type-error.json

[
 "result = [sum(arr) for arr in zip(array1, array2)]",
 "result = list(map(lambda x, y: x + y, array1, array2))",
 "result = []\nfor (i, (x, y)) in enumerate(zip(array1, array2)):\n    result.append(x + y)",
 "dot_prod = [a + b for (a, b) in zip(array1, array2)]",
 "import itertools\narray1 = list(array1)\narray2 = list(array2)\nresult = [sum(elements) for elements in zip(array1, array2)]",
 "dot_prod = sum(map(lambda x, y: x + y, array1, array2))",
 "from itertools import starmap\ndot_prod = list(starmap(lambda x, y: x + y, zip(array1, array2)))",
 "from itertools import zip_longest\nresult = [a + b for (a, b) in zip_longest(array1, array2, fillvalue=0)]",
 "result = list(map(sum, zip(array1, array2)))",
 "result = list(map(lambda arr1, arr2: arr1 + arr2, array1, array2))",
 "dot_prod = []\nfor (i, j) in zip(array1, array2):\n    dot_prod.append(i + j)",
 "import itertools\narray1 = list(array1)\narray2 = list(array2)\ndot_prod = list(itertools.starmap(lambda a, b: a + b, zip(array1, array2)))",
 "import functools\narray1 = list(array1)\narray2 = list(array2)\nresult = functools.reduce(lambda x, y: x + y, zip(array1, array2))",
 "import numpy as np\nresult = array1 + array2",
 "from itertools import zip_longest\ndot_prod = sum((a * b for (a, b) in zip_longest(array1, array2, fillvalue=0)))",
 "dot_prod = sum((a + b for (a, b) in zip(array1, array2)))",
 "dot_prod = sum([a * b for (a, b) in zip(array1, array2)])",
 "dot_prod = sum(map(lambda a, b: a * b, array1, array2))",
 "dot_prod = sum([x * y for (x, y) in zip(array1, array2)])\nresult = dot_prod\nsum_of_elements = dot_prod",
 "import itertools\nresult = sum((a * b for (a, b) in itertools.zip_longest(array1, array2, fillvalue=0)))\nsum_of_elements = sum(array1) + sum(array2)",
 "import numpy as np\narray1_pad = np.pad(array1, (0, len(array2) - len(array1)), 'constant', constant_values=0)\narray2_pad = np.pad(array2, (0, len(array1) - len(array2)), 'constant', constant_values=0)\nresult = [a + b for (a, b) in zip(array1_pad, array2_pad)]",
 "result = [array1[i] + array2[i] if i < len(array1) and i < len(array2) else array1[i] if i < len(array1) else array2[i] for i in range(max(len(array1), len(array2)))]",
 "def np_add(arr1, arr2):\n    result = list(map(sum, zip(arr1, arr2)))\n    return result\nresult = np_add(array1, array2)",
 "from operator import add\nresult = [add(x, y) for (x, y) in zip(array1, array2)]",
 "from operator import add\nresult = list(map(add, array1, array2))",
 "import itertools\nresult = list(itertools.starmap(lambda x, y: x + y, zip(array1, array2)))",
 "from itertools import starmap\nimport operator\ndot_prod = list(starmap(operator.add, zip(array1, array2)))",
 "array1 = [float(i) for i in array1]\narray2 = [float(i) for i in array2]\ndot_prod = [a + b for (a, b) in zip(array1, array2)]",
 "array1 = list(map(float, array1))\narray2 = list(map(float, array2))\ndot_prod = [a + b for (a, b) in zip(array1, array2)]",
 "array1 = [float(i) for i in array1]\narray2 = [float(i) for i in array2]\ndot_prod = []\nfor i in range(len(array1)):\n    dot_prod.append(array1[i] + array2[i])",
