"""simple docstring"""
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING

import numpy as np
import pyarrow as pa

from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter


if TYPE_CHECKING:
 import torch




class        __snake_case	(					TensorFormatter[Mapping, """torch.Tensor""", Mapping]    ):



      def __init__(						self   ,      lowercase=None   ,      **lowercase)     ->      Optional[int]:





        '''simple docstring'''





        super().__init__(features=lowercase)
        a__:					List[Any]      							=     torch_tensor_kwargs
        import torch  # noqa import torch at initialization



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      List[str]:





        '''simple docstring'''





        import torch

        if isinstance(lowercase   ,      lowercase) and column:
          if all(
              isinstance(lowercase   ,      torch.Tensor) and x.shape == column[0].shape and x.dtype == column[0].dtype
              for x in column):
            return torch.stack(lowercase)
        return column



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      int:





        '''simple docstring'''





        import torch

        if isinstance(lowercase   ,      (str, bytes, type(lowercase))):
          return value
        elif isinstance(lowercase   ,      (np.character, np.ndarray)) and np.issubdtype(value.dtype   ,      np.character):
          return value.tolist()

        a__:					List[Any]      							=     {}

        if isinstance(lowercase   ,      (np.number, np.ndarray)) and np.issubdtype(value.dtype   ,      np.integer):
          a__:					Any      							=     {'dtype': torch.intaa}
        elif isinstance(lowercase   ,      (np.number, np.ndarray)) and np.issubdtype(value.dtype   ,      np.floating):
          a__:					Optional[Any]      							=     {'dtype': torch.floataa}
        elif config.PIL_AVAILABLE and "PIL" in sys.modules:
          import PIL.Image

          if isinstance(lowercase   ,      PIL.Image.Image):
            a__:					Any      							=     np.asarray(lowercase)
        return torch.tensor(lowercase   ,      **{**default_dtype, **self.torch_tensor_kwargs})



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      Optional[Any]:





        '''simple docstring'''





        import torch

        # support for torch, tf, jax etc.
        if hasattr(lowercase   ,      '__array__') and not isinstance(lowercase   ,      torch.Tensor):
          a__:					Optional[Any]      							=     data_struct.__array__()
        # support for nested types like struct of list of struct
        if isinstance(lowercase   ,      np.ndarray):
          if data_struct.dtype == object:  # torch tensors cannot be instantied from an array of objects
            return self._consolidate([self.recursive_tensorize(lowercase) for substruct in data_struct])
        elif isinstance(lowercase   ,      (list, tuple)):
          return self._consolidate([self.recursive_tensorize(lowercase) for substruct in data_struct])
        return self._tensorize(lowercase)



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      Dict:





        '''simple docstring'''





        return map_nested(self._recursive_tensorize   ,      lowercase   ,      map_list=lowercase)



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      Mapping:





        '''simple docstring'''





        a__:					Dict      							=     self.numpy_arrow_extractor().extract_row(lowercase)
        a__:					Optional[Any]      							=     self.python_features_decoder.decode_row(lowercase)
        return self.recursive_tensorize(lowercase)



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      "torch.Tensor":





        '''simple docstring'''





        a__:					Optional[Any]      							=     self.numpy_arrow_extractor().extract_column(lowercase)
        a__:					List[str]      							=     self.python_features_decoder.decode_column(lowercase   ,      pa_table.column_names[0])
        a__:					Optional[int]      							=     self.recursive_tensorize(lowercase)
        a__:					str      							=     self._consolidate(lowercase)
        return column



      def   lowerCamelCase_       (						self   ,      lowercase)     ->      Mapping:





        '''simple docstring'''





        a__:					Optional[Any]      							=     self.numpy_arrow_extractor().extract_batch(lowercase)
        a__:					Dict      							=     self.python_features_decoder.decode_batch(lowercase)
        a__:					Union[str, Any]      							=     self.recursive_tensorize(lowercase)
        for column_name in batch:
          a__:					Optional[int]      							=     self._consolidate(batch[column_name])
        return batch



"""simple docstring"""
import unittest

from knapsack import knapsack as k




class        __snake_case	(					unittest.TestCase    ):



      def   lowerCamelCase_       (						self)     ->      Dict:





        '''simple docstring'''





        a__:					List[Any]      							=     0
        a__:					Dict      							=     [0]
        a__:					int      							=     [0]
        a__:					Optional[Any]      							=     len(lowercase)
        self.assertEqual(k.knapsack(lowercase   ,      lowercase   ,      lowercase   ,      lowercase)   ,      0)

        a__:					str      							=     [60]
        a__:					Dict      							=     [10]
        a__:					List[str]      							=     len(lowercase)
        self.assertEqual(k.knapsack(lowercase   ,      lowercase   ,      lowercase   ,      lowercase)   ,      0)



      def   lowerCamelCase_       (						self)     ->      List[Any]:





        '''simple docstring'''





        a__:					int      							=     3
        a__:					str      							=     [1, 2, 3]
        a__:					Dict      							=     [3, 2, 1]
        a__:					Optional[int]      							=     len(lowercase)
        self.assertEqual(k.knapsack(lowercase   ,      lowercase   ,      lowercase   ,      lowercase)   ,      5)



      def   lowerCamelCase_       (						self)     ->      Union[str, Any]:





        '''simple docstring'''





        a__:					Any      							=     50
        a__:					Optional[int]      							=     [60, 1_00, 1_20]
        a__:					str      							=     [10, 20, 30]
        a__:					int      							=     len(lowercase)
        self.assertEqual(k.knapsack(lowercase   ,      lowercase   ,      lowercase   ,      lowercase)   ,      2_20)


if __name__ == "__main__":
 unittest.main()


