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  • replied
    Hey,

    I tried using the plugin for unreal version 4.23, the project loads up to 71% and then disappears. When I do a debug build from Visual Studio, I get the following error:

    Fatal Python error: Py_Initialize: unable to load the file system codec

    I have python 3.8 installed on my machine, do you know what is the source of this error or what can I do to make the plugin work?
    Thanks

    Leave a comment:


  • replied

    Originally posted by FAHR View Post
    How did you manage to upload those gifs?



    Insert image, paste url to e.g. imgur and do not retrieve locally.

    Originally posted by envenger View Post
    With the python plugin being dead, what's the plan next to upgrade this.

    I haven't had a chance to look at the UnrealEnginePython breaking changes for 4.24 yet, but will likely look into making the split between https://github.com/getnamo/machine-learning-remote-ue4 which would still use your local python but via socket.io transparently and https://github.com/getnamo/tensorflow-native-ue4 for native/inference focus.

    The remote is ready to use on e.g. windows systems, I need to squash a bug or two to make it run well on linux. The inference focused plugin needs BP api work.

    Leave a comment:


  • replied
    How did you manage to upload those gifs?

    Leave a comment:


  • replied
    With the python plugin being dead, what's the plan next to upgrade this.

    Leave a comment:


  • replied
    That's great! Congratulations!

    I'm looking forward to the native plugin. Just getting into ML. It's a tough journey.

    Leave a comment:


  • replied
    I'm happy to announce that the Tensorflow plugin was selected as a MegaGrants recipient: https://www.unrealengine.com/en-US/b...estone-in-2019

    This should help make the multi-variant component refactor (tracked at https://github.com/getnamo/tensorflow-ue4/issues/53) a reality. The remote variant has already been implemented and released, we now just have the native variant currently outstanding. Keep an eye out on the issue to track progress for this upgrade. Let me know if there is some specific API you'd be interested in having in either case.

    Leave a comment:


  • replied
    getnamo Thanks for your insight.

    Originally posted by getnamo View Post

    You would probably be interested in models like gpt-2 https://openai.com/blog/better-language-models/ which now has the full 1.5B parameter model released: https://openai.com/blog/gpt-2-1-5b-release/ (it's super heavy though). This can predict fairly decently additional text based on a snippet of input text. It can even answer some questions about a text (reading comprehension).

    Below was an example I used for testing reading comprehension. Everything below SAMPLE 1 is generated by gpt-2 in response to the text above it.

    Leave a comment:


  • replied
    Originally posted by TechLord View Post
    This is awesome. I want to train different with AIs with different Game Lore/World Datasets to drive NPC Chatbots. I'm open to any conversation on this topic.
    You would probably be interested in models like gpt-2 https://openai.com/blog/better-language-models/ which now has the full 1.5B parameter model released: https://openai.com/blog/gpt-2-1-5b-release/ (it's super heavy though). This can predict fairly decently additional text based on a snippet of input text. It can even answer some questions about a text (reading comprehension).

    Below was an example I used for testing reading comprehension. Everything below SAMPLE 1 is generated by gpt-2 in response to the text above it.

    Leave a comment:


  • replied
    Machine Learning Remote Plugin (remote variant of tensorflow-ue4) Released.

    The remote variant of the plugin is now functional, check out: https://github.com/getnamo/machine-learning-remote-ue4 for the plugin and https://github.com/getnamo/ml-remote-server for the complement server. The plugin should be usable in a much wider variety of platforms (anywhere the socket.io plugin can be used so: win, linux, mac, android, ios) and you can host your server part anywhere that supports python 3 (typically linux, win, mac).

    If you wanted a lighter client or a more flexible backend this should be the one to check out. Let me know if you use it and if you're missing some API.

    Leave a comment:


  • replied
    This is awesome. I want to train different with AIs with different Game Lore/World Datasets to drive NPC Chatbots. I'm open to any conversation on this topic.

    Leave a comment:


  • replied
    Plugin Architecture Update
    Working on an API refactor for this plugin to open up more backends and development environments, see https://github.com/getnamo/tensorflow-ue4/issues/53 for the parent issue tracking various parts of this effort.

    The general idea is that you should be able to easily boot up a server (local or truly remote) and do remote dev work as if it was running UnrealEnginePython allowing you to train in more typical linux environments with no restrictions on either machine learning library or versions. The matching unreal frontend would be very lightweight and should be available on most os platforms. This should reduce setup, mismatch, and version headaches. The tensorflow-ue4 (unrealenginepython environment) plugin would still be one of the possible backends and the api will be very similar to the old one, just with the option of swapping it for a remote or a native variant without other code change.

