I installed TensorFlow (version 2.7.0)as per the instructions here. And I ran an example Keras model (https://keras.io/examples/vision/3D_image_classification). Here is the full Colab code (https://colab.research.google.com/github/keras-team/keras-io/blob/master/examples/vision/ipynb/3D_image_classification.ipynb).
The error occurs when I attempt model training:
# Compile model.
initial_learning_rate = 0.0001
lr_schedule = keras.optimizers.schedules.ExponentialDecay(
initial_learning_rate, decay_steps=100000, decay_rate=0.96, staircase=True
)
model.compile(
loss="binary_crossentropy",
optimizer=keras.optimizers.Adam(learning_rate=lr_schedule),
metrics=["acc"],
)
# Define callbacks.
checkpoint_cb = keras.callbacks.ModelCheckpoint(
"3d_image_classification.h5", save_best_only=True
)
early_stopping_cb = keras.callbacks.EarlyStopping(monitor="val_acc", patience=15)
# Train the model, doing validation at the end of each epoch
epochs = 100
model.fit(
train_dataset,
validation_data=validation_dataset,
epochs=epochs,
shuffle=True,
verbose=2,
callbacks=[checkpoint_cb, early_stopping_cb],
)
The error log is quite long, so I attached it as a txt file. The error occurs when I attempt to train the model using the GPU. The error does not happen when I specify with tf.device('/cpu:0'):, so CPU training appears to be fine, and returns similar results when cross-checked with the results obtained on Google Colab. This appears to be an issue specifically due to tensorflow-metal. My tensorflow-metal version is 0.3.0.
