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fengwuyaofengwuyao
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Add bitwiseAnd() ops (#7645)
* Test commit * Support ensureShape in tfjs * Applied changes * Updates doc * Updates doc * Updates doc * Add an example * add dif length and null shape tests * fix the lint error * Update executor tests * Update the header * Implement bitwiseAnd() ops and add kernel in Webcpu backEnd * Fix format * Change to only support int32 type
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16 files changed

+195
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‎.vscode/settings.json

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@@ -18,7 +18,8 @@
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"editor.tabSize": 2,
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"editor.insertSpaces": true,
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"[typescript]": {
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"editor.formatOnSave": true
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"editor.formatOnSave": true,
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"editor.defaultFormatter": "xaver.clang-format"
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},
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"[javascript]": {
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"editor.formatOnSave": true

‎tfjs-backend-cpu/src/kernels/BitwiseAnd.ts

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@@ -0,0 +1,32 @@
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/**
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* @license
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* Copyright 2023 Google LLC.
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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* =============================================================================
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*/
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import {BitwiseAnd, KernelConfig} from '@tensorflow/tfjs-core';
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import {createSimpleBinaryKernelImpl} from '../utils/binary_impl';
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import {binaryKernelFunc} from '../utils/binary_utils';
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export const bitwiseAndImpl =
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createSimpleBinaryKernelImpl(((a: number, b: number) => a & b));
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export const bitwiseAnd = binaryKernelFunc(BitwiseAnd, bitwiseAndImpl);
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export const bitwiseAndConfig: KernelConfig = {
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kernelName: BitwiseAnd,
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backendName: 'cpu',
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kernelFunc: bitwiseAnd
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};

‎tfjs-backend-cpu/src/register_all_kernels.ts

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@@ -42,6 +42,7 @@ import {batchMatMulConfig} from './kernels/BatchMatMul';
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import {batchNormConfig} from './kernels/BatchNorm';
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import {batchToSpaceNDConfig} from './kernels/BatchToSpaceND';
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import {bincountConfig} from './kernels/Bincount';
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import {bitwiseAndConfig} from './kernels/BitwiseAnd';
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import {broadcastArgsConfig} from './kernels/BroadcastArgs';
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import {castConfig} from './kernels/Cast';
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import {ceilConfig} from './kernels/Ceil';
@@ -215,6 +216,7 @@ const kernelConfigs: KernelConfig[] = [
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batchNormConfig,
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batchToSpaceNDConfig,
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bincountConfig,
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bitwiseAndConfig,
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broadcastArgsConfig,
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castConfig,
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ceilConfig,

‎tfjs-backend-cpu/src/shared.ts

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@@ -19,6 +19,7 @@
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export {simpleAbsImpl} from './kernels/Abs';
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export {addImpl} from './kernels/Add';
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export {bincountImpl, bincountReduceImpl} from './kernels/Bincount_impl';
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export {bitwiseAndImpl} from './kernels/BitwiseAnd';
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export {castImpl} from './kernels/Cast';
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export {ceilImpl} from './kernels/Ceil';
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export {concatImpl} from './kernels/Concat_impl';

‎tfjs-backend-wasm/src/setup_test.ts

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@@ -290,6 +290,12 @@ const TEST_FILTERS: TestFilter[] = [
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{startsWith: 'logicalNot '},
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{startsWith: 'logicalOr '},
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{startsWith: 'logicalXor '},
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{
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startsWith: 'bitwiseAnd',
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excludes: [
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'bitwiseAnd',
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]
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},
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{
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startsWith: 'tile ',
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excludes: [

‎tfjs-backend-webgl/src/setup_test.ts

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@@ -22,10 +22,12 @@ import './index';
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import '@tensorflow/tfjs-core/dist/public/chained_ops/register_all_chained_ops';
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// tslint:disable-next-line: no-imports-from-dist
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import '@tensorflow/tfjs-core/dist/register_all_gradients';
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import {registerTestEnvs} from './backend_webgl_test_registry';
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// tslint:disable-next-line: no-imports-from-dist
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import {parseTestEnvFromKarmaFlags, setTestEnvs, setupTestFilters, TEST_ENVS, TestFilter} from '@tensorflow/tfjs-core/dist/jasmine_util';
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import {registerTestEnvs} from './backend_webgl_test_registry';
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registerTestEnvs();
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const TEST_FILTERS: TestFilter[] = [];
@@ -34,7 +36,7 @@ const customInclude = (testName: string) => {
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'isBrowser: false', 'dilation gradient',
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'throws when index is out of bound',
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// otsu tests for threshold op is failing on windows
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'method otsu'
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'method otsu', 'bitwiseAnd'
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];
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for (const subStr of toExclude) {
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if (testName.includes(subStr)) {