 "dot_prod = []\ntemp_idx = 0\nfor (elem1, elem2) in zip(array1, array2):\n    dot_prod.append(elem1 + elem2)\nresult = array1\nsum_of_elements = len(array1)",
 "from itertools import zip_longest\ntemp_arr = [a + b for (a, b) in zip_longest(array1, array2, fillvalue=0)]\ndot_prod = temp_arr\nresult = temp_arr\nsum_of_elements = sum(temp_arr)",
 "array1 = list(array1)\narray2 = list(array2)\nresult = [a + b for (a, b) in zip(array1, array2)]",
 "result = [a + b for (a, b) in zip(list(array1), list(array2))]",
 "import numpy as np\narray1 = np.array(array1)\narray2 = np.array(array2)\nresult = np.vectorize(lambda a, b: a + b)(array1, array2)",
 "result = sum((x * y for (x, y) in zip(array1, array2)))",
 "result = sum(map(lambda x, y: x * y, array1, array2))",
 "result = sum((x * y for (x, y) in zip(list(array1), list(array2))))",
 "import itertools\nresult = sum((a * b for (a, b) in itertools.zip_longest(array1, array2, fillvalue=0)))",
 "dot_prod = list(map(lambda a, b: a + b, array1, array2))",
 "from itertools import zip_longest\nsum_of_elements = sum((a + b for (a, b) in zip_longest(array1, array2, fillvalue=0)))\nresult = [a + b for (a, b) in zip_longest(array1, array2, fillvalue=0)]",
 "import numpy as np\nsum_of_elements = np.sum(array1 + array2)\nresult = array1 + array2",
 "sum_of_elements = sum(array1) + sum(array2)\nresult = [a + b for (a, b) in zip(array1, array2)]",
 "import numpy as np\nresult = array1 + array2\nsum_of_elements = np.sum(result)",
 "sum_of_elements = 0\nresult = []\nfor (i, j) in zip(array1, array2):\n    result.append(i + j)\n    sum_of_elements += i + j",
 "import itertools\nimport operator\nresult = [operator.add(x, y) for (x, y) in zip(array1, array2)]",
 "import itertools\narray_sum = list(itertools.chain.from_iterable(zip(array1, array2)))\nsum_of_elements = sum(array_sum)\nresult = array_sum",
 "from itertools import starmap\nsum_of_elements = sum(starmap(lambda x, y: x + y, zip(array1, array2)))\nresult = list(starmap(lambda x, y: x + y, zip(array1, array2)))",
 "from itertools import zip_longest\nresult = [x + y for (x, y) in zip_longest(array1, array2, fillvalue=0)]\nsum_of_elements = sum(result)",
 "result = list(map(lambda x, y: x + y, array1, array2))\nsum_of_elements = sum(result)",
 "sum_of_elements = sum(map(lambda x, y: x + y, array1, array2))\nresult = list(map(lambda x, y: x + y, array1, array2))",
 "sum_of_elements = sum(map(sum, zip(array1, array2)))\nresult = list(map(sum, zip(array1, array2)))",
 "import numpy as np\nsum_of_elements = np.sum(np.concatenate((array1, array2)))\nresult = array1 + array2",
 "import itertools\nsum_of_elements = sum(array1) + sum(array2)\nresult = list(itertools.starmap(lambda x, y: x + y, zip(array1, array2)))",
 "import numpy as np\nsum_of_elements = np.sum(array1) + np.sum(array2)\nresult = [np.add(a, b) for (a, b) in zip(array1, array2)]",
 "import functools\nsum_of_elements = functools.reduce(lambda x, y: x + y, array1) + functools.reduce(lambda x, y: x + y, array2)\nresult = [a + b for (a, b) in zip(array1, array2)]",
 "sum_of_elements = sum(array1) + sum(array2)\nresult = [sum(x) for x in zip(array1, array2)]",
 "import itertools\nsum_of_elements = sum(array1) + sum(array2)\nresult = list(itertools.starmap(lambda a, b: a + b, zip(array1, array2)))",
