Sequential کتابخانه keras

قائم تقی پور

سلام

این باگ مربوط به pycharm هست و در لینک زیر در مورد رفع این مشکل میتونید مطالعه کنید.

https://stackoverflow.com/questions/23248017/cannot-find-reference-xxx-in-init-py-python-pycharm

همچنین میتونید از یک IDE دیگه مثل ژوپیتر استفاده کنید.

Ranger Omid

استاد اون مشکل حل شد ولی الان ی مشکل دیگ دارم

میگه: ImportError: Keras requires TensorFlow 2.2 or higher. Install TensorFlow via `pip install tensorflow ولی من ورژن tensorflow رو که چک کردم 2.4.4 بود

بعد ی مشکل دیگ از jupyter هم دارم وقتی کدزیر رو وارد میکنم

Model=Sequential()

ارور زیر میاد

---------------------------------------------------------------------------
InternalError                             Traceback (most recent call last)
<ipython-input-7-9bb8e4584392> in <module>
----> 1 Model=Sequential()
      2 Model.add(Dense(12, input_dim=8, activision='relu'))
      3 Model.add(Dense(8, activision='relu'))
      4 Model.add(Dense(1, input_dim=8, activision='sigmoid'))

F:\Anaconda3\lib\site-packages\tensorflow\python\training\tracking\base.py in _method_wrapper(self, *args, **kwargs)
    515     self._self_setattr_tracking = False  # pylint: disable=protected-access
    516     try:
--> 517       result = method(self, *args, **kwargs)
    518     finally:
    519       self._self_setattr_tracking = previous_value  # pylint: disable=protected-access

F:\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\sequential.py in __init__(self, layers, name)
    115     """
    116     # Skip the init in FunctionalModel since model doesn't have input/output yet
--> 117     super(functional.Functional, self).__init__(  # pylint: disable=bad-super-call
    118         name=name, autocast=False)
    119     base_layer.keras_api_gauge.get_cell('Sequential').set(True)

F:\Anaconda3\lib\site-packages\tensorflow\python\training\tracking\base.py in _method_wrapper(self, *args, **kwargs)
    515     self._self_setattr_tracking = False  # pylint: disable=protected-access
    516     try:
--> 517       result = method(self, *args, **kwargs)
    518     finally:
    519       self._self_setattr_tracking = previous_value  # pylint: disable=protected-access

F:\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py in __init__(self, *args, **kwargs)
    291     self._steps_per_execution = None
    292 
--> 293     self._init_batch_counters()
    294     self._base_model_initialized = True
    295 

F:\Anaconda3\lib\site-packages\tensorflow\python\training\tracking\base.py in _method_wrapper(self, *args, **kwargs)
    515     self._self_setattr_tracking = False  # pylint: disable=protected-access
    516     try:
--> 517       result = method(self, *args, **kwargs)
    518     finally:
    519       self._self_setattr_tracking = previous_value  # pylint: disable=protected-access

F:\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py in _init_batch_counters(self)
    299     # `evaluate`, and `predict`.
    300     agg = variables.VariableAggregationV2.ONLY_FIRST_REPLICA
--> 301     self._train_counter = variables.Variable(0, dtype='int64', aggregation=agg)
    302     self._test_counter = variables.Variable(0, dtype='int64', aggregation=agg)
    303     self._predict_counter = variables.Variable(

F:\Anaconda3\lib\site-packages\tensorflow\python\ops\variables.py in __call__(cls, *args, **kwargs)
    260       return cls._variable_v1_call(*args, **kwargs)
    261     elif cls is Variable:
--> 262       return cls._variable_v2_call(*args, **kwargs)
    263     else:
    264       return super(VariableMetaclass, cls).__call__(*args, **kwargs)

F:\Anaconda3\lib\site-packages\tensorflow\python\ops\variables.py in _variable_v2_call(cls, initial_value, trainable, validate_shape, caching_device, name, variable_def, dtype, import_scope, constraint, synchronization, aggregation, shape)
    242     if aggregation is None:
    243       aggregation = VariableAggregation.NONE
--> 244     return previous_getter(
    245         initial_value=initial_value,
    246         trainable=trainable,