‎tfjs-backend-webgpu/src/setup_test.ts

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@@ -146,6 +146,12 @@ const TEST_FILTERS: TestFilter[] = [
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'calling .data() twice works',
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],
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},
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{
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startsWith: 'bitwiseAnd',
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excludes: [
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'bitwiseAnd',
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],
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},
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// exclude unsupported kernels and to be fixed cases
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{

‎tfjs-converter/docs/supported_ops.md

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@@ -201,6 +201,7 @@
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|Tensorflow Op Name|Tensorflow.js Op Name|
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|---|---|
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|BitwiseAnd|bitwiseAnd|
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|Equal|equal|
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|Greater|greater|
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|GreaterEqual|greaterEqual|

‎tfjs-converter/python/tensorflowjs/op_list/logical.json

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@@ -267,5 +267,21 @@
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"notSupported": true
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}
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]
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},
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{
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"tfOpName": "BitwiseAnd",
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"category": "logical",
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"inputs": [
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{
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"start": 0,
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"name": "x",
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"type": "tensor"
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},
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{
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"start": 1,
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"name": "y",
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"type": "tensor"
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}
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]
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}
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]
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]

‎tfjs-converter/src/operations/executors/logical_executor.ts

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@@ -26,8 +26,8 @@ import {InternalOpExecutor, Node} from '../types';
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import {getParamValue} from './utils';
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2828
export const executeOp: InternalOpExecutor =
29-
(node: Node, tensorMap: NamedTensorsMap,
30-
context: ExecutionContext, ops = tfOps): Tensor[] => {
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(node: Node, tensorMap: NamedTensorsMap, context: ExecutionContext,
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ops = tfOps): Tensor[] => {
3131
switch (node.op) {
3232
case 'Equal': {
3333
return [ops.equal(
@@ -80,6 +80,11 @@ export const executeOp: InternalOpExecutor =
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getParamValue('a', node, tensorMap, context) as Tensor,
8181
getParamValue('b', node, tensorMap, context) as Tensor)];
8282
}
83+
case 'BitwiseAnd': {
84+
return [ops.bitwiseAnd(
85+
getParamValue('a', node, tensorMap, context) as Tensor,
86+
getParamValue('b', node, tensorMap, context) as Tensor)];
87+
}
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default:
8489
throw TypeError(`Node type ${node.op} is not implemented`);
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}

‎tfjs-converter/src/operations/executors/logical_executor_test.ts

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@@ -54,7 +54,7 @@ describe('logical', () => {
5454

5555
([
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'Equal', 'NotEqual', 'Greater', 'GreaterEqual', 'Less', 'LessEqual',
57-
'LogicalAnd', 'LogicalOr'
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'LogicalAnd', 'LogicalOr', 'BitwiseAnd'
5858
] as const )
5959
.forEach(op => {
6060
it('should call tfOps.' + op, () => {

‎tfjs-core/src/kernel_names.ts

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@@ -138,6 +138,9 @@ export interface BincountAttrs {
138138
size: number;
139139
}
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141+
export const BitwiseAnd = 'BitwiseAnd';
142+
export type BitwiseAndInputs = BinaryInputs;
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141144
export const BroadcastTo = 'BroadcastTo';
142145
export type BroadcastToInputs = Pick<NamedTensorInfoMap, 'x'>;
143146
export interface BroadCastToAttrs {

