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

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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