@magenta/music - npm Package Compare versions

Comparing version 1.1.8 to 1.1.9

es5/core/chords.d.ts

@@ -7,3 +7,3 @@ import * as tf from '@tensorflow/tfjs-core';
     Diminished = 3,
-    Other = 4
+    Other = 4,
 }
@@ -30,3 +30,3 @@ export declare class ChordSymbolException extends Error {
     depth: number;
-    private index;
+    private index(chord);
     encode(chord: string): tf.Tensor<tf.Rank.R1>;
@@ -36,3 +36,3 @@ }
     depth: number;
-    private index;
+    private index(chord);
     encode(chord: string): tf.Tensor<tf.Rank.R1>;
@@ -39,0 +39,0 @@ }

es5/core/data.d.ts

@@ -37,6 +37,6 @@ import * as tf from '@tensorflow/tfjs-core';
     readonly numSegments: number;
-    abstract readonly depth: number;
-    abstract readonly endTensor: tf.Tensor1D;
-    abstract readonly NUM_SPLITS: number;
-    abstract readonly SEGMENTED_BY_TRACK: boolean;
+    readonly abstract depth: number;
+    readonly abstract endTensor: tf.Tensor1D;
+    readonly abstract NUM_SPLITS: number;
+    readonly abstract SEGMENTED_BY_TRACK: boolean;
     abstract toTensor(noteSequence: INoteSequence): tf.Tensor2D;
@@ -127,6 +127,6 @@ abstract toNoteSequence(tensor: tf.Tensor2D, stepsPerQuarter: number): Promise<INoteSequence>;
     constructor(args: MultitrackConverterArgs);
-    private trackToTensor;
+    private trackToTensor(track?);
     toTensor(noteSequence: INoteSequence): tf.Tensor<tf.Rank.R2>;
-    private tokensToTrack;
+    private tokensToTrack(tokens);
     toNoteSequence(oh: tf.Tensor2D, stepsPerQuarter?: number): Promise<NoteSequence>;
 }

es5/core/data.js

@@ -27,4 +27,4 @@ "use strict";
         while (_) try {
-            if (f = 1, y && (t = op[0] & 2 ? y["return"] : op[0] ? y["throw"] || ((t = y["return"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;
-            if (y = 0, t) op = [op[0] & 2, t.value];
+            if (f = 1, y && (t = y[op[0] & 2 ? "return" : op[0] ? "throw" : "next"]) && !(t = t.call(y, op[1])).done) return t;
+            if (y = 0, t) op = [0, t.value];
             switch (op[0]) {
@@ -362,4 +362,4 @@ case 0: case 1: t = op; break;
         return __awaiter(this, void 0, void 0, function () {
-            var _a, _b, ohs, ns, bassNs, drumsNs;
             var _this = this;
+            var ohs, ns, bassNs, drumsNs, _a, _b;
             return __generator(this, function (_c) {
@@ -530,4 +530,4 @@ switch (_c.label) {
         return __awaiter(this, void 0, void 0, function () {
+            var _this = this;
             var noteSequence, tensors, tracks;
-            var _this = this;
             return __generator(this, function (_a) {
@@ -557,5 +557,5 @@ switch (_a.label) {
                         tracks.forEach(function (track, instrument) {
-                            var _a;
                             track.setNumSteps(_this.totalSteps);
                             (_a = noteSequence.notes).push.apply(_a, track.toNoteSequence(instrument).notes);
+                            var _a;
                         });
@@ -562,0 +562,0 @@ return [2, noteSequence];

es5/core/player.d.ts

@@ -15,3 +15,3 @@ import { INoteSequence, NoteSequence } from '../protobuf/index';
     setTempo(qpm: number): void;
-    private makeClickSequence;
+    private makeClickSequence(seq);
     start(seq: INoteSequence, qpm?: number): Promise<void>;
@@ -26,3 +26,3 @@ stop(): void;
     protected playNote(time: number, note: NoteSequence.INote): void;
-    private getSynth;
+    private getSynth(instrument, program?);
 }
@@ -29,0 +29,0 @@ export declare class SoundFontPlayer extends BasePlayer {

