



"""simple docstring"""





import gc
import unittest

from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
					import jax
					import jax.numpy as jnp
					from flax.jax_utils import replicate
					from flax.training.common_utils import shard



@slow
@require_flax
class    _lowerCAmelCase    (				unittest.TestCase		):





		"""simple docstring"""






		def    UpperCAmelCase__							(					self   ) ->						List[str]:







								'''simple docstring'''

								super().tearDown()
								gc.collect()





		def    UpperCAmelCase__							(					self   ) ->						str:







								'''simple docstring'''

								snake_case_			,		snake_case_   : str						=			FlaxControlNetModel.from_pretrained(
								    """lllyasviel/sd-controlnet-canny"""							,    from_pt=_lowercase							,    dtype=jnp.bfloataa   )
								snake_case_			,		snake_case_   : Tuple						=			FlaxStableDiffusionControlNetPipeline.from_pretrained(
								    """runwayml/stable-diffusion-v1-5"""							,    controlnet=_lowercase							,    from_pt=_lowercase							,    dtype=jnp.bfloataa   )
								snake_case_   : Tuple						=			controlnet_params

								snake_case_   : int						=			"""bird"""
								snake_case_   : Any						=			jax.device_count()
								snake_case_   : List[str]						=			pipe.prepare_text_inputs([prompts] * num_samples   )

								snake_case_   : Optional[int]						=			load_image(
								    """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/bird_canny.png"""   )
								snake_case_   : Any						=			pipe.prepare_image_inputs([canny_image] * num_samples   )

								snake_case_   : List[Any]						=			jax.random.PRNGKey(0   )
								snake_case_   : int						=			jax.random.split(_lowercase							,    jax.device_count()   )

								snake_case_   : List[str]						=			replicate(_lowercase   )
								snake_case_   : Optional[int]						=			shard(_lowercase   )
								snake_case_   : Optional[Any]						=			shard(_lowercase   )

								snake_case_   : str						=			pipe(
								    prompt_ids=_lowercase							,    image=_lowercase							,    params=_lowercase							,    prng_seed=_lowercase							,    num_inference_steps=5_0							,    jit=_lowercase							,    ).images
								assert images.shape == (jax.device_count(), 1, 7_6_8, 5_1_2, 3)

								snake_case_   : int						=			images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]   )
								snake_case_   : Dict						=			images[0, 2_5_3:2_5_6, 2_5_3:2_5_6, -1]

								snake_case_   : Tuple						=			jnp.asarray(jax.device_get(image_slice.flatten()   )   )
								snake_case_   : Dict						=			jnp.array(
								    [0.16_7969, 0.11_6699, 0.08_1543, 0.15_4297, 0.13_2812, 0.10_8887, 0.16_9922, 0.16_9922, 0.20_5078]   )
								print(f'output_slice: {output_slice}'   )
								assert jnp.abs(output_slice - expected_slice   ).max() < 1E-2





		def    UpperCAmelCase__							(					self   ) ->						List[Any]:







								'''simple docstring'''

								snake_case_			,		snake_case_   : str						=			FlaxControlNetModel.from_pretrained(
								    """lllyasviel/sd-controlnet-openpose"""							,    from_pt=_lowercase							,    dtype=jnp.bfloataa   )
								snake_case_			,		snake_case_   : Dict						=			FlaxStableDiffusionControlNetPipeline.from_pretrained(
								    """runwayml/stable-diffusion-v1-5"""							,    controlnet=_lowercase							,    from_pt=_lowercase							,    dtype=jnp.bfloataa   )
								snake_case_   : str						=			controlnet_params

								snake_case_   : List[str]						=			"""Chef in the kitchen"""
								snake_case_   : int						=			jax.device_count()
								snake_case_   : int						=			pipe.prepare_text_inputs([prompts] * num_samples   )

								snake_case_   : Tuple						=			load_image(
								    """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/pose.png"""   )
								snake_case_   : Tuple						=			pipe.prepare_image_inputs([pose_image] * num_samples   )

								snake_case_   : Tuple						=			jax.random.PRNGKey(0   )
								snake_case_   : Optional[Any]						=			jax.random.split(_lowercase							,    jax.device_count()   )

								snake_case_   : Dict						=			replicate(_lowercase   )
								snake_case_   : Union[str, Any]						=			shard(_lowercase   )
								snake_case_   : Optional[int]						=			shard(_lowercase   )

