'''simple docstring'''


import math
import os
import sys





def       lowerCAmelCase					(		UpperCamelCase__				:   str       ):


	"""simple docstring"""
	__UpperCAmelCase							=			''''''
	try:
		with open(UpperCamelCase__    ,					'''rb'''       ) as binary_file:
			__UpperCAmelCase							=			binary_file.read()
		for dat in data:
			__UpperCAmelCase							=			f"""{dat:08b}"""
			result += curr_byte
		return result
	except OSError:
		print('''File not accessible'''       )
		sys.exit()





def       lowerCAmelCase					(		UpperCamelCase__				:   dict[str, str]    ,					UpperCamelCase__				:   str    ,					UpperCamelCase__				:   int    ,					UpperCamelCase__				:   str       ):


	"""simple docstring"""
	lexicon.pop(UpperCamelCase__       )
	__UpperCAmelCase							=			last_match_id

	if math.loga(UpperCamelCase__       ).is_integer():
		for curr_key in lexicon:
			__UpperCAmelCase							=			'''0''' + lexicon[curr_key]

	__UpperCAmelCase							=			bin(UpperCamelCase__       )[2:]





def       lowerCAmelCase					(		UpperCamelCase__				:   str       ):


	"""simple docstring"""
	__UpperCAmelCase							=			{'''0''': '''0''', '''1''': '''1'''}
	__UpperCAmelCase				,			__UpperCAmelCase							=			'''''', ''''''
	__UpperCAmelCase							=			len(UpperCamelCase__       )

	for i in range(len(UpperCamelCase__       )       ):
		curr_string += data_bits[i]
		if curr_string not in lexicon:
			continue

		__UpperCAmelCase							=			lexicon[curr_string]
		result += last_match_id
		add_key_to_lexicon(UpperCamelCase__    ,					UpperCamelCase__    ,					UpperCamelCase__    ,					UpperCamelCase__       )
		index += 1
		__UpperCAmelCase							=			''''''

	while curr_string != "" and curr_string not in lexicon:
		curr_string += "0"

	if curr_string != "":
		__UpperCAmelCase							=			lexicon[curr_string]
		result += last_match_id

	return result





def       lowerCAmelCase					(		UpperCamelCase__				:   str    ,					UpperCamelCase__				:   str       ):


	"""simple docstring"""
	__UpperCAmelCase							=			os.path.getsize(UpperCamelCase__       )
	__UpperCAmelCase							=			bin(UpperCamelCase__       )[2:]
	__UpperCAmelCase							=			len(UpperCamelCase__       )

	return "0" * (length_length - 1) + file_length_binary + compressed





def       lowerCAmelCase					(		UpperCamelCase__				:   str    ,					UpperCamelCase__				:   str       ):


	"""simple docstring"""
	__UpperCAmelCase							=			8
	try:
		with open(UpperCamelCase__    ,					'''wb'''       ) as opened_file:
			__UpperCAmelCase							=			[
			    to_write[i : i + byte_length]
			    for i in range(0    ,					len(UpperCamelCase__       )    ,					UpperCamelCase__       )
			]

			if len(result_byte_array[-1]       ) % byte_length == 0:
				result_byte_array.append('''10000000'''       )
			else:
				result_byte_array[-1] += "1" + "0" * (
				    byte_length - len(result_byte_array[-1]       ) - 1
				)

			for elem in result_byte_array:
				opened_file.write(int(UpperCamelCase__    ,					2       ).to_bytes(1    ,					byteorder='''big'''       )       )
	except OSError:
		print('''File not accessible'''       )
		sys.exit()





def       lowerCAmelCase					(		UpperCamelCase__				:   str    ,					UpperCamelCase__				:   str       ):


	"""simple docstring"""
	__UpperCAmelCase							=			read_file_binary(UpperCamelCase__       )
	__UpperCAmelCase							=			compress_data(UpperCamelCase__       )
	__UpperCAmelCase							=			add_file_length(UpperCamelCase__    ,					UpperCamelCase__       )
	write_file_binary(UpperCamelCase__    ,					UpperCamelCase__       )


if __name__ == "__main__":
					compress(sys.argv[1], sys.argv[2])

