


import doctest
import sys
import warnings
from os.path import abspath, dirname, join

import _pytest

from transformers.testing_utils import HfDoctestModule, HfDocTestParser


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
snake_case      :   Tuple							= abspath(join(dirname(__file__), 'src'))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action='ignore', category=FutureWarning)


def 					SCREAMING_SNAKE_CASE			(  UpperCAmelCase__				):

				"""simple docstring"""






				config.addinivalue_line(
				    'markers' ,'is_pt_tf_cross_test: mark test to run only when PT and TF interactions are tested'				)
				config.addinivalue_line(
				    'markers' ,'is_pt_flax_cross_test: mark test to run only when PT and FLAX interactions are tested'				)
				config.addinivalue_line('markers' ,'is_pipeline_test: mark test to run only when pipelines are tested'				)
				config.addinivalue_line('markers' ,'is_staging_test: mark test to run only in the staging environment'				)
				config.addinivalue_line('markers' ,'accelerate_tests: mark test that require accelerate'				)
				config.addinivalue_line('markers' ,'tool_tests: mark the tool tests that are run on their specific schedule'				)


def 					SCREAMING_SNAKE_CASE			(  UpperCAmelCase__				):

				"""simple docstring"""






				from transformers.testing_utils import pytest_addoption_shared

				pytest_addoption_shared(UpperCAmelCase__				)


def 					SCREAMING_SNAKE_CASE			(  UpperCAmelCase__				):

				"""simple docstring"""






				from transformers.testing_utils import pytest_terminal_summary_main

				_SCREAMING_SNAKE_CASE   =			terminalreporter.config.getoption('--make-reports'				)
				if make_reports:
								pytest_terminal_summary_main(UpperCAmelCase__ ,id=UpperCAmelCase__				)


def 					SCREAMING_SNAKE_CASE			(  UpperCAmelCase__ ,UpperCAmelCase__				):

				"""simple docstring"""






				if exitstatus == 5:
								_SCREAMING_SNAKE_CASE   =			0


# Doctest custom flag to ignore output.
snake_case      :   List[str]							= doctest.register_optionflag('IGNORE_RESULT')

snake_case      :   Any							= doctest.OutputChecker



class  __lowercase	(							lowercase__				):

							"""simple docstring"""


							def 		__magic_name__      (     self					,			A_					,			A_					,			A_						)->						int:
											if IGNORE_RESULT & optionflags:
															return True
											return OutputChecker.check_output(self					,			UpperCAmelCase__					,			UpperCAmelCase__					,			UpperCAmelCase__						)







snake_case      :   Union[str, Any]							= CustomOutputChecker
snake_case      :   List[Any]							= HfDoctestModule



snake_case      :   Optional[int]							= HfDocTestParser



'''simple docstring'''





import math

import flax.linen as nn
import jax.numpy as jnp






def 				_lowerCAmelCase			(   __magic_name__						:     jnp.ndarray   , __magic_name__						:     int   , __magic_name__						:     float = 1   , __magic_name__						:     float = 1   , __magic_name__						:     float = 1.0E4   , __magic_name__						:     bool = False   , __magic_name__						:     float = 1.0   , )				->  jnp.ndarray:
						assert timesteps.ndim == 1, "Timesteps should be a 1d-array"
						assert embedding_dim % 2 == 0, f'''Embedding dimension {embedding_dim} should be even'''
						lowercase :							int    		=float(embedding_dim // 2						)
						lowercase :							Optional[int]    		=math.log(max_timescale / min_timescale						) / (num_timescales - freq_shift)
						lowercase :							Any    		=min_timescale * jnp.exp(jnp.arange(__magic_name__   , dtype=jnp.floataa						) * -log_timescale_increment						)
						lowercase :							List[Any]    		=jnp.expand_dims(__magic_name__   , 1						) * jnp.expand_dims(__magic_name__   , 0						)

						# scale embeddings
						lowercase :							Tuple    		=scale * emb

						if flip_sin_to_cos:
												lowercase :							Dict    		=jnp.concatenate([jnp.cos(__magic_name__						), jnp.sin(__magic_name__						)]   , axis=1						)
						else:
												lowercase :							Any    		=jnp.concatenate([jnp.sin(__magic_name__						), jnp.cos(__magic_name__						)]   , axis=1						)
						lowercase :							List[str]    		=jnp.reshape(__magic_name__   , [jnp.shape(__magic_name__						)[0], embedding_dim]						)
						return signal





class 		__SCREAMING_SNAKE_CASE							(			nn.Module      ):
				lowerCamelCase_		       =    32
				lowerCamelCase_		       =    jnp.floataa







				@nn.compact
				def __call__(       self     :		Tuple		,					UpperCAmelCase__     :		int   ):
										'''simple docstring'''
										lowercase :							List[Any]    		=nn.Dense(self.time_embed_dim		,					dtype=self.dtype		,					name='''linear_1'''   )(UpperCAmelCase__   )
										lowercase :							Any    		=nn.silu(UpperCAmelCase__   )
										lowercase :							int    		=nn.Dense(self.time_embed_dim		,					dtype=self.dtype		,					name='''linear_2'''   )(UpperCAmelCase__   )
										return temb





class 		__SCREAMING_SNAKE_CASE							(			nn.Module      ):
				lowerCamelCase_		       =    32
				lowerCamelCase_		       =    False
				lowerCamelCase_		       =    1







				@nn.compact
				def __call__(       self     :		int		,					UpperCAmelCase__     :		str   ):
										'''simple docstring'''
										return get_sinusoidal_embeddings(
										    UpperCAmelCase__		,					embedding_dim=self.dim		,					flip_sin_to_cos=self.flip_sin_to_cos		,					freq_shift=self.freq_shift   )





