解决tf2 ValueError: Tensor‘s shape (4, 4, 1, 16) is not compatible with supplied shape (4, 4, 3, 16)

雨点打透心脏的1/2处 2022-12-17 07:17 147阅读 0赞

### 解决tf2 ValueError: Tensor’s shape (4, 4, 1, 16) is not compatible with supplied shape (4, 4, 3, 16) ###

#### 代码 ####

test = tf.ones((1,8,8,3))
    new_prediction = new_model.predict(test)

#### 报错信息 ####

---------------------------------------------------------------------------
    ValueError                                Traceback (most recent call last)
    <ipython-input-11-8d3486b18e09> in <module>()
          6 new_model = MyNet()
          7 new_model.load_weights('model_weight')
    ----> 8 new_prediction = new_model.predict(test)
          9 
         10 print(new_prediction)
    
    ~/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py in _method_wrapper(self, *args, **kwargs)
        128       raise ValueError('{} is not supported in multi-worker mode.'.format(
        129           method.__name__))
    --> 130     return method(self, *args, **kwargs)
        131 
        132   return tf_decorator.make_decorator(
    
    ~/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py in predict(self, x, batch_size, verbose, steps, callbacks, max_queue_size, workers, use_multiprocessing)
       1597           for step in data_handler.steps():
       1598             callbacks.on_predict_batch_begin(step)
    -> 1599             tmp_batch_outputs = predict_function(iterator)
       1600             if data_handler.should_sync:
       1601               context.async_wait()
    
    ~/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds)
        778       else:
        779         compiler = "nonXla"
    --> 780         result = self._call(*args, **kwds)
        781 
        782       new_tracing_count = self._get_tracing_count()
    
    ~/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py in _call(self, *args, **kwds)
        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
    
    ~/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py in _initialize(self, args, kwds, add_initializers_to)
        695     self._concrete_stateful_fn = (
        696         self._stateful_fn._get_concrete_function_internal_garbage_collected(  # pylint: disable=protected-access
    --> 697             *args, **kwds))
        698 
        699     def invalid_creator_scope(*unused_args, **unused_kwds):
    
    ~/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py in _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
       2857 
    
    ~/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py in _maybe_define_function(self, args, kwargs)
       3211 
       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
    
    ~/.local/lib/python3.6/site-packages/tensorflow/python/eager/function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes)
       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,
    
    ~/.local/lib/python3.6/site-packages/tensorflow/python/framework/func_graph.py 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)
        984         _, original_func = tf_decorator.unwrap(python_func)
        985 
    --> 986       func_outputs = python_func(*func_args, **func_kwargs)
        987 
        988       # invariant: `func_outputs` contains only Tensors, CompositeTensors,
    
    ~/.local/lib/python3.6/site-packages/tensorflow/python/eager/def_function.py in wrapped_fn(*args, **kwds)
        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)
        601     weak_wrapped_fn = weakref.ref(wrapped_fn)
        602 
    
    ~/.local/lib/python3.6/site-packages/tensorflow/python/framework/func_graph.py in 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:
    
        /Users/1/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py:1462 predict_function  *
            return step_function(self, iterator)
        <ipython-input-4-470bb031585e>:24 call  *
            inputs = self.maxpool1(self.cbr1(inputs))
        <ipython-input-1-470bb031585e>:11 call  *
            inputs = self.conv(inputs)
        /Users/1/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py:982 __call__  **
            self._maybe_build(inputs)
        /Users/1/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py:2643 _maybe_build
            self.build(input_shapes)  # pylint:disable=not-callable
        /Users/1/.local/lib/python3.6/site-packages/tensorflow/python/keras/layers/convolutional.py:204 build
            dtype=self.dtype)
        /Users/1/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py:614 add_weight
            caching_device=caching_device)
        /Users/1/.local/lib/python3.6/site-packages/tensorflow/python/training/tracking/base.py:731 _add_variable_with_custom_getter
            name=name, shape=shape)
        /Users/1/.local/lib/python3.6/site-packages/tensorflow/python/training/tracking/base.py:798 _preload_simple_restoration
            checkpoint_position=checkpoint_position, shape=shape)
        /Users/1/.local/lib/python3.6/site-packages/tensorflow/python/training/tracking/base.py:75 __init__
            self.wrapped_value.set_shape(shape)
        /Users/1/.local/lib/python3.6/site-packages/tensorflow/python/framework/ops.py:1209 set_shape
            (self.shape, shape))
    
        ValueError: Tensor's shape (4, 4, 1, 16) is not compatible with supplied shape (4, 4, 3, 16)

#### 解决办法 ####

test = tf.ones((1,8,8,1))
    new_prediction = new_model.predict(test)

通道数不对应

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