/**

* @license

* Copyright 2020 Google LLC. All Rights Reserved.

* Licensed under the Apache License, Version 2.0 (the "License");

* you may not use this file except in compliance with the License.

* You may obtain a copy of the License at

*

* http://www.apache.org/licenses/LICENSE-2.0

*

* Unless required by applicable law or agreed to in writing, software

* distributed under the License is distributed on an "AS IS" BASIS,

* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

* See the License for the specific language governing permissions and

* limitations under the License.

* =============================================================================

*/

import {ENGINE} from '../engine';

import {SplitV, SplitVAttrs, SplitVInputs} from '../kernel_names';

import {NamedAttrMap} from '../kernel_registry';

import {Tensor} from '../tensor';

import {NamedTensorMap} from '../tensor_types';

import {convertToTensor} from '../tensor_util_env';

import {TensorLike} from '../types';

import {op} from './operation';

/**

* Splits a `tf.Tensor` into sub tensors.

*

* If `numOrSizeSplits` is a number, splits `x` along dimension `axis`

* into `numOrSizeSplits` smaller tensors.

* Requires that `numOrSizeSplits` evenly divides `x.shape[axis]`.

*

* If `numOrSizeSplits` is a number array, splits `x` into

* `numOrSizeSplits.length` pieces. The shape of the `i`-th piece has the

* same size as `x` except along dimension `axis` where the size is

* `numOrSizeSplits[i]`.

*

* ```js

* const x = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8], [2, 4]);

* const [a, b] = tf.split(x, 2, 1);

* a.print();

* b.print();

*

* const [c, d, e] = tf.split(x, [1, 2, 1], 1);

* c.print();

* d.print();

* e.print();

* ```

*

* @param x The input tensor to split.

* @param numOrSizeSplits Either an integer indicating the number of

* splits along the axis or an array of integers containing the sizes of

* each output tensor along the axis. If a number then it must evenly divide

* `x.shape[axis]`; otherwise the sum of sizes must match `x.shape[axis]`.

* Can contain one -1 indicating that dimension is to be inferred.

* @param axis The dimension along which to split. Defaults to 0 (the first

* dim).

*

* @doc {heading: 'Tensors', subheading: 'Slicing and Joining'}

*/

function split_<T extends Tensor>(

}

export const split = /* @__PURE__ */ op({split_});