#!/usr/bin/env node
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/**
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* @license
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* Copyright 2020 Google Inc. 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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/**
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* Entry point for cli tool to build custom tfjs modules
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*/
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import * as fs from 'fs';
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import * as path from 'path';
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import * as yargs from 'yargs';
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import {OP_SCOPE_SUFFIX} from '@tensorflow/tfjs-core';
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import {bail} from './util';
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import {CustomTFJSBundleConfig, SupportedBackends, ModuleProvider} from './types';
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import {getModuleProvider} from './esm_module_provider';
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// Will be configured when loading the config file.
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let moduleProvider: ModuleProvider;
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const BASE_PATH = process.env.BASE_PATH || process.cwd();
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const DEFAULT_CUSTOM_BUNDLE_ARGS: Partial<CustomTFJSBundleConfig> = {
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entries: [],
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models: [],
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kernels: [],
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forwardModeOnly: true,
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backends: ['cpu', 'webgl'],
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moduleOptions: {},
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};
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const argParser = yargs.options({
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config: {
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description: 'Path to custom module config file.',
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type: 'string',
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demandOption: true
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}
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});
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const args = argParser.argv;
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function validateArgs(): CustomTFJSBundleConfig {
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let configFilePath = args.config;
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if (configFilePath == null) {
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bail(`Error: no config file passed`);
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}
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configFilePath = path.resolve(BASE_PATH, configFilePath);
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if (!fs.existsSync(configFilePath)) {
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bail(`Error: config file does not exist at ${configFilePath}`);
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}
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let config;
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try {
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config = JSON.parse(fs.readFileSync(configFilePath, 'utf-8'));
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} catch (error) {
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bail(`Error could not read/parse JSON config file. \n ${error.message}`);
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}
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if (config.outputPath == null) {
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bail('Error: config must specify "outputPath" property');
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}
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console.log(`Using custom module configuration from ${configFilePath}.`);
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const finalConfig = Object.assign({}, DEFAULT_CUSTOM_BUNDLE_ARGS, config);
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if (finalConfig.entries.length !== 0) {
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bail('Error: config.entries not yet supported');
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}
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// if (finalConfig.models.length !== 0) {
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// TODO validate that all these paths exist.
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// bail('Error: config.models not yet supported');
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// }
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for (const requestedBackend of finalConfig.backends) {
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if (requestedBackend !== SupportedBackends.cpu &&
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requestedBackend !== SupportedBackends.webgl &&
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requestedBackend !== SupportedBackends.wasm) {
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bail(`Error: Unsupported backend specified '${requestedBackend}'`);
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}
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}
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// Normalize the paths to absolute paths.
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function normalizePath(p: string) {
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return path.resolve(BASE_PATH, p);
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}
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finalConfig.models = finalConfig.models.map(normalizePath);
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finalConfig.entries = finalConfig.entries.map(normalizePath);
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finalConfig.normalizedOutputPath = normalizePath(finalConfig.outputPath);
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moduleProvider = getModuleProvider(finalConfig.moduleOptions);
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console.log('Final Configuration', finalConfig);
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return finalConfig;
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}
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function getKernelNamesForConfig(config: CustomTFJSBundleConfig) {
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// Later on this will do a union of kernels from entries, models and
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// kernels, (and kernels used by the converter itself) Currently we only
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// support directly listing kernels. remember that this also needs to handle
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// kernels used by gradients if forwardModeOnly is false.
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// Ops in core that are implemented as custom ops may appear in tf.profile
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// they will have __op as a suffix. These do not have corresponding backend
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// kernels so we need to filter them out.
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function isNotCustomOp(kernelName: string) {
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// opSuffix value is defined in tfjs-core/src/operation.ts
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// duplicating it here to avoid an export.
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return !kernelName.endsWith(OP_SCOPE_SUFFIX);
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}
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return config.kernels.filter(isNotCustomOp);
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}
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const customConfig = validateArgs();
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const kernelsToInclude = getKernelNamesForConfig(customConfig);
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customConfig.kernels = kernelsToInclude;
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if (moduleProvider != null) {
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moduleProvider.produceCustomTFJSModule(customConfig);
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} else {
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throw new Error('No module provider has been initialized.');
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}
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