



"""simple docstring"""







import os
import unittest
from tempfile import TemporaryDirectory

import torch
import torch.nn as nn

from accelerate.utils import (
    OffloadedWeightsLoader,
    extract_submodules_state_dict,
    load_offloaded_weight,
    offload_state_dict,
    offload_weight,
)







class 				UpperCamelCase__       (     nn.Module  ):




      """simple docstring"""




      def __init__(				self    :				Optional[Any]	):
        super().__init__()
        lowerCAmelCase_       :    str								=			nn.Linear(3   ,      4	)
        lowerCAmelCase_       :    Tuple								=			nn.BatchNormad(4	)
        lowerCAmelCase_       :    Dict								=			nn.Linear(4   ,      5	)





      def 					SCREAMING_SNAKE_CASE__			(				self    :				Optional[Any]   ,      SCREAMING_SNAKE_CASE_    :				int	):
        return self.lineara(self.batchnorm(self.lineara(SCREAMING_SNAKE_CASE_	)	)	)







class 				UpperCamelCase__       (     unittest.TestCase  ):




      """simple docstring"""




      def 					SCREAMING_SNAKE_CASE__			(				self    :				Optional[Any]	):
        lowerCAmelCase_       :    Dict								=			ModelForTest()
        with TemporaryDirectory() as tmp_dir:
          offload_state_dict(SCREAMING_SNAKE_CASE_   ,      model.state_dict()	)
          lowerCAmelCase_       :    Optional[Any]								=			os.path.join(SCREAMING_SNAKE_CASE_   ,      'index.json'	)
          self.assertTrue(os.path.isfile(SCREAMING_SNAKE_CASE_	)	)
          # TODO: add tests on what is inside the index

          for key in ["linear1.weight", "linear1.bias", "linear2.weight", "linear2.bias"]:
            lowerCAmelCase_       :    Optional[Any]								=			os.path.join(SCREAMING_SNAKE_CASE_   ,      F"{key}.dat"	)
            self.assertTrue(os.path.isfile(SCREAMING_SNAKE_CASE_	)	)
            # TODO: add tests on the fact weights are properly loaded



      def 					SCREAMING_SNAKE_CASE__			(				self    :				List[str]	):
        lowerCAmelCase_       :    Tuple								=			[torch.floataa, torch.floataa, torch.bfloataa]

        for dtype in dtypes:
          lowerCAmelCase_       :    Tuple								=			torch.randn(2   ,      3   ,      dtype=SCREAMING_SNAKE_CASE_	)
          with TemporaryDirectory() as tmp_dir:
            lowerCAmelCase_       :    Union[str, Any]								=			offload_weight(SCREAMING_SNAKE_CASE_   ,      'weight'   ,      SCREAMING_SNAKE_CASE_   ,      {}	)
            lowerCAmelCase_       :    Optional[Any]								=			os.path.join(SCREAMING_SNAKE_CASE_   ,      'weight.dat'	)
            self.assertTrue(os.path.isfile(SCREAMING_SNAKE_CASE_	)	)
            self.assertDictEqual(SCREAMING_SNAKE_CASE_   ,      {'weight': {'shape': [2, 3], 'dtype': str(SCREAMING_SNAKE_CASE_	).split('.'	)[1]}}	)

            lowerCAmelCase_       :    Tuple								=			load_offloaded_weight(SCREAMING_SNAKE_CASE_   ,      index['weight']	)
            self.assertTrue(torch.equal(SCREAMING_SNAKE_CASE_   ,      SCREAMING_SNAKE_CASE_	)	)



      def 					SCREAMING_SNAKE_CASE__			(				self    :				Optional[Any]	):
        lowerCAmelCase_       :    Optional[int]								=			ModelForTest()
        lowerCAmelCase_       :    Any								=			model.state_dict()
        lowerCAmelCase_       :    str								=			{k: v for k, v in state_dict.items() if 'linear2' not in k}
        lowerCAmelCase_       :    int								=			{k: v for k, v in state_dict.items() if 'linear2' in k}

        with TemporaryDirectory() as tmp_dir:
          offload_state_dict(SCREAMING_SNAKE_CASE_   ,      SCREAMING_SNAKE_CASE_	)
          lowerCAmelCase_       :    Optional[Any]								=			OffloadedWeightsLoader(state_dict=SCREAMING_SNAKE_CASE_   ,      save_folder=SCREAMING_SNAKE_CASE_	)

