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 { Elu } from '../kernel_names';
import { convertToTensor } from '../tensor_util_env';
import { op } from './operation';
/**
 * Computes exponential linear element-wise: `x > 0 ? x : (e ^ x) - 1`.
 *
 * ```js
 * const x = tf.tensor1d([-1, 1, -3, 2]);
 *
 * x.elu().print();  // or tf.elu(x)
 * ```
 * @param x The input tensor.
 *
 * @doc {heading: 'Operations', subheading: 'Basic math'}
 */
function elu_(x) {
    const $x = convertToTensor(x, 'x', 'elu', 'float32');
    const inputs = { x: $x };
    return ENGINE.runKernel(Elu, inputs);
}
export const elu = /* @__PURE__ */ op({ elu_ });
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