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    Sam Hodge
    @samhodge
    Sounds great
    but I am not sure if I understand how to do that
    how can you load on the params if the width and height are not known
    so when you do x = mx.sym.var('data')
    y = style_model(x)
    Sam Hodge
    @samhodge
    can you also do some sort of magic like a= mx.sym.var('width'), b=mx.sym.var('height') y=style_model(x,height=a,width=b)
    is that what you mean?
    Anirudh Subramanian
    @anirudh2290
    yes
    Sam Hodge
    @samhodge
    I am honestly a bit of a noob
    Anirudh Subramanian
    @anirudh2290
    i am also a noob with gluon
    Sam Hodge
    @samhodge
    its all good you learn by making mistakes
    let me try this out.
    Anirudh Subramanian
    @anirudh2290
    but with symbolic api you just use placeholders for data, and then bind it to the data at the end, i think this should be possible with gluon too
    Anirudh Subramanian
    @anirudh2290
    apache/incubator-mxnet#6087 you probably need something like this
    Sam Hodge
    @samhodge
    I am hoping I can work out how to get the width and height as symbols to the network
    Sam Hodge
    @samhodge
    I think this relates to my issue
    Sam Hodge
    @samhodge
    @
    Anirudh Subramanian
    @anirudh2290
    @samhodge this should help you
    apache/incubator-mxnet#9893
    Sam Hodge
    @samhodge
    thanks I need to go a few steps back at the moment.
    it seems that the training the model that I am trying to serialise as a symbolic network doesnt work without any modifications
    I will put in a ticket now about this issue
    Sam Hodge
    @samhodge
    apache/incubator-mxnet#9989
    So I would be happy with a fixed resolution for now, but I cannot even get that working.
    Sam Hodge
    @samhodge
    @zhanghang1989 do you have an opinion?
    Lutz Roeder
    @lutzroeder

    Screen Shot 2018-03-07 at 8.23.49 PM.png

    Netron now supports MXNet -symbol.json models. Feedback is welcome.

    Anirudh Subramanian
    @anirudh2290
    @lutzroeder awesome thanks a lot ! i am not sure there are enough people from the community here. i will post this in the slack channel. i know that some people have asked for this in the community.
    ThomasDelteil
    @ThomasDelteil
    Thanks @lutzroeder, really cool, I'll use netron in my next talk to show the model architecture ! Just tried it out with the Crepe model, I am just wondering what makes a convolution show as dilates=(1,) rather than just hiding the dilation factor? (I am assuming dilates=(1,) is the same as no dilation?)
    Lutz Roeder
    @lutzroeder
    @ThomasDelteil The default for dilate is (1,1). Any insights if (1,) is some special encoding are welcome. Currently the app shows the values present in the file. It filters defaults for other formats but they have to be added to the operator file as the app doesn’t depend on the MXNet runtime directly. Feel free to open an issues and will have a look.
    ThomasDelteil
    @ThomasDelteil
    I see, thanks @lutzroeder
    Lutz Roeder
    @lutzroeder
    @ThomasDelteil Added a few heuristics for some common defaults and pushed an update.
    ThomasDelteil
    @ThomasDelteil
    awesome :) I can see the dilate is hidden now :+1:
    nebw
    @nebw
    Hi, I'm trying to compile a mxnet model using NNVM as described here: http://nnvm.tvmlang.org/tutorials/from_mxnet.html#sphx-glr-tutorials-from-mxnet-py Everything works fine, except when I'm trying to compile with cuda as target with batchsize > 1. All NNVM tutorials and examples I could find also only use batchsize 1. The error is: RuntimeError: Batch size: 32 is too large for this schedule (topi/cuda/conv2d_nchw.py", line 527, in schedule_conv2d_nchw)
    Aaron Markham
    @aaronmarkham
    hey, anyone know what happened to data.mxnet.io?
    Arunkumar Venkataramanan
    @ArunkumarRamanan
    TenzTensor Vs MXNet Who is the winner?
    TensorFlow Vs MXNet Who is the winner?
    Alexander Konovalov
    @alexknvl
    depends on the judge
    my roommate had some pretty negative feedback about mxnet recently, which in my experience applies to the majority of such frameworks - non-existent or incomprehensible error reporting
    Ray Zhang
    @OneRaynyDay
    Hi there. I am currently contributing to mxnet on behalf of airbnb. For questions and discussion about development, should I be chatting in here(gitter), or in the slack channel?
    Anton Chernov
    @lebeg
    Wherever you prefer. In general you can use
    Bob Poekert
    @bobpoekert
    calling keras.backend.conv2d with the mxnet backend in a loss function gives me "MXNet Backend: Cannot automatically infer shape for convolution operator.Please provide input shape. Given input shape"
    is there some way to manually specify the input shape?
    AK
    @akuz
    I've built MXNet from source yesterday, and I really want to use it from my C++ project. But I find it unreasonably complicated to find out how to link to it properly, so that my app can find all the header files and all the compiled libraries. I am using cmake. Can anyone recommend a good tutorial/example? I've been searching and trying for two days without success.
    Anton Chernov
    @lebeg
    @akuz Now it is indeed very complicated to use the C++ module of MXNet because of multiple reasons including linking. The most simple way I see is using the c_api.h directly - it has all the needed functionality and is used by all language bindings. You can see an example of using the inference API in the (image-classification) example.
    khaotik
    @khaotik
    Hi, all. What's the right way send/recv tensors across nodes over network? I guess I can hack some zmq sockets together, but is there a standard way to do it?
    khaotik
    @khaotik
    For my use case, it's about separating data production / training pipeline. I'm producing synthetic data on the producer node and sending them to the training node.
    Steffen Rochel
    @srochel
    I'm suggesting to move MXNet related discussions to https://discuss.mxnet.io/ and ASF MXNet Slack channel. I'm offering to add you to ASF MXNet Slack channel (if your email is visible), but let me know if you are not interested or send request to dev@mxnet.apache.org to be added to ASF MXNet Slack channel. You also have the opportunity to subscribe to dev@mxnet.apache.org and user@mxnet.apache.org (more details as well on http://mxnet.incubator.apache.org/community/contribute.html). Looking forward to our collaboration.
    sam-h-bean
    @sam-h-bean
    I have some questions about the Scala API for the Symbol library
    I'm trying to figure out how to do something like this https://github.com/ufoym/mxnet/blob/master/example/vae/VAE.py#L83 however it seems the scala symbol api does not allow the mixing of symbols and constants like the python library does.
    It seems like if I want to use constants in my loss functions I'm going to have to have a very large argsDict when I go to train. Is there a better way>?