es5/core/player.js

@@ -27,4 +27,4 @@ "use strict";
         while (_) try {
-            if (f = 1, y && (t = op[0] & 2 ? y["return"] : op[0] ? y["throw"] || ((t = y["return"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;
-            if (y = 0, t) op = [op[0] & 2, t.value];
+            if (f = 1, y && (t = y[op[0] & 2 ? "return" : op[0] ? "throw" : "next"]) && !(t = t.call(y, op[1])).done) return t;
+            if (y = 0, t) op = [0, t.value];
             switch (op[0]) {
@@ -31,0 +31,0 @@ case 0: case 1: t = op; break;

es5/core/soundfont.d.ts

@@ -28,5 +28,5 @@ export interface SampleInfo {
     initialize(): Promise<void>;
-    private sampleInfoToName;
-    private sampleNameToURL;
-    private nearestVelocity;
+    private sampleInfoToName(sampleInfo);
+    private sampleNameToURL(name);
+    private nearestVelocity(velocity);
     loadSamples(samples: SampleInfo[]): Promise<void>;
@@ -33,0 +33,0 @@ playNote(pitch: number, velocity: number, startTime: number, duration: number, output: any): void;

es5/core/soundfont.js

@@ -17,4 +17,4 @@ "use strict";
         while (_) try {
-            if (f = 1, y && (t = op[0] & 2 ? y["return"] : op[0] ? y["throw"] || ((t = y["return"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;
-            if (y = 0, t) op = [op[0] & 2, t.value];
+            if (f = 1, y && (t = y[op[0] & 2 ? "return" : op[0] ? "throw" : "next"]) && !(t = t.call(y, op[1])).done) return t;
+            if (y = 0, t) op = [0, t.value];
             switch (op[0]) {
@@ -103,4 +103,4 @@ case 0: case 1: t = op; break;
         return __awaiter(this, void 0, void 0, function () {
+            var _this = this;
             var nearestSampleNames, uniqueSampleNames, sampleNamesAndURLs;
-            var _this = this;
             return __generator(this, function (_a) {
@@ -204,4 +204,4 @@ switch (_a.label) {
         return __awaiter(this, void 0, void 0, function () {
+            var _this = this;
             var instrumentSamples;
-            var _this = this;
             return __generator(this, function (_a) {
@@ -208,0 +208,0 @@ switch (_a.label) {

es5/music_rnn/attention.js

@@ -33,3 +33,2 @@ "use strict";
     AttentionWrapper.prototype.call = function (input, c, h, state) {
-        var _a;
         var nextAttnInput = tf.concat([input, state.attention.as2D(1, -1)], 1);
@@ -60,2 +59,3 @@ var nextRnnInput = tf.add(tf.matMul(nextAttnInput, this.attnInputMatrix), this.attnInputBias.as2D(1, -1));
         return { output: output, c: c, h: h, attentionState: { attention: attention, attentionState: attentionState } };
+        var _a;
     };
@@ -62,0 +62,0 @@ return AttentionWrapper;

es5/music_rnn/model.d.ts

@@ -29,7 +29,12 @@ import * as aux_inputs from '../core/aux_inputs';
     isInitialized(): boolean;
-    private instantiateFromSpec;
+    private instantiateFromSpec();
     initialize(): Promise<void>;
     dispose(): void;
     continueSequence(sequence: INoteSequence, steps: number, temperature?: number, chordProgression?: string[]): Promise<INoteSequence>;
-    private sampleRnn;
+    continueSequenceAndReturnProbabilities(sequence: INoteSequence, steps: number, temperature?: number, chordProgression?: string[]): Promise<{
+        sequence: Promise<INoteSequence>;
+        probs: Float32Array[];
+    }>;
+    private continueSequenceImpl(sequence, steps, temperature?, chordProgression?, returnProbs?);
+    private sampleRnn(inputs, steps, temperature, controls?, auxInputs?, returnProbs?);
 }

