


import unittest

import torch

from diffusers import DDIMScheduler, TextToVideoZeroPipeline
from diffusers.utils import load_pt, require_torch_gpu, slow

from ..test_pipelines_common import assert_mean_pixel_difference




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







							'''simple docstring'''







							def 		_UpperCAmelCase	(		self  :				int		):
													_a     =			'runwayml/stable-diffusion-v1-5'
													_a     =			TextToVideoZeroPipeline.from_pretrained(SCREAMING_SNAKE_CASE_		,				torch_dtype=torch.floataa		).to('cuda'		)
													_a     =			DDIMScheduler.from_config(pipe.scheduler.config		)
													_a     =			torch.Generator(device='cuda'		).manual_seed(0		)

													_a     =			'A bear is playing a guitar on Times Square'
													_a     =			pipe(prompt=SCREAMING_SNAKE_CASE_		,				generator=SCREAMING_SNAKE_CASE_		).images

													_a     =			load_pt(
													    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text-to-video/A bear is playing a guitar on Times Square.pt'		)

													assert_mean_pixel_difference(SCREAMING_SNAKE_CASE_		,				SCREAMING_SNAKE_CASE_		)




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowercase_								=    {
    'configuration_codegen': ['CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CodeGenConfig', 'CodeGenOnnxConfig'],
    'tokenization_codegen': ['CodeGenTokenizer'],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase_								=    ['CodeGenTokenizerFast']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase_								=    [
		    'CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'CodeGenForCausalLM',
		    'CodeGenModel',
		    'CodeGenPreTrainedModel',
		]

if TYPE_CHECKING:
		from .configuration_codegen import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, CodeGenConfig, CodeGenOnnxConfig
		from .tokenization_codegen import CodeGenTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_codegen_fast import CodeGenTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_codegen import (
				    CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
				    CodeGenForCausalLM,
				    CodeGenModel,
				    CodeGenPreTrainedModel,
				)

else:
		import sys

		lowercase_								=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