    In addition there is planned work on the tensorflow-native-ue4 plugin to use similar base api as the remote/python one, but with an inference focus. This would enable you to package e.g. .pb file and run inference on your trained model at native speeds. There is a possibility to expand this API to support more than inference directly from BP, but it wouldn't be the focus at this time.

    If you're using the library, feedback on this new architecture work is welcome as I want to make sure it covers use cases you'd be interested in.
    Last edited by getnamo; 12-02-2019, 03:14 PM.

    Leave a comment:


  • replied
    Originally posted by jimmyw_404 View Post
    Love your plugin. I'm thinking about making something quite similar that merely visualizes different information from TensorFlow in an Unreal Engine 3D world.

    I don't know exactly how it'll look yet, but some combination of these two videos:

    https://www.youtube.com/watch?v=3JQ3hYko51Y

    https://www.youtube.com/watch?v=AgkfIQ4IGaM

    I've looked pretty hard and haven't seen anything close to what I'm thinking of building. If I move forward with it I think your plugin will help jumpstart my progress, thanks!
    Sounds like a cool project! The only thing I'm aware of that is similar using this plugin is this german thesis work by Marcel Bock https://www.semanticscholar.org/pape...eefdf65d362b10, article: https://www.dlr.de/sc/en/desktopdefa...74_read-53313/

    Might want to take a look for inspiration.

    Leave a comment:


  • replied
    Originally posted by getnamo View Post

    The plugin is using an embedded python setup, so a separate tensorflow installation is managed by the plugin. What you do need to do is ensure you've installed the cuda and cudNN pre-requisites for gpu https://www.tensorflow.org/install/gpu#windows_setup. Please check https://github.com/getnamo/tensorflo...llation--setup
    Love your plugin. I'm thinking about making something quite similar that merely visualizes different information from TensorFlow in an Unreal Engine 3D world.

    I don't know exactly how it'll look yet, but some combination of these two videos:

    https://www.youtube.com/watch?v=3JQ3hYko51Y

    https://www.youtube.com/watch?v=AgkfIQ4IGaM

    I've looked pretty hard and haven't seen anything close to what I'm thinking of building. If I move forward with it I think your plugin will help jumpstart my progress, thanks!

    Leave a comment:


  • replied
    I managed to get a TF2 version of addExample.py working, but I'm a bit confused on how to correctly implement
    the operation self.c = self.a + self.b

    Code:
    import tensorflow as tf
      import unreal_engine as ue
      from TFPluginAPI import TFPluginAPI
        classExampleAPI(TFPluginAPI):
        #expected optional api: setup your model for training
      defonSetup(self):
        self.a = tf.Variable([0.0], tf.float32)
      self.b = tf.Variable([0.0], tf.float32)
        self.op = tf.Variable(True, tf.bool)
      pass
      
      #expected optional api: parse input object and return a result object, which will be converted to json for UE4
      defonJsonInput(self, jsonInput):
      
      print(jsonInput)
        self.a = tf.dtypes.cast(jsonInput['a'], tf.float32)
      self.b = tf.dtypes.cast(jsonInput['b'], tf.float32)
        ifself.op:
      return tf.add(self.a, self.b).numpy().tolist()
      
      else:
      return tf.subtract(self.a, self.b).numpy().tolist()
        
      
        #custom function to change the op
      defchangeOperation(self, type):
      if(type=='+'):
      self.op =True
        elif(type=='-'):
      self.op =False
        defgetVersion(self, jsonInput):
                ver = tf.__version__
      print(ver)
      return("GPU Available: ", tf.test.is_gpu_available())
     
    #expected optional api: start training your network
      defonBeginTraining(self):
      pass
       
      #NOTE: this is a module function, not a class function. Change your CLASSNAME to reflect your class
      #required function to get our api
      defgetApi():
      #return CLASSNAME.getInstance()
      return ExampleAPI.getInstance()

    Leave a comment:


  • replied
    Originally posted by StevePeters View Post
    I'm getting an issue of ImportError: DLL load failed: The specified module could not be found. similar to getnamo above, however I have tensorflow gpu successfully installed on my computer. I installed tensorflow with Anaconda. Could that have something to do with the plugin not finding it?
    The plugin is using an embedded python setup, so a separate tensorflow installation is managed by the plugin. What you do need to do is ensure you've installed the cuda and cudNN pre-requisites for gpu https://www.tensorflow.org/install/gpu#windows_setup. Please check https://github.com/getnamo/tensorflo...llation--setup

    Leave a comment:

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