
'''simple docstring'''
import math

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






def      UpperCamelCase_				(      A__  ,      A__  ,      A__ = 1  ,      A__ = 1  ,      A__ = 1.0e4  ,      A__ = False  ,      A__ = 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'''
	a_      				=						float(embedding_dim // 2						)
	a_      				=						math.log(max_timescale / min_timescale						) / (num_timescales - freq_shift)
	a_      				=						min_timescale * jnp.exp(jnp.arange(A__  ,      dtype=jnp.floataa						) * -log_timescale_increment						)
	a_      				=						jnp.expand_dims(A__  ,      1						) * jnp.expand_dims(A__  ,      0						)

	# scale embeddings
	a_      				=						scale * emb

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







class   a_ (      nn.Module					):
			lowerCamelCase__	:			int       =    32
			lowerCamelCase__	:			jnp.dtype       =    jnp.floataa




			@nn.compact
			def __call__(       self					,   UpperCAmelCase	):
				a_      				=						nn.Dense(self.time_embed_dim					,   dtype=self.dtype					,   name="""linear_1"""	)(UpperCAmelCase	)
				a_      				=						nn.silu(UpperCAmelCase	)
				a_      				=						nn.Dense(self.time_embed_dim					,   dtype=self.dtype					,   name="""linear_2"""	)(UpperCAmelCase	)
				return temb







class   a_ (      nn.Module					):
			lowerCamelCase__	:			int       =    32
			lowerCamelCase__	:			bool       =    False
			lowerCamelCase__	:			float       =    1




			@nn.compact
			def __call__(       self					,   UpperCAmelCase	):
				return get_sinusoidal_embeddings(
				    UpperCAmelCase					,   embedding_dim=self.dim					,   flip_sin_to_cos=self.flip_sin_to_cos					,   freq_shift=self.freq_shift	)


'''simple docstring'''
def      UpperCamelCase_				(      A__  ,      A__  ,      A__						):
	if len(A__						) != len(A__						):
		raise ValueError("""The length of profit and weight must be same."""						)
	if max_weight <= 0:
		raise ValueError("""max_weight must greater than zero."""						)
	if any(p < 0 for p in profit						):
		raise ValueError("""Profit can not be negative."""						)
	if any(w < 0 for w in weight						):
		raise ValueError("""Weight can not be negative."""						)

	# List created to store profit gained for the 1kg in case of each weight
	# respectively.  Calculate and append profit/weight for each element.
	a_      				=						[p / w for p, w in zip(A__  ,      A__						)]

	# Creating a copy of the list and sorting profit/weight in ascending order
	a_      				=						sorted(A__						)

	# declaring useful variables
	a_      				=						len(A__						)
	a_      				=						0
	a_      				=						0
	a_      				=						0

	# loop till the total weight do not reach max limit e.g. 15 kg and till i<length
	while limit <= max_weight and i < length:
		# flag value for encountered greatest element in sorted_profit_by_weight
		a_      				=						sorted_profit_by_weight[length - i - 1]
		a_      				=						profit_by_weight.index(A__						)
		a_      				=						-1

		# check if the weight encountered is less than the total weight
		# encountered before.
		if max_weight - limit >= weight[index]:
			limit += weight[index]
			# Adding profit gained for the given weight 1 ===
			# weight[index]/weight[index]
			gain += 1 * profit[index]
		else:
			# Since the weight encountered is greater than limit, therefore take the
			# required number of remaining kgs and calculate profit for it.
			# weight remaining / weight[index]
			gain += (max_weight - limit) / weight[index] * profit[index]
			break
		i += 1
	return gain


if __name__ == "__main__":
		print(
		    'Input profits, weights, and then max_weight (all positive ints) separated by '
		    'spaces.'
		)

		lowercase__											=[int(x) for x in input('Input profits separated by spaces: ').split()]
		lowercase__											=[int(x) for x in input('Input weights separated by spaces: ').split()]
		lowercase__											=int(input('Max weight allowed: '))

		# Function Call
		calc_profit(profit, weight, max_weight)
