

import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device


UpperCamelCase__  :      List[Any]			=    False



class       __snake_case  (    unittest.TestCase       ):
  pass






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

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						VersatileDiffusionImageVariationPipeline.from_pretrained('shi-labs/versatile-diffusion')
      pipe.to(_A)
      pipe.set_progress_bar_config(disable=_A)

      SCREAMING_SNAKE_CASE_									=						load_image(
          'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg')
      SCREAMING_SNAKE_CASE_									=						torch.manual_seed(0)
      SCREAMING_SNAKE_CASE_									=						pipe(
          image=_A						,		generator=_A						,		guidance_scale=7.5						,		num_inference_steps=50						,		output_type='numpy'						,		).images

      SCREAMING_SNAKE_CASE_									=						image[0, 253:256, 253:256, -1]

      assert image.shape == (1, 512, 512, 3)
      SCREAMING_SNAKE_CASE_									=						np.array([0.0_4_4_1, 0.0_4_6_9, 0.0_5_0_7, 0.0_5_7_5, 0.0_6_3_2, 0.0_6_5_0, 0.0_8_6_5, 0.0_9_0_9, 0.0_9_4_5])

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






import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


UpperCamelCase__  :      int			=    "\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.\n\nIn March 2021, Hugging Face raised $40 million in a Series B funding round.[3]\n\nOn April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]\n"



class       __snake_case  (    unittest.TestCase     , lowerCAmelCase__       ):

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						load_tool('text-question-answering')
      self.tool.setup()
      SCREAMING_SNAKE_CASE_									=						load_tool('text-question-answering'						,		remote=_A)

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						self.tool(_A						,		'What did Hugging Face do in April 2021?')
      self.assertEqual(_A						,		'launched the BigScience Research Workshop')

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						self.remote_tool(_A						,		'What did Hugging Face do in April 2021?')
      self.assertEqual(_A						,		'launched the BigScience Research Workshop')

  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						self.tool(text=_A						,		question='What did Hugging Face do in April 2021?')
      self.assertEqual(_A						,		'launched the BigScience Research Workshop')


  def 						lowerCAmelCase__     (					self):
      SCREAMING_SNAKE_CASE_									=						self.remote_tool(text=_A						,		question='What did Hugging Face do in April 2021?')
      self.assertEqual(_A						,		'launched the BigScience Research Workshop')


