





import unittest

import numpy as np
import torch

from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()

class   lowerCAmelCase				(   unittest.TestCase     ):
 @property
 def 	A_      ( self    : Dict      )     ->      Optional[Any]:
     torch.manual_seed(0      )
     lowerCamelCase__       : List[Any]   					=						UNetaDModel(
         block_out_channels=(32, 64)     ,	layers_per_block=2     ,	sample_size=32     ,	in_channels=3     ,	out_channels=3     ,	down_block_types=('DownBlock2D', 'AttnDownBlock2D')     ,	up_block_types=('AttnUpBlock2D', 'UpBlock2D')     ,	)
     return model







 def 	A_      ( self    : Union[str, Any]      )     ->      List[str]:
     lowerCamelCase__       : Union[str, Any]   					=						self.dummy_uncond_unet
     lowerCamelCase__       : Optional[Any]   					=						KarrasVeScheduler()

     lowerCamelCase__       : List[str]   					=						KarrasVePipeline(unet=UpperCAmelCase     ,	scheduler=UpperCAmelCase      )
     pipe.to(UpperCAmelCase      )
     pipe.set_progress_bar_config(disable=UpperCAmelCase      )

     lowerCamelCase__       : Any   					=						torch.manual_seed(0      )
     lowerCamelCase__       : int   					=						pipe(num_inference_steps=2     ,	generator=UpperCAmelCase     ,	output_type='numpy'      ).images

     lowerCamelCase__       : Tuple   					=						torch.manual_seed(0      )
     lowerCamelCase__       : List[str]   					=						pipe(num_inference_steps=2     ,	generator=UpperCAmelCase     ,	output_type='numpy'     ,	return_dict=UpperCAmelCase      )[0]

     lowerCamelCase__       : Union[str, Any]   					=						image[0, -3:, -3:, -1]
     lowerCamelCase__       : List[Any]   					=						image_from_tuple[0, -3:, -3:, -1]

     assert image.shape == (1, 32, 32, 3)
     lowerCamelCase__       : Optional[Any]   					=						np.array([0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]      )

     assert np.abs(image_slice.flatten() - expected_slice      ).max() < 1e-2
     assert np.abs(image_from_tuple_slice.flatten() - expected_slice      ).max() < 1e-2


@slow
@require_torch
class   lowerCAmelCase				(   unittest.TestCase     ):
 def 	A_      ( self    : Dict      )     ->      Optional[Any]:
     lowerCamelCase__       : List[Any]   					=						'google/ncsnpp-celebahq-256'
     lowerCamelCase__       : Dict   					=						UNetaDModel.from_pretrained(UpperCAmelCase      )
     lowerCamelCase__       : Any   					=						KarrasVeScheduler()

     lowerCamelCase__       : Tuple   					=						KarrasVePipeline(unet=UpperCAmelCase     ,	scheduler=UpperCAmelCase      )
     pipe.to(UpperCAmelCase      )
     pipe.set_progress_bar_config(disable=UpperCAmelCase      )

     lowerCamelCase__       : List[Any]   					=						torch.manual_seed(0      )
     lowerCamelCase__       : Optional[int]   					=						pipe(num_inference_steps=20     ,	generator=UpperCAmelCase     ,	output_type='numpy'      ).images

     lowerCamelCase__       : List[Any]   					=						image[0, -3:, -3:, -1]
     assert image.shape == (1, 256, 256, 3)
     lowerCamelCase__       : str   					=						np.array([0.5_7_8, 0.5_8_1_1, 0.5_9_2_4, 0.5_8_0_9, 0.5_8_7, 0.5_8_8_6, 0.5_8_6_1, 0.5_8_0_2, 0.5_8_6]      )

     assert np.abs(image_slice.flatten() - expected_slice      ).max() < 1e-2












from __future__ import annotations

import time
from collections.abc import Sequence
from random import randint

from matplotlib import pyplot as plt


def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)     ->	tuple[int | None, int | None, float]:
    if not arr:
        return None, None, 0
    if low == high:
        return low, high, arr[low]

    lowerCamelCase__       : Union[str, Any]   					=						(low + high) // 2
    lowerCamelCase__					,				lowerCamelCase__					,				lowerCamelCase__       : str   					=						max_subarray(_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)
    lowerCamelCase__					,				lowerCamelCase__					,				lowerCamelCase__       : Optional[Any]   					=						max_subarray(_UpperCAmelCase		,      mid + 1		,      _UpperCAmelCase					)
    lowerCamelCase__					,				lowerCamelCase__					,				lowerCamelCase__       : int   					=						max_cross_sum(_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)
    if left_sum >= right_sum and left_sum >= cross_sum:
        return left_low, left_high, left_sum
    elif right_sum >= left_sum and right_sum >= cross_sum:
        return right_low, right_high, right_sum
    return cross_left, cross_right, cross_sum


def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase					)     ->	tuple[int, int, float]:
    lowerCamelCase__					,				lowerCamelCase__       : Union[str, Any]   					=						float('-inf'					), -1
    lowerCamelCase__					,				lowerCamelCase__       : Tuple   					=						float('-inf'					), -1

    lowerCamelCase__       : int | float   					=						0
    for i in range(_UpperCAmelCase		,      low - 1		,      -1					):
        summ += arr[i]
        if summ > left_sum:
            lowerCamelCase__       : Optional[int]   					=						summ
            lowerCamelCase__       : Tuple   					=						i

    lowerCamelCase__       : int   					=						0
    for i in range(mid + 1		,      high + 1					):
        summ += arr[i]
        if summ > right_sum:
            lowerCamelCase__       : int   					=						summ
            lowerCamelCase__       : List[Any]   					=						i

    return max_left, max_right, (left_sum + right_sum)


def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase					)     ->	float:
    lowerCamelCase__       : Any   					=						[randint(1		,      _UpperCAmelCase					) for _ in range(_UpperCAmelCase					)]
    lowerCamelCase__       : Tuple   					=						time.time()
    max_subarray(_UpperCAmelCase		,      0		,      input_size - 1					)
    lowerCamelCase__       : List[Any]   					=						time.time()
    return end - start


def 			SCREAMING_SNAKE_CASE (			)     ->	None:
    lowerCamelCase__       : Optional[Any]   					=						[10, 100, 1000, 1_0000, 5_0000, 10_0000, 20_0000, 30_0000, 40_0000, 50_0000]
    lowerCamelCase__       : Optional[Any]   					=						[time_max_subarray(_UpperCAmelCase					) for input_size in input_sizes]
    print('No of Inputs\t\tTime Taken'					)
    for input_size, runtime in zip(_UpperCAmelCase		,      _UpperCAmelCase					):
        print(_UpperCAmelCase		,      '\t\t'		,      _UpperCAmelCase					)
    plt.plot(_UpperCAmelCase		,      _UpperCAmelCase					)
    plt.xlabel('Number of Inputs'					)
    plt.ylabel('Time taken in seconds'					)
    plt.show()


if __name__ == "__main__":
    from doctest import testmod

    testmod()





