@tensorflow/tfjs-core
Version:
Hardware-accelerated JavaScript library for machine intelligence
325 lines • 74.4 kB
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';
import { identityPoolTest } from './identity_pool_test';
describeWithFlags('maxPool', ALL_ENVS, () => {
it('x=[1,1,1] f=[1,1] s=1 [0] => [0]', async () => {
const x = tf.tensor3d([123], [1, 1, 1]);
const result = tf.maxPool(x, 1, 1, 0);
expectArraysClose(await result.data(), [123]);
});
it('x=[3,3,1] f=[2,2] s=1, p=0', async () => {
// Feed forward.
const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 9, 8], [3, 3, 1]);
const result = tf.maxPool(x, 2, 1, 0);
expect(result.shape).toEqual([2, 2, 1]);
expectArraysClose(await result.data(), [5, 6, 9, 9]);
});
it('x=[3,3,1] f=[2,2] s=1 p=same', async () => {
const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 9, 8], [3, 3, 1]);
const result = tf.maxPool(x, 2, 1, 'same');
const resultData = await result.data();
tf.test_util.expectArraysClose(resultData, new Float32Array([5, 6, 6, 9, 9, 8, 9, 9, 8]));
});
it('x=[3,3,1] f=[3,3] s=1 p=explicit', async () => {
const x = tf.tensor3d([0, 1, 2, 3, 4, 5, 6, 7, 8], [3, 3, 1]);
const padding = [[0, 0], [1, 2], [0, 1], [0, 0]];
const result = tf.maxPool(x, 3, 1, padding);
expect(result.shape).toEqual([4, 2, 1]);
expectArraysClose(await result.data(), [5, 5, 8, 8, 8, 8, 8, 8]);
});
it('x=[2,3,3,1] f=[2,2] s=1', async () => {
// Feed forward.
const x = tf.tensor4d([1, 2, 3, 4, 5, 6, 7, 9, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 3, 1]);
const result = tf.maxPool(x, 2, 1, 0);
expect(result.shape).toEqual([2, 2, 2, 1]);
expectArraysClose(await result.data(), [5, 6, 9, 9, 5, 6, 8, 9]);
});
it('[x=[3,3,1] f=[2,2] s=1 ignores NaNs', async () => {
const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, NaN, 9], [3, 3, 1]);
const result = tf.maxPool(x, 2, 1, 0);
expect(result.shape).toEqual([2, 2, 1]);
expectArraysClose(await result.data(), [5, 6, 7, 9]);
});
it('x=[3,3,2] f=[2,2] s=1', async () => {
// Feed forward.
const x = tf.tensor3d([1, 99, 2, 88, 3, 77, 4, 66, 5, 55, 6, 44, 7, 33, 9, 22, 8, 11], [3, 3, 2]);
const result = tf.maxPool(x, 2, 1, 0);
expect(result.shape).toEqual([2, 2, 2]);
expectArraysClose(await result.data(), [5, 99, 6, 88, 9, 66, 9, 55]);
});
it('x=[4,4,1] f=[2,2] s=2', async () => {
// Feed forward.
const x = tf.tensor3d([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], [4, 4, 1]);
const result = tf.maxPool(x, 2, 2, 0);
expect(result.shape).toEqual([2, 2, 1]);
expectArraysClose(await result.data(), [5, 7, 13, 15]);
});
it('x=[2,2,1] f=[2,2] s=1 p=same', async () => {
// Feed forward.
const x = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const fSize = 2;
const strides = 1;
const result = tf.maxPool(x, fSize, strides, 'same');
expect(result.shape).toEqual([2, 2, 1]);
expectArraysClose(await result.data(), [4, 4, 4, 4]);
});
it('x=[2,2,3] f=[2,2] s=3 p=1 default dimRoundingMode', () => {
// Feed forward.
const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], [2, 2, 3]);
const result = tf.maxPool(x, 2, 3, 1);
expect(result.shape).toEqual([1, 1, 3]);
});
it('x=[2,2,3] f=[1,1] s=2 p=1 dimRoundingMode=floor', () => {
// Feed forward.
const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], [2, 2, 3]);
const result = tf.maxPool(x, 1, 2, 1, 'floor');
expect(result.shape).toEqual([2, 2, 3]);
});
it('x=[2,2,3] f=[2,2] s=3 p=1 dimRoundingMode=floor', () => {
// Feed forward.
const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], [2, 2, 3]);
const result = tf.maxPool(x, 2, 3, 1, 'floor');
expect(result.shape).toEqual([1, 1, 3]);
});
it('x=[2,2,3] f=[2,2] s=3 p=1 dimRoundingMode=round', () => {
// Feed forward.
const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], [2, 2, 3]);
const result = tf.maxPool(x, 2, 3, 1, 'round');
expect(result.shape).toEqual([2, 2, 3]);
});
it('x=[2,2,3] f=[2,2] s=3 p=1 dimRoundingMode=ceil', () => {
// Feed forward.
