





'''simple docstring'''







from unittest.mock import Mock, patch

from file_transfer.send_file import send_file






@patch("socket.socket"						)
@patch("builtins.open"						)
def  _lowerCamelCase				( lowercase						:      int    ,							lowercase						:      List[str]						)	->	int:
				_a								= Mock()
				_a								= conn, Mock()
				_a								= iter([1, None]						)
				_a								= lambda lowercase						: next(_A						)

				# ===== invoke =====
				send_file(filename="mytext.txt"    ,							testing=_A						)

				# ===== ensurance =====
				sock.assert_called_once()
				sock.return_value.bind.assert_called_once()
				sock.return_value.listen.assert_called_once()
				sock.return_value.accept.assert_called_once()
				conn.recv.assert_called_once()

				file.return_value.__enter__.assert_called_once()
				file.return_value.__enter__.return_value.read.assert_called()

				conn.send.assert_called_once()
				conn.close.assert_called_once()
				sock.return_value.shutdown.assert_called_once()
				sock.return_value.close.assert_called_once()

'''simple docstring'''




import math

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






def 				snake_case__							(			_A:					jnp.ndarray      ,   _A:					int      ,   _A:					float = 1      ,   _A:					float = 1      ,   _A:					float = 1.0e4      ,   _A:					bool = False      ,   _A:					float = 1.0      ,   )    ->	jnp.ndarray:

		'''simple docstring'''


		assert timesteps.ndim == 1, "Timesteps should be a 1d-array"
		assert embedding_dim % 2 == 0, f"Embedding dimension {embedding_dim} should be even"
		lowerCAmelCase   					=  float(embedding_dim // 2 )
		lowerCAmelCase   					=  math.log(max_timescale / min_timescale ) / (num_timescales - freq_shift)
		lowerCAmelCase   					=  min_timescale * jnp.exp(jnp.arange(_A      ,   dtype=jnp.floataa ) * -log_timescale_increment )
		lowerCAmelCase   					=  jnp.expand_dims(_A      ,   1 ) * jnp.expand_dims(_A      ,   0 )

		# scale embeddings
		lowerCAmelCase   					=  scale * emb

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






class 				a__(					nn.Module	):


			'''simple docstring'''






			UpperCAmelCase_			:     int      =       3_2
			UpperCAmelCase_			:     jnp.dtype      =       jnp.floataa



			@nn.compact
			def __call__(   self       ,    __lowerCAmelCase):




					"""simple docstring"""


					lowerCAmelCase   					=  nn.Dense(self.time_embed_dim       ,    dtype=self.dtype       ,    name="""linear_1""")(__lowerCAmelCase)
					lowerCAmelCase   					=  nn.silu(__lowerCAmelCase)
					lowerCAmelCase   					=  nn.Dense(self.time_embed_dim       ,    dtype=self.dtype       ,    name="""linear_2""")(__lowerCAmelCase)
					return temb







class 				a__(					nn.Module	):


			'''simple docstring'''






			UpperCAmelCase_			:     int      =       3_2
			UpperCAmelCase_			:     bool      =       False
			UpperCAmelCase_			:     float      =       1



			@nn.compact
			def __call__(   self       ,    __lowerCAmelCase):




					"""simple docstring"""


					return get_sinusoidal_embeddings(
					    __lowerCAmelCase       ,    embedding_dim=self.dim       ,    flip_sin_to_cos=self.flip_sin_to_cos       ,    freq_shift=self.freq_shift)