 "result = [a + b for (a, b) in zip(array1, array2)]\nsum_of_elements = sum(result)",
 "from itertools import starmap\nresult = list(starmap(lambda x, y: x + y, zip(array1, array2)))\nsum_of_elements = sum(result)",
 "result = map(lambda x, y: x + y, array1, array2)\nsum_of_elements = sum(result)",
 "result = []\nsum_of_elements = 0\nfor (a, b) in zip(array1, array2):\n    result.append(a + b)\n    sum_of_elements += a + b",
 "import itertools\nresult = [i + j for (i, j) in itertools.zip_longest(array1, array2, fillvalue=0)]\nsum_of_elements = sum(result)",
 "sum_of_elements = 0\nresult = []\nfor (i, j) in zip(array1, array2):\n    result.append(i + j)\n    sum_of_elements = sum_of_elements + i + j",
 "sum_of_elements = sum((i + j for (i, j) in zip(array1, array2)))\nresult = [i + j for (i, j) in zip(array1, array2)]",
 "sum_of_elements = sum(array1 + array2)\nresult = list(array1 + array2)",
 "import numpy as np\narray1 = np.array(array1)\narray2 = np.array(array2)\ndot_prod = np.tensordot(array1, array2, axes=0)",
 "dot_prod = sum((x * y for (x, y) in zip(array1, array2) if x is not None and y is not None))",
 "dot_prod = sum(filter(None, (x * y for (x, y) in zip(array1, array2))))",
 "dot_prod = sum(filter(lambda x: x is not None, (x * y for (x, y) in zip(array1, array2))))",
 "import itertools\npairs = list(itertools.product(array1, array2))\ndot_prod = sum([pair[0] * pair[1] for pair in pairs])",
 "dot_prod = [a * b for (a, b) in zip(array1, array2)]",
 "dot_prod = []\nfor i in range(len(array1)):\n    dot_prod.append(array1[i] * array2[i])",
 "dot_prod = 0\nfor (x, y) in zip(array1, array2):\n    dot_prod += x * y",
 "import itertools\npairs = list(itertools.product(array1, array2))\ndot_prod = sum((x * y for (x, y) in pairs))",
 "import functools\nimport operator\ndot_prod = functools.reduce(operator.add, (x * y for (x, y) in zip(array1, array2)))",
 "dot_prod = 0\nfor (x, y) in zip(array1, array2):\n    if x is not None and y is not None:\n        dot_prod += x * y",
 "import itertools\narray1_filtered = [x for x in array1 if x is not None]\narray2_filtered = [y for y in array2 if y is not None]\ndot_prod = sum((x * y for (x, y) in zip(array1_filtered, array2_filtered)))",
 "dot_prod = 0\nfor (x, y) in zip(array1, array2):\n    if x and y:\n        dot_prod += x * y",
 "import itertools\narray1 = list(array1)\narray2 = list(array2)\ndot_prod = sum((x * y for (x, y) in itertools.zip_longest(array1, array2) if x and y))",
 "dot_prod = sum([x * y for (x, y) in zip(array1, array2) if x is not None])",
 "dot_prod = 0\nfor (x, y) in zip(array1, array2):\n    if x is not None:\n        dot_prod += x * y",
 "import numpy as np\narray1 = np.array(array1)\narray2 = np.array(array2)\ndot_prod = np.sum(np.outer(array1, array2))",
 "dot_prod = list(map(lambda a, b: a * b, array1, array2))",
 "dot_prod = [array1[i] * array2[i] for i in range(len(array1))]",
 "dot_prod = list(map(lambda x, y: x * y, array1, array2))",
 "import itertools\npairs = list(itertools.product(array1, array2))\ndot_prod = sum([x * y for (x, y) in pairs])",
 "dot_prod = 0\nfor x in array1:\n    for y in array2:\n        dot_prod += x * y",