es5/music_rnn/model.js

@@ -17,4 +17,4 @@ "use strict";
         while (_) try {
-            if (f = 1, y && (t = op[0] & 2 ? y["return"] : op[0] ? y["throw"] || ((t = y["return"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;
-            if (y = 0, t) op = [op[0] & 2, t.value];
+            if (f = 1, y && (t = y[op[0] & 2 ? "return" : op[0] ? "throw" : "next"]) && !(t = t.call(y, op[1])).done) return t;
+            if (y = 0, t) op = [0, t.value];
             switch (op[0]) {
@@ -70,4 +70,4 @@ case 0: case 1: t = op; break;
         return __awaiter(this, void 0, void 0, function () {
+            var _this = this;
             var vars, hasAttention, rnnPrefix, l, _loop_1, this_1, state_1;
-            var _this = this;
             return __generator(this, function (_a) {
@@ -147,4 +147,24 @@ switch (_a.label) {
         return __awaiter(this, void 0, void 0, function () {
-            var oh, result, _a, _b;
+            var result;
+            return __generator(this, function (_a) {
+                switch (_a.label) {
+                    case 0: return [4, this.continueSequenceImpl(sequence, steps, temperature, chordProgression, false)];
+                    case 1:
+                        result = _a.sent();
+                        return [2, result.sequence];
+                }
+            });
+        });
+    };
+    MusicRNN.prototype.continueSequenceAndReturnProbabilities = function (sequence, steps, temperature, chordProgression) {
+        return __awaiter(this, void 0, void 0, function () {
+            return __generator(this, function (_a) {
+                return [2, this.continueSequenceImpl(sequence, steps, temperature, chordProgression, true)];
+            });
+        });
+    };
+    MusicRNN.prototype.continueSequenceImpl = function (sequence, steps, temperature, chordProgression, returnProbs) {
+        return __awaiter(this, void 0, void 0, function () {
             var _this = this;
+            var oh, samplesAndProbs, result, probs, i, _a, _b;
             return __generator(this, function (_c) {
@@ -176,11 +196,31 @@ switch (_c.label) {
                                 undefined;
-                            var samples = _this.sampleRnn(inputs, steps, temperature, controls, auxInputs);
-                            return tf.stack(samples).as2D(samples.length, outputSize);
+                            var rnnResult = _this.sampleRnn(inputs, steps, temperature, controls, auxInputs, returnProbs);
+                            var samples = rnnResult.samples;
+                            return {
+                                samples: tf.stack(samples).as2D(samples.length, outputSize),
+                                probs: rnnResult.probs
+                            };
                         });
-                        _b = (_a = this.dataConverter).toNoteSequence;
                         return [4, oh];
                     case 3:
-                        result = _b.apply(_a, [_c.sent(), sequence.quantizationInfo.stepsPerQuarter]);
-                        oh.dispose();
-                        return [2, result];
+                        samplesAndProbs = _c.sent();
+                        result = this.dataConverter.toNoteSequence(samplesAndProbs.samples, sequence.quantizationInfo.stepsPerQuarter);
+                        probs = [];
+                        if (!returnProbs) return [3, 7];
+                        i = 0;
+                        _c.label = 4;
+                    case 4:
+                        if (!(i < samplesAndProbs.probs.length)) return [3, 7];
+                        _b = (_a = probs).push;
+                        return [4, samplesAndProbs.probs[i].data()];
+                    case 5:
+                        _b.apply(_a, [_c.sent()]);
+                        samplesAndProbs.probs[i].dispose();
+                        _c.label = 6;
+                    case 6:
+                        i++;
+                        return [3, 4];
+                    case 7:
+                        oh.samples.dispose();
+                        return [2, { sequence: result, probs: probs }];
                 }
@@ -190,4 +230,3 @@ });
     };
-    MusicRNN.prototype.sampleRnn = function (inputs, steps, temperature, controls, auxInputs) {
-        var _a;
+    MusicRNN.prototype.sampleRnn = function (inputs, steps, temperature, controls, auxInputs, returnProbs) {
         var length = inputs.shape[0];
@@ -205,2 +244,3 @@ var outputSize = inputs.shape[1];
         var samples = [];
+        var probs = [];
         var splitInputs = tf.split(inputs.toFloat(), length);
@@ -216,6 +256,15 @@ var splitControls = controls ? tf.split(controls, controls.shape[0]) : undefined;
                 var logits = lastOutput.matMul(this.lstmFcW).add(this.lstmFcB);
-                var sampledOutput = (temperature ?
-                    tf.multinomial(logits.div(tf.scalar(temperature)), 1)
-                        .as1D() :
-                    logits.argMax(1).as1D());
+                var sampledOutput = void 0;
+                if (returnProbs || temperature) {
+                    var theseProbs = temperature ?
+                        tf.softmax(logits.div(tf.scalar(temperature))) :
+                        tf.softmax(logits);
+                    probs.push(theseProbs);
+                    sampledOutput =
+                        tf.multinomial(theseProbs, 1, undefined, true)
+                            .as1D();
+                }
+                else {
+                    sampledOutput = logits.argMax(1).as1D();
+                }
                 nextInput = tf.oneHot(sampledOutput, outputSize).toFloat();
@@ -248,3 +297,4 @@ samples.push(nextInput.as1D().toBool());
         }
-        return samples;
+        return { samples: samples, probs: probs };
+        var _a;
     };
@@ -251,0 +301,0 @@ return MusicRNN;

