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82 lines
2.5 KiB
Python
82 lines
2.5 KiB
Python
from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import ZeroRetriever
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from opencompass.openicl.icl_inferencer import GenInferencer
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from opencompass.datasets import SanitizedMBPPDataset, MBPPEvaluator
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sanitized_mbpp_reader_cfg = dict(input_columns=["text", "test_list"], output_column="test_list_2")
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sanitized_mbpp_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template='''\
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You are an expert Python programmer, and here is your task: Write a function to find the similar elements from the given two tuple lists. Your code should pass these tests:
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assert similar_elements((3, 4, 5, 6),(5, 7, 4, 10)) == (4, 5)
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assert similar_elements((1, 2, 3, 4),(5, 4, 3, 7)) == (3, 4)
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assert similar_elements((11, 12, 14, 13),(17, 15, 14, 13)) == (13, 14)
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[BEGIN]
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'def similar_elements(test_tup1, test_tup2):
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res = tuple(set(test_tup1) & set(test_tup2))
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return (res)'
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[DONE]
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You are an expert Python programmer, and here is your task: Write a python function to identify non-prime numbers. Your code should pass these tests:
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assert is_not_prime(2) == False
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assert is_not_prime(10) == True
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assert is_not_prime(35) == True
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[BEGIN]
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'import math
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def is_not_prime(n):
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result = False
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for i in range(2,int(math.sqrt(n)) + 1):
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if n % i == 0:
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result = True
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return result'
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[DONE]
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You are an expert Python programmer, and here is your task: Write a function to find the largest integers from a given list of numbers using heap queue algorithm. Your code should pass these tests:
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assert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],3)==[85, 75, 65]
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assert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],2)==[85, 75]
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assert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[85, 75, 65, 58, 35]
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[BEGIN]
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'import heapq as hq
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def heap_queue_largest(nums,n):
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largest_nums = hq.nlargest(n, nums)
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return largest_nums'
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[DONE]
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You are an expert Python programmer, and here is your task: {text} Your code should pass these tests:
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{test_list}
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[BEGIN]
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'''
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),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer, max_out_len=512),
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)
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sanitized_mbpp_eval_cfg = dict(evaluator=dict(type=MBPPEvaluator), pred_role="BOT")
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sanitized_mbpp_datasets = [
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dict(
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type=SanitizedMBPPDataset,
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abbr="sanitized_mbpp",
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path="./data/mbpp/sanitized-mbpp.jsonl",
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reader_cfg=sanitized_mbpp_reader_cfg,
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infer_cfg=sanitized_mbpp_infer_cfg,
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eval_cfg=sanitized_mbpp_eval_cfg,
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)
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]
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