 "dot_prod = sum([x * y for (x, y) in zip(array1, array2) if x is not None and y is not None])",
 "import itertools\narray1_filtered = list(filter(lambda x: x is not None, array1))\narray2_filtered = list(filter(lambda y: y is not None, array2))\ndot_prod = sum((x * y for (x, y) in zip(array1_filtered, array2_filtered)))",
 "import itertools\narray1_filtered = list(filter(None, array1))\narray2_filtered = list(filter(None, array2))\ndot_prod = sum((x * y for (x, y) in zip(array1_filtered, array2_filtered)))",
 "import itertools\narray1_filtered = [x for x in array1 if x]\narray2_filtered = [y for y in array2 if y]\ndot_prod = sum((x * y for (x, y) in zip(array1_filtered, array2_filtered)))",
 "import itertools\narray1_filtered = list(filter(bool, array1))\narray2_filtered = list(filter(bool, array2))\ndot_prod = sum((x * y for (x, y) in zip(array1_filtered, array2_filtered)))",
 "dot_prod = sum([x * y for (x, y) in zip(array1, array2) if x and y])",
 "dot_prod = 0\nfor i in range(len(array1)):\n    if array1[i] and array2[i]:\n        dot_prod += array1[i] * array2[i]",
 "import itertools\narray1_filtered = [x for x in array1 if x is not None]\narray2_filtered = [y for y in array2 if y is not None]\ndot_prod = sum([x * y for (x, y) in itertools.zip_longest(array1_filtered, array2_filtered, fillvalue=0)])",
 "import numpy as np\nimport itertools\narray1 = [1, 2, 3]\narray2 = [4, 5, 6]\npairs = np.array(list(itertools.product(array1, array2)))\ndot_prod = np.sum(pairs[:, 0] * pairs[:, 1])",
 "import numpy as np\nimport itertools\narray1 = [1, 2, 3]\narray2 = [4, 5, 6]\npairs = np.array(list(itertools.product(array1, array2)))\ndot_prod = np.dot(pairs[:, 0], pairs[:, 1])",
 "import numpy as np\nimport itertools\narray1 = [1, 2, 3]\narray2 = [4, 5, 6]\npairs = np.array(list(itertools.product(array1, array2)))\ndot_prod = np.multiply(pairs[:, 0], pairs[:, 1]).sum()",
 "import numpy as np\nimport itertools\narray1 = [1, 2, 3]\narray2 = [4, 5, 6]\npairs = np.array(list(itertools.product(array1, array2)))\ndot_prod = np.einsum('i,i->', pairs[:, 0], pairs[:, 1])",
 "import numpy as np\nimport itertools\narray1 = [1, 2, 3]\narray2 = [4, 5, 6]\npairs = np.array(list(itertools.product(array1, array2)))\ndot_prod = np.inner(pairs[:, 0], pairs[:, 1])",
 "import numpy as np\narray1 = np.array(array1)\narray2 = np.array(array2)\ndot_prod = np.tensordot(array1, array2, axes=0).sum()",
 "import numpy as np\narray1 = np.array(array1)\narray2 = np.array(array2)\ndot_prod = np.outer(array1, array2).sum()",
 "import numpy as np\narray1 = np.array(array1)\narray2 = np.array(array2)\ndot_prod = np.kron(array1, array2).sum()",
 "dot_prod = [x + y for (x, y) in zip(array1, array2)]\nresult = dot_prod",
 "dot_prod = list(map(lambda x, y: x + y, array1, array2))\nresult = dot_prod",
 "result = []\nfor (i, (val1, val2)) in enumerate(zip(array1, array2)):\n    sum_of_elements = val1 + val2\n    result.append(sum_of_elements)",
 "import itertools\nresult = [x + y for (x, y) in itertools.zip_longest(array1, array2, fillvalue=0)]",
 "import itertools\nresult = [sum(elements) for elements in itertools.zip_longest(array1, array2, fillvalue=0)]",
