"use strict";
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/**
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* @license
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* Copyright 2019 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.summaryFileWriter = exports.SummaryFileWriter = 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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var SummaryFileWriter = /** @class */ (function () {
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function SummaryFileWriter(resourceHandle) {
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this.resourceHandle = resourceHandle;
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(0, nodejs_kernel_backend_1.ensureTensorflowBackend)();
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this.backend = (0, nodejs_kernel_backend_1.nodeBackend)();
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}
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/**
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* Write a scalar summary.
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*
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* @param name A name of the summary. The summary tag for TensorBoard will be
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* this name.
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* @param value A real numeric scalar value, as `tf.Scalar` or a JavaScript
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* `number`.
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* @param step Required `int64`-castable, monotonically-increasing step value.
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* @param description Optional long-form description for this summary, as a
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* `string`. *Not implemented yet*.
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*/
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SummaryFileWriter.prototype.scalar = function (name, value, step, description) {
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// N.B.: Unlike the Python TensorFlow API, step is a required parameter,
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// because the construct of global step does not exist in TensorFlow.js.
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if (description != null) {
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throw new Error('scalar() does not support description yet');
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}
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this.backend.writeScalarSummary(this.resourceHandle, step, name, value);
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};
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/**
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* Write a histogram summary, for later analysis in TensorBoard's 'Histograms'
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* and 'Distributions' dashboards (data written using this API will appear in
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* both places). Like `SummaryFileWriter.scalar` points, each histogram is
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* associated with a `step` and a `name`. All the histograms with the same
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* `name` constitute a time series of histograms.
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*
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* The histogram is calculated over all the elements of the given `Tensor`
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* without regard to its shape or rank.
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*
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* @param name A name for this summary. The summary tag used for TensorBoard
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* will be this name.
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* @param data A Tensor of any shape. The histogram is computed over its
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* elements, which must be castable to `float32`.
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* @param step Monotonically-increasing step value.
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* @param buckets Optional positive `number`. The output will have this many
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* buckets, except in two edge cases. If there is no data, then there are
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* no buckets. If there is data but all points have the same value, then
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* there is one bucket whose left and right endpoints are the same.
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* @param description Optional long-form description for this summary, as a
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* `string`. Markdown is supported. Defaults to empty.
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*/
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SummaryFileWriter.prototype.histogram = function (name, data, step, buckets, description) {
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this.backend.writeHistogramSummary(this.resourceHandle, step, name, data, buckets, description);
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};
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/**
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* Force summary writer to send all buffered data to storage.
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*/
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SummaryFileWriter.prototype.flush = function () {
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this.backend.flushSummaryWriter(this.resourceHandle);
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};
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return SummaryFileWriter;
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}());
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exports.SummaryFileWriter = SummaryFileWriter;
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/**
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* Use a cache for `SummaryFileWriter` instance.
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*
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* Using multiple instances of `SummaryFileWriter` pointing to the same
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* logdir has potential problems. Using this cache avoids those problems.
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*/
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var summaryFileWriterCache = {};
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/**
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* Create a summary file writer for TensorBoard.
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*
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* Example:
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* ```js
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* const tf = require('@tensorflow/tfjs-node');
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*
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* const summaryWriter = tf.node.summaryFileWriter('/tmp/tfjs_tb_logdir');
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*
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* for (let step = 0; step < 100; ++step) {
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* summaryWriter.scalar('dummyValue', Math.sin(2 * Math.PI * step / 8), step);
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* }
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* ```
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*
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* @param logdir Log directory in which the summary data will be written.
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* @param maxQueue Maximum queue length (default: `10`).
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* @param flushMillis Flush every __ milliseconds (default: `120e3`, i.e,
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* `120` seconds).
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* @param filenameSuffix Suffix of the protocol buffer file names to be
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* written in the `logdir` (default: `.v2`).
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* @returns An instance of `SummaryFileWriter`.
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*
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* @doc {heading: 'TensorBoard', namespace: 'node'}
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*/
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function summaryFileWriter(logdir, maxQueue, flushMillis, filenameSuffix) {
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if (maxQueue === void 0) { maxQueue = 10; }
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if (flushMillis === void 0) { flushMillis = 120000; }
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if (filenameSuffix === void 0) { filenameSuffix = '.v2'; }
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tfjs_1.util.assert(logdir != null && typeof logdir === 'string' && logdir.length > 0, function () {
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return "Invalid logdir: ".concat(logdir, ". Expected a non-empty string for logdir.");
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});
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if (!(logdir in summaryFileWriterCache)) {
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(0, nodejs_kernel_backend_1.ensureTensorflowBackend)();
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var backend = (0, nodejs_kernel_backend_1.nodeBackend)();
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var writerResource = backend.summaryWriter(logdir);
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backend.createSummaryFileWriter(writerResource, logdir, maxQueue, flushMillis, filenameSuffix);
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summaryFileWriterCache[logdir] = new SummaryFileWriter(writerResource);
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}
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return summaryFileWriterCache[logdir];
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}
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exports.summaryFileWriter = summaryFileWriter;
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