What does the following line of code do?optimizer.step()1 pointMakes an update to its parametersMakes a prediction Clears the gradient Computes the gradient of the loss with respect to all the learnable parameters
Question
What does the following line of code do?optimizer.step()1 pointMakes an update to its parametersMakes a prediction Clears the gradient Computes the gradient of the loss with respect to all the learnable parameters
Solution
The line of code optimizer.step() makes an update to its parameters. This is typically used in the context of training a machine learning model, where the optimizer is used to adjust the attributes of the model (such as weights and learning rate) in order to reduce errors (i.e., to make the model's predictions as close as possible to the actual values).
Similar Questions
What does the following line of code do :loss.backward()1 pointupdate parameterscompute gradient of the loss with respect to all the learnable parameterszero the gradients before running the backward pass
What does the following line of code do :w.grad.data.zero_()1 pointcalculate the iterationupdate parameterszero the gradients before running the backward pass
Gradient Descent is an optimization algorithm used for ______
In Gradient Descent, refers to the magnitude of updates to the parameters, and refers to the direction of updates.
1 pointWhat is the purpose of the gradient descent algorithm in machine learning? To minimize the loss function To maximize the loss function To minimize the output function To maximize the output function
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