38 lines
948 B
Python
38 lines
948 B
Python
# %% Импорт библиотек
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import torch
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import torch.nn as nn
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# %% Входные переменные
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input_ = 32*32
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hidden_1 = 5
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hidden_2 = 12
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output = 2
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learning_rate = 1e-3
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weights_1 = torch.rand(size=(input_, hidden_1), requires_grad=True)
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weights_2 = torch.rand(size=(hidden_1, hidden_2), requires_grad=True)
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weights_3 = torch.rand(size=(hidden_2, output), requires_grad=True)
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random_input = torch.rand(1, input_)
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true_label = torch.zeros(1, output)
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true_label[0][0] = 1
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# %% Цикл обучения
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criterion = nn.CrossEntropyLoss()
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optimizer = torch.optim.SGD([weights_1, weights_2, weights_3], lr=learning_rate)
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hidden_layer_1 = random_input @ weights_1
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hidden_layer_2 = hidden_layer_1 @ weights_2
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output_layer = hidden_layer_2 @ weights_3
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loss = criterion(output_layer, true_label)
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print(loss)
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optimizer.zero_grad()
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loss.backward()
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optimizer.step()
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print(weights_1._grad)
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print(weights_2._grad)
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print(weights_3._grad)
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