/**
 * @license
 * Copyright 2019 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 { Tensor } from '../tensor';
import { TensorLike } from '../types';
import { Activation } from './fused_util';
/**
 * Computes the dot product of two matrices with optional activation and bias.
 *
 * ```js
 * const a = tf.tensor2d([-1, -2], [1, 2]);
 * const b = tf.tensor2d([1, 2, 3, 4], [2, 2]);
 * const bias = tf.tensor2d([1, 2], [1, 2]);
 *
 * tf.fused.matMul(a, b, false, false, bias, 'relu').print();
 * ```
 *
 * @param a First matrix in dot product operation.
 * @param b Second matrix in dot product operation.
 * @param transposeA If true, `a` is transposed before multiplication.
 * @param transposeB If true, `b` is transposed before multiplication.
 * @param bias Matrix to be added to the result.
 * @param activation Name of activation kernel (defaults to `linear`).
 */
/** @doc {heading: 'Operations', subheading: 'Matrices', namespace: 'fused'} */
declare function matMul_<T extends Tensor>(a: T | TensorLike, b: T | TensorLike, transposeA?: boolean, transposeB?: boolean, bias?: Tensor | TensorLike, activation?: Activation): T;
export declare const matMul: typeof matMul_;
export { Activation };