@tensorflow/tfjs-core
Version:
Hardware-accelerated JavaScript library for machine intelligence
43 lines • 2.18 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.
* =============================================================================
*/
Object.defineProperty(exports, "__esModule", { value: true });
var kernel_names_1 = require("../../../kernel_names");
var conv_util = require("../../../ops/conv_util");
var cpu_util_1 = require("../cpu_util");
var MaxPoolWithArgmax_impl_1 = require("./MaxPoolWithArgmax_impl");
exports.maxPoolWithArgmaxConfig = {
kernelName: kernel_names_1.MaxPoolWithArgmax,
backendName: 'cpu',
kernelFunc: function (_a) {
var inputs = _a.inputs, attrs = _a.attrs, backend = _a.backend;
var x = inputs.x;
var _b = attrs, filterSize = _b.filterSize, strides = _b.strides, pad = _b.pad, includeBatchInIndex = _b.includeBatchInIndex;
var cpuBackend = backend;
cpu_util_1.assertNotComplex(x, 'MaxPoolWithArgmax');
var values = cpuBackend.data.get(x.dataId).values;
var convInfo = conv_util.computePool2DInfo(x.shape, filterSize, strides, [1, 1], pad);
var _c = MaxPoolWithArgmax_impl_1.maxPoolWithArgmaxImpl(values, x.shape, x.dtype, includeBatchInIndex, convInfo), pooled = _c[0], indexes = _c[1];
var pooledDataId = cpuBackend.write(pooled, convInfo.outShape, x.dtype);
var indexesDataId = cpuBackend.write(indexes, convInfo.outShape, x.dtype);
return [
{ dataId: pooledDataId, shape: convInfo.outShape, dtype: x.dtype },
{ dataId: indexesDataId, shape: convInfo.outShape, dtype: 'int32' }
];
}
};
//# sourceMappingURL=MaxPoolWithArgmax.js.map