gx

chenyc

2025-02-12 ea42ff3ebee1eeb3fb29423aa848a249441db81c

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/**
 * @license
 * Copyright 2018 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 { ENGINE } from '../engine';
import { tidy } from '../globals';
import { Transpose } from '../kernel_names';
import { convertToTensor } from '../tensor_util_env';
import * as util from '../util';
import { complex } from './complex';
import { imag } from './imag';
import { neg } from './neg';
import { op } from './operation';
import { real } from './real';
/**
 * Transposes the `tf.Tensor`. Permutes the dimensions according to `perm`.
 *
 * The returned `tf.Tensor`'s dimension `i` will correspond to the input
 * dimension `perm[i]`. If `perm` is not given, it is set to `[n-1...0]`,
 * where `n` is the rank of the input `tf.Tensor`. Hence by default, this
 * operation performs a regular matrix transpose on 2-D input `tf.Tensor`s.
 *
 * ```js
 * const a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
 *
 * a.transpose().print();  // or tf.transpose(a)
 * ```
 *
 * @param x The tensor to transpose.
 * @param perm The permutation of the dimensions of a.
 * @param conjugate Will conjugate complex input if true.
 *
 * @doc {heading: 'Operations', subheading: 'Matrices'}
 */
function transpose_(x, perm, conjugate) {
    const $x = convertToTensor(x, 'x', 'transpose');
    if (perm == null) {
        perm = $x.shape.map((s, i) => i).reverse();
    }
    util.assert($x.rank === perm.length, () => `Error in transpose: rank of input ${$x.rank} ` +
        `must match length of perm ${perm}.`);
    perm.forEach(axis => {
        util.assert(axis >= 0 && axis < $x.rank, () => `All entries in 'perm' must be between 0 and ${$x.rank - 1}` +
            ` but got ${perm}`);
    });
    if ($x.rank <= 1) {
        return $x.clone();
    }
    const inputs = { x: $x };
    const attrs = { perm };
    if ($x.dtype === 'complex64') {
        return tidy(() => {
            let $real = real($x);
            let $imag = imag($x);
            $real = ENGINE.runKernel(Transpose, { x: $real }, attrs);
            $imag = ENGINE.runKernel(Transpose, { x: $imag }, attrs);
            if (conjugate) {
                $imag = neg($imag);
            }
            return complex($real, $imag);
        });
    }
    return ENGINE.runKernel(Transpose, inputs, attrs);
}
export const transpose = /* @__PURE__ */ op({ transpose_ });
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