@tensorflow/tfjs-node/dist/kernels/DepthwiseConv2dNative.js

"use strict";
/**
 * @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 tfjs_1 = require("@tensorflow/tfjs");
var nodejs_kernel_backend_1 = require("../nodejs_kernel_backend");
exports.depthwiseConv2dNativeConfig = {
    kernelName: tfjs_1.DepthwiseConv2dNative,
    backendName: 'tensorflow',
    kernelFunc: function (args) {
        var _a = args.inputs, x = _a.x, filter = _a.filter;
        var backend = args.backend;
        var _b = args.attrs, strides = _b.strides, pad = _b.pad, dilations = _b.dilations, dimRoundingMode = _b.dimRoundingMode;
        var $dilations = dilations;
        if ($dilations == null) {
            $dilations = [1, 1];
        }
        var convInfo = tfjs_1.backend_util.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad, dimRoundingMode, true /* depthwise */);
        return depthwiseConv2dNativeImpl(x, filter, convInfo, backend);
    }
};
function depthwiseConv2dNativeImpl(input, filter, convInfo, backend) {
    if (convInfo.padInfo.type !== 'VALID' && convInfo.padInfo.type !== 'SAME' &&
        convInfo.padInfo.type !== 'EXPLICIT') {
        throw new Error("TF Backend supports only 'valid' and 'same' padding " +
            ("while padding was " + convInfo.padInfo.type));
    }
    var strides = [1, convInfo.strideHeight, convInfo.strideWidth, 1];
    var padding = convInfo.padInfo.type;
    var dataFormat = convInfo.dataFormat === 'channelsLast' ? 'NHWC' : 'NCHW';
    var dilations = [1, convInfo.dilationHeight, convInfo.dilationWidth, 1];
    var opAttrs = [
        nodejs_kernel_backend_1.createTensorsTypeOpAttr('T', input.dtype),
        { name: 'strides', type: backend.binding.TF_ATTR_INT, value: strides },
        { name: 'padding', type: backend.binding.TF_ATTR_STRING, value: padding }, {
            name: 'data_format',
            type: backend.binding.TF_ATTR_STRING,
            value: dataFormat
        },
        { name: 'dilations', type: backend.binding.TF_ATTR_INT, value: dilations }
    ];
    if (padding === 'EXPLICIT') {
        var padValue = [
            convInfo.padInfo.top, convInfo.padInfo.bottom, convInfo.padInfo.left,
            convInfo.padInfo.right
        ];
        opAttrs.push({
            name: 'explicit_paddings',
            type: backend.binding.TF_ATTR_INT,
            value: dataFormat === 'NHWC' ? [0, 0].concat(padValue, [0, 0]) : [0, 0, 0, 0].concat(padValue)
        });
    }
    return backend.executeSingleOutput(tfjs_1.DepthwiseConv2dNative, opAttrs, [input, filter]);
}
exports.depthwiseConv2dNativeImpl = depthwiseConv2dNativeImpl;