@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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JavaScript
/**
* @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('where', ALL_ENVS, () => {
it('Scalars.', async () => {
const a = tf.scalar(10);
const b = tf.scalar(20);
const c = tf.scalar(1, 'bool');
expectArraysClose(await tf.where(c, a, b).data(), [10]);
});
it('Invalid condition type', () => {
const c = tf.tensor1d([1, 0, 1, 0], 'int32');
const a = tf.tensor1d([10, 10, 10, 10], 'bool');
const b = tf.tensor1d([20, 20, 20, 20], 'bool');
const f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
});
it('Tensor1D', async () => {
const c = tf.tensor1d([1, 0, 1, 0], 'bool');
const a = tf.tensor1d([10, 10, 10, 10]);
const b = tf.tensor1d([20, 20, 20, 20]);
expectArraysClose(await tf.where(c, a, b).data(), [10, 20, 10, 20]);
});
it('Tensor1D different a/b shapes', () => {
let c = tf.tensor1d([1, 0, 1, 0], 'bool');
let a = tf.tensor1d([10, 10, 10]);
let b = tf.tensor1d([20, 20, 20, 20]);
let f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
c = tf.tensor1d([1, 0, 1, 0], 'bool');
a = tf.tensor1d([10, 10, 10, 10]);
b = tf.tensor1d([20, 20, 20]);
f = () => {
tf.where(c, a, b);
};
});
it('Tensor1D different condition/a shapes', () => {
const c = tf.tensor1d([1, 0, 1, 0], 'bool');
const a = tf.tensor1d([10, 10, 10]);
const b = tf.tensor1d([20, 20, 20]);
const f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
});
it('Tensor2D', async () => {
const c = tf.tensor2d([[1, 0], [0, 1]], [2, 2], 'bool');
const a = tf.tensor2d([[10, 10], [10, 10]], [2, 2]);
const b = tf.tensor2d([[5, 5], [5, 5]], [2, 2]);
expectArraysClose(await tf.where(c, a, b).data(), [10, 5, 5, 10]);
});
it('Tensor2D different a/b shapes', () => {
let c = tf.tensor2d([[1, 1], [0, 0]], [2, 2], 'bool');
let a = tf.tensor2d([[5, 5, 5], [5, 5, 5]], [2, 3]);
let b = tf.tensor2d([[4, 4], [4, 4]], [2, 2]);
let f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
c = tf.tensor2d([[1, 1], [0, 0]], [2, 2], 'bool');
a = tf.tensor2d([[5, 5], [5, 5]], [2, 2]);
b = tf.tensor2d([[4, 4, 4], [4, 4, 4]], [2, 3]);
f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
});
it('Tensor2D different condition/a shapes', () => {
const c = tf.tensor2d([[1, 0], [0, 1]], [2, 2], 'bool');
const a = tf.tensor2d([[10, 10, 10], [10, 10, 10]], [2, 3]);
const b = tf.tensor2d([[5, 5, 5], [5, 5, 5]], [2, 3]);
const f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
});
it('Tensor2D different `a` dimension w/ condition rank=1', async () => {
const c = tf.tensor1d([1, 0, 1, 0], 'bool');
let a = tf.tensor2d([[10, 10], [10, 10]], [2, 2]);
let b = tf.tensor2d([[5, 5], [5, 5]], [2, 2]);
const f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
a = tf.tensor2d([[10], [10], [10], [10]], [4, 1]);
b = tf.tensor2d([[5], [5], [5], [5]], [4, 1]);
expectArraysClose(await tf.where(c, a, b).data(), [10, 5, 10, 5]);
