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AddN.ts
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AddN.ts
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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 {AddN, AddNInputs, buffer, KernelConfig, KernelFunc, Tensor, TensorInfo, TypedArray} from '@tensorflow/tfjs-core';
import {MathBackendCPU} from '../backend_cpu';
import {assertNotComplex} from '../cpu_util';
export function addN(args: {inputs: AddNInputs, backend: MathBackendCPU}):
TensorInfo {
const {inputs, backend} = args;
const tensors = inputs as Tensor[];
assertNotComplex(inputs, 'addN');
const vals =
tensors.map(t => backend.data.get(t.dataId).values as TypedArray);
const outBuf = buffer(tensors[0].shape, tensors[0].dtype as 'float32');
const outVals = outBuf.values;
for (let i = 0; i < tensors.length; i++) {
const currVals = vals[i];
for (let j = 0; j < outVals.length; j++) {
outVals[j] += currVals[j];
}
}
return backend.makeTensorInfo(outBuf.shape, outBuf.dtype, outBuf.values);
}
export const addNConfig: KernelConfig = {
kernelName: AddN,
backendName: 'cpu',
kernelFunc: addN as unknown as KernelFunc
};