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InvalidArgumentError: Graph execution error - Try to implement FCN

I'm a beginner in the world of neural networks and I have a Fully-Convolutional Neural Network for segmentation.
The model's architecture is the following:
seg_model = Sequential()
seg_model.add(Conv2D(40, (3,3), input_shape=(16,16, 3), activation="relu", padding="same"))
seg_model.add(Conv2D(20, (3,3), activation="relu", padding="same"))
seg_model.add(Dropout(0.3))
seg_model.add(Conv2D(1, (3,3), activation="sigmoid", padding="same"))
seg_model.compile(optimizer="rmsprop", loss="binary_crossentropy", metrics=["accuracy", "mae"])
After I implemented the input generators for data augmentation and tried to train the model, received an InvalidArgumentError: Graph execution error.
How can I solve this problem?
Input generators:
seg_datagen_params = {
'rotation_range' : 90,
'horizontal_flip': True,
'vertical_flip': True,
'fill_mode': 'constant',
'zoom_range': 0.4
}
seg_datagen = ImageDataGenerator(**seg_datagen_params)
seg_train_input = seg_datagen.flow(x_seg_train, batch_size=64, seed=1)
seg_train_output = seg_datagen.flow(y_seg_train, batch_size=64, seed=1)
seg_val_input = seg_datagen.flow(x_seg_val, batch_size=64, seed=2)
seg_val_output = seg_datagen.flow(y_seg_val, batch_size=64, seed=2)
train_seg_generator = zip(seg_train_input, seg_train_output)
val_seg_generator = zip(seg_val_input, seg_val_output)
Model training for segmentation:
earlystopping_callback = tf.keras.callbacks.EarlyStopping(monitor='val_loss', patience=10)
history = seg_model.fit_generator(generator=train_seg_generator, validation_data=val_seg_generator, epochs=200, verbose=1, callbacks=[earlystopping_callback])
InvalidArgumentError: Graph execution error:
Epoch 1/200
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:5: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.
"""
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
<ipython-input-86-b8831b0614dc> in <module>()
3 earlystopping_callback = tf.keras.callbacks.EarlyStopping(monitor='val_loss', patience=10)
4
----> 5 history = seg_model.fit_generator(generator=train_seg_generator, validation_data=val_seg_generator, epochs=200, verbose=1, callbacks=[earlystopping_callback])
6
7 tr_losses = history.history['loss']
2 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
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: Graph execution error:
Detected at node 'binary_crossentropy/logistic_loss/mul' defined at (most recent call last):
File "/usr/lib/python3.7/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/usr/local/lib/python3.7/dist-packages/traitlets/config/application.py", line 846, in launch_instance
app.start()
File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelapp.py", line 499, in start
self.io_loop.start()
File "/usr/local/lib/python3.7/dist-packages/tornado/platform/asyncio.py", line 132, in start
self.asyncio_loop.run_forever()
File "/usr/lib/python3.7/asyncio/base_events.py", line 541, in run_forever
self._run_once()
File "/usr/lib/python3.7/asyncio/base_events.py", line 1786, in _run_once
handle._run()
File "/usr/lib/python3.7/asyncio/events.py", line 88, in _run
self._context.run(self._callback, *self._args)
File "/usr/local/lib/python3.7/dist-packages/tornado/platform/asyncio.py", line 122, in _handle_events
handler_func(fileobj, events)
File "/usr/local/lib/python3.7/dist-packages/tornado/stack_context.py", line 300, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 577, in _handle_events
self._handle_recv()
File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 606, in _handle_recv
self._run_callback(callback, msg)
File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 556, in _run_callback
callback(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/tornado/stack_context.py", line 300, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 233, in dispatch_shell
handler(stream, idents, msg)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/ipkernel.py", line 208, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/zmqshell.py", line 537, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2718, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2822, in run_ast_nodes
if self.run_code(code, result):
File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2882, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-84-b8831b0614dc>", line 5, in <module>
history = seg_model.fit_generator(generator=train_seg_generator, validation_data=val_seg_generator, epochs=200, verbose=1, callbacks=[earlystopping_callback])
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 2223, in fit_generator
initial_epoch=initial_epoch)
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1384, in fit
tmp_logs = self.train_function(iterator)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1021, in train_function
return step_function(self, iterator)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1010, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1000, in run_step
outputs = model.train_step(data)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 860, in train_step
loss = self.compute_loss(x, y, y_pred, sample_weight)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 919, in compute_loss
y, y_pred, sample_weight, regularization_losses=self.losses)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/compile_utils.py", line 201, in __call__
loss_value = loss_obj(y_t, y_p, sample_weight=sw)
File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 141, in __call__
losses = call_fn(y_true, y_pred)
File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 245, in call
return ag_fn(y_true, y_pred, **self._fn_kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 1932, in binary_crossentropy
backend.binary_crossentropy(y_true, y_pred, from_logits=from_logits),
File "/usr/local/lib/python3.7/dist-packages/keras/backend.py", line 5247, in binary_crossentropy
return tf.nn.sigmoid_cross_entropy_with_logits(labels=target, logits=output)
Node: 'binary_crossentropy/logistic_loss/mul'
required broadcastable shapes
[[{{node binary_crossentropy/logistic_loss/mul}}]] [Op:__inference_train_function_25457]

