@tensorflow/tfjs-node
Version:
This repository provides native TensorFlow execution in backend JavaScript applications under the Node.js runtime, accelerated by the TensorFlow C binary under the hood. It provides the same API as [TensorFlow.js](https://js.tensorflow.org/api/latest/).
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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.
* =============================================================================
*/
var __spreadArray = (this && this.__spreadArray) || function (to, from, pack) {
if (pack || arguments.length === 2) for (var i = 0, l = from.length, ar; i < l; i++) {
if (ar || !(i in from)) {
if (!ar) ar = Array.prototype.slice.call(from, 0, i);
ar[i] = from[i];
}
}
return to.concat(ar || Array.prototype.slice.call(from));
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.depthwiseConv2dNativeImpl = exports.depthwiseConv2dNativeConfig = void 0;
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 ".concat(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 = [
(0, 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' ? __spreadArray(__spreadArray([0, 0], padValue, true), [0, 0], false) : __spreadArray([0, 0, 0, 0], padValue, true)
});
}
return backend.executeSingleOutput(tfjs_1.DepthwiseConv2dNative, opAttrs, [input, filter]);
}
exports.depthwiseConv2dNativeImpl = depthwiseConv2dNativeImpl;