






"""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 							__SCREAMING_SNAKE_CASE						(				unittest.TestCase		):


							def 						_UpperCamelCase       (			self      :						Optional[Any]			,    snake_case      :						Any			,    snake_case      :						Optional[int]							):
													'''simple docstring'''





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


							def 						_UpperCamelCase       (			self      :						Optional[Any]							):
													'''simple docstring'''





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


							def 						_UpperCamelCase       (			self      :						List[Any]			,    snake_case      :						List[str]=0			,    snake_case      :						int=(4, 4, 64, 64)			,    snake_case      :						Optional[Any]=False							):
													'''simple docstring'''





													A__						:  Any		  =  jnp.bfloataa if fpaa else jnp.floataa
													A__						:  int		  =  jnp.array(load_hf_numpy(self.get_file_format(snake_case			,    snake_case							)							)			,    dtype=snake_case							)
													return image


							def 						_UpperCamelCase       (			self      :						List[str]			,    snake_case      :						int=False			,    snake_case      :						Optional[int]="CompVis/stable-diffusion-v1-4"							):
													'''simple docstring'''





													A__						:  List[Any]		  =  jnp.bfloataa if fpaa else jnp.floataa
													A__						:  List[str]		  =  """bf16""" if fpaa else None

													A__  ,  A__						:  List[Any]		  =  FlaxUNetaDConditionModel.from_pretrained(
													    snake_case			,    subfolder="""unet"""			,    dtype=snake_case			,    revision=snake_case							)
													return model, params


							def 						_UpperCamelCase       (			self      :						Dict			,    snake_case      :						int=0			,    snake_case      :						Dict=(4, 77, 768)			,    snake_case      :						Dict=False							):
													'''simple docstring'''





													A__						:  Dict		  =  jnp.bfloataa if fpaa else jnp.floataa
													A__						:  Any		  =  jnp.array(load_hf_numpy(self.get_file_format(snake_case			,    snake_case							)							)			,    dtype=snake_case							)
													return hidden_states


							@parameterized.expand(
							    [
							        # fmt: off
							        [83, 4, [-0.2323, -0.1304, 0.0813, -0.3093, -0.0919, -0.1571, -0.1125, -0.5806]],
							        [17, 0.55, [-0.0831, -0.2443, 0.0901, -0.0919, 0.3396, 0.0103, -0.3743, 0.0701]],
							        [8, 0.89, [-0.4863, 0.0859, 0.0875, -0.1658, 0.9199, -0.0114, 0.4839, 0.4639]],
							        [3, 1000, [-0.5649, 0.2402, -0.5518, 0.1248, 1.1328, -0.2443, -0.0325, -1.0078]],
							        # fmt: on
							    ]							)
							def 						_UpperCamelCase       (			self      :						Optional[Any]			,    snake_case      :						Optional[Any]			,    snake_case      :						str			,    snake_case      :						Optional[int]							):
													'''simple docstring'''





													A__  ,  A__						:  str		  =  self.get_unet_model(model_id="""CompVis/stable-diffusion-v1-4"""			,    fpaa=snake_case							)
													A__						:  int		  =  self.get_latents(snake_case			,    fpaa=snake_case							)
													A__						:  Tuple		  =  self.get_encoder_hidden_states(snake_case			,    fpaa=snake_case							)

													A__						:  Tuple		  =  model.apply(
													    {"""params""": params}			,    snake_case			,    jnp.array(snake_case			,    dtype=jnp.intaa							)			,    encoder_hidden_states=snake_case			,    ).sample

													assert sample.shape == latents.shape

													A__						:  List[str]		  =  jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())							)			,    dtype=jnp.floataa							)
													A__						:  int		  =  jnp.array(snake_case			,    dtype=jnp.floataa							)

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


							@parameterized.expand(
							    [
							        # fmt: off
							        [83, 4, [0.1514, 0.0807, 0.1624, 0.1016, -0.1896, 0.0263, 0.0677, 0.2310]],
							        [17, 0.55, [0.1164, -0.0216, 0.0170, 0.1589, -0.3120, 0.1005, -0.0581, -0.1458]],
							        [8, 0.89, [-0.1758, -0.0169, 0.1004, -0.1411, 0.1312, 0.1103, -0.1996, 0.2139]],
							        [3, 1000, [0.1214, 0.0352, -0.0731, -0.1562, -0.0994, -0.0906, -0.2340, -0.0539]],
							        # fmt: on
							    ]							)
							def 						_UpperCamelCase       (			self      :						List[Any]			,    snake_case      :						Optional[Any]			,    snake_case      :						Optional[int]			,    snake_case      :						Optional[Any]							):
													'''simple docstring'''





													A__  ,  A__						:  List[Any]		  =  self.get_unet_model(model_id="""stabilityai/stable-diffusion-2"""			,    fpaa=snake_case							)
													A__						:  List[str]		  =  self.get_latents(snake_case			,    shape=(4, 4, 96, 96)			,    fpaa=snake_case							)
													A__						:  List[Any]		  =  self.get_encoder_hidden_states(snake_case			,    shape=(4, 77, 1024)			,    fpaa=snake_case							)

													A__						:  Dict		  =  model.apply(
													    {"""params""": params}			,    snake_case			,    jnp.array(snake_case			,    dtype=jnp.intaa							)			,    encoder_hidden_states=snake_case			,    ).sample

													assert sample.shape == latents.shape

													A__						:  Optional[Any]		  =  jnp.asarray(jax.device_get((sample[-1, -2:, -2:, :2].flatten())							)			,    dtype=jnp.floataa							)
													A__						:  Dict		  =  jnp.array(snake_case			,    dtype=jnp.floataa							)

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














"""simple docstring"""



import os

try:
						from .build_directory_md import good_file_paths
except ImportError:
						from build_directory_md import good_file_paths  # type: ignore

A_    =							list(good_file_paths())
assert filepaths, "good_file_paths() failed!"

A_    =							[file for file in filepaths if file != file.lower()]
if upper_files:
						print(F'{len(upper_files)} files contain uppercase characters:')
						print('''\n'''.join(upper_files) + '''\n''')

A_    =							[file for file in filepaths if ''' ''' in file]
if space_files:
						print(F'{len(space_files)} files contain space characters:')
						print('''\n'''.join(space_files) + '''\n''')

A_    =							[file for file in filepaths if '''-''' in file]
if hyphen_files:
						print(F'{len(hyphen_files)} files contain hyphen characters:')
						print('''\n'''.join(hyphen_files) + '''\n''')

A_    =							[file for file in filepaths if os.sep not in file]
if nodir_files:
						print(F'{len(nodir_files)} files are not in a directory:')
						print('''\n'''.join(nodir_files) + '''\n''')

A_    =							len(upper_files + space_files + hyphen_files + nodir_files)
if bad_files:
						import sys

						sys.exit(bad_files)