model.fit gives me Graph execution error. How do I solve?

I am new to image processing and machine learning in python. I have been trying to execute a model in google colab using inceptionv3 but i am stuck at fitting the model.
r = model.fit(
training_set,
validation_data=test_set,
epochs=10,
steps_per_epoch=len(training_set),
validation_steps=len(test_set)
)
it is showing me the below errors
Epoch 1/10
---------------------------------------------------------------------------
UnimplementedError Traceback (most recent call last)
<ipython-input-24-c27d8fba63ce> in <module>()
6 epochs=10,
7 steps_per_epoch=len(training_set),
----> 8 validation_steps=len(test_set)
9 )
1 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
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:
UnimplementedError: Graph execution error:
Detected at node 'model/conv2d/Conv2D' defined at (most recent call last):
File "/usr/lib/python3.7/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/usr/local/lib/python3.7/dist-packages/traitlets/config/application.py", line 846, in launch_instance
app.start()
File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelapp.py", line 499, in start
self.io_loop.start()
File "/usr/local/lib/python3.7/dist-packages/tornado/platform/asyncio.py", line 132, in start
self.asyncio_loop.run_forever()
File "/usr/lib/python3.7/asyncio/base_events.py", line 541, in run_forever
self._run_once()
File "/usr/lib/python3.7/asyncio/base_events.py", line 1786, in _run_once
handle._run()
File "/usr/lib/python3.7/asyncio/events.py", line 88, in _run
self._context.run(self._callback, *self._args)
File "/usr/local/lib/python3.7/dist-packages/tornado/platform/asyncio.py", line 122, in _handle_events
handler_func(fileobj, events)
File "/usr/local/lib/python3.7/dist-packages/tornado/stack_context.py", line 300, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 577, in _handle_events
self._handle_recv()
File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 606, in _handle_recv
self._run_callback(callback, msg)
File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 556, in _run_callback
callback(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/tornado/stack_context.py", line 300, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 233, in dispatch_shell
handler(stream, idents, msg)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/ipkernel.py", line 208, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/zmqshell.py", line 537, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2718, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2822, in run_ast_nodes
if self.run_code(code, result):
File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2882, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-20-8cba7706098f>", line 12, in <module>
validation_steps=validation_data
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1409, in fit
tmp_logs = self.train_function(iterator)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1051, in train_function
return step_function(self, iterator)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1040, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1030, in run_step
outputs = model.train_step(data)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 889, in train_step
y_pred = self(x, training=True)
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 490, in __call__
return super().__call__(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py", line 1014, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 92, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py", line 459, in call
inputs, training=training, mask=mask)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py", line 596, in _run_internal_graph
outputs = node.layer(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py", line 1014, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 92, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/layers/convolutional/base_conv.py", line 250, in call
outputs = self.convolution_op(inputs, self.kernel)
File "/usr/local/lib/python3.7/dist-packages/keras/layers/convolutional/base_conv.py", line 232, in convolution_op
name=self.__class__.__name__)
Node: 'model/conv2d/Conv2D'
DNN library is not found.
[[{{node model/conv2d/Conv2D}}]] [Op:__inference_train_function_12299]
the whole code is in my git repository: https://github.com/Aditya757/MyRepository.git
the image of the dataset is here: https://i.stack.imgur.com/jWaJ8.png

Try to truncate to max_length=64 when tokenization. It worked in my case when training the text classification model.
The error appears when I set max_lenght to 128 or above.