es5/music_vae/model.d.ts

@@ -42,15 +42,15 @@ import * as tf from '@tensorflow/tfjs-core';
     constructor(checkpointURL: string, spec?: MusicVAESpec);
-    private instantiateFromSpec;
+    private instantiateFromSpec();
     dispose(): void;
-    private getLstmLayers;
+    private getLstmLayers(cellFormat, vars);
     initialize(): Promise<void>;
     isInitialized(): boolean;
     interpolate(inputSequences: INoteSequence[], numInterps: number | number[], temperature?: number, chordProgression?: string[]): Promise<INoteSequence[]>;
-    private getSegmentLengths;
-    private encodeChordProgression;
+    private getSegmentLengths(inputTensors);
+    private encodeChordProgression(chordProgression);
     encode(inputSequences: INoteSequence[], chordProgression?: string[]): Promise<tf.Tensor<tf.Rank.R2>>;
     decode(z: tf.Tensor2D, temperature?: number, chordProgression?: string[], stepsPerQuarter?: number): Promise<INoteSequence[]>;
-    private getInterpolatedZs;
+    private getInterpolatedZs(z, numInterps);
     sample(numSamples: number, temperature?: number, chordProgression?: string[], stepsPerQuarter?: number): Promise<INoteSequence[]>;
 }
-export { LayerVars, Encoder, Decoder, Nade, MusicVAE, };
+export { LayerVars, Encoder, Decoder, Nade, MusicVAE };

es5/music_vae/model.js

@@ -27,4 +27,4 @@ "use strict";
         while (_) try {
-            if (f = 1, y && (t = op[0] & 2 ? y["return"] : op[0] ? y["throw"] || ((t = y["return"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;
-            if (y = 0, t) op = [op[0] & 2, t.value];
+            if (f = 1, y && (t = y[op[0] & 2 ? "return" : op[0] ? "throw" : "next"]) && !(t = t.call(y, op[1])).done) return t;
+            if (y = 0, t) op = [0, t.value];
             switch (op[0]) {
@@ -204,3 +204,2 @@ case 0: case 1: t = op; break;
         return tf.tidy(function () {
-            var _a;
             var lstmCell = initLstmCells(z, _this.lstmCellVars, _this.zToInitStateVars);
@@ -236,2 +235,3 @@ var samples = [];
             return tf.stack(samples, 1);
+            var _a;
         });
@@ -258,3 +258,2 @@ };
         return tf.tidy(function () {
-            var _a;
             var lstmCell = initLstmCells(z, _this.lstmCellVars, _this.zToInitStateVars);
@@ -277,2 +276,3 @@ var samples = [];
             return tf.concat(samples, 1);
+            var _a;
         });
@@ -350,4 +350,4 @@ };
         return __awaiter(this, void 0, void 0, function () {
+            var _this = this;
             var LSTM_CELL_FORMAT, MUTLI_LSTM_CELL_FORMAT, CONDUCTOR_PREFIX, BIDI_LSTM_CELL, ENCODER_FORMAT, HIER_ENCODER_FORMAT, vars, encMu, fwLayers_1, bwLayers_1, baseEncoders, fwLayers, bwLayers, decVarPrefix, decVarPrefixes, i, baseDecoders, condLstmLayers, condZtoInitState;
-            var _this = this;
             return __generator(this, function (_a) {
@@ -451,4 +451,4 @@ switch (_a.label) {
         return __awaiter(this, void 0, void 0, function () {
+            var _this = this;
             var inputZs, interpZs, outputSequenes;
-            var _this = this;
             return __generator(this, function (_a) {
@@ -482,4 +482,4 @@ switch (_a.label) {
         return __awaiter(this, void 0, void 0, function () {
+            var _this = this;
             var numSteps, numSegments, isEndTensor, isEndArray, maxSegmentLength, segmentLengths, offset, fromIndex;
-            var _this = this;
             return __generator(this, function (_a) {
@@ -533,4 +533,4 @@ switch (_a.label) {
         return __awaiter(this, void 0, void 0, function () {
+            var _this = this;
             var inputTensors, segmentLengths, _a, newInputTensors, z;
-            var _this = this;
             return __generator(this, function (_b) {
@@ -585,4 +585,4 @@ switch (_b.label) {
         return __awaiter(this, void 0, void 0, function () {
+            var _this = this;
             var numSteps, ohSeqs, outputSequences, _i, ohSeqs_1, oh, _a, _b;
-            var _this = this;
             return __generator(this, function (_c) {
@@ -678,4 +678,4 @@ switch (_c.label) {
         return __awaiter(this, void 0, void 0, function () {
+            var _this = this;
             var randZs, outputSequenes;
-            var _this = this;
             return __generator(this, function (_a) {
@@ -682,0 +682,0 @@ switch (_a.label) {

