/**
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* @license
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* Copyright 2020 Google Inc. All Rights Reserved.
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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* =============================================================================
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*/
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/// <amd-module name="@tensorflow/tfjs-core/dist/ops/buffer" />
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import { TensorBuffer } from '../tensor';
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import { DataType, DataTypeMap, Rank, ShapeMap } from '../types';
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/**
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* Creates an empty `tf.TensorBuffer` with the specified `shape` and `dtype`.
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*
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* The values are stored in CPU as `TypedArray`. Fill the buffer using
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* `buffer.set()`, or by modifying directly `buffer.values`.
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*
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* When done, call `buffer.toTensor()` to get an immutable `tf.Tensor` with
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* those values.
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*
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* ```js
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* // Create a buffer and set values at particular indices.
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* const buffer = tf.buffer([2, 2]);
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* buffer.set(3, 0, 0);
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* buffer.set(5, 1, 0);
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*
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* // Convert the buffer back to a tensor.
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* buffer.toTensor().print();
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* ```
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*
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* @param shape An array of integers defining the output tensor shape.
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* @param dtype The dtype of the buffer. Defaults to 'float32'.
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* @param values The values of the buffer as `TypedArray`. Defaults to
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* zeros.
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*
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* @doc {heading: 'Tensors', subheading: 'Creation'}
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*/
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export declare function buffer<R extends Rank, D extends DataType = 'float32'>(shape: ShapeMap[R], dtype?: D, values?: DataTypeMap[D]): TensorBuffer<R, D>;
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