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Browse files- __pycache__/gradify.cpython-310.pyc +0 -0
- demo.yaml +21 -29
- gradify.py +4 -8
- requirements.txt +1 -1
__pycache__/gradify.cpython-310.pyc
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demo.yaml
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lite_metadata:
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gradio_version: 3.32.0
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class_string: gradio.interface.Interface
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kwargs:
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title:
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description: Given two sorted arrays nums1 and nums2 of size m and n respectively,
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return the median of the two sorted arrays
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article: null
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css: null
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allow_flagging: never
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inputs:
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label: nums2
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type: array
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outputs:
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kwargs:
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label: output
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fn:
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class_string: gradify.gradify_closure
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kwargs:
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argmaps:
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- label: nums2
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postprocessing: 'lambda array: list(map(int, array[0]))'
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func_kwargs: {}
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\ nums1.sort()\n n = len(nums1)\n if n % 2 == 0:\n return\
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\ (nums1[n // 2] + nums1[n // 2 - 1]) / 2\n else:\n return nums1[n\
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\ // 2]\n"
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lite_metadata:
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gradio_version: 3.32.0
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liteobj_version: 0.0.7
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class_string: gradio.interface.Interface
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kwargs:
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title: gitio array median
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description: Given two sorted arrays nums1 and nums2 of size m and n respectively,
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return the median of the two sorted arrays
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article: null
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css: null
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allow_flagging: never
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inputs:
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- class_string: gradio.components.Dataframe
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kwargs:
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label: nums1
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type: array
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- class_string: gradio.components.Dataframe
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kwargs:
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label: nums2
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type: array
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outputs:
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- class_string: gradio.components.Number
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kwargs:
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label: output
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fn:
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class_string: gradify.gradify_closure
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kwargs:
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argmaps:
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- label: nums1
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postprocessing: 'lambda array: list(map(int, array[0]))'
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- label: nums2
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postprocessing: 'lambda array: list(map(int, array[0]))'
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func_kwargs: {}
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source: "def findMedianSortedArrays(nums1, nums2):\n nums1.extend(nums2)\n\
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\ nums1.sort()\n n = len(nums1)\n if n % 2 == 0:\n return\
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\ (nums1[n // 2] + nums1[n // 2 - 1]) / 2\n else:\n return nums1[n\
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\ // 2]\n"
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gradify.py
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def gradify_closure(
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from types import FunctionType
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for k, v in ldict.items():
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if isinstance(v, FunctionType):
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raise gr.Error(f"Error: {e}")
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return gradify_func
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def exec_to_dict(source, target=None):
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ldict = {}
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exec(source, globals(), ldict)
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return ldict.get(target, None) if target else ldict
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def gradify_closure(source, argmaps, func_kwargs={}):
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ldict = {}
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exec(source, globals(), ldict)
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from types import FunctionType
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for k, v in ldict.items():
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if isinstance(v, FunctionType):
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raise gr.Error(f"Error: {e}")
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return gradify_func
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requirements.txt
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gradio==3.32
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liteobj==0.0.
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gradio==3.32
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liteobj==0.0.7
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