a = tf.tensor2d([[10, 10], [10, 10], [10, 10], [10, 10]], [4, 2]);
b = tf.tensor2d([[5, 5], [5, 5], [5, 5], [5, 5]], [4, 2]);
expectArraysClose(await tf.where(c, a, b).data(), [10, 10, 5, 5, 10, 10, 5, 5]);
});
it('Tensor3D', async () => {
const c = tf.tensor3d([[[1], [0], [1]], [[0], [0], [0]]], [2, 3, 1], 'bool');
const a = tf.tensor3d([[[5], [5], [5]], [[5], [5], [5]]], [2, 3, 1]);
const b = tf.tensor3d([[[3], [3], [3]], [[3], [3], [3]]], [2, 3, 1]);
expectArraysClose(await tf.where(c, a, b).data(), [5, 3, 5, 3, 3, 3]);
});
it('Tensor3D with scalar condition', async () => {
const a = tf.ones([1, 3, 3]);
const b = tf.zeros([1, 3, 3]);
expectArraysClose(await tf.where(tf.ones([1], 'bool'), a, b).data(), [1, 1, 1, 1, 1, 1, 1, 1, 1]);
expectArraysClose(await tf.where(tf.zeros([1], 'bool'), a, b).data(), [0, 0, 0, 0, 0, 0, 0, 0, 0]);
});
it('1D condition with higher rank a and b', async () => {
const condition = tf.tensor1d([1, 0, 0, 1, 1], 'bool');
const a = tf.ones([5, 2, 2]);
const b = tf.fill([5, 2, 2], 3);
expectArraysClose(await tf.where(condition, a, b).data(), [1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1]);
});
it('Tensor3D different a/b shapes', () => {
const c = tf.tensor3d([[[1], [0], [1]], [[0], [0], [0]]], [2, 3, 1], 'bool');
let a = tf.tensor3d([[[5], [5]], [[5], [5]]], [2, 2, 1]);
let b = tf.tensor3d([[[3], [3], [3]], [[3], [3], [3]]], [2, 3, 1]);
let f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
a = tf.tensor3d([[[5], [5], [5]], [[5], [5], [5]]], [2, 3, 1]);
b = tf.tensor3d([[[3], [3]], [[3], [3]]], [2, 2, 1]);
f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
});
it('Tensor3D different condition/a shapes', () => {
const c = tf.tensor3d([[[1], [0]], [[0], [0]]], [2, 2, 1], 'bool');
const a = tf.tensor3d([[[5], [5], [5]], [[5], [5], [5]]], [2, 3, 1]);
const b = tf.tensor3d([[[3], [3], [3]], [[3], [3], [3]]], [2, 3, 1]);
const f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
});
it('Tensor3D different `a` dimension w/ condition rank=1', async () => {
const c = tf.tensor1d([1, 0, 1, 0], 'bool');
let a = tf.tensor3d([[[9, 9], [9, 9]], [[9, 9], [9, 9]]], [2, 2, 2]);
let b = tf.tensor3d([[[8, 8], [8, 8]], [[8, 8], [8, 8]]], [2, 2, 2]);
const f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
a = tf.tensor3d([[[9]], [[9]], [[9]], [[9]]], [4, 1, 1]);
b = tf.tensor3d([[[8]], [[8]], [[8]], [[8]]], [4, 1, 1]);
expectArraysClose(await tf.where(c, a, b).data(), [9, 8, 9, 8]);
a = tf.tensor3d([[[9], [9]], [[9], [9]], [[9], [9]], [[9], [9]]], [4, 2, 1]);
b = tf.tensor3d([[[8], [8]], [[8], [8]], [[8], [8]], [[8], [8]]], [4, 2, 1]);
expectArraysClose(await tf.where(c, a, b).data(), [9, 9, 8, 8, 9, 9, 8, 8]);
});
it('Tensor4D', async () => {
const c = tf.tensor4d([1, 0, 1, 1], [2, 2, 1, 1], 'bool');
const a = tf.tensor4d([7, 7, 7, 7], [2, 2, 1, 1]);
const b = tf.tensor4d([3, 3, 3, 3], [2, 2, 1, 1]);
expectArraysClose(await tf.where(c, a, b).data(), [7, 3, 7, 7]);
