Function train_step

tests/performance_test/vgg/tl2-static-eager.py:40–50

(x_batch, y_batch)

# training function
def train_step(x_batch, y_batch):
    # forward + backward
    with tf.GradientTape() as tape:
        ## compute outputs
        _logits = vgg(x_batch)
        ## compute loss and update model
        _loss = loss_object(_logits, y_batch)

    grad = tape.gradient(_loss, train_weights)
    optimizer.apply_gradients(zip(grad, train_weights))
    return _loss


# begin training