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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 * as tf from '../index';
import { ALL_ENVS, describeWithFlags } from '../jasmine_util';
import { expectArraysClose } from '../test_util';
describeWithFlags('atanh', ALL_ENVS, () => {
    it('basic', async () => {
        const values = [-0.25, 0.25, 0.5, .75, -0.4];
        const a = tf.tensor1d(values);
        const result = tf.atanh(a);
        const expected = [];
        for (let i = 0; i < a.size; i++) {
            expected[i] = Math.atanh(values[i]);
        }
        expectArraysClose(await result.data(), expected);
    });
    it('scalar', async () => {
        const value = 0.2;
        const a = tf.scalar(value);
        const result = tf.atanh(a);
        const expected = [Math.atanh(value)];
        expectArraysClose(await result.data(), expected);
    });
    it('tensor2d', async () => {
        const values = [0.2, 0.3, 0.4, 0.5];
        const a = tf.tensor2d(values, [2, 2]);
        const result = tf.atanh(a);
        const expected = [];
        for (let i = 0; i < a.size; i++) {
            expected[i] = Math.atanh(values[i]);
        }
        expectArraysClose(await result.data(), expected);
    });
    it('propagates NaNs', async () => {
        const a = tf.tensor1d([0.5, NaN, 0]);
        const res = tf.atanh(a);
        expectArraysClose(await res.data(), [Math.atanh(0.5), NaN, Math.atanh(0)]);
    });
    it('NaN outside function domain', async () => {
        const a = tf.tensor1d([-2, 0, 2]);
        const res = tf.atanh(a);
        expectArraysClose(await res.data(), [NaN, Math.atanh(0), NaN]);
    });
    it('gradients: Scalar', async () => {
        const a = tf.scalar(0.5);
        const dy = tf.scalar(8);
        const gradients = tf.grad(a => tf.atanh(a))(a, dy);
        expect(gradients.shape).toEqual(a.shape);
        expect(gradients.dtype).toEqual('float32');
        expectArraysClose(await gradients.data(), [8 / (1 - 0.5 * 0.5)]);
    });
    it('gradient with clones', async () => {
        const a = tf.scalar(0.5);
        const dy = tf.scalar(8);
        const gradients = tf.grad(a => tf.atanh(a.clone()).clone())(a, dy);
        expect(gradients.shape).toEqual(a.shape);
        expect(gradients.dtype).toEqual('float32');
        expectArraysClose(await gradients.data(), [8 / (1 - 0.5 * 0.5)]);
    });
    it('gradients: Tensor1D', async () => {
        const aValues = [-0.1, 0.2, 0.3, -0.5];
        const dyValues = [1, 2, 3, 4];
        const a = tf.tensor1d(aValues);
        const dy = tf.tensor1d(dyValues);
        const gradients = tf.grad(a => tf.atanh(a))(a, dy);
        const expected = [];
        for (let i = 0; i < a.size; i++) {
            expected[i] = dyValues[i] / (1 - Math.pow(aValues[i], 2));
        }
        expect(gradients.shape).toEqual(a.shape);
        expect(gradients.dtype).toEqual('float32');
        expectArraysClose(await gradients.data(), expected);
    });
    it('gradients: Tensor2D', async () => {
        const aValues = [-0.3, 0.1, 0.2, 0.3];
        const dyValues = [1, 2, 3, 4];
        const a = tf.tensor2d(aValues, [2, 2]);
        const dy = tf.tensor2d(dyValues, [2, 2]);
        const gradients = tf.grad(a => tf.atanh(a))(a, dy);
        const expected = [];
        for (let i = 0; i < a.size; i++) {
            expected[i] = dyValues[i] / (1 - Math.pow(aValues[i], 2));
        }
        expect(gradients.shape).toEqual(a.shape);
        expect(gradients.dtype).toEqual('float32');
        expectArraysClose(await gradients.data(), expected);
    });
    it('throws when passed a non-tensor', () => {
        expect(() => tf.atanh({}))
            .toThrowError(/Argument 'x' passed to 'atanh' must be a Tensor/);
    });
    it('accepts a tensor-like object', async () => {
        const result = tf.atanh(0.2);
        expectArraysClose(await result.data(), [Math.atanh(0.2)]);
    });
    it('throws for string tensor', () => {
        expect(() => tf.atanh('q'))
            .toThrowError(/Argument 'x' passed to 'atanh' must be numeric/);
    });
});
