fix: import collision for types

browsecomp_eval.py

@@ -10,7 +10,7 @@
 import re
 import pandas
 from . import common
-from .types import Eval, EvalResult, SamplerBase, SingleEvalResult
+from .eval_types import Eval, EvalResult, SamplerBase, SingleEvalResult
 
 # from: https://github.com/centerforaisafety/hle/blob/7b6be5aad6f9b43af3857de7867f3b52f6e4acb3/hle_eval/run_model_predictions.py#L11
 QUERY_TEMPLATE = """

common.py

@@ -9,7 +9,7 @@
 import requests
 from tqdm import tqdm
 
-from .types import EvalResult, Message, SamplerBase, SingleEvalResult
+from .eval_types import EvalResult, Message, SamplerBase, SingleEvalResult
 
 QUERY_TEMPLATE_MULTICHOICE = """
 Answer the following multiple choice question. The last line of your response should be of the following format: 'Answer: $LETTER' (without quotes) where LETTER is one of ABCD. Think step by step before answering.

drop_eval.py

@@ -16,7 +16,7 @@
 
 from . import common
 from .common import ANSWER_PATTERN, HTML_JINJA
-from .types import Eval, EvalResult, SamplerBase, SingleEvalResult
+from .eval_types import Eval, EvalResult, SamplerBase, SingleEvalResult
 
 """
 From here through _normalize_answer was originally copied from:

gpqa_eval.py

@@ -11,7 +11,7 @@
 
 from . import common
 from .common import ANSWER_PATTERN_MULTICHOICE, HTML_JINJA, format_multichoice_question
-from .types import Eval, EvalResult, MessageList, SamplerBase, SingleEvalResult
+from .eval_types import Eval, EvalResult, MessageList, SamplerBase, SingleEvalResult
 
 
 class GPQAEval(Eval):

humaneval_eval.py

@@ -20,7 +20,7 @@
 
 from . import common
 from .common import HTML_JINJA
-from .types import Eval, EvalResult, SamplerBase, SingleEvalResult
+from .eval_types import Eval, EvalResult, SamplerBase, SingleEvalResult
 
 
 def evaluate_functional_correctness(

math_eval.py

@@ -12,7 +12,7 @@
 
 from . import common
 from .common import ANSWER_PATTERN, HTML_JINJA, check_equality
-from .types import Eval, EvalResult, SamplerBase, SingleEvalResult
+from .eval_types import Eval, EvalResult, SamplerBase, SingleEvalResult
 
 QUERY_TEMPLATE = """
 Solve the following math problem step by step. The last line of your response should be of the form Answer: $ANSWER (without quotes) where $ANSWER is the answer to the problem.

mgsm_eval.py

@@ -10,7 +10,7 @@
 
 from . import common
 from .mmlu_eval import HTML_JINJA
-from .types import Eval, EvalResult, SamplerBase, SingleEvalResult
+from .eval_types import Eval, EvalResult, SamplerBase, SingleEvalResult
 
 ALL_LANGUAGES = ["bn", "de", "en", "es", "fr", "ja", "ru", "sw", "te", "th", "zh"]
 LATIN_LANGUAGES = ["de", "en", "es", "fr", "sw"]

mmlu_eval.py

@@ -18,7 +18,7 @@
     normalize_extracted_answer,
     normalize_response,
 )
-from .types import Eval, EvalResult, SamplerBase, SingleEvalResult
+from .eval_types import Eval, EvalResult, SamplerBase, SingleEvalResult
 
 subject2category = {
     "abstract_algebra": "stem",

sampler/chat_completion_sampler.py

@@ -5,7 +5,7 @@
 import openai
 from openai import OpenAI
 
-from ..types import MessageList, SamplerBase
+from ..eval_types import MessageList, SamplerBase
 
 OPENAI_SYSTEM_MESSAGE_API = "You are a helpful assistant."
 OPENAI_SYSTEM_MESSAGE_CHATGPT = (

sampler/claude_sampler.py

@@ -2,7 +2,7 @@
 
 import anthropic
 
-from ..types import MessageList, SamplerBase
+from ..eval_types import MessageList, SamplerBase
 
 CLAUDE_SYSTEM_MESSAGE_LMSYS = (
     "The assistant is Claude, created by Anthropic. The current date is "

sampler/o_chat_completion_sampler.py

@@ -4,7 +4,7 @@
 import openai
 from openai import OpenAI
 
-from ..types import MessageList, SamplerBase
+from ..eval_types import MessageList, SamplerBase
 
 
 class OChatCompletionSampler(SamplerBase):

sampler/responses_sampler.py

@@ -6,7 +6,7 @@
 import openai
 from openai import OpenAI
 
-from ..types import MessageList, SamplerBase
+from ..eval_types import MessageList, SamplerBase
 
 
 class ResponsesSampler(SamplerBase):

simpleqa_eval.py

@@ -8,7 +8,7 @@
 import re
 import pandas
 from . import common
-from .types import Eval, EvalResult, SamplerBase, SingleEvalResult
+from .eval_types import Eval, EvalResult, SamplerBase, SingleEvalResult
 
 GRADER_TEMPLATE = """
 Your job is to look at a question, a gold target, and a predicted answer, and then assign a grade of either ["CORRECT", "INCORRECT", "NOT_ATTEMPTED"].