Invalid Argument Error / Graph Execution Error

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I'm having multiple errors while running this VGG training code (code and errors shown below). I don't know if its because of my dataset or is it something else.

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow.keras.preprocessing import image
from tensorflow.keras.applications.vgg16 import preprocess_input
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from sklearn.metrics.pairwise import cosine_similarity
import os
import scipy

train_directory = 'sign_data/train' #To be changed
test_directory = 'sign_data/test' #To be changed

train_datagen = ImageDataGenerator(
    rescale = 1./255,
    rotation_range = 0.1,
    width_shift_range = 0.2,
    height_shift_range = 0.2,
    shear_range = 0.1
)

train_generator = train_datagen.flow_from_directory(
    train_directory,
    target_size = (224, 224),
    color_mode = 'rgb',
    shuffle = True,
    batch_size=32
    
)


test_datagen = ImageDataGenerator(
    rescale = 1./255,
)

test_generator = test_datagen.flow_from_directory(
    test_directory,
    target_size = (224, 224),
    color_mode = 'rgb',
    shuffle = True,
    batch_size=32
)

from tensorflow.keras.applications.vgg16 import VGG16   
vgg_basemodel = VGG16(include_top=True)

from tensorflow.keras.callbacks import ReduceLROnPlateau, ModelCheckpoint, EarlyStopping

early_stopping = EarlyStopping(monitor='val_loss', mode='min', verbose=1, patience=5)

vgg_model = tf.keras.Sequential(vgg_basemodel.layers[:-1])
vgg_model.add(tf.keras.layers.Dense(10, activation = 'softmax'))

# Freezing original layers
for layer in vgg_model.layers[:-1]:
    layer.trainable = False

vgg_model.compile(loss='categorical_crossentropy',
                  optimizer=tf.keras.optimizers.SGD(momentum=0.9, learning_rate=0.001, decay=0.01),
                  metrics=['accuracy'])

history = vgg_model.fit(train_generator,
              epochs=30,
              batch_size=64,
              validation_data=test_generator,
              callbacks=[early_stopping])

# finetuning with all layers set trainable

for layer in vgg_model.layers:
    layer.trainable = True

vgg_model.compile(loss='categorical_crossentropy',
                  optimizer=tf.keras.optimizers.SGD(momentum=0.9, lr=0.0001),
                  metrics=['accuracy'])

history2 = vgg_model.fit(train_generator,
              epochs=5,
              batch_size=64,
              validation_data=test_generator,
              callbacks=[early_stopping])

vgg_model.save('saved_models/vgg_finetuned_model')

First error: Invalid Argument Error

    InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-13-292bf57ef59f> in <module>()
     14               batch_size=64,
     15               validation_data=test_generator,
---> 16               callbacks=[early_stopping])
     17 
     18 # finetuning with all layers set trainable

    /usr/local/lib/python3.7/dist-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

/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:

Second Error: Graph Execution Error

    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 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-13-292bf57ef59f>", line 16, in <module>
      callbacks=[early_stopping])
    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=[32,10] labels_size=[32,128]
     [[]] [Op:__inference_train_function_11227]

I'm running this on google colaboratory. Is there a module that I should install? Or is it purely an error on the code itself?



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