


"""simple docstring"""
import unittest

import numpy as np
import torch

from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device

from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAGE_GENERATION_PARAMS
from ..test_pipelines_common import PipelineTesterMixin


enable_full_determinism()



class 			_UpperCAmelCase (							__snake_case,				unittest.TestCase				):






		'''simple docstring'''

		lowerCamelCase__				=DDIMPipeline
		lowerCamelCase__				=UNCONDITIONAL_IMAGE_GENERATION_PARAMS
		lowerCamelCase__				=PipelineTesterMixin.required_optional_params - {
		    'num_images_per_prompt',
		    'latents',
		    'callback',
		    'callback_steps',
		}
		lowerCamelCase__				=UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS
		lowerCamelCase__				=False



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			torch.manual_seed(0					)
			__snake_case	:						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''')				,       )
			__snake_case	:						Optional[Any]						=				DDIMScheduler()
			__snake_case	:						Dict						=				{'''unet''': unet, '''scheduler''': scheduler}
			return components



		def 				SCREAMING_SNAKE_CASE  (self				,       a_				,       a_=0					):





			'''simple docstring'''

			if str(a_					).startswith('''mps'''					):
				__snake_case	:						Any						=				torch.manual_seed(a_					)
			else:
				__snake_case	:						Union[str, Any]						=				torch.Generator(device=a_					).manual_seed(a_					)
			__snake_case	:						Dict						=				{
			    '''batch_size''': 1,
			    '''generator''': generator,
			    '''num_inference_steps''': 2,
			    '''output_type''': '''numpy''',
			}
			return inputs



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Tuple						=				'''cpu'''

			__snake_case	:						Optional[int]						=				self.get_dummy_components()
			__snake_case	:						List[Any]						=				self.pipeline_class(**a_					)
			pipe.to(a_					)
			pipe.set_progress_bar_config(disable=a_					)

			__snake_case	:						Tuple						=				self.get_dummy_inputs(a_					)
			__snake_case	:						List[Any]						=				pipe(**a_					).images
			__snake_case	:						int						=				image[0, -3:, -3:, -1]

			self.assertEqual(image.shape				,       (1, 32, 32, 3)					)
			__snake_case	:						Optional[Any]						=				np.array(
			    [1.000E00, 5.717E-01, 4.717E-01, 1.000E00, 0.000E00, 1.000E00, 3.000E-04, 0.000E00, 9.000E-04]					)
			__snake_case	:						List[str]						=				np.abs(image_slice.flatten() - expected_slice					).max()
			self.assertLessEqual(a_				,       1E-3					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			super().test_dict_tuple_outputs_equivalent(expected_max_difference=3E-3					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			super().test_save_load_local(expected_max_difference=3E-3					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			super().test_save_load_optional_components(expected_max_difference=3E-3					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			super().test_inference_batch_single_identical(expected_max_diff=3E-3					)



@slow
@require_torch_gpu
class 			_UpperCAmelCase (							unittest.TestCase				):






		'''simple docstring'''

		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Union[str, Any]						=				'''google/ddpm-cifar10-32'''

			__snake_case	:						str						=				UNetaDModel.from_pretrained(a_					)
			__snake_case	:						List[Any]						=				DDIMScheduler()

			__snake_case	:						Optional[Any]						=				DDIMPipeline(unet=a_				,       scheduler=a_					)
			ddim.to(a_					)
			ddim.set_progress_bar_config(disable=a_					)

			__snake_case	:						List[str]						=				torch.manual_seed(0					)
			__snake_case	:						int						=				ddim(generator=a_				,       eta=0.0				,       output_type='''numpy'''					).images

			__snake_case	:						str						=				image[0, -3:, -3:, -1]

			assert image.shape == (1, 32, 32, 3)
			__snake_case	:						Union[str, Any]						=				np.array([0.1723, 0.1617, 0.1600, 0.1626, 0.1497, 0.1513, 0.1505, 0.1442, 0.1453]					)

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



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Dict						=				'''google/ddpm-ema-bedroom-256'''

			__snake_case	:						Optional[Any]						=				UNetaDModel.from_pretrained(a_					)
			__snake_case	:						List[str]						=				DDIMScheduler.from_pretrained(a_					)

			__snake_case	:						Tuple						=				DDIMPipeline(unet=a_				,       scheduler=a_					)
			ddpm.to(a_					)
			ddpm.set_progress_bar_config(disable=a_					)

			__snake_case	:						List[str]						=				torch.manual_seed(0					)
			__snake_case	:						List[str]						=				ddpm(generator=a_				,       output_type='''numpy'''					).images

			__snake_case	:						str						=				image[0, -3:, -3:, -1]

			assert image.shape == (1, 2_56, 2_56, 3)
			__snake_case	:						Tuple						=				np.array([0.0060, 0.0201, 0.0344, 0.0024, 0.0018, 0.0002, 0.0022, 0.0000, 0.0069]					)

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









"""simple docstring"""
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
#   python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since the output of this script is fed into Makefile commands it doesn't print a newline after the results

import re
import subprocess
import sys


SCREAMING_SNAKE_CASE :    Union[str, Any]									=				subprocess.check_output("""git merge-base main HEAD""".split()).decode("""utf-8""")
SCREAMING_SNAKE_CASE :    Any									=				subprocess.check_output(F'git diff --name-only {fork_point_sha}'.split()).decode("""utf-8""").split()

SCREAMING_SNAKE_CASE :    Union[str, Any]									=				"""|""".join(sys.argv[1:])
SCREAMING_SNAKE_CASE :    int									=				re.compile(rF'^({joined_dirs}).*?\.py$')

SCREAMING_SNAKE_CASE :    str									=				[x for x in modified_files if regex.match(x)]
print(""" """.join(relevant_modified_files), end="""""")