Invalid Argument Error: Graph Execution Error and Traceback Error

I'm having multiple errors while running this vanilla rnn training code (code and errors shown below). I don't know if its because of my dataset or is it something else.
The data is made up of opcodes in assembly language.
The size of the training data is (2000, 53203).
This is vanilla RNN training code
import numpy as np
X_test = data[:200]
Y_test = np.array(Y_data[:200])
X_train = data[200:]
Y_train = np.array(Y_data[200:])
from tensorflow.keras.layers import SimpleRNN, Embedding, Dense
from tensorflow.keras.models import Sequential
model = Sequential()
model.add(Embedding(len(word_to_index), 32)) # 임베딩 벡터의 차원은 32
model.add(SimpleRNN(32)) # RNN 셀의 hidden_size는 32
model.add(Dense(1, activation='sigmoid'))
model.compile(optimizer='rmsprop', loss='binary_crossentropy', metrics=['acc'])
history = model.fit(X_train, Y_train, epochs=4, batch_size=64, validation_split=0.2)
It's Error Code...
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
C:\Users\ADMINI~1\AppData\Local\Temp/ipykernel_13744/877033043.py in <module>
8
9 model.compile(optimizer='rmsprop', loss='binary_crossentropy', metrics=['acc'])
---> 10 history = model.fit(X_train, Y_train, epochs=4, batch_size=64, validation_split=0.2)
~\anaconda3\lib\site-packages\keras\utils\traceback_utils.py in 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
~\anaconda3\lib\site-packages\tensorflow\python\eager\execute.py 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:
InvalidArgumentError: Graph execution error:
Detected at node 'sequential_3/embedding_2/embedding_lookup' defined at (most recent call last):
File "C:\Users\Administrator\anaconda3\lib\runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "C:\Users\Administrator\anaconda3\lib\runpy.py", line 87, in _run_code
exec(code, run_globals)
File "C:\Users\Administrator\anaconda3\lib\site-packages\ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "C:\Users\Administrator\anaconda3\lib\site-packages\traitlets\config\application.py", line 846, in launch_instance
app.start()
File "C:\Users\Administrator\anaconda3\lib\site-packages\ipykernel\kernelapp.py", line 677, in start
self.io_loop.start()
File "C:\Users\Administrator\anaconda3\lib\site-packages\tornado\platform\asyncio.py", line 199, in start
self.asyncio_loop.run_forever()
File "C:\Users\Administrator\anaconda3\lib\asyncio\base_events.py", line 596, in run_forever
self._run_once()
File "C:\Users\Administrator\anaconda3\lib\asyncio\base_events.py", line 1890, in _run_once
handle._run()
File "C:\Users\Administrator\anaconda3\lib\asyncio\events.py", line 80, in _run
self._context.run(self._callback, *self._args)
File "C:\Users\Administrator\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 457, in dispatch_queue
await self.process_one()
File "C:\Users\Administrator\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 446, in process_one
await dispatch(*args)
File "C:\Users\Administrator\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 353, in dispatch_shell
await result
File "C:\Users\Administrator\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 648, in execute_request
reply_content = await reply_content
File "C:\Users\Administrator\anaconda3\lib\site-packages\ipykernel\ipkernel.py", line 353, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "C:\Users\Administrator\anaconda3\lib\site-packages\ipykernel\zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "C:\Users\Administrator\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2901, in run_cell
result = self._run_cell(
File "C:\Users\Administrator\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2947, in _run_cell
return runner(coro)
File "C:\Users\Administrator\anaconda3\lib\site-packages\IPython\core\async_helpers.py", line 68, in _pseudo_sync_runner
coro.send(None)
File "C:\Users\Administrator\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3172, in run_cell_async
has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
File "C:\Users\Administrator\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3364, in run_ast_nodes
if (await self.run_code(code, result, async_=asy)):
File "C:\Users\Administrator\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3444, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "C:\Users\ADMINI~1\AppData\Local\Temp/ipykernel_13744/877033043.py", line 10, in <module>
history = model.fit(X_train, Y_train, epochs=4, batch_size=64, validation_split=0.2)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\engine\training.py", line 1445, in fit
val_logs = self.evaluate(
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\engine\training.py", line 1756, in evaluate
tmp_logs = self.test_function(iterator)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\engine\training.py", line 1557, in test_function
return step_function(self, iterator)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\engine\training.py", line 1546, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\engine\training.py", line 1535, in run_step
outputs = model.test_step(data)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\engine\training.py", line 1499, in test_step
y_pred = self(x, training=False)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\engine\training.py", line 490, in __call__
return super().__call__(*args, **kwargs)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\engine\base_layer.py", line 1014, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 92, in error_handler
return fn(*args, **kwargs)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\engine\sequential.py", line 374, in call
return super(Sequential, self).call(inputs, training=training, mask=mask)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\engine\functional.py", line 458, in call
return self._run_internal_graph(
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\engine\functional.py", line 596, in _run_internal_graph
outputs = node.layer(*args, **kwargs)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\engine\base_layer.py", line 1014, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 92, in error_handler
return fn(*args, **kwargs)
File "C:\Users\Administrator\anaconda3\lib\site-packages\keras\layers\core\embedding.py", line 199, in call
out = tf.nn.embedding_lookup(self.embeddings, inputs)
Node: 'sequential_3/embedding_2/embedding_lookup'
indices[25,40743] = 575 is not in [0, 575)
[[{{node sequential_3/embedding_2/embedding_lookup}}]] [Op:__inference_test_function_4239]
I'm running this on JupyterLab

