layers.Conv2D( ) -> Running this function kills the Python Kernel

import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' import tensorflow as tf from tensorflow import keras from tensorflow.keras import layers from tensorflow.keras.datasets import cifar10 tf.__version__ # outputs -> '2.8.0' # Normalizing the data (x_train, y_train), (x_test, y_test) = cifar10.load_data() x_train = x_train.astype("float32") / 255.0 x_test = x_test.astype("float32") / 255.0 # defining Model using Functional api def my_model(): inputs = keras.Input(shape=(32,32,3)) x = layers.Conv2D(32,3)(inputs) x = layers.BatchNormalization()(x) x = keras.activations.relu(x) x = layers.MaxPooling2D()(x) x = layers.Conv2D(64,5,padding="same")(x) x = layers.BatchNormalization()(x) x = keras.activations.relu(x) x = layers.Conv2D(128,3)(x) x = layers.BatchNormalization()(x) x = keras.activations.relu(x) x = layers.Flatten()(x) x = layers.Dense(64, activation='relu')(x) outputs = layers.Dense(10)(x) model = keras.Model(inputs= inputs, outputs=outputs) return model # Building the model model = my_model() # Compiling the model model.compile( loss=keras.losses.SparseCategoricalCrossentropy(from_logits = True), optimizer = keras.optimizers.Adam(learning_rate=3e-4), metrics=['accuracy'], ) # running the model model.fit(x_train, y_train, batch_size= 64, epochs=10, verbose =2) # testing the model model.evaluate(x_test, y_test, batch_size = 1, verbose =2) 

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I tried this above code on both Jupyter notebook & VSCODE.

On both occasions, its killing the python kernel. Below is the error message screen shot from VS code.

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Error message from VS Code

when i run a simple MLP & also deep MLP on MNIST digit dataset. it works fine even when i had more than 10 million parameters. So I am guessing its definitely not the VRAM because for the above CNN model parameters from model.summary( ) = ~400K.

This problem occurs only when i use Conv2D function.

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Using tensor flow 2.8.0

CPU: i7 – 7920hq

GPU: Quadro P4000 8 GB

RAM: 64GB.

OS: Win 11 pro

Using latest nvidia driver, cuda tool kit, cudnn.

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Installed tensorlow using the tutorial below.

https://github.com/jeffheaton/t81_558_deep_learning/blob/master/install/manual_setup2.ipynb

(found from a youtube video) https://www.youtube.com/watch?v=OEFKlRSd8Ic

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I would appreciate if someone can help me fix this issue.