Error when saving model using model.save #1246
Comments
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I encountered the same problem months ago. #1017 |
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Hi @AdrienDeverin, I just put the exact example from the TensorFlow.NET GitHub page to try out and face this problem. I attached the code again here for easy reference, and the error occurs at the last line, which is the using static Tensorflow.Binding;
using static Tensorflow.KerasApi;
using Tensorflow;
using Tensorflow.NumPy;
var layers = keras.layers;
// input layer
var inputs = keras.Input(shape: (32, 32, 3), name: "img");
// convolutional layer
var x = layers.Conv2D(32, 3, activation: "relu").Apply(inputs);
x = layers.Conv2D(64, 3, activation: "relu").Apply(x);
var block_1_output = layers.MaxPooling2D(3).Apply(x);
x = layers.Conv2D(64, 3, activation: "relu", padding: "same").Apply(block_1_output);
x = layers.Conv2D(64, 3, activation: "relu", padding: "same").Apply(x);
var block_2_output = layers.Add().Apply(new Tensors(x, block_1_output));
x = layers.Conv2D(64, 3, activation: "relu", padding: "same").Apply(block_2_output);
x = layers.Conv2D(64, 3, activation: "relu", padding: "same").Apply(x);
var block_3_output = layers.Add().Apply(new Tensors(x, block_2_output));
x = layers.Conv2D(64, 3, activation: "relu").Apply(block_3_output);
x = layers.GlobalAveragePooling2D().Apply(x);
x = layers.Dense(256, activation: "relu").Apply(x);
x = layers.Dropout(0.5f).Apply(x);
// output layer
var outputs = layers.Dense(10).Apply(x);
// build keras model
var model = keras.Model(inputs, outputs, name: "toy_resnet");
model.summary();
// compile keras model in tensorflow static graph
model.compile(optimizer: keras.optimizers.RMSprop(1e-3f),
loss: keras.losses.SparseCategoricalCrossentropy(from_logits: true),
metrics: new[] { "acc" });
// prepare dataset
var ((x_train, y_train), (x_test, y_test)) = keras.datasets.cifar10.load_data();
// normalize the input
x_train = x_train / 255.0f;
// training
model.fit(x_train[new Slice(0, 2000)], y_train[new Slice(0, 2000)],
batch_size: 64,
epochs: 10,
validation_split: 0.2f);
// save the model
model.save("./toy_resnet_model"); |
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Have you try with a direct path folder (folder need to be created before) ?
Example : @"C:\GitHub\TestTF\ResnetModel"
Normally you get .pb file in it after
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Thanks for your prompt response. I've tried to put a full path folder, but the problem remains. |
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It's really strange. I tried it myself an no problem appear. Everything go well. Try with this config (normally it doesn't matter, your seems good) :
My import : |
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Hi, I have tried your code but I failed to reproduce it. I ran it and everything seemed to go well. The only difference between our code is that I changed epoch to 1 and batch to 4 to make it faster to complete the training. I guess that doesn't matter. P.S. I was using the CPU redist package. |
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Hi @AdrienDeverin and @AsakusaRinne, thank you both for your help. Let me explain what exactly happened: I have 2 computers, A and B. I started trying the example code on computer A, where I created a new project with .NET Framework 4.8. Then I faced the problem described at the beginning. I tried different stuff as suggested by @AdrienDeverin but it didn't solve the problem. Later on, I created a new project based on .NET 8.0 on computer A, and it worked like a charm. I tried to replicate the solution on computer B, also with .NET 8 and all the same Nuget packages installed. It now gives me a different error on the Have you experienced this before? This is pretty confusing for me. Ps: this is the project properties for your reference. I'm using VS2022 V17.9.6 |
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I didn't manage to reproduce it on my PC. Could you please clone the repo and add project reference to it, so that a detailed trace back will be shown? |
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Me too, I tried to reproduce your bug, but it's working correctly on my computer... :/ Another idea to understand where the problem lies: since you have done what I said earlier, you could use the debug mode and see in the code step by step where you go (and compare with computer A)... |
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Hi all, thank you for your support. I've tried again with a fresh project on computer B based on .NET 8.0 in a local folder and it works perfectly now. I guess the previous problem on |
It's expected to support .NET framework 4.5. Could you please run with the tf.net repo and put the detailed traceback here if you'd like to dig on it? |
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I was figuring out a solution to make .NET Framework-based app work, but not sure if this is a bug or anything. Let me detail the process so that someone facing the same issue knows how to get through it.
How did I get it work:
When I checked the output debug folder, I noticed the size difference in the Tensorflow.Binding.dll and Tensorflow.Keras.dll between the original and the solution. Copying these two files from the updated solution folder to the previous project folder solve the error too. Thus, I guess there should be some differences in the Tensorflow.Binding.dll and Tensorflow.Keras.dll between the release NuGet packages and the repo. Do you have any idea on this @AsakusaRinne? |
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It might be the NuGut package is not up to date. |
Indeed doing a custom build with the official Repo solves the model.save() exception. After tinkering around I found two more structural alternative solutions: Option 1) Just add only the Tensorflow.Keras project from the Repo (after download/unpacking) to your own solution, and then reference that added (external) project from your own project in your own solution. That way all necessary dependencies (from both Tensorflow.Keras and Tensorflow.NET) will be included in your debug/release folders. alternative: Option 2) Create your own local NuGet packages from a fresh build:
Option 1) is easier but requires that you add the Repo Tensorflow.Keras project to every solution/project. Option 2) is cleaner as it's easily re-usable for new solutions/projects - it requires minimal installation (only the local Tensorflow.Keras NuGet package + tensorflow.dll ref) for new development. Thanks so much for putting me on the right trail for a solution. Of course it would be most wonderful if SciSharp could just resubmit a new working build as a package to NuGet - all these workarounds would be unnecessary. The Repo code itself seems to be fine. |
Description
Hi, I'm new to Tensorflow.net. I'm just playing around with the "Toy version of ResNet in Keras" example on the main page and got an error at the model.save("./toy_resnet_model");
C# threw an exception: System.InvalidOperationException: 'Collection was modified; enumeration operation may not execute.'
I tried to debug and trace the problem and it seems like the exception was thrown at some point within this function:
which is part of
which is part of
Package installed:
Any help would be appreciated! Thank you.
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