Tensorflow not loading in Docker Container

Question

I am trying to deploy a web application with ML.NET to a docker container (it works no problem when I run it in IIS Express) but when I run it in the docker file that was created by visual studio, I get the following error saying that tensor flow was not found:

System.Reflection.TargetInvocationException: Exception has been thrown by the target of an invocation. ---> System.Reflection.TargetInvocationException: Exception has been thrown by the target of an invocation. ---> System.Reflection.TargetInvocationException: Exception has been thrown by the target of an invocation. ---> System.DllNotFoundException: Unable to load shared library 'tensorflow' or one of its dependencies. In order to help diagnose loading problems, consider setting the LD_DEBUG environment variable: libtensorflow: cannot open shared object file: No such file or directory at Tensorflow.c_api.TF_NewGraph() at Tensorflow.Graph..ctor() at Microsoft.ML.TensorFlow.TensorFlowUtils.LoadTFSession(IExceptionContext ectx, Byte[] modelBytes, String modelFile) at Microsoft.ML.Vision.ImageClassificationModelParameters..ctor(IHostEnvironment env, ModelLoadContext ctx) at Microsoft.ML.Vision.ImageClassificationModelParameters.Create(IHostEnvironment env, ModelLoadContext ctx) --- End of inner exception stack trace --- at System.RuntimeMethodHandle.InvokeMethod(Object target, Object[] arguments, Signature sig, Boolean constructor, Boolean wrapExceptions) at System.Reflection.RuntimeMethodInfo.Invoke(Object obj, BindingFlags invokeAttr, Binder binder, Object[] parameters, CultureInfo culture) at System.Reflection.MethodBase.Invoke(Object obj, Object[] parameters) at Microsoft.ML.Runtime.ComponentCatalog.LoadableClassInfo.CreateInstanceCore(Object[] ctorArgs) at Microsoft.ML.Runtime.ComponentCatalog.LoadableClassInfo.CreateInstance(IHostEnvironment env, Object args, Object[] extra) at Microsoft.ML.Runtime.ComponentCatalog.TryCreateInstance[TRes](IHostEnvironment env, Type signatureType, TRes& result, String name, String options, Object[] extra) at Microsoft.ML.Runtime.ComponentCatalog.TryCreateInstance[TRes,TSig](IHostEnvironment env, TRes& result, String name, String options, Object[] extra) at Microsoft.ML.ModelLoadContext.TryLoadModelCore[TRes,TSig](IHostEnvironment env, TRes& result, Object[] extra) at Microsoft.ML.ModelLoadContext.TryLoadModel[TRes,TSig](IHostEnvironment env, TRes& result, RepositoryReader rep, Entry ent, String dir, Object[] extra) at Microsoft.ML.ModelLoadContext.LoadModel[TRes,TSig](IHostEnvironment env, TRes& result, RepositoryReader rep, Entry ent, String dir, Object[] extra) at Microsoft.ML.ModelLoadContext.LoadModelOrNull[TRes,TSig](IHostEnvironment env, TRes& result, RepositoryReader rep, String dir, Object[] extra) at Microsoft.ML.ModelLoadContext.LoadModelOrNull[TRes,TSig](IHostEnvironment env, TRes& result, String name, Object[] extra) at Microsoft.ML.ModelLoadContext.LoadModel[TRes,TSig](IHostEnvironment env, TRes& result, String name, Object[] extra) at Microsoft.ML.Data.MulticlassPredictionTransformer.Create(IHostEnvironment env, ModelLoadContext ctx)

here is the docker file for reference:

FROM mcr.microsoft.com/dotnet/core/aspnet:3.1-buster-slim AS base
WORKDIR /app
EXPOSE 80
EXPOSE 443

FROM mcr.microsoft.com/dotnet/core/sdk:3.1-buster AS build
WORKDIR /src
COPY ["Hotdogapp/Server/Hotdogapp.Server.csproj", "Hotdogapp/Server/"]
COPY ["Hotdogapp/Shared/Hotdogapp.Shared.csproj", "Hotdogapp/Shared/"]
COPY ["Hotdogapp/Client/Hotdogapp.Client.csproj", "Hotdogapp/Client/"]
RUN dotnet restore "Hotdogapp/Server/Hotdogapp.Server.csproj"
COPY . .
WORKDIR "/src/Hotdogapp/Server"
RUN dotnet build "Hotdogapp.Server.csproj" -c Release -o /app/build

FROM build AS publish
RUN dotnet publish "Hotdogapp.Server.csproj" -c Release -o /app/publish


FROM base AS final
WORKDIR /app
COPY --from=publish /app/publish .
ENTRYPOINT ["dotnet", "Hotdogapp.Server.dll"]

is there a special image I should be using for ML.NET/ TensorFlow?

Which version of SciSharp.TensorFlow.Redist do you have referenced? — halllo
– halllo, Commented Aug 12, 2020 at 10:10
just updated to 2.3.0 and 1.5.1 for Microsoft.ML and still getting the same error — Tacot
– Tacot, Commented Aug 13, 2020 at 16:03

user9096829 · Accepted Answer · 2020-10-08 02:39:00Z

1

The error is thrown because it can't find one of the dependencies libtensorflow.so is using. To find out which dependency is missing, you can go to the runtime folder (/bin/${configuration}/${framework}/runtime/linux-x64/native) and try the following cmd, which should tell you the missing dependeny.

ldd libtensorflow.so

To solve the issue, you can simply install the missing dependency, or use a lower version of tf runtime, (for example redist.tensorflow 1.*) works for me. You can also raise an issue in Tensorflow.Net, where you could get better answer.

edited Oct 8, 2020 at 2:39

answered Oct 7, 2020 at 23:44

user9096829

394 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

Matt Thalman · Accepted Answer · 2020-08-03 19:26:30Z

0

TensorFlow is a python package so you'll need to install that into your Docker image as a dependency. Try adding this to the final stage of the Dockerfile:

RUN apt-get update \
    && apt-get install -y \
        python3-pip \
    && rm -rf /var/lib/apt/lists/*
RUN ln -sf /usr/bin/python3 /usr/bin/python \
    && python -m pip install tensorflow

answered Aug 3, 2020 at 19:26

Matt Thalman

4,0342 gold badges20 silver badges31 bronze badges

Collectives™ on Stack Overflow

Tensorflow not loading in Docker Container

2 Answers 2

Comments

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Related