I’m trying to do LSTM neural network for fake news detection. I’m getting this error.
I’m running the code on a VM with Ubuntu 22.04.1 LTS. I followed the instructions to install TensorFlow but still got the error.
InvalidArgumentError Traceback (most recent call last)
Cell In[22], line 1
----> 1 model.fit(x_train, final_y_train, batch_size=32, epochs=10, validation_data=(x_test,final_y_test))
File ~/miniconda3/envs/tf/lib/python3.9/site-packages/keras/utils/traceback_utils.py:70, in filter_traceback.<locals>.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 ~/miniconda3/envs/tf/lib/python3.9/site-packages/tensorflow/python/eager/execute.py:52, in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
50 try:
51 ctx.ensure_initialized()
---> 52 tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
53 inputs, attrs, num_outputs)
54 except core._NotOkStatusException as e:
55 if name is not None:
InvalidArgumentError: Graph execution error:
Detected at node 'sequential/embedding/embedding_lookup' defined at (most recent call last):
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/ipykernel_launcher.py", line 17, in <module>
app.launch_new_instance()
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/traitlets/config/application.py", line 992, in launch_instance
app.start()
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/ipykernel/kernelapp.py", line 711, in start
self.io_loop.start()
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/tornado/platform/asyncio.py", line 215, in start
self.asyncio_loop.run_forever()
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/asyncio/base_events.py", line 601, in run_forever
self._run_once()
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/asyncio/base_events.py", line 1905, in _run_once
handle._run()
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/asyncio/events.py", line 80, in _run
self._context.run(self._callback, *self._args)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue
await self.process_one()
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/ipykernel/kernelbase.py", line 499, in process_one
await dispatch(*args)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell
await result
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/ipykernel/kernelbase.py", line 729, in execute_request
reply_content = await reply_content
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/ipykernel/ipkernel.py", line 411, in do_execute
res = shell.run_cell(
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/ipykernel/zmqshell.py", line 531, in run_cell
return super().run_cell(*args, **kwargs)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/IPython/core/interactiveshell.py", line 3006, in run_cell
result = self._run_cell(
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/IPython/core/interactiveshell.py", line 3061, in _run_cell
result = runner(coro)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/IPython/core/async_helpers.py", line 129, in _pseudo_sync_runner
coro.send(None)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/IPython/core/interactiveshell.py", line 3266, in run_cell_async
has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/IPython/core/interactiveshell.py", line 3445, in run_ast_nodes
if await self.run_code(code, result, async_=asy):
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/IPython/core/interactiveshell.py", line 3505, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "/tmp/ipykernel_30336/2957581064.py", line 1, in <module>
model.fit(x_train, final_y_train, batch_size=32, epochs=10, validation_data=(x_test,final_y_test))
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/engine/training.py", line 1685, in fit
tmp_logs = self.train_function(iterator)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/engine/training.py", line 1284, in train_function
return step_function(self, iterator)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/engine/training.py", line 1268, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/engine/training.py", line 1249, in run_step
outputs = model.train_step(data)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/engine/training.py", line 1050, in train_step
y_pred = self(x, training=True)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/engine/training.py", line 558, in __call__
return super().__call__(*args, **kwargs)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/engine/base_layer.py", line 1145, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/engine/sequential.py", line 412, in call
return super().call(inputs, training=training, mask=mask)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/engine/functional.py", line 512, in call
return self._run_internal_graph(inputs, training=training, mask=mask)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/engine/functional.py", line 669, in _run_internal_graph
outputs = node.layer(*args, **kwargs)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/engine/base_layer.py", line 1145, in __call__
outputs = call_fn(inputs, *args, **kwargs)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "/home/ubuntu/miniconda3/envs/tf/lib/python3.9/site-packages/keras/layers/core/embedding.py", line 272, in call
out = tf.nn.embedding_lookup(self.embeddings, inputs)
Node: 'sequential/embedding/embedding_lookup'
indices[20,205] = 7518 is not in [0, 5000)
[[{{node sequential/embedding/embedding_lookup}}]] [Op:__inference_train_function_4240]
The source code can be found here
https://github.com/abolfazl-talebzadeh/tensorflow_keras_LSTM