package.json

 {
   "name": "@magenta/music",
-  "version": "1.1.8",
+  "version": "1.1.9",
   "description": "Make music in the browser with machine learning.",
@@ -5,0 +5,0 @@ "main": "es5/index.js",

README.md

@@ -11,6 +11,6 @@ # @magenta/music
 
-* [Example Applcations](#example-applications)
-* [Supported Models](#supported-models)
-* [Getting Started](#getting-started)
-* [Model Checkpoints](#model-checkpoints)
+- [Example Applications](#example-applications)
+- [Supported Models](#supported-models)
+- [Getting Started](#getting-started)
+- [Model Checkpoints](#model-checkpoints)
 
@@ -21,6 +21,6 @@ ## Example Applications
 
-* [Beat Blender](https://g.co/beatblender) by [Google Creative Lab](https://github.com/googlecreativelab)
-* [Melody Mixer](https://g.co/melodymixer) by [Google Creative Lab](https://github.com/googlecreativelab)
-* [Latent Loops](https://goo.gl/magenta/latent-loops) by [Google Pie Shop](https://github.com/teampieshop)
-* [Neural Drum Machine](https://codepen.io/teropa/pen/RMGxOQ) by [Tero Parviainen](https://github.com/teropa)
+- [Beat Blender](https://g.co/beatblender) by [Google Creative Lab](https://github.com/googlecreativelab)
+- [Melody Mixer](https://g.co/melodymixer) by [Google Creative Lab](https://github.com/googlecreativelab)
+- [Latent Loops](https://goo.gl/magenta/latent-loops) by [Google Pie Shop](https://github.com/teampieshop)
+- [Neural Drum Machine](https://codepen.io/teropa/pen/RMGxOQ) by [Tero Parviainen](https://github.com/teropa)
 
@@ -92,5 +92,6 @@ ## Supported Models
 
-model.initialize()
-    .then(() => model.sample(1))
-    .then((samples) => player.start(samples[0]));
+model
+  .initialize()
+  .then(() => model.sample(1))
+  .then(samples => player.start(samples[0]));
 ```
@@ -141,10 +142,10 @@
   "type": "MusicRNN",
-    "dataConverter": {
-      "type": "MelodyConverter",
-      "args": {
-        "minPitch": 48,
-        "maxPitch": 83
-      }
-    },
-    "chordEncoder": "PitchChordEncoder"
+  "dataConverter": {
+    "type": "MelodyConverter",
+    "args": {
+      "minPitch": 48,
+      "maxPitch": 83
+    }
+  },
+  "chordEncoder": "PitchChordEncoder"
 }
@@ -156,2 +157,3 @@ ```
 <!-- links -->
+
 [melody-rnn]: https://github.com/tensorflow/magenta/tree/master/magenta/models/melody_rnn
@@ -158,0 +160,0 @@ [drums-rnn]: https://github.com/tensorflow/magenta/tree/master/magenta/models/drums_rnn

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Improved metrics

Total package byte prevSize

3879686

increased by0.08%

Lines of code

88610

increased by0.12%

Number of lines in readme file

161

increased by1.26%

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Number of package files

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