sangge
d58adda9ab
- Add plain KNN implementation with JSONL data processing - Create Docker deployment setup with python:3.13-slim base - Add comprehensive OJ-style testing system with accuracy validation - Update README with detailed scoring mechanism explanation - Add run.sh script following competition manual requirements 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
22 lines
698 B
Bash
22 lines
698 B
Bash
#!/bin/bash
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SCRIPT_DIR=$(dirname "$0")
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PARENT_DIR="$(dirname "$SCRIPT_DIR")"
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# 根据运行环境选择文件路径
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if [ "$ALIPAY_APP_ENV" = "prod" ]; then
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PREDICTIONS_RESULT_FILE="/home/admin/workspace/job/output/predictions/predictions.jsonl"
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DATASET_FILE="/home/admin/workspace/job/input/test.jsonl"
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else
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PREDICTIONS_RESULT_FILE="${PARENT_DIR}/data/predictions.jsonl"
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DATASET_FILE="${PARENT_DIR}/data/data.jsonl"
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fi
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echo $PREDICTIONS_RESULT_FILE
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#以上内容**不可**修改!
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#选手仅可修改下面的test为自己的实际比赛代码入口
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chmod +x "${SCRIPT_DIR}/test"
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"${SCRIPT_DIR}/test" \
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--dataset "$DATASET_FILE" \
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--predictions "$PREDICTIONS_RESULT_FILE" |