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* @license\n * Copyright 2020 Google LLC. All Rights Reserved.\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n * http://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless required by applicable law or agreed to in writing, software\n * distributed under the License is distributed on an \"AS IS\" BASIS,\n * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n * See the License for the specific language governing permissions and\n * limitations under the License.\n * =============================================================================\n */\n\nimport * as tf from '../index';\nimport {ALL_ENVS, describeWithFlags} from '../jasmine_util';\nimport {expectArraysClose} from '../test_util';\n\ndescribeWithFlags('atanh', ALL_ENVS, () => {\n  it('basic', async () => {\n    const values = [-0.25, 0.25, 0.5, .75, -0.4];\n    const a = tf.tensor1d(values);\n    const result = tf.atanh(a);\n\n    const expected = [];\n    for (let i = 0; i < a.size; i++) {\n      expected[i] = Math.atanh(values[i]);\n    }\n    expectArraysClose(await result.data(), expected);\n  });\n\n  it('scalar', async () => {\n    const value = 0.2;\n    const a = tf.scalar(value);\n    const result = tf.atanh(a);\n\n    const expected = [Math.atanh(value)];\n    expectArraysClose(await result.data(), expected);\n  });\n\n  it('tensor2d', async () => {\n    const values = [0.2, 0.3, 0.4, 0.5];\n    const a = tf.tensor2d(values, [2, 2]);\n    const result = tf.atanh(a);\n\n    const expected = [];\n    for (let i = 0; i < a.size; i++) {\n      expected[i] = Math.atanh(values[i]);\n    }\n    expectArraysClose(await result.data(), expected);\n  });\n\n  it('propagates NaNs', async () => {\n    const a = tf.tensor1d([0.5, NaN, 0]);\n    const res = tf.atanh(a);\n    expectArraysClose(await res.data(), [Math.atanh(0.5), NaN, Math.atanh(0)]);\n  });\n\n  it('NaN outside function domain', async () => {\n    const a = tf.tensor1d([-2, 0, 2]);\n    const res = tf.atanh(a);\n    expectArraysClose(await res.data(), [NaN, Math.atanh(0), NaN]);\n  });\n\n  it('gradients: Scalar', async () => {\n    const a = tf.scalar(0.5);\n    const dy = tf.scalar(8);\n\n    const gradients = tf.grad(a => tf.atanh(a))(a, dy);\n\n    expect(gradients.shape).toEqual(a.shape);\n    expect(gradients.dtype).toEqual('float32');\n    expectArraysClose(await gradients.data(), [8 / (1 - 0.5 * 0.5)]);\n  });\n\n  it('gradient with clones', async () => {\n    const a = tf.scalar(0.5);\n    const dy = tf.scalar(8);\n\n    const gradients = tf.grad(a => tf.atanh(a.clone()).clone())(a, dy);\n\n    expect(gradients.shape).toEqual(a.shape);\n    expect(gradients.dtype).toEqual('float32');\n    expectArraysClose(await gradients.data(), [8 / (1 - 0.5 * 0.5)]);\n  });\n\n  it('gradients: Tensor1D', async () => {\n    const aValues = [-0.1, 0.2, 0.3, -0.5];\n    const dyValues = [1, 2, 3, 4];\n    const a = tf.tensor1d(aValues);\n    const dy = tf.tensor1d(dyValues);\n\n    const gradients = tf.grad(a => tf.atanh(a))(a, dy);\n\n    const expected = [];\n    for (let i = 0; i < a.size; i++) {\n      expected[i] = dyValues[i] / (1 - Math.pow(aValues[i], 2));\n    }\n\n    expect(gradients.shape).toEqual(a.shape);\n    expect(gradients.dtype).toEqual('float32');\n    expectArraysClose(await gradients.data(), expected);\n  });\n\n  it('gradients: Tensor2D', async () => {\n    const aValues = [-0.3, 0.1, 0.2, 0.3];\n    const dyValues = [1, 2, 3, 4];\n    const a = tf.tensor2d(aValues, [2, 2]);\n    const dy = tf.tensor2d(dyValues, [2, 2]);\n\n    const gradients = tf.grad(a => tf.atanh(a))(a, dy);\n\n    const expected = [];\n    for (let i = 0; i < a.size; i++) {\n      expected[i] = dyValues[i] / (1 - Math.pow(aValues[i], 2));\n    }\n\n    expect(gradients.shape).toEqual(a.shape);\n    expect(gradients.dtype).toEqual('float32');\n    expectArraysClose(await gradients.data(), expected);\n  });\n\n  it('throws when passed a non-tensor', () => {\n    expect(() => tf.atanh({} as tf.Tensor))\n        .toThrowError(/Argument 'x' passed to 'atanh' must be a Tensor/);\n  });\n\n  it('accepts a tensor-like object', async () => {\n    const result = tf.atanh(0.2);\n    expectArraysClose(await result.data(), [Math.atanh(0.2)]);\n  });\n\n  it('throws for string tensor', () => {\n    expect(() => tf.atanh('q'))\n        .toThrowError(/Argument 'x' passed to 'atanh' must be numeric/);\n  });\n});\n"]}