								snake_case_   : Dict						=			pipe(
								    prompt_ids=_lowercase							,    image=_lowercase							,    params=_lowercase							,    prng_seed=_lowercase							,    num_inference_steps=5_0							,    jit=_lowercase							,    ).images
								assert images.shape == (jax.device_count(), 1, 7_6_8, 5_1_2, 3)

								snake_case_   : str						=			images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]   )
								snake_case_   : Dict						=			images[0, 2_5_3:2_5_6, 2_5_3:2_5_6, -1]

								snake_case_   : Union[str, Any]						=			jnp.asarray(jax.device_get(image_slice.flatten()   )   )
								snake_case_   : Tuple						=			jnp.array(
								    [[0.27_1484, 0.26_1719, 0.27_5391, 0.27_7344, 0.27_9297, 0.29_1016, 0.29_4922, 0.30_2734, 0.30_2734]]   )
								print(f'output_slice: {output_slice}'   )
								assert jnp.abs(output_slice - expected_slice   ).max() < 1E-2






"""simple docstring"""





import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_rjieba
@require_tokenizers
class    _lowerCAmelCase    (				SCREAMING_SNAKE_CASE__  ,				unittest.TestCase		):





		"""simple docstring"""






		_lowerCamelCase			  =       RoFormerTokenizer
		_lowerCamelCase			  =       RoFormerTokenizerFast
		_lowerCamelCase			  =       True
		_lowerCamelCase			  =       True





		def    UpperCAmelCase__							(					self   ) ->						Any:







								'''simple docstring'''

								super().setUp()





		def    UpperCAmelCase__							(					self							,    **_lowercase   ) ->						str:







								'''simple docstring'''

								return self.tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""							,    **_lowercase   )





		def    UpperCAmelCase__							(					self							,    **_lowercase   ) ->						Union[str, Any]:







								'''simple docstring'''

								return self.rust_tokenizer_class.from_pretrained("""junnyu/roformer_chinese_base"""							,    **_lowercase   )





		def    UpperCAmelCase__							(					self   ) ->						Dict:







								'''simple docstring'''

								snake_case_   : Tuple						=			"""永和服装饰品有限公司,今天天气非常好"""
								snake_case_   : int						=			"""永和 服装 饰品 有限公司 , 今 天 天 气 非常 好"""
								return input_text, output_text





		def    UpperCAmelCase__							(					self   ) ->						str:







								'''simple docstring'''

								snake_case_   : List[str]						=			self.get_tokenizer()
								snake_case_			,		snake_case_   : Optional[Any]						=			self.get_chinese_input_output_texts()
								snake_case_   : List[str]						=			tokenizer.tokenize(_lowercase   )

								self.assertListEqual(_lowercase							,    output_text.split()   )

								snake_case_   : str						=			tokens + [tokenizer.unk_token]
								snake_case_   : Tuple						=			[2_2_9_4_3, 2_1_3_3_2, 3_4_4_3_1, 4_5_9_0_4, 1_1_7, 3_0_6, 1_2_3_1, 1_2_3_1, 2_6_5_3, 3_3_9_9_4, 1_2_6_6, 1_0_0]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase   )							,    _lowercase   )





		def    UpperCAmelCase__							(					self   ) ->						Any:







								'''simple docstring'''

								snake_case_   : int						=			self.get_rust_tokenizer()
								snake_case_			,		snake_case_   : List[Any]						=			self.get_chinese_input_output_texts()
								snake_case_   : Union[str, Any]						=			tokenizer.tokenize(_lowercase   )
								self.assertListEqual(_lowercase							,    output_text.split()   )
								snake_case_   : Optional[int]						=			tokens + [tokenizer.unk_token]
								snake_case_   : Union[str, Any]						=			[2_2_9_4_3, 2_1_3_3_2, 3_4_4_3_1, 4_5_9_0_4, 1_1_7, 3_0_6, 1_2_3_1, 1_2_3_1, 2_6_5_3, 3_3_9_9_4, 1_2_6_6, 1_0_0]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase   )							,    _lowercase   )





		def    UpperCAmelCase__							(					self   ) ->						Tuple:







								'''simple docstring'''

								pass





		def    UpperCAmelCase__							(					self   ) ->						Optional[Any]:







								'''simple docstring'''

								pass





		def    UpperCAmelCase__							(					self   ) ->						Optional[int]:







								'''simple docstring'''

								pass

