Node.js (JavaScript) Wrapper API

[keon]

Because JavaScript is Awesome

[ZECTBynmo]

+1!

[dhritzkiv]

+1

[fiws]

👍

[mikealche]

+1

[jagandecapri]

Just what I was searching for. 👍

As quoted from the offical website http://www.tensorflow.org/

we’re hoping to entice you to contribute SWIG interfaces to your favorite language -- be it Go, Java, Lua, Javascript, or R.

I am new to this whole SWIG thing but searched around and found this. http://www.swig.org/Doc3.0/Javascript.html

Not really sure how this works. Do we need to write swig interface file specifically for Javascript or is it auto-generated when running some commands or is somebody already working on this (this would be awesome) ?

[imgntn]

+1 👍

[prathamesh7pute]

+1

[chenzxcvb]

+1

[dmitriykharchenko]

+1

[marcbaetica]

+1

[lowe0292]

👍

[mattkosoy]

👍

[nikhilk]

+1!

Just starting out on one, but new to writing a nodejs addon. Checking out the swig interface files to see if they're going to be helpful, or if I should just use the c++ API.

[vnglst]

+1

[jalona]

+1

[Foorack]

+1

[tngan]

+1

[vincentvanhoucke]

This is something the core TensorFlow team is unlikely to tackle in the near future, so if you want to contribute it, please go ahead! I would recommend circulating a proposed implementation on the discuss mailing list early on, so that a consensus about where such API might live (in repo / off repo / in 'contrib' directory) can be reached ahead of time.

[Foorack]

Anyone up to write a NodeJS library? 👍
I think it would be better with a official NodeJS API however a community one will be as (if not more) interesting in my opinion. I know there are multiple ways of approaching this however I strongly recommend node-gyp for performance. I will gladly contribute in any way I can, however, this is something I will not be able to do alone. Would be best if a few other people is interested as well, specially someone with C++ knowledge.

[augbog]

👍

[tngan]

@Foorack I am willing to contribute it if some people are interested as well. Is it possible to move the discussion to a slack channel ? (see #31)

[Foorack]

@tngan The slack channel is private, however I was able to join with the herokuapp link. 👍

[tngan]

We hope more developers to discuss and contribute. Now we have a slack channel named as nodejs (see #31), and a Github repository node-tensorflow is reserved. Thanks @Foorack !

[marcbaetica]

I am willing to contribute. Thanks for the initiative guys!

[Foorack]

@miguelalche Glad to see you're interested! Please join the slack channel and someone will add you to the repository. ^^

[cauerego]

I look forward for contributing ( specially along with #132 ) !!

[gpresland]

+1

[mpj]

Hooray for node! Let's do this.

[7immer]

propelml.org - Looks interesting. I've not used it but its GPU enabled and runs in both the browser and on node

[thefill]

@7ammer propelml.org looks rather promising. Thanks for sharing this with us ;-)

[troyam]

Because NodeJS it's fast! ;D

[jart]

If an ambitious member of the community wants the glory of solving this problem, and having it merged into the TensorFlow contrib codebase, here are some tips on how I would do it. Please note I'm not going to do this.

You can add Node to workspace.bzl just like TensorBoard did in js.bzl.
Please note TensorFlow can not depend on rules_nodejs.

load("@io_bazel_rules_closure//closure:defs.bzl", "filegroup_external")

filegroup_external(
    name = "org_nodejs",
    # MIT with portions licensed:
    # - MIT
    # - Old MIT
    # - 2-Clause-BSD
    # - 3-Clause-BSD
    # - ISC
    # - Unicode
    # - zlib
    # - Artistic 2.0
    licenses = ["notice"],
    sha256_urls_extract_macos = {
        "910395e1e98fb351c62b5702a9deef22aaecf05d6df1d7edc283337542207f3f": [
            "https://mirror.bazel.build/nodejs.org/dist/v6.9.1/node-v6.9.1-darwin-x64.tar.xz",
            "http://nodejs.org/dist/v6.9.1/node-v6.9.1-darwin-x64.tar.xz",
        ],
    },
    sha256_urls_windows = {
        "1914bfb950be8d576ce9e49c8a0e51c9f2402560fe3c19093e69bc1306a56e9e": [
            "https://mirror.bazel.build/raw.githubusercontent.com/nodejs/node/v6.9.1/LICENSE",
            "https://raw.githubusercontent.com/nodejs/node/v6.9.1/LICENSE",
        ],
        "513923b0490ebb7466a56483a62595814ed9d036d6f35476debb0cd606bec526": [
            "https://mirror.bazel.build/nodejs.org/dist/v6.9.1/win-x64/node.exe",
            "http://nodejs.org/dist/v6.9.1/win-x64/node.exe",
        ],
        "3951aefa4afd6fb836ab06468b1fc2a69fa75bd66ec2f5a0e08c4e32547681e3": [
            "https://mirror.bazel.build/nodejs.org/dist/v6.9.1/win-x64/node.lib",
            "http://nodejs.org/dist/v6.9.1/win-x64/node.lib",
        ],
    },
    sha256_urls_extract = {
        "d4eb161e4715e11bbef816a6c577974271e2bddae9cf008744627676ff00036a": [
            "https://mirror.bazel.build/nodejs.org/dist/v6.9.1/node-v6.9.1-linux-x64.tar.xz",
            "http://nodejs.org/dist/v6.9.1/node-v6.9.1-linux-x64.tar.xz",
        ],
    },
    strip_prefix = {
        "node-v6.9.1-darwin-x64.tar.xz": "node-v6.9.1-darwin-x64",
        "node-v6.9.1-linux-x64.tar.xz": "node-v6.9.1-linux-x64",
    },
    executable = [
        "node",
        "node.exe",
    ],
    default_visibility = ["//tensorflow/contrib/node:__subpackages__"],
)

