



"""simple docstring"""


import pytest

import datasets


# Import fixture modules as plugins
snake_case_    					=	["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]

def 			_lowerCAmelCase				(       lowercase_		,     lowercase_						):
						# Mark tests as "unit" by default if not marked as "integration" (or already marked as "unit")
						for item in items:
												if any(marker in item.keywords for marker in ['integration', 'unit']						):
																		continue
												item.add_marker(pytest.mark.unit						)

def 			_lowerCAmelCase				(       lowercase_						):
						config.addinivalue_line('markers'		,     'torchaudio_latest: mark test to run with torchaudio>=0.12'						)

@pytest.fixture(autouse=lowercase_						)
def 			_lowerCAmelCase				(       lowercase_		,     lowercase_						):
						# test_hf_cache_home = tmp_path_factory.mktemp("cache")  # TODO: why a cache dir per test function does not work?
						UpperCAmelCase					=			tmp_path_factory.getbasetemp() / 'cache'
						UpperCAmelCase					=			test_hf_cache_home / 'datasets'
						UpperCAmelCase					=			test_hf_cache_home / 'metrics'
						UpperCAmelCase					=			test_hf_cache_home / 'modules'
						monkeypatch.setattr('datasets.config.HF_DATASETS_CACHE'		,     str(lowercase_						)						)
						monkeypatch.setattr('datasets.config.HF_METRICS_CACHE'		,     str(lowercase_						)						)
						monkeypatch.setattr('datasets.config.HF_MODULES_CACHE'		,     str(lowercase_						)						)
						UpperCAmelCase					=			test_hf_datasets_cache / 'downloads'
						monkeypatch.setattr('datasets.config.DOWNLOADED_DATASETS_PATH'		,     str(lowercase_						)						)
						UpperCAmelCase					=			test_hf_datasets_cache / 'downloads' / 'extracted'
						monkeypatch.setattr('datasets.config.EXTRACTED_DATASETS_PATH'		,     str(lowercase_						)						)

@pytest.fixture(autouse=lowercase_		,     scope='session'						)
def 			_lowerCAmelCase				(       ):
						datasets.disable_progress_bar()

@pytest.fixture(autouse=lowercase_						)
def 			_lowerCAmelCase				(       lowercase_						):
						# don't take tests into account when counting downloads
						monkeypatch.setattr('datasets.config.HF_UPDATE_DOWNLOAD_COUNTS'		,     lowercase_						)






@pytest.fixture
def 			_lowerCAmelCase				(       lowercase_						):
						# Required to suppress RemovedIn20Warning when feature(s) are not compatible with SQLAlchemy 2.0
						# To be removed once SQLAlchemy 2.0 supported
						monkeypatch.setattr('sqlalchemy.util.deprecations.SILENCE_UBER_WARNING'		,     lowercase_						)










"""simple docstring"""


import math

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

def 			_lowerCAmelCase				(       lowercase_		,     lowercase_		,     lowercase_ = 1		,     lowercase_ = 1		,     lowercase_ = 1.0e4		,     lowercase_ = False		,     lowercase_ = 1.0		,     ):
						assert timesteps.ndim == 1, "Timesteps should be a 1d-array"
						assert embedding_dim % 2 == 0, F"""Embedding dimension {embedding_dim} should be even"""
						UpperCAmelCase					=			float(embedding_dim // 2						)
						UpperCAmelCase					=			math.log(max_timescale / min_timescale						) / (num_timescales - freq_shift)
						UpperCAmelCase					=			min_timescale * jnp.exp(jnp.arange(lowercase_		,     dtype=jnp.floataa						) * -log_timescale_increment						)
						UpperCAmelCase					=			jnp.expand_dims(lowercase_		,     1						) * jnp.expand_dims(lowercase_		,     0						)

						# scale embeddings
						UpperCAmelCase					=			scale * emb

						if flip_sin_to_cos:
												UpperCAmelCase					=			jnp.concatenate([jnp.cos(lowercase_						), jnp.sin(lowercase_						)]		,     axis=1						)
						else:
												UpperCAmelCase					=			jnp.concatenate([jnp.sin(lowercase_						), jnp.cos(lowercase_						)]		,     axis=1						)
						UpperCAmelCase					=			jnp.reshape(lowercase_		,     [jnp.shape(lowercase_						)[0], embedding_dim]						)
						return signal







class 				A_      (					nn.Module    ):



						"""simple docstring"""
						__UpperCamelCase		    =							32
						__UpperCamelCase		    =							jnp.floataa






						@nn.compact
						def __call__( self			:Union[str, Any]       ,  lowercase_			:Tuple )    ->      str:
												UpperCAmelCase					=			nn.Dense(self.time_embed_dim       ,  dtype=self.dtype       ,  name='linear_1' )(lowercase_ )
												UpperCAmelCase					=			nn.silu(lowercase_ )
												UpperCAmelCase					=			nn.Dense(self.time_embed_dim       ,  dtype=self.dtype       ,  name='linear_2' )(lowercase_ )
												return temb







class 				A_      (					nn.Module    ):



						"""simple docstring"""
						__UpperCamelCase		    =							32
						__UpperCamelCase		    =							False
						__UpperCamelCase		    =							1






						@nn.compact
						def __call__( self			:Any       ,  lowercase_			:int )    ->      Union[str, Any]:
												return get_sinusoidal_embeddings(
												    lowercase_       ,  embedding_dim=self.dim       ,  flip_sin_to_cos=self.flip_sin_to_cos       ,  freq_shift=self.freq_shift )





