{"task": {"agent_timeout": 1800, "task": "495", "verifier_timeout": 1800, "instruction": "# 495: DS-1000 Task\n\n## Prompt\nProblem:\nI have a file with arrays or different shapes. I want to zeropad all the array to match the largest shape. The largest shape is (93,13).\nTo test this I have the following code:\na = np.ones((41,13))\nhow can I zero pad this array to match the shape of (93,13)? And ultimately, how can I do it for thousands of rows? Specifically, I want to pad to the right and bottom of original array in 2D.\nA:\n<code>\nimport numpy as np\na = np.ones((41, 13))\nshape = (93, 13)\n</code>\nresult = ... # 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": []}