【发布时间】：2021-12-29 20:14:34
【问题描述】：
我正在构建一个带有边界框的对象检测模型，构建成功后，我想将它与 vgg16 分类器合并。
我已经用谷歌搜索了错误。但是还是不能调试。
我知道 40 是我的 batch_size，5 是我的标签数量，4 是我的模型的输出。
下面是我的模型：
vgg16_model = keras.applications.vgg16.VGG16()
model_1 = Sequential()
for layer in vgg16_model.layers[:-4]:
model_1.add(layer)
for layer in model_1.layers:
layer.trainable = False
flatten = model_1.output
flatten = Flatten()(flatten)
bboxhead = Dense(128,activation="relu")(flatten)
bboxhead = Dense(64,activation="relu")(bboxhead)
bboxhead = Dense(32,activation="relu")(bboxhead)
bboxhead = Dense(4,activation="relu")(bboxhead)
box_model = Model(inputs = model_1.input,outputs = bboxhead)
数据生成器：
batch_size = 40
train_datagen = ImageDataGenerator(rescale=1./255, validation_split=0.2,
rotation_range=40, horizontal_flip=True,
fill_mode='nearest')
train_gen = train_datagen.flow_from_directory(path, target_size=(224,224),
class_mode='categorical', batch_size=batch_size,
subset='training')
val_gen = train_datagen.flow_from_directory(path, target_size=(224,224),
class_mode='categorical', batch_size=batch_size,
subset='validation')
我的模特：
from tensorflow.keras.optimizers import Adam
opt = Adam(1e-4)
box_model.compile(loss='mse',optimizer=opt)
steps, val_steps = train_gen.n/batch_size, val_gen.n/batch_size
num_epochs = 30
history = box_model.fit(train_gen,validation_data=val_gen,epochs=30,verbose=1)
错误信息是：
Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.
Cause: closure mismatch, requested ('self', 'step_function'), but source function had ()
To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
WARNING: AutoGraph could not transform <function Model.make_train_function.<locals>.train_function at 0x7efbbdd35b90> and will run it as-is.
Please report this to the TensorFlow team. When filing the bug, set the verbosity to 10 (on Linux, `export AUTOGRAPH_VERBOSITY=10`) and attach the full output.
Cause: closure mismatch, requested ('self', 'step_function'), but source function had ()
To silence this warning, decorate the function with @tf.autograph.experimental.do_not_convert
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
<ipython-input-78-48e34ab17b66> in <module>()
1 #history = box_model.fit(train_gen, validation_data=val_gen, epochs=num_epochs,steps_per_epoch=steps, validation_steps=val_steps)
2
----> 3 history = box_model.fit(train_gen,validation_data=val_gen,epochs=30,verbose=1)
1 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
57 try:
58 ctx.ensure_initialized()
---> 59 tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
60 inputs, attrs, num_outputs)
61 except core._NotOkStatusException as e:
InvalidArgumentError: Incompatible shapes: [40,5] vs. [40,4]
[[node mean_squared_error/SquaredDifference
(defined at /usr/local/lib/python3.7/dist-packages/keras/losses.py:1204)
]] [Op:__inference_train_function_15076]
Errors may have originated from an input operation.
Input Source operations connected to node mean_squared_error/SquaredDifference:
In[0] model_8/dense_27/Relu (defined at /usr/local/lib/python3.7/dist-packages/keras/backend.py:4867)
In[1] IteratorGetNext (defined at /usr/local/lib/python3.7/dist-packages/keras/engine/training.py:866)
Operation defined at: (most recent call last)
>>> File "/usr/lib/python3.7/runpy.py", line 193, in _run_module_as_main
>>> "__main__", mod_spec)
>>>
>>> File "/usr/lib/python3.7/runpy.py", line 85, in _run_code
>>> exec(code, run_globals)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py", line 16, in <module>
>>> app.launch_new_instance()
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/traitlets/config/application.py", line 846, in launch_instance
>>> app.start()
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelapp.py", line 499, in start
>>> self.io_loop.start()
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/tornado/platform/asyncio.py", line 132, in start
>>> self.asyncio_loop.run_forever()
>>>
>>> File "/usr/lib/python3.7/asyncio/base_events.py", line 541, in run_forever
>>> self._run_once()
>>>
>>> File "/usr/lib/python3.7/asyncio/base_events.py", line 1786, in _run_once
>>> handle._run()
>>>
>>> File "/usr/lib/python3.7/asyncio/events.py", line 88, in _run
>>> self._context.run(self._callback, *self._args)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/tornado/platform/asyncio.py", line 122, in _handle_events
>>> handler_func(fileobj, events)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/tornado/stack_context.py", line 300, in null_wrapper
>>> return fn(*args, **kwargs)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 452, in _handle_events
>>> self._handle_recv()
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 481, in _handle_recv
>>> self._run_callback(callback, msg)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 431, in _run_callback
>>> callback(*args, **kwargs)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/tornado/stack_context.py", line 300, in null_wrapper
>>> return fn(*args, **kwargs)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 283, in dispatcher
>>> return self.dispatch_shell(stream, msg)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 233, in dispatch_shell
>>> handler(stream, idents, msg)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 399, in execute_request
>>> user_expressions, allow_stdin)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/ipykernel/ipkernel.py", line 208, in do_execute
>>> res = shell.run_cell(code, store_history=store_history, silent=silent)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/ipykernel/zmqshell.py", line 537, in run_cell
>>> return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2718, in run_cell
>>> interactivity=interactivity, compiler=compiler, result=result)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2822, in run_ast_nodes
>>> if self.run_code(code, result):
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2882, in run_code
>>> exec(code_obj, self.user_global_ns, self.user_ns)
>>>
>>> File "<ipython-input-78-48e34ab17b66>", line 3, in <module>
>>> history = box_model.fit(train_gen,validation_data=val_gen,epochs=30,verbose=1)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler
>>> return fn(*args, **kwargs)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1216, in fit
>>> """The logic for one evaluation step.
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 878, in train_function
>>> - A TensorFlow tensor, or a list of tensors
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 867, in step_function
>>> validation_batch_size=None,
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 860, in run_step
>>> validation_data=None,
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 810, in train_step
>>> """Runs a single training step."""
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/keras/engine/compile_utils.py", line 201, in __call__
>>> loss_value = loss_obj(y_t, y_p, sample_weight=sw)
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 141, in __call__
>>> call_fn = tf.__internal__.autograph.tf_convert(self.call, tf.__internal__.autograph.control_status_ctx())
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 245, in call
>>> ag_fn = tf.__internal__.autograph.tf_convert(self.fn, tf.__internal__.autograph.control_status_ctx())
>>>
>>> File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 1204, in mean_squared_error
【问题讨论】：
标签： python machine-learning deep-learning classification object-detection