license:cc region:us
---
license: cc
pretty_name: HPCPerfOpt (HPC Performance Optimization Benchmark)  # Example: SQuAD

# configs:
#     - mcq-single
#     - mcq-multiple
#     - rodinia-chatgpt-mcq

# dataset_info:
#   # features:
#   #   - name: {feature_name_0}    # Example: id
#   #     dtype: {feature_dtype_0}  # Example: int32
#   #   - name: {feature_name_1}    # Example: text
#   #     dtype: {feature_dtype_1}  # Example: string
#   #   - name: {feature_name_2}    # Example: image
#   #     dtype: {feature_dtype_2}  # Example: image
#     # Example for SQuAD:
#     # - name: id
#     #   dtype: string
#     # - name: title
#     #   dtype: string
#     # - name: context
#     #   dtype: string
#     # - name: question
#     #   dtype: string
#     # - name: answers
#     #   sequence:
#     #     - name: text
#     #       dtype: string
#     #     - name: answer_start
#     #       dtype: int32
#   config_name: mcq-single  # Example for glue: sst2
#   splits:
#     - name: test                  # Example: train
#   #     num_bytes: {split_num_bytes_0}        # Example for SQuAD: 79317110
#   #     num_examples: {split_num_examples_0}  # Example for SQuAD: 87599
#   # download_size: {dataset_download_size}   # Example for SQuAD: 35142551
#   # dataset_size: {dataset_size}             # Example for SQuAD: 89789763


# # - config_name: mcq-multiple
# #   data_files:
# #   - split: test
# #     path: "mcq-multiple.csv"
    
# # - config_name: rodinia-chatgpt
# #   data_files:
# #   - split: test
# #     path: "rodinia-chatgpt-mcq.csv"

# task_categories:
# - question-answering
# tags:
# - code
# size_categories:
# - n<1K

---
This dataset contains Multiple Choice question-answer pairs.

There are 3 test files separated on the basis of how they were created: 
test1.csv manual data collection from tutorials, etc
test2.csv scraped profiling tool Codee documentation
test3.csv ChatGPT-generated-MCQ (need to update format and randomize answers.)