{"task": {"agent_timeout": 1800, "task": "299", "verifier_timeout": 1800, "instruction": "# 299: DS-1000 Task\n\n## Prompt\nProblem:\nLet's say I have a 2d numpy integer array like this\na = array([[1,0,3], [2,4,1]])\nI would like to encode this as a 2D one-hot array(in C order, e.g., a[1,1] corresponds to b[4]) for integers.\nb = array([[0,1,0,0,0], [1,0,0,0,0], [0,0,0,1,0], [0,0,1,0,0], [0,0,0,0,1], [0,1,0,0,0]])\nThe leftmost element always corresponds to the smallest element in `a`, and the rightmost vice versa.\nIs there a quick way to do this only using numpy? Quicker than just looping over a to set elements of b, that is.\nA:\n<code>\nimport numpy as np\na = np.array([[1,0,3], [2,4,1]])\n</code>\nb = ... # put solution in this variable\nBEGIN SOLUTION\n<code>\n\n## What to do\n- Edit `solution/solution.py` so the code passes the DS-1000 tests.\n- Do not access the internet or install new packages; required libraries are preinstalled in the Docker image.\n- Run tests locally via `bash tests/test.sh`.\n\n## Notes\n- Keep the variable names/signatures implied by the prompt/code_context.\n- The evaluator uses the original DS-1000 `code_context` (`test_execution` / `test_string`).\n", "memory": "", "runnable": false, "difficulty": "", "language": "", "cpus": "", "instruction_truncated": false, "category": "", "compose": false, "has_solution": true, "oracle": null, "docker_image": "ds1000:latest", "taskset": "ds1000", "tags": []}, "runs": []}