gx优化

chenyc

2025-05-29 92f69c57b920cf62ecc9f15f9ed196fa26dbf2ac

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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 { makeOnesTypedArray, sizeFromShape } from '../util';
import { assertNonNegativeIntegerDimensions } from '../util_base';
import { complex } from './complex';
import { zeros } from './zeros';
/**
 * Creates a `tf.Tensor` with all elements set to 1.
 *
 * ```js
 * tf.ones([2, 2]).print();
 * ```
 *
 * @param shape An array of integers defining the output tensor shape.
 * @param dtype The type of an element in the resulting tensor. Defaults to
 *     'float'.
 *
 * @doc {heading: 'Tensors', subheading: 'Creation'}
 */
export function ones(shape, dtype = 'float32') {
    assertNonNegativeIntegerDimensions(shape);
    if (dtype === 'complex64') {
        const real = ones(shape, 'float32');
        const imag = zeros(shape, 'float32');
        return complex(real, imag);
    }
    const values = makeOnesTypedArray(sizeFromShape(shape), dtype);
    return ENGINE.makeTensor(values, shape, dtype);
}
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