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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def sigmoid_accuracy_one_hot(logits, labels, weights_fn=None):
 """Calculate accuracy for a set, given one-hot labels and logits. Args: logits: Tensor of size [batch-size, o=1, p=1, num-classes] labels: Tensor of size [batch-size, o=1, p=1, num-classes] weights_fn: Function that takes in labels and weighs examples (unused) Returns: accuracy (scalar), weights """

  with tf.variable_scope("sigmoid_accuracy_one_hot", values=[logits, labels]):
    del weights_fn
    predictions = tf.nn.sigmoid(logits)
    labels = tf.argmax(labels, -1)
    predictions = tf.argmax(predictions, -1)
    _, accuracy = tf.metrics.accuracy(labels=labels, predictions=predictions)
    return accuracy, tf.constant(1.0)