Matteo Rapa matteorapa

## cuda.ipynb

      
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                matteorapa
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              August 24, 2024 22:02
            
              
                cuda.ipynb
              
          
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## genetic.py
def generate_initial_population(num_population):
    # [learning_rate, hidden_size, number_of_layers, fitness]
    learning_rate = np.empty([num_population, 1], dtype=np.float32)
    hidden_size = np.empty([num_population, 1], dtype=np.int32)
    number_of_layers = np.empty([num_population, 1], dtype=np.int32)
    fitness = np.zeros([num_population, 1], dtype=np.float32)

    for i in range(num_population):

        learning_rate[i] = round(random.uniform(0.001, 0.1), 3)

## first.txt
My first gist on github.
	def generate_initial_population(num_population):
	# [learning_rate, hidden_size, number_of_layers, fitness]
	learning_rate = np.empty([num_population, 1], dtype=np.float32)
	hidden_size = np.empty([num_population, 1], dtype=np.int32)
	number_of_layers = np.empty([num_population, 1], dtype=np.int32)
	fitness = np.zeros([num_population, 1], dtype=np.float32)

	for i in range(num_population):

	learning_rate[i] = round(random.uniform(0.001, 0.1), 3)