_split: test
+doc_to_text: "Question: {{problem}}\nAnswer:"
+doc_to_target: "{{answer}}"
+process_results: !function utils.process_results
+metric_list:
+  - metric: exact_match
+    aggregation: mean
+    higher_is_better: true
+generation_kwargs:
+  until:
+    - "Question:"
+    - "</s>"
+    - "<|im_end|>"
+    - "<|eot_id|>"
+  do_sample: false
+  temperature: 0.0
+  max_gen_toks: 32768
+repeats: 1
+num_fewshot: 0
+metadata:
+  version: 0.0

lm_eval/tasks/aime/utils.py

+import re
+from typing import Dict, List
+
+
+def process_results(doc: dict, results: List[str]) -> Dict[str, int]:
+    retval = 0
+    response = results[0]
+
+    # Try to extract answer from $...$ format first
+    indices = [pos for pos, char in enumerate(response) if char == "$"]
+    if len(indices) <= 1:
+        answer = response
+    else:
+        answer = response[indices[0] + 1 : indices[-1]]
+
+    # Extract from \\boxed{} if present
+    boxed_answer = last_boxed_only_string(response)
+    if boxed_answer is not None:
+        try:
+            boxed_content = remove_boxed(boxed_answer)
+            if boxed_content is not None:
+                answer = boxed_content
+        except (AssertionError, IndexError):
+            pass
+
+    # Check if answer matches target
+    answer_key = next(k for k in doc.keys() if k.lower() == "answer")
+    target = str(doc[answer_key])
+    if is_equiv(answer, target):
+        retval = 1
+
+    return {"exact_match": retval}
+
+
+# string normalization from https://github.com/EleutherAI/lm-evaluation-harness/blob/master/lm_eval/tasks/hendrycks_math.py
+def is_equiv(str1, str2, verbose=False):
+    if str1 is None and str2 is None:
+        print("WARNING: Both None")
+        return True
+    if str1 is None or str2 is None:
+        return False
+
+    try:
+        ss1 = strip_string(str1)
+        ss2 = strip_string(str2)
+        if verbose:
+            print(ss1, ss2)
+        return ss1 == ss2
+    except Exception:
+        return str1 == str2
+
+
+def remove_boxed(s):
+    if "\\boxed " in s:
+        left = "\\boxed "
+        assert s[: len(left)] == left
+        return s[len(left) :]
+
+    left = "\\boxed{"
+
+    assert s[: len(left)] == left
+    assert s[-1] == "}"
+
+    return s[len(left) : -1]
+
+
+def last_boxed_only_string(string):
+    idx = string.rfind("\\boxed")
+    if "\\boxed " in string:
+        return "\\boxed " + string.split("\\boxed ")[-1].split("$")[0]
+    if idx < 0:
+        idx = string.rfind("\\fbox")
+        if idx < 0:
+            return None
+
+    i = idx
+    right_brace_idx = None
+    num_left_braces_open = 0
+    while i < len(string):
+        if string[i] == "{":
+            num_left_braces_open += 1
+        if string[i] == "}":
+            num_left_braces_open -= 1
+            if num_left_braces_open == 0:
+                right_brace_idx = i
+                break
+        i += 1
+
+    if right_brace_idx is None:
+        retval = None
+    else:
+        retval = string[idx : right_brace_idx + 1]
+
+    return retval
+
+
+def fix_fracs(string):
+    substrs = string.split("\\frac")
+    new_str = substrs[0]
+    if len(substrs) > 1:
+        substrs = substrs[1:]
+        for substr in substrs:
+            new_str += "\\frac"
+            if substr[0] == "{":
+                new_str += substr
+            else:
+                try:
+                    assert len(substr) >= 2
+                except AssertionError:
+                    return string
+                a = substr[0]
+                b = substr[1]
+                if b != "{":
+                    if len(substr) > 2:
+                        post_substr = substr[2:]
+                        new_str += "{" + a + "}{" + b + "}" + post_substr
+                    else:
+                        new_str += "{" + a + "}{" + b + "}"
+                else:
+                    if len(substr) > 2:
+                        post_substr = substr[2:]
+                        new_str += "{" + a + "}" + b + post_substr
+                    else:
+                        new_str += "{" + a + "}" + b
+    string = new_str
+    return string
+
+
+def fix_a_slash_b(string):
+    if len(string.split("/")) != 2:
+        return string
+    a = string.split("/")[0]
+    b = string.split("/")[1]
+    try:
+        a = int(a)
+        b = int(b)
+        assert string == "{}/{}".format(a, b)
+        new_string = "\\frac{" + str(a) + "}{" + str(b) + "}"
+        return new_string
+    except AssertionError:
+        return string
+
+
+def remove_right_units(string):
+    # "\\text{ " only ever occurs (at least in the val set) when describing units
+    if "\\text{ " in string:
+        splits = string.split("\\text{ ")
+        assert len(splits) == 2
+        return splits[0]
+    else:
+        return string
+
+
+def fix_sqrt(string):
+    if "\\sqrt" not in string:
+        return string
+    splits = string.split("\\sqrt")
+    new_string = splits[0]
+    for split in splits[1:]:
+        if split[0] != "{":
+            a = split[0]
+            new_substr = "\\sqrt{" + a + "}" + split[1:]
+        else:
+            new_substr = "\\sqrt" + split
+        new_string += new_substr
+    return new_string
+
+
+def strip_string(string):
+    # linebreaks
+    string = string.replace("\n", "")
+
+    # remove inverse spaces
+    string = string.replace("\\!", "")
+
+    # replace \\ with \
+    string = string.replace("\\\\", "\\")
+
+    # replace tfrac and dfrac with frac
+    string = string.replace("tfrac", "frac")
+    string = string.replace("dfrac", "frac")
+
+    # remove \left and \right
+    string = string.replace("\\left", "")
+    string = string.replace("\\right", "")
+
+    # Remove circ (degrees)
+    string = string.replace("^{\\circ}", "")
+    string = string.replace("^\\circ", "")
+
+    # remove dollar signs
+    string = string.replace("\\$", "")
+
+    # remove units (on the right)
+    string = remove_right_units(string)
+
+    # remove percentage
+    string = string.replace("\\%", "")
+    string = string.replace("\%", "")  # noqa: W605
+
+    # " 0." equivalent to " ." and "{0." equivalent to "{." Alternatively, add "0" if "." is the start of the string
+    string = string.replace(" .", " 0.")
+    string = string.replace("{.", "{0.")
+    # if empty, return empty string
+    if len(string) == 0:
+        return string
+    if string[0] == ".":
+        string = "0" + string
+
+    # to consider: get rid of e.g. "k = " or "q = " at beginning
+    if len(string.split("=")) == 2:
+        if len(string.split("=")[0]) <= 2:
+            string = string.split("=")[1]
+
+    # fix sqrt3 --> sqrt{3}
+    string = fix_sqrt(string)
+
+    # remove spaces
+    string = string.replace(" ", "")
+
+    # \frac1b or \frac12 --> \frac{1}{b} and \frac{1}{2}, etc. Even works with \frac1{72} (but not \frac{72}1). Also does a/b --> \\frac{a}{b}
+    string = fix_fracs(string)
+
+    # manually change 0.5 --> \frac{1}{2}
+    if string == "0.5":
+        string = "\\frac{1}{2}"
+
+    # NOTE: X/Y changed to \frac{X}{Y} in dataset, but in simple cases fix in case the model output is X/Y
+    string = fix_a_slash_b(string)
+
+    return string