model.fit() InvalidArgumentError

I have an image classification project. I would like to fit the model. However, I got error messages.
This is my code for fitting the model.
model.fit(x=train_batches,
steps_per_epoch=len(train_batches),
validation_data=valid_batches,
validation_steps=len(valid_batches),
epochs=10,
verbose=2
)
This is the error message:
Epoch 1/10
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
<ipython-input-25-59cb8d37476a> in <module>()
5 validation_steps=len(valid_batches),
6 epochs=10,
----> 7 verbose=2
8 )
1 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
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: Graph execution error:
Detected at node 'categorical_crossentropy/softmax_cross_entropy_with_logits' defined at (most recent call last):
File "/usr/lib/python3.7/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/usr/local/lib/python3.7/dist-packages/traitlets/config/application.py", line 846, in launch_instance
app.start()
File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelapp.py", line 499, in start
self.io_loop.start()
File "/usr/local/lib/python3.7/dist-packages/tornado/platform/asyncio.py", line 132, in start
self.asyncio_loop.run_forever()
File "/usr/lib/python3.7/asyncio/base_events.py", line 541, in run_forever
self._run_once()
File "/usr/lib/python3.7/asyncio/base_events.py", line 1786, in _run_once
handle._run()
File "/usr/lib/python3.7/asyncio/events.py", line 88, in _run
self._context.run(self._callback, *self._args)
File "/usr/local/lib/python3.7/dist-packages/tornado/platform/asyncio.py", line 122, in _handle_events
handler_func(fileobj, events)
File "/usr/local/lib/python3.7/dist-packages/tornado/stack_context.py", line 300, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 452, in _handle_events
self._handle_recv()
File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 481, in _handle_recv
self._run_callback(callback, msg)
File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 431, in _run_callback
callback(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/tornado/stack_context.py", line 300, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 233, in dispatch_shell
handler(stream, idents, msg)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/ipkernel.py", line 208, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/usr/local/lib/python3.7/dist-packages/ipykernel/zmqshell.py", line 537, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2718, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2828, in run_ast_nodes
if self.run_code(code, result):
File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2882, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-25-59cb8d37476a>", line 7, in <module>
verbose=2
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1384, in fit
tmp_logs = self.train_function(iterator)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1021, in train_function
return step_function(self, iterator)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1010, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1000, in run_step
outputs = model.train_step(data)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 860, in train_step
loss = self.compute_loss(x, y, y_pred, sample_weight)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 919, in compute_loss
y, y_pred, sample_weight, regularization_losses=self.losses)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/compile_utils.py", line 201, in __call__
loss_value = loss_obj(y_t, y_p, sample_weight=sw)
File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 141, in __call__
losses = call_fn(y_true, y_pred)
File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 245, in call
return ag_fn(y_true, y_pred, **self._fn_kwargs)
File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 1790, in categorical_crossentropy
y_true, y_pred, from_logits=from_logits, axis=axis)
File "/usr/local/lib/python3.7/dist-packages/keras/backend.py", line 5099, in categorical_crossentropy
labels=target, logits=output, axis=axis)
Node: 'categorical_crossentropy/softmax_cross_entropy_with_logits'
logits and labels must be broadcastable: logits_size=[10,2] labels_size=[10,4]
[[{{node categorical_crossentropy/softmax_cross_entropy_with_logits}}]] [Op:__inference_train_function_1479]

Looking at the error message, you have 4 different classes in your data. However, the logits contain 2 values for each sample. You probably need to adjust the final layer of your network. The output layer should output a tensor of dimension [batch_size, num_classes], or namely [batch_size, 4] but you are outputting [batch_size, 2].

