4e2d8cd89163c0fd4b4e14e4f3d13b58d7e3b29f,examples/nas/naive-tf/train.py,,accuracy,#Any#Any#,56

Before Change

    bs = target.shape[0]
    predicted = tf.cast(tf.argmax(output, 1), target.dtype)
    target = tf.reshape(target, [-1])
    return sum(tf.cast(predicted == target, tf.float32)) / bs


if __name__ == "__main__":
    cifar10 = tf.keras.datasets.cifar10

After Change

def accuracy(truth, logits):
    truth = tf.reshape(truth, -1)
    predicted = tf.cast(tf.math.argmax(logits, axis=1), truth.dtype)
    equal = tf.cast(predicted == truth, tf.int32)
    return tf.math.reduce_sum(equal).numpy() / equal.shape[0]

def accuracy_metrics(truth, logits):
    acc = accuracy(truth, logits)
    return {"accuracy": acc}

Instances