});
it('Tensor4D different a/b shapes', () => {
const c = tf.tensor4d([1, 0, 1, 1], [2, 2, 1, 1], 'bool');
let a = tf.tensor4d([7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7], [2, 3, 2, 1]);
let b = tf.tensor4d([3, 3, 3, 3], [2, 2, 1, 1]);
let f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
a = tf.tensor4d([7, 7, 7, 7], [2, 2, 1, 1]);
b = tf.tensor4d([3, 3, 3, 3, 3, 3, 3, 3], [2, 2, 2, 1]);
f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
});
it('Tensor4D broadcastable a/b shapes', () => {
const c = tf.tensor4d([1, 0, 1, 1], [2, 2, 1, 1], 'bool');
const a = tf.tensor4d([7, 7, 7, 7, 7, 7, 7, 7], [2, 2, 2, 1]);
const b = [3];
let f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
const a1 = [7];
const b1 = tf.tensor4d([3, 3, 3, 3, 3, 3, 3, 3], [2, 2, 2, 1]);
f = () => {
tf.where(c, a1, b1);
};
expect(f).toThrowError();
});
it('Tensor4D different condition/a shapes', () => {
const c = tf.tensor4d([1, 0, 1, 1, 1, 0, 1, 1], [2, 2, 2, 1], 'bool');
const a = tf.tensor4d([7, 7, 7, 7], [2, 2, 1, 1]);
const b = tf.tensor4d([3, 3, 3, 3], [2, 2, 1, 1]);
const f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
});
it('Tensor4D different `a` dimension w/ condition rank=1', async () => {
const c = tf.tensor1d([1, 0, 1, 0], 'bool');
let a = tf.tensor4d([7, 7, 7, 7, 7, 7, 7, 7], [2, 2, 2, 1]);
let b = tf.tensor4d([3, 3, 3, 3, 3, 3, 3, 3], [2, 2, 2, 1]);
const f = () => {
tf.where(c, a, b);
};
expect(f).toThrowError();
a = tf.tensor4d([7, 7, 7, 7], [4, 1, 1, 1]);
b = tf.tensor4d([3, 3, 3, 3], [4, 1, 1, 1]);
expectArraysClose(await tf.where(c, a, b).data(), [7, 3, 7, 3]);
a = tf.tensor4d([7, 7, 7, 7, 7, 7, 7, 7], [4, 2, 1, 1]);
b = tf.tensor4d([3, 3, 3, 3, 3, 3, 3, 3], [4, 2, 1, 1]);
expectArraysClose(await tf.where(c, a, b).data(), [7, 7, 3, 3, 7, 7, 3, 3]);
});
it('TensorLike', async () => {
expectArraysClose(await tf.where(true, 10, 20).data(), [10]);
});
it('TensorLike Chained', async () => {
const a = tf.scalar(10);
expectArraysClose(await a.where(true, 20).data(), [10]);
});
it('throws when passed condition as a non-tensor', () => {
expect(() => tf.where({}, tf.scalar(1, 'bool'), tf.scalar(1, 'bool')))
.toThrowError(/Argument 'condition' passed to 'where' must be a Tensor/);
});
it('throws when passed a as a non-tensor', () => {
expect(() => tf.where(tf.scalar(1, 'bool'), {}, tf.scalar(1, 'bool')))
.toThrowError(/Argument 'a' passed to 'where' must be a Tensor/);
});
it('throws when passed b as a non-tensor', () => {
expect(() => tf.where(tf.scalar(1, 'bool'), tf.scalar(1, 'bool'), {}))
.toThrowError(/Argument 'b' passed to 'where' must be a Tensor/);
});
it('accepts a tensor-like object', async () => {
const a = 10;
const b = 20;
const c = 1;
expectArraysClose(await tf.where(c, a, b).data(), [10]);
});
it('1D gradient', async () => {
const c = tf.tensor1d([1, 0, 1], 'bool');
const a = tf.tensor1d([1, 2, 3]);