InvalidArgumentError: Graph execution error in B3

activity = model.fit(train_gen, epochs=10, # Increase number of epochs if you have sufficient hardware
validation_data=val_gen,
verbose = 1
)
Epoch 1/10
Traceback (most recent call last):
File "C:\Users\BLRCSE~1\AppData\Local\Temp/ipykernel_15312/3305335964.py", line 1, in
activity = model.fit(train_gen, epochs=10, # Increase number of epochs if you have sufficient hardware
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 67, in error_handler
raise e.with_traceback(filtered_tb) from None
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\tensorflow\python\eager\execute.py", line 54, in quick_execute
tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
InvalidArgumentError: Graph execution error:
Detected at node 'gradient_tape/sequential_1/dense_5/MatMul/MatMul' defined at (most recent call last):
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\runpy.py", line 87, in run_code
exec(code, run_globals)
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\spyder_kernels\console_main.py", line 23, in
start.main()
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\spyder_kernels\console\start.py", line 328, in main
kernel.start()
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\ipykernel\kernelapp.py", line 677, in start
self.io_loop.start()
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\tornado\platform\asyncio.py", line 199, in start
self.asyncio_loop.run_forever()
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\asyncio\base_events.py", line 596, in run_forever
self._run_once()
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\asyncio\base_events.py", line 1890, in _run_once
handle._run()
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\asyncio\events.py", line 80, in _run
self._context.run(self._callback, *self._args)
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 457, in dispatch_queue
await self.process_one()
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 446, in process_one
await dispatch(*args)
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 353, in dispatch_shell
await result
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\ipykernel\kernelbase.py", line 648, in execute_request
reply_content = await reply_content
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\ipykernel\ipkernel.py", line 353, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\ipykernel\zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2901, in run_cell
result = self._run_cell(
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 2947, in _run_cell
return runner(coro)
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\IPython\core\async_helpers.py", line 68, in pseudo_sync_runner
coro.send(None)
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3172, in run_cell_async
has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3364, in run_ast_nodes
if (await self.run_code(code, result, async=asy)):
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\IPython\core\interactiveshell.py", line 3444, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "C:\Users\BLRCSE~1\AppData\Local\Temp/ipykernel_15312/1931121224.py", line 1, in
activity = model.fit(train_gen,
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\keras\utils\traceback_utils.py", line 64, in error_handler
return fn(*args, **kwargs)
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\keras\engine\training.py", line 1384, in fit
tmp_logs = self.train_function(iterator)
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\keras\engine\training.py", line 1021, in train_function
return step_function(self, iterator)
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\keras\engine\training.py", line 1010, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\keras\engine\training.py", line 1000, in run_step
outputs = model.train_step(data)
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\keras\engine\training.py", line 863, in train_step
self.optimizer.minimize(loss, self.trainable_variables, tape=tape)
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\keras\optimizer_v2\optimizer_v2.py", line 530, in minimize
grads_and_vars = self._compute_gradients(
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\keras\optimizer_v2\optimizer_v2.py", line 583, in _compute_gradients
grads_and_vars = self._get_gradients(tape, loss, var_list, grad_loss)
File "C:\Users\BLRCSE513-WS01\anaconda3\lib\site-packages\keras\optimizer_v2\optimizer_v2.py", line 464, in _get_gradients
grads = tape.gradient(loss, var_list, grad_loss)
Node: 'gradient_tape/sequential_1/dense_5/MatMul/MatMul'
Matrix size-incompatible: In[0]: [32,2], In[1]: [120,1]
[[{{node gradient_tape/sequential_1/dense_5/MatMul/MatMul}}]] [Op:__inference_train_function_47374]

If memory growth is enabled for a PhysicalDevice, the runtime initialization will not allocate all memory on the device. Memory growth cannot be configured on a PhysicalDevice with virtual devices configured.
For example:
import tensorflow as tf
physical_devices = tf.config.list_physical_devices('GPU')
try:
tf.config.experimental.set_memory_growth(physical_devices[0], True)
except:
# Invalid device or cannot modify virtual devices once initialized.
pass