





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       __A					(					nn.Module				):

			'''simple docstring'''







			def __init__(					self							):



				'''simple docstring'''







				super().__init__()
				lowerCamelCase__              =	nn.Linear(3 ,						4							)
				lowerCamelCase__              =	nn.BatchNormad(4							)
				lowerCamelCase__              =	nn.Linear(4 ,						5							)





			def 	__lowerCamelCase       (					self ,						__lowerCAmelCase							):



				'''simple docstring'''







				return self.lineara(self.batchnorm(self.lineara(_A							)							)							)






class       __A					(					unittest.TestCase				):

			'''simple docstring'''







			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	ModelForTest()
				with TemporaryDirectory() as tmp_dir:
					offload_state_dict(_A ,						model.state_dict()							)
					lowerCamelCase__              =	os.path.join(_A ,						'''index.json'''							)
					self.assertTrue(os.path.isfile(_A							)							)
					# TODO: add tests on what is inside the index

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





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	[torch.floataa, torch.floataa, torch.bfloataa]

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

						lowerCamelCase__              =	load_offloaded_weight(_A ,						index['''weight''']							)
						self.assertTrue(torch.equal(_A ,						_A							)							)





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	ModelForTest()
				lowerCamelCase__              =	model.state_dict()
				lowerCamelCase__              =	{k: v for k, v in state_dict.items() if 'linear2' not in k}
				lowerCamelCase__              =	{k: v for k, v in state_dict.items() if 'linear2' in k}

				with TemporaryDirectory() as tmp_dir:
					offload_state_dict(_A ,						_A							)
					lowerCamelCase__              =	OffloadedWeightsLoader(state_dict=_A ,						save_folder=_A							)

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

				lowerCamelCase__              =	{k: v for k, v in state_dict.items() if 'weight' in k}
				lowerCamelCase__              =	{k: v for k, v in state_dict.items() if 'weight' not in k}

				with TemporaryDirectory() as tmp_dir:
					offload_state_dict(_A ,						_A							)
					lowerCamelCase__              =	OffloadedWeightsLoader(state_dict=_A ,						save_folder=_A							)

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

				with TemporaryDirectory() as tmp_dir:
					offload_state_dict(_A ,						_A							)
					# Duplicates are removed
					lowerCamelCase__              =	OffloadedWeightsLoader(state_dict=_A ,						save_folder=_A							)

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





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	{'a.1': 0, 'a.10': 1, 'a.2': 2}
				lowerCamelCase__              =	extract_submodules_state_dict(_A ,						['''a.1''', '''a.2''']							)
				self.assertDictEqual(_A ,						{'''a.1''': 0, '''a.2''': 2}							)

				lowerCamelCase__              =	{'a.1.a': 0, 'a.10.a': 1, 'a.2.a': 2}
				lowerCamelCase__              =	extract_submodules_state_dict(_A ,						['''a.1''', '''a.2''']							)
				self.assertDictEqual(_A ,						{'''a.1.a''': 0, '''a.2.a''': 2}							)










def lowerCAmelCase__(__snake_case							)       ->   int:







	'''simple docstring'''







	if not grid or not grid[0]:
		raise TypeError('''The grid does not contain the appropriate information'''							)

	for cell_n in range(1 ,len(grid[0]							)							):
		grid[0][cell_n] += grid[0][cell_n - 1]
	lowerCamelCase__              =	grid[0]

	for row_n in range(1 ,len(__snake_case							)							):
		lowerCamelCase__              =	grid[row_n]
		lowerCamelCase__              =	fill_row(__snake_case ,__snake_case							)
		lowerCamelCase__              =	grid[row_n]

	return grid[-1][-1]





def lowerCAmelCase__(__snake_case ,__snake_case							)       ->   list:







	'''simple docstring'''







	current_row[0] += row_above[0]
	for cell_n in range(1 ,len(__snake_case							)							):
		current_row[cell_n] += min(current_row[cell_n - 1] ,row_above[cell_n]							)

	return current_row


if __name__ == "__main__":
			import doctest

			doctest.testmod()



