Matrix size-incompatible error

[jaker07]

I'm working on "model_4" in lesson 3, the "Breaking our CCN Model down" videos. When I try to fit the model, it almost completes the first epoch and then I get the following error:

`Epoch 1/5
47/47 [==============================] - ETA: 0s - loss: 0.7146 - accuracy: 0.5713

InvalidArgumentError Traceback (most recent call last)
in <cell line: 2>()
1 # Fit the model
----> 2 history_4 = model_4.fit(train_data,
3 epochs=5,
4 steps_per_epoch=len(train_data),
5 validation_data=test_data,

1 frames
/usr/local/lib/python3.10/dist-packages/tensorflow/python/eager/execute.py 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:

InvalidArgumentError: Graph execution error:

Detected at node 'sequential/dense/MatMul' defined at (most recent call last):
File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.10/dist-packages/ipykernel_launcher.py", line 16, in
app.launch_new_instance()
File "/usr/local/lib/python3.10/dist-packages/traitlets/config/application.py", line 992, in launch_instance
app.start()
File "/usr/local/lib/python3.10/dist-packages/ipykernel/kernelapp.py", line 619, in start
self.io_loop.start()
File "/usr/local/lib/python3.10/dist-packages/tornado/platform/asyncio.py", line 195, in start
self.asyncio_loop.run_forever()
File "/usr/lib/python3.10/asyncio/base_events.py", line 603, in run_forever
self._run_once()
File "/usr/lib/python3.10/asyncio/base_events.py", line 1909, in _run_once
handle._run()
File "/usr/lib/python3.10/asyncio/events.py", line 80, in _run
self._context.run(self._callback, *self._args)
File "/usr/local/lib/python3.10/dist-packages/tornado/ioloop.py", line 685, in
lambda f: self._run_callback(functools.partial(callback, future))
File "/usr/local/lib/python3.10/dist-packages/tornado/ioloop.py", line 738, in _run_callback
ret = callback()
File "/usr/local/lib/python3.10/dist-packages/tornado/gen.py", line 825, in inner
self.ctx_run(self.run)
File "/usr/local/lib/python3.10/dist-packages/tornado/gen.py", line 786, in run
yielded = self.gen.send(value)
File "/usr/local/lib/python3.10/dist-packages/ipykernel/kernelbase.py", line 361, in process_one
yield gen.maybe_future(dispatch(*args))
File "/usr/local/lib/python3.10/dist-packages/tornado/gen.py", line 234, in wrapper
yielded = ctx_run(next, result)
File "/usr/local/lib/python3.10/dist-packages/ipykernel/kernelbase.py", line 261, in dispatch_shell
yield gen.maybe_future(handler(stream, idents, msg))
File "/usr/local/lib/python3.10/dist-packages/tornado/gen.py", line 234, in wrapper
yielded = ctx_run(next, result)
File "/usr/local/lib/python3.10/dist-packages/ipykernel/kernelbase.py", line 539, in execute_request
self.do_execute(
File "/usr/local/lib/python3.10/dist-packages/tornado/gen.py", line 234, in wrapper
yielded = ctx_run(next, result)
File "/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py", line 302, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/usr/local/lib/python3.10/dist-packages/ipykernel/zmqshell.py", line 539, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py", line 2975, in run_cell
result = self._run_cell(
File "/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py", line 3030, in _run_cell
return runner(coro)
File "/usr/local/lib/python3.10/dist-packages/IPython/core/async_helpers.py", line 78, in pseudo_sync_runner
coro.send(None)
File "/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py", line 3257, in run_cell_async
has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
File "/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py", line 3473, in run_ast_nodes
if (await self.run_code(code, result, async=asy)):
File "/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py", line 3553, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 2, in <cell line: 2>
history_4 = model_4.fit(train_data,
File "/usr/local/lib/python3.10/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 1729, in fit
val_logs = self.evaluate(
File "/usr/local/lib/python3.10/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 2072, in evaluate
tmp_logs = self.test_function(iterator)
File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 1852, in test_function
return step_function(self, iterator)
File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 1836, in step_function
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 1824, in run_step
outputs = model.test_step(data)
File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 1788, in test_step
y_pred = self(x, training=False)
File "/usr/local/lib/python3.10/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/keras/engine/training.py", line 558, in call
return super().call(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/keras/engine/base_layer.py", line 1145, in call
outputs = call_fn(inputs, *args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/keras/utils/traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/keras/engine/sequential.py", line 412, in call
return super().call(inputs, training=training, mask=mask)
File "/usr/local/lib/python3.10/dist-packages/keras/engine/functional.py", line 512, in call
return self._run_internal_graph(inputs, training=training, mask=mask)
File "/usr/local/lib/python3.10/dist-packages/keras/engine/functional.py", line 669, in _run_internal_graph
outputs = node.layer(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/keras/utils/traceback_utils.py", line 65, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/keras/engine/base_layer.py", line 1145, in call
outputs = call_fn(inputs, *args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/keras/utils/traceback_utils.py", line 96, in error_handler
return fn(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/keras/layers/core/dense.py", line 241, in call
outputs = tf.matmul(a=inputs, b=self.kernel)
Node: 'sequential/dense/MatMul'
Matrix size-incompatible: In[0]: [32,566440], In[1]: [475240,1]
[[{{node sequential/dense/MatMul}}]] [Op:__inference_test_function_1567]`

I rechecked many times to make sure my code matched what was shown in the videos, and then just to make sure I directly copied the code from the course Colab notebook and still get the same error. It seems there is some dimensionality problem between the "flatten" layer and the last dense layer, but I'm not able to figure out what is causing it.

In some of the previous videos, I was getting dimension related errors due to a change in the TF "fit" function between when the videos were made and present time, but the fix I used on those doesn't work here. Any ideas about what could be going on?

[jaker07]

I figured it out - Turns out I had a typo in my dimensions a few steps back... just took me two days to figure that out :(