[Help needed] InvalidArgumentError when running TensorFlow codes - TensorFlow Developer Certificate in 2023: Zero to Mastery

[shaeka]

Was following through TensorFlow Developer Certificate in 2023: Zero to Mastery using M1 Macbook Pro and ran into an error in part 166. Building Model 1 (with a data augmentation layer and 1% of training data). Help needed!

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Code:

Setup input shape and base model, freezing the base model layers

input_shape = (224, 224, 3)
base_model = tf.keras.applications.EfficientNetB0(include_top=False)
base_model.trainable = False

Create input layer

inputs = layers.Input(shape=input_shape, name='input_layer')

Add in data augmentation Sequential model as a layer

x = data_augmentation(inputs)

Give base_model the inputs (after augmentation) and don't train it

x = base_model(x, training=False)

Pool output features of the base model

x = layers.GlobalAveragePooling2D(name='global_average_pooling_layer')(x)

Put a dense layer on as the output

outputs = layers.Dense(10, activation='softmax', name='output_layer')(x)

Make a model using the inputs and outputs

model_1 = keras.Model(inputs, outputs)

Compile the model

model_1.compile(loss='categorical_crossentropy',
optimizer=tf.keras.optimizers.Adam(),
metrics=['accuracy'])

Fit the model

history_1_percent = model_1.fit(train_data_1_percent,
epochs=5,
steps_per_epoch=len(train_data_1_percent),
validation_data=test_data,
validation_steps=int(0.25 * len(test_data)),
# Track model training logs
callbacks=[create_tensorboard_callback(dir_name='transfer_learning',
experiment_name='1_percent_data_aug')])

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Error:
InvalidArgumentError Traceback (most recent call last)
Input In [166], in <cell line: 30>()
25 model_1.compile(loss='categorical_crossentropy',
26 optimizer=tf.keras.optimizers.Adam(),
27 metrics=['accuracy'])
29 ### Fit the model
---> 30 history_1_percent = model_1.fit(train_data_1_percent,
31 epochs=5,
32 steps_per_epoch=len(train_data_1_percent),
33 validation_data=test_data,
34 validation_steps=len(test_data),
35 # Track model training logs
36 callbacks=[create_tensorboard_callback(dir_name='transfer_learning',
37 experiment_name='1_percent_data_aug')])

File ~/tensorflow-test/env/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67, in filter_traceback..error_handler(*args, **kwargs)
65 except Exception as e: # pylint: disable=broad-except
66 filtered_tb = _process_traceback_frames(e.traceback)
---> 67 raise e.with_traceback(filtered_tb) from None
68 finally:
69 del filtered_tb

File ~/tensorflow-test/env/lib/python3.8/site-packages/tensorflow/python/eager/execute.py:54, in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
52 try:
53 ctx.ensure_initialized()
---> 54 tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
55 inputs, attrs, num_outputs)
56 except core._NotOkStatusException as e:
57 if name is not None:

InvalidArgumentError: Cannot assign a device for operation model_18/data_augmentation/random_rotation_1/stateful_uniform/RngReadAndSkip: Could not satisfy explicit device specification '' because the node {{colocation_node model_18/data_augmentation/random_rotation_1/stateful_uniform/RngReadAndSkip}} was colocated with a group of nodes that required incompatible device '/job:localhost/replica:0/task:0/device:GPU:0'. All available devices [/job:localhost/replica:0/task:0/device:CPU:0, /job:localhost/replica:0/task:0/device:GPU:0].
Colocation Debug Info:
Colocation group had the following types and supported devices:
Root Member(assigned_device_name_index_=2 requested_device_name_='/job:localhost/replica:0/task:0/device:GPU:0' assigned_device_name_='/job:localhost/replica:0/task:0/device:GPU:0' resource_device_name_='/job:localhost/replica:0/task:0/device:GPU:0' supported_device_types_=[CPU] possible_devices_=[]
RngReadAndSkip: CPU
_Arg: GPU CPU

Colocation members, user-requested devices, and framework assigned devices, if any:
model_18_data_augmentation_random_rotation_1_stateful_uniform_rngreadandskip_resource (_Arg) framework assigned device=/job:localhost/replica:0/task:0/device:GPU:0
model_18/data_augmentation/random_rotation_1/stateful_uniform/RngReadAndSkip (RngReadAndSkip)

 [[{{node model_18/data_augmentation/random_rotation_1/stateful_uniform/RngReadAndSkip}}]] [Op:__inference_train_function_329630]