
import gc
import unittest

from parameterized import parameterized

from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow


if is_flax_available():
						import jax
						import jax.numpy as jnp
@slow
@require_flax
class  lowercase__(				unittest.TestCase							):



	"""simple docstring"""




	def 						_lowercase  (       self  :			Dict       ,							SCREAMING_SNAKE_CASE_  :			int       ,							SCREAMING_SNAKE_CASE_  :			Union[str, Any]       )       ->     Tuple:
					return f'''gaussian_noise_s={seed}_shape={'_'.join([str(SCREAMING_SNAKE_CASE_       ) for s in shape]       )}.npy'''
	def 						_lowercase  (       self  :			List[str]       )       ->     List[Any]:
					# clean up the VRAM after each test
					super().tearDown()
					gc.collect()
	def 						_lowercase  (       self  :			Union[str, Any]       ,							SCREAMING_SNAKE_CASE_  :			Dict=0       ,							SCREAMING_SNAKE_CASE_  :			Optional[Any]=(4, 4, 6_4, 6_4)       ,							SCREAMING_SNAKE_CASE_  :			Union[str, Any]=False       )       ->     List[str]:
					lowercase_       =					jnp.bfloataa if fpaa else jnp.floataa
					lowercase_       =					jnp.array(load_hf_numpy(self.get_file_format(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )       )       ,							dtype=SCREAMING_SNAKE_CASE_       )
					return image
	def 						_lowercase  (       self  :			str       ,							SCREAMING_SNAKE_CASE_  :			Any=False       ,							SCREAMING_SNAKE_CASE_  :			Any="CompVis/stable-diffusion-v1-4"       )       ->     str:
					lowercase_       =					jnp.bfloataa if fpaa else jnp.floataa
					lowercase_       =					'''bf16''' if fpaa else None

					lowercase_  ,	lowercase_       =					FlaxUNetaDConditionModel.from_pretrained(
					    SCREAMING_SNAKE_CASE_       ,							subfolder='''unet'''       ,							dtype=SCREAMING_SNAKE_CASE_       ,							revision=SCREAMING_SNAKE_CASE_       )
					return model, params
	def 						_lowercase  (       self  :			Union[str, Any]       ,							SCREAMING_SNAKE_CASE_  :			Any=0       ,							SCREAMING_SNAKE_CASE_  :			Dict=(4, 7_7, 7_6_8)       ,							SCREAMING_SNAKE_CASE_  :			List[str]=False       )       ->     Dict:
					lowercase_       =					jnp.bfloataa if fpaa else jnp.floataa
					lowercase_       =					jnp.array(load_hf_numpy(self.get_file_format(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )       )       ,							dtype=SCREAMING_SNAKE_CASE_       )
					return hidden_states
	@parameterized.expand(
	    [
	        # fmt: off
	        [8_3, 4, [-0.23_23, -0.13_04, 0.08_13, -0.30_93, -0.09_19, -0.15_71, -0.11_25, -0.58_06]],
	        [1_7, 0.55, [-0.08_31, -0.24_43, 0.09_01, -0.09_19, 0.33_96, 0.01_03, -0.37_43, 0.07_01]],
	        [8, 0.89, [-0.48_63, 0.08_59, 0.08_75, -0.16_58, 0.91_99, -0.01_14, 0.48_39, 0.46_39]],
	        [3, 1_0_0_0, [-0.56_49, 0.24_02, -0.55_18, 0.12_48, 1.13_28, -0.24_43, -0.03_25, -1.00_78]],
	        # fmt: on
	    ]       )
	def 						_lowercase  (       self  :			Optional[Any]       ,							SCREAMING_SNAKE_CASE_  :			int       ,							SCREAMING_SNAKE_CASE_  :			str       ,							SCREAMING_SNAKE_CASE_  :			str       )       ->     int:
					lowercase_  ,	lowercase_       =					self.get_unet_model(model_id='''CompVis/stable-diffusion-v1-4'''       ,							fpaa=SCREAMING_SNAKE_CASE_       )
					lowercase_       =					self.get_latents(SCREAMING_SNAKE_CASE_       ,							fpaa=SCREAMING_SNAKE_CASE_       )
					lowercase_       =					self.get_encoder_hidden_states(SCREAMING_SNAKE_CASE_       ,							fpaa=SCREAMING_SNAKE_CASE_       )

					lowercase_       =					model.apply(
					    {'''params''': params}       ,							SCREAMING_SNAKE_CASE_       ,							jnp.array(SCREAMING_SNAKE_CASE_       ,							dtype=jnp.intaa       )       ,							encoder_hidden_states=SCREAMING_SNAKE_CASE_       ,							).sample

					assert sample.shape == latents.shape

					lowercase_       =					jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())       )       ,							dtype=jnp.floataa       )
					lowercase_       =					jnp.array(SCREAMING_SNAKE_CASE_       ,							dtype=jnp.floataa       )

					# Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, in the same hardware
					assert jnp.allclose(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							atol=1e-2       )




	@parameterized.expand(
	    [
	        # fmt: off
	        [8_3, 4, [0.15_14, 0.08_07, 0.16_24, 0.10_16, -0.18_96, 0.02_63, 0.06_77, 0.23_10]],
	        [1_7, 0.55, [0.11_64, -0.02_16, 0.01_70, 0.15_89, -0.31_20, 0.10_05, -0.05_81, -0.14_58]],
	        [8, 0.89, [-0.17_58, -0.01_69, 0.10_04, -0.14_11, 0.13_12, 0.11_03, -0.19_96, 0.21_39]],
	        [3, 1_0_0_0, [0.12_14, 0.03_52, -0.07_31, -0.15_62, -0.09_94, -0.09_06, -0.23_40, -0.05_39]],
	        # fmt: on
	    ]       )
	def 						_lowercase  (       self  :			Union[str, Any]       ,							SCREAMING_SNAKE_CASE_  :			Dict       ,							SCREAMING_SNAKE_CASE_  :			Tuple       ,							SCREAMING_SNAKE_CASE_  :			int       )       ->     Dict:
					lowercase_  ,	lowercase_       =					self.get_unet_model(model_id='''stabilityai/stable-diffusion-2'''       ,							fpaa=SCREAMING_SNAKE_CASE_       )
					lowercase_       =					self.get_latents(SCREAMING_SNAKE_CASE_       ,							shape=(4, 4, 9_6, 9_6)       ,							fpaa=SCREAMING_SNAKE_CASE_       )
					lowercase_       =					self.get_encoder_hidden_states(SCREAMING_SNAKE_CASE_       ,							shape=(4, 7_7, 1_0_2_4)       ,							fpaa=SCREAMING_SNAKE_CASE_       )

					lowercase_       =					model.apply(
					    {'''params''': params}       ,							SCREAMING_SNAKE_CASE_       ,							jnp.array(SCREAMING_SNAKE_CASE_       ,							dtype=jnp.intaa       )       ,							encoder_hidden_states=SCREAMING_SNAKE_CASE_       ,							).sample

					assert sample.shape == latents.shape

					lowercase_       =					jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())       )       ,							dtype=jnp.floataa       )
					lowercase_       =					jnp.array(SCREAMING_SNAKE_CASE_       ,							dtype=jnp.floataa       )

					# Found torch (float16) and flax (bfloat16) outputs to be within this tolerance, on the same hardware
					assert jnp.allclose(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							atol=1e-2       )








"""simple docstring"""







import os
import unittest

from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 						_A  (  _a    ,unittest.TestCase  ):







    """simple docstring"""




    UpperCAmelCase       :							str	=       LayoutLMTokenizer
    UpperCAmelCase       :							int	=       LayoutLMTokenizerFast
    UpperCAmelCase       :							Union[str, Any]	=       True
    UpperCAmelCase       :							Optional[Any]	=       True






    def 	__snake_case							(					self				:    Optional[int]):
      super().setUp()

      a						:		Tuple      							=			[
          "[UNK]",
          "[CLS]",
          "[SEP]",
          "want",
          "##want",
          "##ed",
          "wa",
          "un",
          "runn",
          "##ing",
          ",",
          "low",
          "lowest",
      ]
      a						:		Optional[Any]      							=			os.path.join(self.tmpdirname				, VOCAB_FILES_NAMES["vocab_file"])
      with open(self.vocab_file				, "w"				, encoding="utf-8") as vocab_writer:
        vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))






    def 	__snake_case							(					self				:    Optional[int]				, **__UpperCAmelCase				:    Tuple):
      return LayoutLMTokenizer.from_pretrained(self.tmpdirname				, **__UpperCAmelCase)






    def 	__snake_case							(					self				:    Union[str, Any]				, __UpperCAmelCase				:    str):
      a						:		Tuple      							=			"UNwant\u00E9d,running"
      a						:		Dict      							=			"unwanted, running"
      return input_text, output_text






    def 	__snake_case							(					self				:    Any):
      a						:		List[Any]      							=			self.tokenizer_class(self.vocab_file)

      a						:		str      							=			tokenizer.tokenize("UNwant\u00E9d,running")
      self.assertListEqual(__UpperCAmelCase				, ["un", "##want", "##ed", ",", "runn", "##ing"])
      self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase)				, [7, 4, 5, 10, 8, 9])






    def 	__snake_case							(					self				:    Dict):
      pass






