gx

chenyc

2025-02-12 ea42ff3ebee1eeb3fb29423aa848a249441db81c

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/**
 * @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 { ENGINE } from '../engine';
import { Equal } from '../kernel_names';
import { makeTypesMatch } from '../tensor_util';
import { convertToTensor } from '../tensor_util_env';
import { assertAndGetBroadcastShape } from './broadcast_util';
import { op } from './operation';
/**
 * Returns the truth value of (a == b) element-wise. Supports broadcasting.
 *
 * ```js
 * const a = tf.tensor1d([1, 2, 3]);
 * const b = tf.tensor1d([2, 2, 2]);
 *
 * a.equal(b).print();
 * ```
 *
 * @param a The first input tensor.
 * @param b The second input tensor. Must have the same dtype as `a`.
 *
 * @doc {heading: 'Operations', subheading: 'Logical'}
 */
function equal_(a, b) {
    let $a = convertToTensor(a, 'a', 'equal', 'string_or_numeric');
    let $b = convertToTensor(b, 'b', 'equal', 'string_or_numeric');
    [$a, $b] = makeTypesMatch($a, $b);
    assertAndGetBroadcastShape($a.shape, $b.shape);
    const inputs = { a: $a, b: $b };
    return ENGINE.runKernel(Equal, inputs);
}
export const equal = /* @__PURE__ */ op({ equal_ });
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