 "import itertools\npairs = itertools.zip_longest(array1, array2, fillvalue=0)\ndot_prod = [x + y for (x, y) in pairs]\nresult = dot_prod",
 "result = map(lambda x, y: x + y, array1, array2)",
 "result = []\nfor i in range(min(len(array1), len(array2))):\n    result.append(array1[i] + array2[i])",
 "import itertools\ndef add(x, y):\n    return x + y\nresult = list(itertools.starmap(add, zip(array1, array2)))",
 "import operator\nresult = list(map(operator.add, array1, array2))",
 "result = []\nfor index in range(max(len(array1), len(array2))):\n    a = array1[index] if index < len(array1) else 0\n    b = array2[index] if index < len(array2) else 0\n    result.append(a + b)",
 "result = []\nfor i in range(max(len(array1), len(array2))):\n    total = 0\n    if i < len(array1):\n        total += array1[i]\n    if i < len(array2):\n        total += array2[i]\n    result.append(total)",
 "dot_prod = sum(array1) + sum(array2)\nresult = dot_prod",
 "import numpy as np\narray1 = np.array(array1)\narray2 = np.array(array2)\ndot_prod = np.zeros(len(array1))\nfor i in range(len(array1)):\n    dot_prod[i] = array1[i] + array2[i]\nresult = dot_prod",
 "import functools\nresult = list(functools.reduce(lambda x, y: x + y, zip(array1, array2)))",
 "import numpy as np\npairs = np.array(list(zip(array1, array2)) + [(0, 0)] * abs(len(array1) - len(array2)))\ndot_prod = [x + y for (x, y) in pairs]\nresult = dot_prod",
 "import numpy as np\npairs = np.array(list(zip(array1, array2)) + [(0, 0)] * abs(len(array1) - len(array2)))\ndot_prod = np.sum(pairs, axis=1)\nresult = dot_prod",
 "result = list(map(lambda val1, val2: val1 + val2, array1, array2))",
 "result = [array1[i] + array2[i] for i in range(min(len(array1), len(array2)))]",
 "result = list(map(lambda x, y: x + y, array1[:min(len(array1), len(array2))], array2[:min(len(array1), len(array2))]))",
 "import itertools\ndef add(x, y):\n    return x + y\narray1 = [1, 2, 3, 4, 5]\narray2 = [6, 7, 8, 9, 10]\nresult = []\nfor i in range(len(array1)):\n    result.append(add(array1[i], array2[i]))",
 "result = [array1[i] + array2[i] if i < len(array1) and i < len(array2) else array1[i] if i < len(array1) else array2[i] if i < len(array2) else 0 for i in range(max(len(array1), len(array2)))]",
 "result = []\nfor i in range(max(len(array1), len(array2))):\n    if i < len(array1) and i < len(array2):\n        result.append(array1[i] + array2[i])\n    elif i < len(array1):\n        result.append(array1[i])\n    else:\n        result.append(array2[i])",
 "import numpy as np\nresult = np.add(array1[:len(array2)], array2[:len(array1)]) if len(array1) < len(array2) else np.add(array1[:len(array2)], array2[:len(array1)]) if len(array1) > len(array2) else np.add(array1, array2)",
 "result = []\nmin_len = min(len(array1), len(array2))\nfor i in range(min_len):\n    result.append(array1[i] + array2[i])\nif len(array1) > len(array2):\n    result.extend(array1[min_len:])\nelse:\n    result.extend(array2[min_len:])",
 "result = list(map(lambda x, y: x + y if x and y else x or y or 0, array1, array2))",
 "import itertools\narray1 = list(itertools.chain(array1, [0] * (len(array2) - len(array1))))\narray2 = list(itertools.chain(array2, [0] * (len(array1) - len(array2))))\nresult = [x + y for (x, y) in zip(array1, array2)]",
