def split(split_dim, num_split, value, name="split"): """Splits a tensor into `num_split` tensors along one dimension. Splits `value` along dimension `split_dim` into `num_split` smaller tensors. Requires that `num_split` evenly divide `value.shape[split_dim]`. For example: ```python # 'value' is a tensor with shape [5, 30] # Split 'value' into 3 tensors along dimension 1 split0, split1, split2 = tf.split(1, 3, value) tf.shape(split0) ==> [5, 10] ``` Args: split_dim: A 0-D `int32` `Tensor`. The dimension along which to split. Must be in the range `[0, rank(value))`. num_split: A Python integer. The number of ways to split. value: The `Tensor` to split. name: A name for the operation (optional). Returns: `num_split` `Tensor` objects resulting from splitting `value`. """ return gen_array_ops._split(split_dim=split_dim, num_split=num_split, value=value, name=name)