const b = tf.tensor1d([4, 5, 6]);
const dy = tf.tensor1d([1, 2, 3]);
const grads = tf.grads((c, a, b) => tf.where(c, a, b));
const [dc, da, db] = grads([c, a, b], dy);
expectArraysClose(await dc.data(), [0, 0, 0]);
expectArraysClose(await da.data(), [1, 0, 3]);
expectArraysClose(await db.data(), [0, 2, 0]);
expect(dc.shape).toEqual(c.shape);
expect(da.shape).toEqual(a.shape);
expect(db.shape).toEqual(b.shape);
});
it('gradient with clones', async () => {
const c = tf.tensor1d([1, 0, 1], 'bool');
const a = tf.tensor1d([1, 2, 3]);
const b = tf.tensor1d([4, 5, 6]);
const dy = tf.tensor1d([1, 2, 3]);
const grads = tf.grads((c, a, b) => tf.where(c.clone(), a.clone(), b.clone()).clone());
const [dc, da, db] = grads([c, a, b], dy);
expectArraysClose(await dc.data(), [0, 0, 0]);
expectArraysClose(await da.data(), [1, 0, 3]);
expectArraysClose(await db.data(), [0, 2, 0]);
expect(dc.shape).toEqual(c.shape);
expect(da.shape).toEqual(a.shape);
expect(db.shape).toEqual(b.shape);
});
it('2D gradient', async () => {
const c = tf.tensor2d([1, 0, 1, 1, 1, 0], [2, 3], 'bool');
const a = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
const b = tf.tensor2d([7, 8, 9, 10, 11, 12], [2, 3]);
const dy = tf.tensor2d([1, 2, 3, 4, 5, 6], [2, 3]);
const grads = tf.grads((c, a, b) => tf.where(c, a, b));
const [dc, da, db] = grads([c, a, b], dy);
expectArraysClose(await dc.data(), [0, 0, 0, 0, 0, 0]);
expectArraysClose(await da.data(), [1, 0, 3, 4, 5, 0]);
expectArraysClose(await db.data(), [0, 2, 0, 0, 0, 6]);
expect(dc.shape).toEqual(c.shape);
expect(da.shape).toEqual(a.shape);
expect(db.shape).toEqual(b.shape);
});
it('3D gradient', async () => {
const c = tf.tensor3d([1, 1, 0, 1, 1, 0], [2, 3, 1], 'bool');
const a = tf.tensor3d([1, 2, 3, 4, 5, 6], [2, 3, 1]);
const b = tf.tensor3d([7, 8, 9, 10, 11, 12], [2, 3, 1]);
const dy = tf.tensor3d([1, 2, 3, 4, 5, 6], [2, 3, 1]);
const grads = tf.grads((c, a, b) => tf.where(c, a, b));
const [dc, da, db] = grads([c, a, b], dy);
expectArraysClose(await dc.data(), [0, 0, 0, 0, 0, 0]);
expectArraysClose(await da.data(), [1, 2, 0, 4, 5, 0]);
expectArraysClose(await db.data(), [0, 0, 3, 0, 0, 6]);
expect(dc.shape).toEqual(c.shape);
expect(da.shape).toEqual(a.shape);
expect(db.shape).toEqual(b.shape);
});
it('4D gradient', async () => {
const c = tf.tensor4d([1, 1, 0, 1], [2, 2, 1, 1], 'bool');
const a = tf.tensor4d([1, 2, 3, 4], [2, 2, 1, 1]);
const b = tf.tensor4d([5, 6, 7, 8], [2, 2, 1, 1]);
const dy = tf.tensor4d([1, 2, 3, 4], [2, 2, 1, 1]);
const grads = tf.grads((c, a, b) => tf.where(c, a, b));
const [dc, da, db] = grads([c, a, b], dy);
expectArraysClose(await dc.data(), [0, 0, 0, 0]);
expectArraysClose(await da.data(), [1, 2, 0, 4]);
expectArraysClose(await db.data(), [0, 0, 3, 0]);
expect(dc.shape).toEqual(c.shape);
expect(da.shape).toEqual(a.shape);
expect(db.shape).toEqual(b.shape);
});
});
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