@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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TypeScript
/**
* @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 };