const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], [2, 2, 3]);
const result = tf.maxPool(x, 2, 3, 1, 'ceil');
expect(result.shape).toEqual([2, 2, 3]);
});
it('throws when x is not rank 3', () => {
// tslint:disable-next-line:no-any
const x = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8, 9], [3, 3]);
expect(() => tf.maxPool(x, 2, 1, 0)).toThrowError();
});
it('throws when dimRoundingMode is set and pad is same', () => {
const x = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const pad = 'same';
const dimRoundingMode = 'round';
expect(() => tf.maxPool(x, 2, 1, pad, dimRoundingMode)).toThrowError();
});
it('throws when dimRoundingMode is set and pad is valid', () => {
const x = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const pad = 'valid';
const dimRoundingMode = 'round';
expect(() => tf.maxPool(x, 2, 1, pad, dimRoundingMode)).toThrowError();
});
it('throws when dimRoundingMode is set and pad is a non-integer number', () => {
const x = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const pad = 1.2;
const dimRoundingMode = 'round';
expect(() => tf.maxPool(x, 2, 1, pad, dimRoundingMode)).toThrowError();
});
it('throws when dimRoundingMode is set and pad is explicit by non-integer ' +
'number', () => {
const x = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const pad = [[0, 0], [0, 2.1], [1, 1], [0, 0]];
const dimRoundingMode = 'round';
expect(() => tf.maxPool(x, 2, 1, pad, dimRoundingMode)).toThrowError();
});
it('throws when passed a non-tensor', () => {
expect(() => tf.maxPool({}, 2, 1, 'valid'))
.toThrowError(/Argument 'x' passed to 'maxPool' must be a Tensor/);
});
it('accepts a tensor-like object', async () => {
const x = [[[0]]]; // 1x1x1
const result = tf.maxPool(x, 1, 1, 0);
expectArraysClose(await result.data(), [0]);
});
identityPoolTest(tf.maxPool);
});
describeWithFlags('maxPoolBackprop', ALL_ENVS, () => {
it('gradients x=[3,3,1] f=[2,2] s=1 no dup max value, test #1', async () => {
const dy = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8, 9], [3, 3, 1]);
const expected = [0, 0, 0, 0, 1, 2, 0, 3, 4];
const dx = tf.grad((x) => x.maxPool(2, 1, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradient with clones x=[3,3,1] f=[2,2] s=1', async () => {
const dy = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const x = tf.tensor3d([1, 2, 3, 4, 5, 6, 7, 8, 9], [3, 3, 1]);
const expected = [0, 0, 0, 0, 1, 2, 0, 3, 4];
const dx = tf.grad((x) => tf.maxPool(x.clone(), 2, 1, 0).clone())(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradients x=[3,3,1] f=[2,2] s=1 no dup max value, test #2', async () => {
const dy = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const x = tf.tensor3d([9, 5, 6, 6, 8, 4, 9, 5, 10], [3, 3, 1]);
const expected = [1, 0, 0, 0, 2, 0, 3, 0, 4];
const dx = tf.grad((x) => x.maxPool(2, 1, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradients x=[2,3,3,1] f=[2,2] s=1 no duplicate max value', async () => {
// This test batches the [3,3,1] tests.
const dy = tf.tensor4d([1, 2, 3, 4, 1, 2, 3, 4], [2, 2, 2, 1]);
const x = tf.tensor4d([1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 5, 6, 6, 8, 4, 9, 5, 10], [2, 3, 3, 1]);
const expected = [0, 0, 0, 0, 1, 2, 0, 3, 4, 1, 0, 0, 0, 2, 0, 3, 0, 4];
const dx = tf.grad((x) => x.maxPool(2, 1, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradient x=[3,3,1] f=[2,2] s=1 dup max value, test 1', async () => {
const dy = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const x = tf.tensor3d([0, 0, 0, 0, 5, 0, 0, 0, 0], [3, 3, 1]);
const expected = [0, 0, 0, 0, 10, 0, 0, 0, 0];
const dx = tf.grad((x) => x.maxPool(2, 1, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradient x=[3,3,1] f=[2,2] s=1 dup max value, test 2', async () => {
const dy = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const x = tf.tensor3d([1, 3, 2, 1, 2, 1, 1, 1, 5], [3, 3, 1]);
const expected = [0, 3, 0, 0, 3, 0, 0, 0, 4];
const dx = tf.grad((x) => x.maxPool(2, 1, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradient x=[2,3,3,1] f=[2,2] s=1 dup max value in 2nd input', async () => {
const dy = tf.tensor4d([1, 2, 3, 4, 5, 6, 7, 8], [2, 2, 2, 1]);
const x = tf.tensor4d([1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 9, 8], [2, 3, 3, 1]);
const expected = new Float32Array([0, 0, 0, 0, 1, 2, 0, 3, 4, 0, 0, 0, 0, 5, 6, 0, 15, 0]);
const dx = tf.grad((x) => x.maxPool(2, 1, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradient x=[4,4,1] f=[2,2] s=2 test #1', async () => {
const dy = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const x = tf.tensor3d([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], [4, 4, 1]);
const expected = [0, 0, 0, 0, 0, 1, 0, 2, 0, 0, 0, 0, 0, 3, 0, 4];
const dx = tf.grad((x) => x.maxPool(2, 2, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradient x=[4,4,1] f=[2,2] s=2 test #2', async () => {
const dy = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const x = tf.tensor3d([1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1], [4, 4, 1]);
const expected = [0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0];
const dx = tf.grad((x) => x.maxPool(2, 2, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradient x=[5,5,1] f=[3,3] s=2 no duplicate max value', async () => {
const dy = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const x = tf.tensor3d([
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24
], [5, 5, 1]);
const expected = [
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 0, 4
];
const dx = tf.grad((x) => x.maxPool(3, 2, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradient x=[5,5,1] f=[3,3] s=2 duplicate max value', async () => {
const dy = tf.tensor3d([1, 2, 3, 4], [2, 2, 1]);
const x = tf.tensor3d([
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 24,
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 12
], [5, 5, 1]);
const expected = [
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
];
const dx = tf.grad((x) => x.maxPool(3, 2, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
// Max pool backprop depth > 1.
