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如下所示:
def softmax(logits, axis=None, name=None, dim=None): """Computes softmax activations. This function performs the equivalent of softmax = tf.exp(logits) / tf.reduce_sum(tf.exp(logits), axis) Args: logits: A non-empty `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. axis: The dimension softmax would be performed on. The default is -1 which indicates the last dimension. name: A name for the operation (optional). dim: Deprecated alias for `axis`. Returns: A `Tensor`. Has the same type and shape as `logits`. Raises: InvalidArgumentError: if `logits` is empty or `axis` is beyond the last dimension of `logits`. """ axis = deprecation.deprecated_argument_lookup("axis", axis, "dim", dim) if axis is None: axis = -1 return _softmax(logits, gen_nn_ops.softmax, axis, name)