 "import numpy as np\narray1 = np.pad(array1, (0, max(len(array2) - len(array1), 0)), mode='constant')\narray2 = np.pad(array2, (0, max(len(array1) - len(array2), 0)), mode='constant')\nresult = array1 + array2",
 "import numpy as np\narray1 = np.resize(array1, max(len(array1), len(array2)))\narray2 = np.resize(array2, max(len(array1), len(array2)))\nresult = array1 + array2",
 "from typing import List\ndef calculate_sum(arr1: List[int], arr2: List[int]) -> List[int]:\n    result = []\n    for i in range(len(arr1)):\n        result.append(arr1[i] + arr2[i])\n    return result\narray1 = [1, 2, 3]\narray2 = [4, 5, 6]\nresult = calculate_sum(array1, array2)",
 "import numpy as np\narray1 = [1, 2, 3]\narray2 = [4, 5, 6]\nresult = np.add(array1, array2)",
 "array1 = [1, 2, 3]\narray2 = [4, 5, 6]\nresult = [a + b for (a, b) in zip(array1, array2)]",
 "array1 = [1, 2, 3]\narray2 = [4, 5, 6]\nresult = []\nfor i in range(len(array1)):\n    result.append(array1[i] + array2[i])",
 "result = sum([x + y for (x, y) in zip(array1, array2)])",
 "import numpy as np\nresult = np.sum(array1) + np.sum(array2)",
 "import numpy as np\nresult = np.sum(np.concatenate((array1, array2)))",
 "result = sum(array1) + sum(array2)",
 "result = array1 + array2\ndot_prod = result",
 "result = array1 + array2\ndot_prod = result.copy()",
 "import itertools\nresult = list(itertools.starmap(lambda x, y: x + y, zip(array1, array2)))\ndot_prod = result",
 "result = [x + y for (x, y) in zip(array1, array2)]\ndot_prod = result.copy()",
 "result = list(map(lambda x, y: x + y, array1, array2))\ndot_prod = result.copy()",
 "import numpy as np\nresult = np.array([x + y for (x, y) in zip(array1, array2)])\ndot_prod = result.copy()",
 "import itertools\npairs = zip(array1, array2)\ndot_prod = sum([x * y for (x, y) in pairs])",
 "result = [x + y for (x, y) in zip(array1, array2)]\nresult = list(map(int, result))",
 "result = [x + y for (x, y) in zip(array1, array2)]\nresult = [int(x) for x in result]",
 "result = [x + y for (x, y) in zip(array1, array2)]\nresult = [str(x) for x in result]",
 "import itertools\npairs = list(itertools.zip_longest(array1, array2, fillvalue=0))\ndot_prod = [x + y for (x, y) in pairs]",
 "import numpy as np\narray1 = np.array(array1)\narray2 = np.array(array2)\ndot_prod = np.zeros_like(array1)\nfor i in range(len(array1)):\n    dot_prod[i] = array1[i] + array2[i]",
 "import itertools\narray1 = [1, 2, 3]\narray2 = [4, 5, 6]\ndot_prod = [x + y for (x, y) in itertools.zip_longest(array1, array2, fillvalue=0)]",
 "array1 = [1, 2, 3]\narray2 = [4, 5, 6]\ndot_prod = []\nfor i in range(max(len(array1), len(array2))):\n    x = array1[i] if i < len(array1) else 0\n    y = array2[i] if i < len(array2) else 0\n    dot_prod.append(x + y)",
 "import itertools\narray1 = list(array1)\narray2 = list(array2)\ndot_prod = list(itertools.starmap(lambda x, y: x + y, zip(array1, array2)))",
 "import numpy as np\npairs = np.column_stack((array1, array2))\ndot_prod = np.sum(pairs, axis=0, dtype=np.float64)",
 "import numpy as np\npairs = np.column_stack((array1, array2))\ndot_prod = np.sum(pairs, axis=0, dtype=np.int32)"
]