
"""simple docstring"""




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  snake_case     (							unittest.TestCase   ):

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									return f'gaussian_noise_s={seed}_shape={"_".join([str(SCREAMING_SNAKE_CASE_    ) for s in shape]    )}.npy'

							def _lowercase					(self    ):

									"""simple docstring"""







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

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_=0       ,       SCREAMING_SNAKE_CASE_=(4, 4, 64, 64)       ,       SCREAMING_SNAKE_CASE_=False    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = jnp.bfloataa if fpaa else jnp.floataa
									SCREAMING_SNAKE_CASE_						 = jnp.array(load_hf_numpy(self.get_file_format(SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    )    )       ,       dtype=SCREAMING_SNAKE_CASE_    )
									return image

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_=False       ,       SCREAMING_SNAKE_CASE_="CompVis/stable-diffusion-v1-4"    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = jnp.bfloataa if fpaa else jnp.floataa
									SCREAMING_SNAKE_CASE_						 = '''bf16''' if fpaa else None

									SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_						 = FlaxUNetaDConditionModel.from_pretrained(
									    SCREAMING_SNAKE_CASE_       ,       subfolder='''unet'''       ,       dtype=SCREAMING_SNAKE_CASE_       ,       revision=SCREAMING_SNAKE_CASE_    )
									return model, params

							def _lowercase					(self       ,       SCREAMING_SNAKE_CASE_=0       ,       SCREAMING_SNAKE_CASE_=(4, 77, 7_68)       ,       SCREAMING_SNAKE_CASE_=False    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_						 = jnp.bfloataa if fpaa else jnp.floataa
									SCREAMING_SNAKE_CASE_						 = 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
							        [83, 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]],
							        [17, 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, 10_00, [-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       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_						 = self.get_unet_model(model_id='''CompVis/stable-diffusion-v1-4'''       ,       fpaa=SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = self.get_latents(SCREAMING_SNAKE_CASE_       ,       fpaa=SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = self.get_encoder_hidden_states(SCREAMING_SNAKE_CASE_       ,       fpaa=SCREAMING_SNAKE_CASE_    )

									SCREAMING_SNAKE_CASE_						 = 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

									SCREAMING_SNAKE_CASE_						 = jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())    )       ,       dtype=jnp.floataa    )
									SCREAMING_SNAKE_CASE_						 = 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
							        [83, 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]],
							        [17, 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, 10_00, [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       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_    ):

									"""simple docstring"""







									SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_						 = self.get_unet_model(model_id='''stabilityai/stable-diffusion-2'''       ,       fpaa=SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = self.get_latents(SCREAMING_SNAKE_CASE_       ,       shape=(4, 4, 96, 96)       ,       fpaa=SCREAMING_SNAKE_CASE_    )
									SCREAMING_SNAKE_CASE_						 = self.get_encoder_hidden_states(SCREAMING_SNAKE_CASE_       ,       shape=(4, 77, 10_24)       ,       fpaa=SCREAMING_SNAKE_CASE_    )

									SCREAMING_SNAKE_CASE_						 = 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

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




from __future__ import annotations



def        _lowerCamelCase ( __a,							__a    ):
		SCREAMING_SNAKE_CASE_						 = 0
		SCREAMING_SNAKE_CASE_						 = len(__a    ) - 1

		while i < j:
				if nums[i] + nums[j] == target:
						return [i, j]
				elif nums[i] + nums[j] < target:
						SCREAMING_SNAKE_CASE_						 = i + 1
				else:
						SCREAMING_SNAKE_CASE_						 = j - 1

		return []


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						print(f'''{two_pointer([2, 7, 11, 15], 9) = }''')