{
  "context": "This evaluation assesses the engineer's ability to use CuPy's array splitting functions (split, array_split, hsplit, vsplit, dsplit) to implement a batch data processing module. The focus is on selecting and applying the appropriate splitting functions for different dimensional scenarios.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "array_split usage",
      "description": "Uses cupy.array_split() or cp.array_split() in split_into_chunks() function to handle unequal chunk sizes when array cannot be evenly divided",
      "max_score": 30
    },
    {
      "name": "hsplit usage",
      "description": "Uses cupy.hsplit() or cp.hsplit() in split_columns() function to split 2D arrays horizontally (column-wise)",
      "max_score": 20
    },
    {
      "name": "vsplit usage",
      "description": "Uses cupy.vsplit() or cp.vsplit() in split_rows() function to split 2D arrays vertically (row-wise)",
      "max_score": 20
    },
    {
      "name": "dsplit usage",
      "description": "Uses cupy.dsplit() or cp.dsplit() in split_depth() function to split 3D arrays along the third dimension (depth-wise)",
      "max_score": 20
    },
    {
      "name": "Correct function parameters",
      "description": "Passes correct parameters to splitting functions: array as first argument and indices_or_sections (num_chunks) as second argument",
      "max_score": 10
    }
  ]
}