Halo, i get error while running the code i downloaded from github .Eventho I didnt change any code . it said the dimension is not fit with the first layer of convolution.
here is the error message.
ValueError Traceback (most recent call last)
Input In [7], in <cell line: 24>()
22 # Train the model
23 print(f’\nMODEL TRAINING:’)
—> 24 model.fit(training_images, training_labels, epochs=5)
26 # Evaluate on the test set
27 print(f’\nMODEL EVALUATION:’)
File ~\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\keras\engine\training.py:108, in enable_multi_worker.._method_wrapper(self, *args, **kwargs)
106 def _method_wrapper(self, *args, **kwargs):
107 if not self._in_multi_worker_mode(): # pylint: disable=protected-access
→ 108 return method(self, *args, **kwargs)
110 # Running inside run_distribute_coordinator already.
111 if dc_context.get_current_worker_context():
File ~\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\keras\engine\training.py:1098, 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)
1091 with trace.Trace(
1092 ‘TraceContext’,
1093 graph_type=‘train’,
1094 epoch_num=epoch,
1095 step_num=step,
1096 batch_size=batch_size):
1097 callbacks.on_train_batch_begin(step)
→ 1098 tmp_logs = train_function(iterator)
1099 if data_handler.should_sync:
1100 context.async_wait()
File ~\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\eager\def_function.py:780, in Function.call(self, *args, **kwds)
778 else:
779 compiler = “nonXla”
→ 780 result = self._call(*args, **kwds)
782 new_tracing_count = self._get_tracing_count()
783 without_tracing = (tracing_count == new_tracing_count)
File ~\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\eager\def_function.py:823, in Function._call(self, *args, **kwds)
820 try:
821 # This is the first call of call, so we have to initialize.
822 initializers =
→ 823 self._initialize(args, kwds, add_initializers_to=initializers)
824 finally:
825 # At this point we know that the initialization is complete (or less
826 # interestingly an exception was raised) so we no longer need a lock.
827 self._lock.release()
File ~\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\eager\def_function.py:696, in Function._initialize(self, args, kwds, add_initializers_to)
693 self._lifted_initializer_graph = lifted_initializer_graph
694 self._graph_deleter = FunctionDeleter(self._lifted_initializer_graph)
695 self._concrete_stateful_fn = (
→ 696 self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access
697 *args, **kwds))
699 def invalid_creator_scope(*unused_args, **unused_kwds):
700 “”“Disables variable creation.”""
File ~\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\eager\function.py:2855, in Function._get_concrete_function_internal_garbage_collected(self, *args, **kwargs)
2853 args, kwargs = None, None
2854 with self._lock:
→ 2855 graph_function, _, _ = self._maybe_define_function(args, kwargs)
2856 return graph_function
File ~\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\eager\function.py:3213, in Function._maybe_define_function(self, args, kwargs)
3210 return self._define_function_with_shape_relaxation(args, kwargs)
3212 self._function_cache.missed.add(call_context_key)
→ 3213 graph_function = self._create_graph_function(args, kwargs)
3214 self._function_cache.primary[cache_key] = graph_function
3215 return graph_function, args, kwargs
File ~\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\eager\function.py:3065, in Function.create_graph_function(self, args, kwargs, override_flat_arg_shapes)
3060 missing_arg_names = [
3061 "%sd" (arg, i) for i, arg in enumerate(missing_arg_names)
3062 ]
3063 arg_names = base_arg_names + missing_arg_names
3064 graph_function = ConcreteFunction(
→ 3065 func_graph_module.func_graph_from_py_func(
3066 self._name,
3067 self._python_function,
3068 args,
3069 kwargs,
3070 self.input_signature,
3071 autograph=self._autograph,
3072 autograph_options=self._autograph_options,
3073 arg_names=arg_names,
3074 override_flat_arg_shapes=override_flat_arg_shapes,
3075 capture_by_value=self._capture_by_value),
3076 self._function_attributes,
3077 function_spec=self.function_spec,
3078 # Tell the ConcreteFunction to clean up its graph once it goes out of
3079 # scope. This is not the default behavior since it gets used in some
3080 # places (like Keras) where the FuncGraph lives longer than the
3081 # ConcreteFunction.
3082 shared_func_graph=False)
3083 return graph_function
File ~\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\framework\func_graph.py:986, 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)
983 else:
984 _, original_func = tf_decorator.unwrap(python_func)
→ 986 func_outputs = python_func(*func_args, **func_kwargs)
988 # invariant: func_outputs contains only Tensors, CompositeTensors,
989 # TensorArrays and Nones.
990 func_outputs = nest.map_structure(convert, func_outputs,
991 expand_composites=True)
File ~\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\eager\def_function.py:600, in Function._defun_with_scope..wrapped_fn(*args, **kwds)
585 # We register a variable creator with reduced priority. If an outer
586 # variable creator is just modifying keyword arguments to the variable
587 # constructor, this will work harmoniously. Since the scope registered
(…)
595 # better than the alternative, tracing the initialization graph but giving
596 # the user a variable type they didn’t want.
597 with ops.get_default_graph()._variable_creator_scope(scope, priority=50): # pylint: disable=protected-access
598 # wrapped allows AutoGraph to swap in a converted function. We give
599 # the function a weak reference to itself to avoid a reference cycle.
→ 600 return weak_wrapped_fn().wrapped(*args, **kwds)
File ~\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\framework\func_graph.py:973, in func_graph_from_py_func..wrapper(*args, **kwargs)
971 except Exception as e: # pylint:disable=broad-except
972 if hasattr(e, “ag_error_metadata”):
→ 973 raise e.ag_error_metadata.to_exception(e)
974 else:
975 raise
ValueError: in user code:
C:\Users\User\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\keras\engine\training.py:806 train_function *
return step_function(self, iterator)
C:\Users\User\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\keras\engine\training.py:796 step_function **
outputs = model.distribute_strategy.run(run_step, args=(data,))
C:\Users\User\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:1211 run
return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
C:\Users\User\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2585 call_for_each_replica
return self._call_for_each_replica(fn, args, kwargs)
C:\Users\User\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2945 _call_for_each_replica
return fn(*args, **kwargs)
C:\Users\User\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\keras\engine\training.py:789 run_step **
outputs = model.train_step(data)
C:\Users\User\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\keras\engine\training.py:747 train_step
y_pred = self(x, training=True)
C:\Users\User\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\keras\engine\base_layer.py:975 __call__
input_spec.assert_input_compatibility(self.input_spec, inputs,
C:\Users\User\anaconda3\envs\gputest\lib\site-packages\tensorflow\python\keras\engine\input_spec.py:191 assert_input_compatibility
raise ValueError('Input ' + str(input_index) + ' of layer ' +
ValueError: Input 0 of layer sequential_5 is incompatible with the layer: : expected min_ndim=4, found ndim=3. Full shape received: [32, 28, 28]
How do i fi the error? thank you for the answer