/**

* @license

* Copyright 2020 Google Inc. 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 {TensorBuffer} from '../tensor';

import {DataType, DataTypeMap, Rank, ShapeMap} from '../types';

import * as util from '../util';

/**

* Creates an empty `tf.TensorBuffer` with the specified `shape` and `dtype`.

*

* The values are stored in CPU as `TypedArray`. Fill the buffer using

* `buffer.set()`, or by modifying directly `buffer.values`.

*

* When done, call `buffer.toTensor()` to get an immutable `tf.Tensor` with

* those values.

*

* ```js

* // Create a buffer and set values at particular indices.

* const buffer = tf.buffer([2, 2]);

* buffer.set(3, 0, 0);

* buffer.set(5, 1, 0);

*

* // Convert the buffer back to a tensor.

* buffer.toTensor().print();

* ```

*

* @param shape An array of integers defining the output tensor shape.

* @param dtype The dtype of the buffer. Defaults to 'float32'.

* @param values The values of the buffer as `TypedArray`. Defaults to

* zeros.

*

* @doc {heading: 'Tensors', subheading: 'Creation'}

*/

export function buffer<R extends Rank, D extends DataType = 'float32'>(

}