I cannot seem to train my model. When I do this, an error occurs that stops me from training it. The strange thing is that when I run the tests, it passes all… I cannot find the error. Could you please help me?
(Solution code removed, as posting it publicly is against the honour code of this community, regardless if it is correct or not. You can share the errors you get)
train model:
train_steps = 2
batch_size = 256
train_generator = train_dataset.shuffle(len(train_Q1),
seed=7,
reshuffle_each_iteration=True).batch(batch_size=batch_size)
val_generator = val_dataset.shuffle(len(val_Q1),
seed=7,
reshuffle_each_iteration=True).batch(batch_size=batch_size)
model = train_model(Siamese, TripletLoss,text_vectorization,
train_generator,
val_generator,
train_steps=train_steps,)
Epoch 1/2
UnimplementedError Traceback (most recent call last)
Cell In[81], line 9
3 train_generator = train_dataset.shuffle(len(train_Q1),
4 seed=7,
5 reshuffle_each_iteration=True).batch(batch_size=batch_size)
6 val_generator = val_dataset.shuffle(len(val_Q1),
7 seed=7,
8 reshuffle_each_iteration=True).batch(batch_size=batch_size)
----> 9 model = train_model(Siamese, TripletLoss,text_vectorization,
10 train_generator,
11 val_generator,
12 train_steps=train_steps,)
Cell In[80], line 29, in train_model(Siamese, TripletLoss, text_vectorizer, train_dataset, val_dataset, d_feature, lr, train_steps)
25 model.compile(loss=TripletLoss,
26 optimizer = tf.keras.optimizers.Adam(learning_rate=lr)
27 )
28 # Train the model
—> 29 model.fit(train_dataset,
30 epochs = train_steps,
31 validation_data = val_dataset,
32 )
34 ### END CODE HERE ###
36 return model
File /usr/local/lib/python3.8/dist-packages/keras/src/utils/traceback_utils.py:70, in filter_traceback..error_handler(*args, **kwargs)
67 filtered_tb = _process_traceback_frames(e.traceback)
68 # To get the full stack trace, call:
69 # tf.debugging.disable_traceback_filtering()
—> 70 raise e.with_traceback(filtered_tb) from None
71 finally:
72 del filtered_tb
File /usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/execute.py:53, in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
51 try:
52 ctx.ensure_initialized()
—> 53 tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
54 inputs, attrs, num_outputs)
55 except core._NotOkStatusException as e:
56 if name is not None:
UnimplementedError: Graph execution error:
Detected at node ‘SiameseModel/Cast’ defined at (most recent call last):
File “/usr/lib/python3.8/runpy.py”, line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File “/usr/lib/python3.8/runpy.py”, line 87, in _run_code
exec(code, run_globals)
File “/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py”, line 17, in
app.launch_new_instance()
File “/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py”, line 1043, in launch_instance
app.start()
File “/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py”, line 728, in start
self.io_loop.start()
File “/usr/local/lib/python3.8/dist-packages/tornado/platform/asyncio.py”, line 195, in start
self.asyncio_loop.run_forever()
File “/usr/lib/python3.8/asyncio/base_events.py”, line 570, in run_forever
self._run_once()
File “/usr/lib/python3.8/asyncio/base_events.py”, line 1859, in _run_once
handle._run()
File “/usr/lib/python3.8/asyncio/events.py”, line 81, in _run
self._context.run(self._callback, *self._args)
File “/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py”, line 516, in dispatch_queue
await self.process_one()
File “/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py”, line 505, in process_one
await dispatch(*args)
File “/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py”, line 412, in dispatch_shell
await result
File “/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py”, line 740, in execute_request
reply_content = await reply_content
File “/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py”, line 422, in do_execute
res = shell.run_cell(
File “/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py”, line 540, in run_cell
return super().run_cell(*args, **kwargs)
File “/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py”, line 3009, in run_cell
result = self._run_cell(
File “/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py”, line 3064, in _run_cell
result = runner(coro)
File “/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py”, line 129, in pseudo_sync_runner
coro.send(None)
File “/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py”, line 3269, in run_cell_async
has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
File “/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py”, line 3448, in run_ast_nodes
if await self.run_code(code, result, async=asy):
File “/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py”, line 3508, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File “/tmp/ipykernel_14/1427930616.py”, line 9, in
model = train_model(Siamese, TripletLoss,text_vectorization,
File “/tmp/ipykernel_14/2844875914.py”, line 29, in train_model
model.fit(train_dataset,
File “/usr/local/lib/python3.8/dist-packages/keras/src/utils/traceback_utils.py”, line 65, in error_handler
return fn(*args, **kwargs)
File “/usr/local/lib/python3.8/dist-packages/keras/src/engine/training.py”, line 1742, in fit
tmp_logs = self.train_function(iterator)
File “/usr/local/lib/python3.8/dist-packages/keras/src/engine/training.py”, line 1338, in train_function
return step_function(self, iterator)
File “/usr/local/lib/python3.8/dist-packages/keras/src/engine/training.py”, line 1322, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File “/usr/local/lib/python3.8/dist-packages/keras/src/engine/training.py”, line 1303, in run_step
outputs = model.train_step(data)
File “/usr/local/lib/python3.8/dist-packages/keras/src/engine/training.py”, line 1080, in train_step
y_pred = self(x, training=True)
File “/usr/local/lib/python3.8/dist-packages/keras/src/utils/traceback_utils.py”, line 65, in error_handler
return fn(*args, **kwargs)
File “/usr/local/lib/python3.8/dist-packages/keras/src/engine/training.py”, line 569, in call
return super().call(*args, **kwargs)
File “/usr/local/lib/python3.8/dist-packages/keras/src/utils/traceback_utils.py”, line 65, in error_handler
return fn(*args, **kwargs)
File “/usr/local/lib/python3.8/dist-packages/keras/src/engine/base_layer.py”, line 1150, in call
outputs = call_fn(inputs, *args, **kwargs)
File “/usr/local/lib/python3.8/dist-packages/keras/src/utils/traceback_utils.py”, line 96, in error_handler
return fn(*args, **kwargs)
File “/usr/local/lib/python3.8/dist-packages/keras/src/engine/functional.py”, line 512, in call
return self._run_internal_graph(inputs, training=training, mask=mask)
File “/usr/local/lib/python3.8/dist-packages/keras/src/engine/functional.py”, line 651, in _run_internal_graph
y = self._conform_to_reference_input(y, ref_input=x)
File “/usr/local/lib/python3.8/dist-packages/keras/src/engine/functional.py”, line 748, in _conform_to_reference_input
tensor = tf.cast(tensor, dtype=ref_input.dtype)
Node: ‘SiameseModel/Cast’
2 root error(s) found.
(0) UNIMPLEMENTED: Cast string to float is not supported
[[{{node SiameseModel/Cast}}]]
(1) CANCELLED: Function was cancelled before it was started
0 successful operations.
0 derived errors ignored. [Op:__inference_train_function_43371]