"use strict";
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/**
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* @license
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* Copyright 2020 Google LLC. All Rights Reserved.
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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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Object.defineProperty(exports, "__esModule", { value: true });
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exports.argMaxConfig = void 0;
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var tfjs_1 = require("@tensorflow/tfjs");
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var nodejs_kernel_backend_1 = require("../nodejs_kernel_backend");
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exports.argMaxConfig = {
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kernelName: tfjs_1.ArgMax,
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backendName: 'tensorflow',
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kernelFunc: function (args) {
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var x = args.inputs.x;
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var backend = args.backend;
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var axis = args.attrs.axis;
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var toDispose = [];
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var xInput = x;
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if (x.dtype === 'bool') {
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xInput = x.toInt();
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toDispose.push(xInput);
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}
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var axisScalar = (0, tfjs_1.scalar)(axis, 'int32');
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toDispose.push(axisScalar);
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var opAttrs = [
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(0, nodejs_kernel_backend_1.createTensorsTypeOpAttr)('T', xInput.dtype),
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(0, nodejs_kernel_backend_1.createTensorsTypeOpAttr)('Tidx', 'int32'),
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(0, nodejs_kernel_backend_1.createTensorsTypeOpAttr)('output_type', 'int32')
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];
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var res = backend.executeSingleOutput(tfjs_1.ArgMax, opAttrs, [xInput, axisScalar]);
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toDispose.forEach(function (t) { return t.dispose(); });
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return res;
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}
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};
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