          # Every key is there with the right value
          self.assertEqual(sorted(SCREAMING_SNAKE_CASE_	)   ,      sorted(state_dict.keys()	)	)
          for key, param in state_dict.items():
            self.assertTrue(torch.allclose(SCREAMING_SNAKE_CASE_   ,      weight_map[key]	)	)

        lowerCAmelCase_       :    List[str]								=			{k: v for k, v in state_dict.items() if 'weight' in k}
        lowerCAmelCase_       :    List[str]								=			{k: v for k, v in state_dict.items() if 'weight' not in k}

        with TemporaryDirectory() as tmp_dir:
          offload_state_dict(SCREAMING_SNAKE_CASE_   ,      SCREAMING_SNAKE_CASE_	)
          lowerCAmelCase_       :    Union[str, Any]								=			OffloadedWeightsLoader(state_dict=SCREAMING_SNAKE_CASE_   ,      save_folder=SCREAMING_SNAKE_CASE_	)

          # Every key is there with the right value
          self.assertEqual(sorted(SCREAMING_SNAKE_CASE_	)   ,      sorted(state_dict.keys()	)	)
          for key, param in state_dict.items():
            self.assertTrue(torch.allclose(SCREAMING_SNAKE_CASE_   ,      weight_map[key]	)	)

        with TemporaryDirectory() as tmp_dir:
          offload_state_dict(SCREAMING_SNAKE_CASE_   ,      SCREAMING_SNAKE_CASE_	)
          # Duplicates are removed
          lowerCAmelCase_       :    List[Any]								=			OffloadedWeightsLoader(state_dict=SCREAMING_SNAKE_CASE_   ,      save_folder=SCREAMING_SNAKE_CASE_	)

          # Every key is there with the right value
          self.assertEqual(sorted(SCREAMING_SNAKE_CASE_	)   ,      sorted(state_dict.keys()	)	)
          for key, param in state_dict.items():
            self.assertTrue(torch.allclose(SCREAMING_SNAKE_CASE_   ,      weight_map[key]	)	)





      def 					SCREAMING_SNAKE_CASE__			(				self    :				Optional[Any]	):
        lowerCAmelCase_       :    List[Any]								=			{'a.1': 0, 'a.10': 1, 'a.2': 2}
        lowerCAmelCase_       :    Union[str, Any]								=			extract_submodules_state_dict(SCREAMING_SNAKE_CASE_   ,      ['a.1', 'a.2']	)
        self.assertDictEqual(SCREAMING_SNAKE_CASE_   ,      {'a.1': 0, 'a.2': 2}	)

        lowerCAmelCase_       :    Optional[Any]								=			{'a.1.a': 0, 'a.10.a': 1, 'a.2.a': 2}
        lowerCAmelCase_       :    Tuple								=			extract_submodules_state_dict(SCREAMING_SNAKE_CASE_   ,      ['a.1', 'a.2']	)
        self.assertDictEqual(SCREAMING_SNAKE_CASE_   ,      {'a.1.a': 0, 'a.2.a': 2}	)










"""simple docstring"""







def     UpperCamelCase_   (   lowerCAmelCase__				:    list[int]   ,       lowerCAmelCase__				:    list[int]						)						->       None:

  """simple docstring"""




  lowerCAmelCase_       :    List[Any]								=			len(lowerCAmelCase__						)
  print('The following activities are selected:'						)

  # The first activity is always selected
  lowerCAmelCase_       :    str								=			0
  print(lowerCAmelCase__   ,       end=','						)

  # Consider rest of the activities
  for j in range(lowerCAmelCase__						):
    # If this activity has start time greater than
    # or equal to the finish time of previously
    # selected activity, then select it
    if start[j] >= finish[i]:
      print(lowerCAmelCase__   ,       end=','						)
      lowerCAmelCase_       :    Tuple								=			j


if __name__ == "__main__":
     import doctest

     doctest.testmod()

     lowercase__		:    List[str]				   =     [1, 3, 0, 5, 8, 5]
     lowercase__		:    Dict				   =     [2, 4, 6, 7, 9, 9]
     print_max_activities(start, finish)





