@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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JavaScript
/**
* @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 { convertToTensor } from '../tensor_util_env';
import * as util from '../util';
import { matMul } from './mat_mul';
import { op } from './operation';
import { reshape } from './reshape';
/**
* Computes the dot product of two matrices and/or vectors, `t1` and `t2`.
*
* ```js
* const a = tf.tensor1d([1, 2]);
* const b = tf.tensor2d([[1, 2], [3, 4]]);
* const c = tf.tensor2d([[1, 2, 3], [4, 5, 6]]);
*
* a.dot(b).print(); // or tf.dot(a, b)
* b.dot(a).print();
* b.dot(c).print();
* ```
* @param t1 The first tensor in the dot operation.
* @param t2 The second tensor in the dot operation.
*
* @doc {heading: 'Operations', subheading: 'Matrices'}
*/
function dot_(t1, t2) {
const $t1 = convertToTensor(t1, 't1', 'dot');
const $t2 = convertToTensor(t2, 't2', 'dot');
util.assert(($t1.rank === 1 || $t1.rank === 2) && ($t2.rank === 1 || $t2.rank === 2), () => `Error in dot: inputs must all be rank 1 or 2, but got ranks ` +
`${$t1.rank} and ${$t2.rank}.`);
const t1Inner = ($t1.rank === 1 ? $t1.size : $t1.shape[1]);
const t2Inner = ($t2.rank === 1 ? $t2.size : $t2.shape[0]);
util.assert(t1Inner === t2Inner, () => `Error in dot: inner dimensions of inputs must match, but got ` +
`${t1Inner} and ${t2Inner}.`);
if ($t1.rank === 1 && $t2.rank === 1) {
const t12D = reshape($t1, [1, -1]);
const t22D = reshape($t2, [-1, 1]);
const t1t2 = matMul(t12D, t22D);
return reshape(t1t2, []);
}
else if ($t1.rank === 1 && $t2.rank === 2) {
const t12D = reshape($t1, [1, -1]);
const t22D = reshape($t2, [$t2.shape[0], $t2.shape[1]]);
const t1t2 = matMul(t12D, t22D);
return reshape(t1t2, [t1t2.size]);
}
else if ($t1.rank === 2 && $t2.rank === 1) {
const t22D = reshape($t2, [-1, 1]);
const t1t2 = matMul($t1, t22D);
return reshape(t1t2, [t1t2.size]);
}
else {
const t22D = reshape($t2, [$t2.shape[0], $t2.shape[1]]);
const t1t2 = matMul($t1, t22D);
return t1t2;
}
}
export const dot = op({ dot_ });
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