'''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 						A   (   unittest.TestCase   ):





							def       snake_case__						(      self				:							List[Any]     ,		__a				:							List[str]     ,		__a				:							Optional[Any]	)							->	List[Any]:
								return f"""gaussian_noise_s={seed}_shape={'_'.join([str(__a	) for s in shape]	)}.npy"""





							def       snake_case__						(      self				:							Dict	)							->	Union[str, Any]:
								# clean up the VRAM after each test
								super().tearDown()
								gc.collect()





							def       snake_case__						(      self				:							Optional[Any]     ,		__a				:							Tuple=0     ,		__a				:							List[Any]=(4, 4, 6_4, 6_4)     ,		__a				:							Optional[Any]=False	)							->	Tuple:
								__UpperCAmelCase							=			jnp.bfloataa if fpaa else jnp.floataa
								__UpperCAmelCase							=			jnp.array(load_hf_numpy(self.get_file_format(__a     ,		__a	)	)     ,		dtype=__a	)
								return image





							def       snake_case__						(      self				:							int     ,		__a				:							Optional[Any]=False     ,		__a				:							Optional[Any]="CompVis/stable-diffusion-v1-4"	)							->	Any:
								__UpperCAmelCase							=			jnp.bfloataa if fpaa else jnp.floataa
								__UpperCAmelCase							=			'''bf16''' if fpaa else None

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





							def       snake_case__						(      self				:							str     ,		__a				:							int=0     ,		__a				:							Tuple=(4, 7_7, 7_6_8)     ,		__a				:							Optional[int]=False	)							->	Union[str, Any]:
								__UpperCAmelCase							=			jnp.bfloataa if fpaa else jnp.floataa
								__UpperCAmelCase							=			jnp.array(load_hf_numpy(self.get_file_format(__a     ,		__a	)	)     ,		dtype=__a	)
								return hidden_states





							@parameterized.expand(
							    [
							        # fmt: off
							        [8_3, 4, [-0.2_3_2_3, -0.1_3_0_4, 0.0_8_1_3, -0.3_0_9_3, -0.0_9_1_9, -0.1_5_7_1, -0.1_1_2_5, -0.5_8_0_6]],
							        [1_7, 0.5_5, [-0.0_8_3_1, -0.2_4_4_3, 0.0_9_0_1, -0.0_9_1_9, 0.3_3_9_6, 0.0_1_0_3, -0.3_7_4_3, 0.0_7_0_1]],
							        [8, 0.8_9, [-0.4_8_6_3, 0.0_8_5_9, 0.0_8_7_5, -0.1_6_5_8, 0.9_1_9_9, -0.0_1_1_4, 0.4_8_3_9, 0.4_6_3_9]],
							        [3, 1_0_0_0, [-0.5_6_4_9, 0.2_4_0_2, -0.5_5_1_8, 0.1_2_4_8, 1.1_3_2_8, -0.2_4_4_3, -0.0_3_2_5, -1.0_0_7_8]],
							        # fmt: on
							    ]	)
							def       snake_case__						(      self				:							Tuple     ,		__a				:							Tuple     ,		__a				:							str     ,		__a				:							Optional[Any]	)							->	Any:
								__UpperCAmelCase				,			__UpperCAmelCase							=			self.get_unet_model(model_id='''CompVis/stable-diffusion-v1-4'''     ,		fpaa=__a	)
								__UpperCAmelCase							=			self.get_latents(__a     ,		fpaa=__a	)
								__UpperCAmelCase							=			self.get_encoder_hidden_states(__a     ,		fpaa=__a	)

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

								assert sample.shape == latents.shape

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

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






							@parameterized.expand(
							    [
							        # fmt: off
							        [8_3, 4, [0.1_5_1_4, 0.0_8_0_7, 0.1_6_2_4, 0.1_0_1_6, -0.1_8_9_6, 0.0_2_6_3, 0.0_6_7_7, 0.2_3_1_0]],
							        [1_7, 0.5_5, [0.1_1_6_4, -0.0_2_1_6, 0.0_1_7_0, 0.1_5_8_9, -0.3_1_2_0, 0.1_0_0_5, -0.0_5_8_1, -0.1_4_5_8]],
							        [8, 0.8_9, [-0.1_7_5_8, -0.0_1_6_9, 0.1_0_0_4, -0.1_4_1_1, 0.1_3_1_2, 0.1_1_0_3, -0.1_9_9_6, 0.2_1_3_9]],
							        [3, 1_0_0_0, [0.1_2_1_4, 0.0_3_5_2, -0.0_7_3_1, -0.1_5_6_2, -0.0_9_9_4, -0.0_9_0_6, -0.2_3_4_0, -0.0_5_3_9]],
							        # fmt: on
							    ]	)
							def       snake_case__						(      self				:							Optional[Any]     ,		__a				:							Optional[int]     ,		__a				:							Optional[Any]     ,		__a				:							Optional[Any]	)							->	Union[str, Any]:
								__UpperCAmelCase				,			__UpperCAmelCase							=			self.get_unet_model(model_id='''stabilityai/stable-diffusion-2'''     ,		fpaa=__a	)
								__UpperCAmelCase							=			self.get_latents(__a     ,		shape=(4, 4, 9_6, 9_6)     ,		fpaa=__a	)
								__UpperCAmelCase							=			self.get_encoder_hidden_states(__a     ,		shape=(4, 7_7, 1_0_2_4)     ,		fpaa=__a	)

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

								assert sample.shape == latents.shape

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

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