Now let's say you want you have a Node program, e.g. tsc.js, which you want to turn into something you can bazel run //tensorflow/contrib/node:generate. One quick way you could do this in Bazel is by defining a macro in tensorflow/contrib/node/defs.bzl:

def node_binary(name, srcs, data=None, visibility=None, testonly=None, **kwargs):
  native.sh_binary(
      name = name,
      srcs = [name + ".sh"],
      data = srcs + data + ["@org_nodejs"],
      testonly = testonly,
      visibility = visibility,
      **kwargs
  )
  
  native.genrule(
      name = name + "_sh",
      srcs = [srcs[0]],
      outs = [name + ".sh"],
      cmd = "cat >$@ <<'EOF'\n" +
            "#!/bin/bash\n" +
            "NODE=external/org_nodejs/bin/node\n" +
            "if [[ -e external/org_nodejs/node.exe ]]; then\n" +
            "  NODE=external/org_nodejs/node.exe\n" +
            "fi\n" +
            "exec $${NODE} $(location " + srcs[0] + ") \"$$@\"\n" +
            "EOF",
      executable = True,
      testonly = testonly,
      visibility = ["//visibility:private"],
  )

Now for the fun part. I would write a single .js file (even if it had to be 30,000 lines long like tex.web) with zero dependencies other than the Node standard library. The inputs for this program would be ops.pbtxt and all the other pbtxt files in api_def/base_api. The output to this program would be exactly one gigantic C++ file that talks to TensorFlow C API and Node C++ Addon API based on this example.

load("//tensorflow/contrib/node:defs.bzl", "node_binary")
load("@domain_registry//java/google/registry/builddefs:zip_file.bzl", "zip_file")

node_binary(
    name = "generate",
    srcs = ["generate.js"],
    data = [
        "//tensorflow/core:ops/ops.pbtxt",
        "//tensorflow/core/api_def:base_api_def",
    ],
)

genrule(
    name = "api",
    srcs = [
        "//tensorflow/core:ops/ops.pbtxt",
        "//tensorflow/core/api_def:base_api_def",
    ],
    cmd = "$(location :generate) $(location api.cc) $(SRCS)",
    outs = ["api.cc"],
    tools = [":generate"],
)

zip_file(
    name = "tfnode",
    srcs = [
        "package.json",
        "README.md",
        "api.cc",
        "binding.gyp",
        "tfnode.js",
    ],
    mappings = {"tensorflow/contrib/node": "package"},
)

Then you bazel build //tensorflow/contrib/node:tfnode.zip and bam you've got your NodeJS project all bundled and ready for distribution to places like NPM.

If I wrote this (which I won't) it would be a barebones direct mapping of the TensorFlow API definitions. Then I would encourage our friends in the community to veneer the library. There's a diversity of visions out there on friendly modern high-level idiomatic JS and ML APIs, each catering to different use cases. However they could all share this binding in common.

Please note there are examples of where we already generate language bindings. See tensorflow/go/genop/main.go and tensorflow/go/op/generate.go for inspiration.

[lastmjs]

Looks like the TensorFlow team is making this a top priority now: https://js.tensorflow.org/faq/

[lastmjs]

We might want to move this discussion to here: tensorflow/tfjs#36

Progress on Node.js bindings to the C API will be tracked at that issue.

[nkreeger]

As update to this issue - we have open-sourced the Node.js binding for TFJS: https://github.com/tensorflow/tfjs-node

We are working hard at getting a proper NPM build and will release it soon!

[martinwicke]

I will close this issue. Please track tensorflow/tfjs and tensorflow/tfjs-node for further updates.

[nuchi]

Related and possibly of interest: I managed to get TF running in the browser via Webassembly. See https://humantoanimal.com for a demo; I will be providing more details in the future.

[lastmjs]

@nuchi, so did you compile the necessary TensorFlow code from the C API to WebAssembly? Or are you using TensorFlow.js?

[nuchi]

@lastmjs I explain in more detail in the link I provided. Short version: I added Webassembly as an XLA compilation target. I did not use Tensorflow.js in any way.

[huan]

@nuchi Great work! and I know another WebAssemble research on TensorFlow at here:
https://medium.com/@tomasreimers/compiling-tensorflow-for-the-browser-f3387b8e1e1c

[rchipka]

Glad to see that there's official progress on this. I'd love to have fast, parallel GPU compute power at my fingertips with the ease and composability of JS.

I started working on a NodeJS binding for TensorFlow a while ago, but a haven't had much free time to devote to it lately.

The concept is similar to @jart's suggested approach.

I had three goals in mind for the project:

1. Don't require building or installing tensorflow

Instead, it should download and use the pre-built, multi-platform python binaries and download any needed source files on the fly.

2. Don't require a complete C++ or JS reproduction or abstraction of the API

Instead, it should provide a complete 1-to-1 interface with the C API, providing convenient JS abstractions as much as possible.

3. Don't maintain the C API bindings by hand

Instead, it should use a swig script to map the core data structures between Tensorflow/stdc++/V8/node and the rest will follow.

---

I got pretty far along with this, but last I remember a was having issues with TF_Session related segfaults.

Right now it's just collecting dust, so if someone wants to jump in and help with this I'd gladly accept PRs.

[wt-huang]

Closing as this is resolved