/**
|
* @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 {_FusedMatMul, _FusedMatMulAttrs, _FusedMatMulInputs, add, KernelConfig, matMul, Tensor, Tensor3D, tidy} from '@tensorflow/tfjs';
|
|
import {NodeJSKernelBackend} from '../nodejs_kernel_backend';
|
|
export const _fusedMatMulConfig: KernelConfig = {
|
kernelName: _FusedMatMul,
|
backendName: 'tensorflow',
|
kernelFunc: (args) => {
|
const {a, b, bias, preluActivationWeights} =
|
args.inputs as _FusedMatMulInputs;
|
const backend = args.backend as NodeJSKernelBackend;
|
const {transposeA, transposeB, activation, leakyreluAlpha} =
|
args.attrs as unknown as _FusedMatMulAttrs;
|
|
// Core TensorFlow does not have a fused BatchMatMul op. Combine calls to
|
// achieve the same results:
|
return tidy(() => {
|
let result: Tensor3D =
|
matMul(a as Tensor, b as Tensor, transposeA, transposeB);
|
if (bias != null) {
|
result = add(result, bias as Tensor);
|
}
|
|
result = backend.applyActivation(
|
result, activation, preluActivationWeights as Tensor, leakyreluAlpha);
|
|
return result;
|
});
|
}
|
};
|