{"task": {"agent_timeout": 1800, "task": "443", "verifier_timeout": 1800, "instruction": "# 443: DS-1000 Task\n\n## Prompt\nProblem:\nI have two arrays A (len of 3.8million) and B (len of 20k). For the minimal example, lets take this case:\nA = np.array([1,1,2,3,3,3,4,5,6,7,8,8])\nB = np.array([1,2,8])\nNow I want the resulting array to be:\nC = np.array([1,1,2,8,8])\ni.e. if any value in A is not found in B, remove it from A, otherwise keep it.\nI would like to know if there is any way to do it without a for loop because it is a lengthy array and so it takes long time to loop.\nA:\n<code>\nimport numpy as np\nA = np.array([1,1,2,3,3,3,4,5,6,7,8,8])\nB = np.array([1,2,8])\n</code>\nC = ... # 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": []}