it('gradient x=[3,3,2] f=[2,2] s=1, no duplicate max value', async () => {
// This test combines the first two 3x3x1 tests with no duplicates to
// make depth=2,
// dy is slightly modified to show the difference.
const dy = tf.tensor3d([1, 44, 2, 33, 3, 22, 4, 11], [2, 2, 2]);
const x = tf.tensor3d([1, 99, 2, 55, 3, 66, 4, 66, 5, 88, 6, 44, 7, 99, 8, 55, 9, 100], [3, 3, 2]);
const expected = [0, 44, 0, 0, 0, 0, 0, 0, 1, 33, 2, 0, 0, 22, 3, 0, 4, 11];
const dx = tf.grad((x) => x.maxPool(2, 1, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradient x=[3,3,2] f=[2,2] s=1 duplicate max value', async () => {
// This test combines the first two 3x3x1 tests with duplicates to
// make depth=2,
// dy is slightly modified to show the difference.
const dy = tf.tensor3d([1, 44, 2, 33, 3, 22, 4, 11], [2, 2, 2]);
const x = tf.tensor3d([0, 1, 0, 3, 0, 2, 0, 1, 5, 2, 0, 1, 0, 1, 0, 1, 0, 5], [3, 3, 2]);
const expected = new Float32Array([0, 0, 0, 77, 0, 0, 0, 0, 10, 22, 0, 0, 0, 0, 0, 0, 0, 11]);
const dx = tf.grad((x) => x.maxPool(2, 1, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradient x=[4,4,2] f=[2,2] s=1', async () => {
// This test combines the first two 4x4x1 tests with duplicates to make
// depth=2,
// dy is slightly modified to show the difference.
const dy = tf.tensor3d([1, 11, 2, 22, 3, 33, 4, 44], [2, 2, 2]);
const x = tf.tensor3d([
0, 1, 1, 2, 2, 2, 3, 1, 4, 1, 5, 1, 6, 1, 7, 1,
8, 1, 9, 1, 10, 1, 11, 1, 12, 1, 13, 2, 14, 2, 15, 1
], [4, 4, 2]);
const expected = [
0, 0, 0, 11, 0, 22, 0, 0, 0, 0, 1, 0, 0, 0, 2, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 33, 0, 44, 4, 0
];
const dx = tf.grad((x) => x.maxPool(2, 2, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradient x=[3,3,1] f=3 s=1 p=explicit', async () => {
const dy = tf.tensor3d([1, 11, 2, 22, 3, 33, 4, 44], [4, 2, 1]);
const x = tf.tensor3d([0, 1, 2, 3, 4, 5, 6, 7, 8], [3, 3, 1]);
const padding = [[0, 0], [1, 2], [0, 1], [0, 0]];
const expected = [0, 0, 0, 0, 0, 12, 0, 0, 108];
const dx = tf.grad((x) => x.maxPool(3, 1, padding))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
it('gradient x=5x5x2, f=3, s=2 no duplicate max value', async () => {
// This test combines the first two 5x5x1 tests with duplicates to make
// depth=2,
// dy is slightly modified to show the difference.
const dy = tf.tensor3d([1, 11, 2, 22, 3, 33, 4, 44], [2, 2, 2]);
const x = tf.tensor3d([
0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8,
8, 9, 9, 10, 10, 11, 11, 12, 24, 13, 13, 14, 14, 15, 15, 16, 16,
17, 17, 18, 18, 19, 19, 20, 20, 21, 21, 22, 22, 23, 23, 24, 12
], [5, 5, 2]);
const expected = [
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 110, 0, 0, 2, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 4, 0
];
const dx = tf.grad((x) => x.maxPool(3, 2, 0))(x, dy);
expect(dx.shape).toEqual(x.shape);
expectArraysClose(await dx.data(), expected);
});
});
//# sourceMappingURL=data:application/json;base64,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