def forward(self, inputs): for layer in self.layers: inputs = layer.forward(inputs) return inputs
时间: 2024-05-19 17:16:16 浏览: 155
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As an AI language model, I cannot provide the full context of the code snippet. However, I can explain what the code does.
This code defines a `forward` method in a neural network class. The method takes `inputs` as an argument, which is a tensor or a multidimensional array that represents the input data to the neural network.
The method iterates over each layer in the neural network and calls the `forward` method of each layer with the `inputs` as its argument. The `forward` method of each layer computes the output of that layer based on its internal parameters and the input data. The computed output is then passed as input to the next layer until the output of the last layer is computed.
Finally, the method returns the output of the last layer, which is the final output of the neural network.
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