| 1 | /**
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| 2 | * @license
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| 3 | * Copyright 2020 Google LLC. All Rights Reserved.
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| 4 | * Licensed under the Apache License, Version 2.0 (the "License");
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| 5 | * you may not use this file except in compliance with the License.
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| 6 | * You may obtain a copy of the License at
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| 7 | *
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| 8 | * http://www.apache.org/licenses/LICENSE-2.0
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| 9 | *
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| 10 | * Unless required by applicable law or agreed to in writing, software
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| 11 | * distributed under the License is distributed on an "AS IS" BASIS,
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| 12 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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| 13 | * See the License for the specific language governing permissions and
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| 14 | * limitations under the License.
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| 15 | * =============================================================================
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| 16 | */
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| 17 | import { convertToTensor } from '../tensor_util_env';
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| 18 | import * as util from '../util';
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| 19 | import { matMul } from './mat_mul';
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| 20 | import { op } from './operation';
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| 21 | import { reshape } from './reshape';
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| 22 | /**
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| 23 | * Computes the dot product of two matrices and/or vectors, `t1` and `t2`.
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| 24 | *
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| 25 | * ```js
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| 26 | * const a = tf.tensor1d([1, 2]);
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| 27 | * const b = tf.tensor2d([[1, 2], [3, 4]]);
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| 28 | * const c = tf.tensor2d([[1, 2, 3], [4, 5, 6]]);
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| 29 | *
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| 30 | * a.dot(b).print(); // or tf.dot(a, b)
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| 31 | * b.dot(a).print();
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| 32 | * b.dot(c).print();
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| 33 | * ```
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| 34 | * @param t1 The first tensor in the dot operation.
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| 35 | * @param t2 The second tensor in the dot operation.
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| 36 | *
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| 37 | * @doc {heading: 'Operations', subheading: 'Matrices'}
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| 38 | */
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| 39 | function dot_(t1, t2) {
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| 40 | const $t1 = convertToTensor(t1, 't1', 'dot');
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| 41 | const $t2 = convertToTensor(t2, 't2', 'dot');
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| 42 | util.assert(($t1.rank === 1 || $t1.rank === 2) && ($t2.rank === 1 || $t2.rank === 2), () => `Error in dot: inputs must all be rank 1 or 2, but got ranks ` +
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| 43 | `${$t1.rank} and ${$t2.rank}.`);
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| 44 | const t1Inner = ($t1.rank === 1 ? $t1.size : $t1.shape[1]);
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| 45 | const t2Inner = ($t2.rank === 1 ? $t2.size : $t2.shape[0]);
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| 46 | util.assert(t1Inner === t2Inner, () => `Error in dot: inner dimensions of inputs must match, but got ` +
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| 47 | `${t1Inner} and ${t2Inner}.`);
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| 48 | if ($t1.rank === 1 && $t2.rank === 1) {
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| 49 | const t12D = reshape($t1, [1, -1]);
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| 50 | const t22D = reshape($t2, [-1, 1]);
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| 51 | const t1t2 = matMul(t12D, t22D);
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| 52 | return reshape(t1t2, []);
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| 53 | }
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| 54 | else if ($t1.rank === 1 && $t2.rank === 2) {
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| 55 | const t12D = reshape($t1, [1, -1]);
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| 56 | const t22D = reshape($t2, [$t2.shape[0], $t2.shape[1]]);
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| 57 | const t1t2 = matMul(t12D, t22D);
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| 58 | return reshape(t1t2, [t1t2.size]);
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| 59 | }
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| 60 | else if ($t1.rank === 2 && $t2.rank === 1) {
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| 61 | const t22D = reshape($t2, [-1, 1]);
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| 62 | const t1t2 = matMul($t1, t22D);
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| 63 | return reshape(t1t2, [t1t2.size]);
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| 64 | }
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| 65 | else {
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| 66 | const t22D = reshape($t2, [$t2.shape[0], $t2.shape[1]]);
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| 67 | const t1t2 = matMul($t1, t22D);
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| 68 | return t1t2;
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| 69 | }
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| 70 | }
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| 71 | export const dot = op({ dot_ });
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| 72 | //# 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