‎tfjs-core/src/ops/bitwise_and.ts

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@@ -0,0 +1,65 @@
1+
/**
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* @license
3+
* Copyright 2023 Google LLC.
4+
* Licensed under the Apache License, Version 2.0 (the "License");
5+
* you may not use this file except in compliance with the License.
6+
* You may obtain a copy of the License at
7+
*
8+
* http://www.apache.org/licenses/LICENSE-2.0
9+
*
10+
* Unless required by applicable law or agreed to in writing, software
11+
* distributed under the License is distributed on an "AS IS" BASIS,
12+
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13+
* See the License for the specific language governing permissions and
14+
* limitations under the License.
15+
* =============================================================================
16+
*/
17+
18+
import {ENGINE} from '../engine';
19+
import {BitwiseAnd, BitwiseAndInputs} from '../kernel_names';
20+
import {Tensor} from '../tensor';
21+
import {NamedTensorMap} from '../tensor_types';
22+
import {convertToTensor} from '../tensor_util_env';
23+
import {Rank} from '../types';
24+
import {arraysEqual} from '../util_base';
25+
26+
import {op} from './operation';
27+
28+
/**
29+
* Bitwise `AND` operation for input tensors.
30+
*
31+
* Given two input tensors, returns a new tensor
32+
* with the `AND` calculated values.
33+
*
34+
* The method supports int32 values
35+
*
36+
*
37+
* ```js
38+
* const x = tf.tensor1d([0, 5, 3, 14], 'int32');
39+
* const y = tf.tensor1d([5, 0, 7, 11], 'int32');
40+
* tf.bitwiseAnd(x, y).print();
41+
* ```
42+
*
43+
* @param x The input tensor to be calculated.
44+
* @param y The input tensor to be calculated.
45+
*
46+
* @doc {heading: 'Operations', subheading: 'Logical'}
47+
*/
48+
function bitwiseAnd_<R extends Rank>(x: Tensor, y: Tensor): Tensor<R> {
49+
const $x = convertToTensor(x, 'x', 'bitwiseAnd');
50+
const $y = convertToTensor(y, 'y', 'bitwiseAnd');
51+
52+
if (!arraysEqual($x.shape, $y.shape)) {
53+
throw new Error(`BitwiseAnd: Tensors must have the same shape. x: ${
54+
$x.shape}, y: ${$y.shape}`);
55+
}
56+
if ($x.dtype !== 'int32' || $y.dtype !== 'int32') {
57+
throw new Error(
58+
`BitwiseAnd: Only supports 'int32' values in tensor, found type of x: ${
59+
$x.dtype} and type of y: ${$y.dtype}`);
60+
}
61+
62+
const inputs: BitwiseAndInputs = {a: $x, b: $y};
63+
return ENGINE.runKernel(BitwiseAnd, inputs as unknown as NamedTensorMap);
64+
}
65+
export const bitwiseAnd = /* @__PURE__ */ op({bitwiseAnd_});

‎tfjs-core/src/ops/bitwise_and_test.ts

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@@ -0,0 +1,46 @@
1+
/**
2+
* @license
3+
* Copyright 2023 Google LLC.
4+
* Licensed under the Apache License, Version 2.0 (the "License");
5+
* you may not use this file except in compliance with the License.
6+
* You may obtain a copy of the License at
7+
*
8+
* http://www.apache.org/licenses/LICENSE-2.0
9+
*
10+
* Unless required by applicable law or agreed to in writing, software
11+
* distributed under the License is distributed on an "AS IS" BASIS,
12+
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13+
* See the License for the specific language governing permissions and
14+
* limitations under the License.
15+
* =============================================================================
16+
*/
17+
import * as tf from '../index';
18+
import {ALL_ENVS, describeWithFlags} from '../jasmine_util';
19+
import {expectArraysClose} from '../test_util';
20+
import {bitwiseAnd} from './bitwise_and';
21+
22+
describeWithFlags('bitwiseAnd', ALL_ENVS, () => {
23+
it('a bitwiseAnd b', async () => {
24+
const a = tf.tensor1d([0, 5, 3, 14], 'int32');
25+
const b = tf.tensor1d([5, 0, 7, 11], 'int32');
26+
27+
const res = bitwiseAnd(a, b);
28+
expectArraysClose(await res.data(), [0, 0, 3, 10]);
29+
});
30+
31+
it('different shape', () => {
32+
const a = tf.tensor1d([0, 5, 3, 14]);
33+
const b = tf.tensor1d([5, 0, 7]);
34+
35+
expect(() => bitwiseAnd(a, b))
36+
.toThrowError(/BitwiseAnd: Tensors must have the same shape/);
37+
});
38+
39+
it('wrong type', () => {
40+
const a = tf.tensor1d([0, 1, 3, 14], 'float32');
41+
const b = tf.tensor1d([5, 0, 7, 12], 'float32');
42+
43+
expect(() => bitwiseAnd(a, b))
44+
.toThrowError(/BitwiseAnd: Only supports 'int32' values in tensor/);
45+
});
46+
});

‎tfjs-core/src/ops/ops.ts

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@@ -39,6 +39,7 @@ export {batchNorm2d} from './batchnorm2d';
3939
export {batchNorm3d} from './batchnorm3d';
4040
export {batchNorm4d} from './batchnorm4d';
4141
export {bincount} from './bincount';
42+
export {bitwiseAnd} from './bitwise_and';
4243
export {broadcastArgs} from './broadcast_args';
4344
export {broadcastTo} from './broadcast_to';
4445
export {buffer} from './buffer';

‎tfjs-node/src/run_tests.ts

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@@ -48,6 +48,7 @@ jasmine_util.setTestEnvs([{
4848

4949
const IGNORE_LIST: string[] = [
5050
// Always ignore version tests:
51+
'bitwiseAnd',
5152
'version version',
5253
'unreliable is true due to both auto gc and string tensors',
5354
'unreliable is true due to auto gc',

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