Value Error

[LuvolwethuTokwe]

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[244], line 1
----> 1 training_history = Plant_Detector.fit(x= training_set, validation_data = validation_set, epochs = 10)

File ~\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\keras\engine\training.py:1193, in Model.fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)
   1186 with trace.Trace(
   1187     'train',
   1188     epoch_num=epoch,
   1189     step_num=step,
   1190     batch_size=batch_size,
   1191     _r=1):
   1192   callbacks.on_train_batch_begin(step)
-> 1193   tmp_logs = self.train_function(iterator)
   1194   if data_handler.should_sync:
   1195     context.async_wait()

File ~\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\eager\def_function.py:885, in Function.__call__(self, *args, **kwds)
    882 compiler = "xla" if self._jit_compile else "nonXla"
    884 with OptionalXlaContext(self._jit_compile):
--> 885   result = self._call(*args, **kwds)
    887 new_tracing_count = self.experimental_get_tracing_count()
    888 without_tracing = (tracing_count == new_tracing_count)

File ~\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\eager\def_function.py:933, in Function._call(self, *args, **kwds)
    930 try:
    931   # This is the first call of __call__, so we have to initialize.
    932   initializers = []
--> 933   self._initialize(args, kwds, add_initializers_to=initializers)
    934 finally:
    935   # At this point we know that the initialization is complete (or less
    936   # interestingly an exception was raised) so we no longer need a lock.
    937   self._lock.release()

File ~\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\eager\def_function.py:759, in Function._initialize(self, args, kwds, add_initializers_to)
    756 self._lifted_initializer_graph = lifted_initializer_graph
    757 self._graph_deleter = FunctionDeleter(self._lifted_initializer_graph)
    758 self._concrete_stateful_fn = (
--> 759     self._stateful_fn._get_concrete_function_internal_garbage_collected(  # pylint: disable=protected-access
    760         *args, **kwds))
    762 def invalid_creator_scope(*unused_args, **unused_kwds):
    763   """Disables variable creation."""

File ~\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\eager\function.py:3066, in Function._get_concrete_function_internal_garbage_collected(self, *args, **kwargs)
   3064   args, kwargs = None, None
   3065 with self._lock:
-> 3066   graph_function, _ = self._maybe_define_function(args, kwargs)
   3067 return graph_function

File ~\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\eager\function.py:3463, in Function._maybe_define_function(self, args, kwargs)
   3459   return self._define_function_with_shape_relaxation(
   3460       args, kwargs, flat_args, filtered_flat_args, cache_key_context)
   3462 self._function_cache.missed.add(call_context_key)
-> 3463 graph_function = self._create_graph_function(args, kwargs)
   3464 self._function_cache.primary[cache_key] = graph_function
   3466 return graph_function, filtered_flat_args

File ~\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\eager\function.py:3298, in Function._create_graph_function(self, args, kwargs, override_flat_arg_shapes)
   3293 missing_arg_names = [
   3294     "%s_%d" % (arg, i) for i, arg in enumerate(missing_arg_names)
   3295 ]
   3296 arg_names = base_arg_names + missing_arg_names
   3297 graph_function = ConcreteFunction(
-> 3298     func_graph_module.func_graph_from_py_func(
   3299         self._name,
   3300         self._python_function,
   3301         args,
   3302         kwargs,
   3303         self.input_signature,
   3304         autograph=self._autograph,
   3305         autograph_options=self._autograph_options,
   3306         arg_names=arg_names,
   3307         override_flat_arg_shapes=override_flat_arg_shapes,
   3308         capture_by_value=self._capture_by_value),
   3309     self._function_attributes,
   3310     function_spec=self.function_spec,
   3311     # Tell the ConcreteFunction to clean up its graph once it goes out of
   3312     # scope. This is not the default behavior since it gets used in some
   3313     # places (like Keras) where the FuncGraph lives longer than the
   3314     # ConcreteFunction.
   3315     shared_func_graph=False)
   3316 return graph_function

File ~\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\framework\func_graph.py:1007, in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes, acd_record_initial_resource_uses)
   1004 else:
   1005   _, original_func = tf_decorator.unwrap(python_func)
-> 1007 func_outputs = python_func(*func_args, **func_kwargs)
   1009 # invariant: `func_outputs` contains only Tensors, CompositeTensors,
   1010 # TensorArrays and `None`s.
   1011 func_outputs = nest.map_structure(convert, func_outputs,
   1012                                   expand_composites=True)

File ~\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\eager\def_function.py:668, in Function._defun_with_scope.<locals>.wrapped_fn(*args, **kwds)
    664 with default_graph._variable_creator_scope(scope, priority=50):  # pylint: disable=protected-access
    665   # __wrapped__ allows AutoGraph to swap in a converted function. We give
    666   # the function a weak reference to itself to avoid a reference cycle.
    667   with OptionalXlaContext(compile_with_xla):
--> 668     out = weak_wrapped_fn().__wrapped__(*args, **kwds)
    669   return out

File ~\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\framework\func_graph.py:994, in func_graph_from_py_func.<locals>.wrapper(*args, **kwargs)
    992 except Exception as e:  # pylint:disable=broad-except
    993   if hasattr(e, "ag_error_metadata"):
--> 994     raise e.ag_error_metadata.to_exception(e)
    995   else:
    996     raise

ValueError: in user code:

    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\keras\engine\training.py:862 train_function  *
        return step_function(self, iterator)
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\keras\engine\training.py:852 step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:1286 run
        return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2849 call_for_each_replica
        return self._call_for_each_replica(fn, args, kwargs)
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:3632 _call_for_each_replica
        return fn(*args, **kwargs)
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\keras\engine\training.py:845 run_step  **
        outputs = model.train_step(data)
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\keras\engine\training.py:803 train_step
        loss = self.compiled_loss(
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\keras\engine\compile_utils.py:204 __call__
        loss_value = loss_obj(y_t, y_p, sample_weight=sw)
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\keras\losses.py:155 __call__
        losses = call_fn(y_true, y_pred)
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\keras\losses.py:259 call  **
        return ag_fn(y_true, y_pred, **self._fn_kwargs)
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\util\dispatch.py:206 wrapper
        return target(*args, **kwargs)
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\keras\losses.py:1679 categorical_crossentropy
        return backend.categorical_crossentropy(
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\util\dispatch.py:206 wrapper
        return target(*args, **kwargs)
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\keras\backend.py:4875 categorical_crossentropy
        target.shape.assert_is_compatible_with(output.shape)
    C:\Users\Luvolwethu Tokwe\anaconda3\envs\TFNew\lib\site-packages\tensorflow\python\framework\tensor_shape.py:1161 assert_is_compatible_with
        raise ValueError("Shapes %s and %s are incompatible" % (self, other))

    ValueError: Shapes (None, 9) and (None, 1024) are incompatible

[sachinprasadhs]

Could you please provide the sample reproducible code to replicate the reported behavior. Thanks

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