F:\Anaconda3\lib\site-packages\tensorflow\python\ops\variables.py in <lambda>(**kws)
    235                         shape=None):
    236     """Call on Variable class. Useful to force the signature."""
--> 237     previous_getter = lambda **kws: default_variable_creator_v2(None, **kws)
    238     for _, getter in ops.get_default_graph()._variable_creator_stack:  # pylint: disable=protected-access
    239       previous_getter = _make_getter(getter, previous_getter)

F:\Anaconda3\lib\site-packages\tensorflow\python\ops\variable_scope.py in default_variable_creator_v2(next_creator, **kwargs)
   2652   shape = kwargs.get("shape", None)
   2653 
-> 2654   return resource_variable_ops.ResourceVariable(
   2655       initial_value=initial_value,
   2656       trainable=trainable,

F:\Anaconda3\lib\site-packages\tensorflow\python\ops\variables.py in __call__(cls, *args, **kwargs)
    262       return cls._variable_v2_call(*args, **kwargs)
    263     else:
--> 264       return super(VariableMetaclass, cls).__call__(*args, **kwargs)
    265 
    266 

F:\Anaconda3\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py in __init__(self, initial_value, trainable, collections, validate_shape, caching_device, name, dtype, variable_def, import_scope, constraint, distribute_strategy, synchronization, aggregation, shape)
   1572       self._init_from_proto(variable_def, import_scope=import_scope)
   1573     else:
-> 1574       self._init_from_args(
   1575           initial_value=initial_value,
   1576           trainable=trainable,

F:\Anaconda3\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py in _init_from_args(self, initial_value, trainable, collections, caching_device, name, dtype, constraint, synchronization, aggregation, distribute_strategy, shape)
   1715               self._update_uid = initial_value.checkpoint_position.restore_uid
   1716               initial_value = initial_value.wrapped_value
-> 1717             initial_value = ops.convert_to_tensor(initial_value,
   1718                                                   name="initial_value",
   1719                                                   dtype=dtype)

F:\Anaconda3\lib\site-packages\tensorflow\python\profiler\trace.py in wrapped(*args, **kwargs)
    161         with Trace(trace_name, **trace_kwargs):
    162           return func(*args, **kwargs)
--> 163       return func(*args, **kwargs)
    164 
    165     return wrapped

F:\Anaconda3\lib\site-packages\tensorflow\python\framework\ops.py in convert_to_tensor(value, dtype, name, as_ref, preferred_dtype, dtype_hint, ctx, accepted_result_types)
   1538 
   1539     if ret is None:
-> 1540       ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
   1541 
   1542     if ret is NotImplemented:

F:\Anaconda3\lib\site-packages\tensorflow\python\framework\tensor_conversion_registry.py in _default_conversion_function(***failed resolving arguments***)
     50 def _default_conversion_function(value, dtype, name, as_ref):
     51   del as_ref  # Unused.
---> 52   return constant_op.constant(value, dtype, name=name)
     53 
     54 

F:\Anaconda3\lib\site-packages\tensorflow\python\framework\constant_op.py in constant(value, dtype, shape, name)
    262     ValueError: if called on a symbolic tensor.
    263   """
--> 264   return _constant_impl(value, dtype, shape, name, verify_shape=False,
    265                         allow_broadcast=True)
    266 

F:\Anaconda3\lib\site-packages\tensorflow\python\framework\constant_op.py in _constant_impl(value, dtype, shape, name, verify_shape, allow_broadcast)
    274       with trace.Trace("tf.constant"):
    275         return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
--> 276     return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
    277 
    278   g = ops.get_default_graph()

F:\Anaconda3\lib\site-packages\tensorflow\python\framework\constant_op.py in _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
    299 def _constant_eager_impl(ctx, value, dtype, shape, verify_shape):
    300   """Implementation of eager constant."""
--> 301   t = convert_to_eager_tensor(value, ctx, dtype)
    302   if shape is None:
    303     return t

F:\Anaconda3\lib\site-packages\tensorflow\python\framework\constant_op.py in convert_to_eager_tensor(value, ctx, dtype)
     95     except AttributeError:
     96       dtype = dtypes.as_dtype(dtype).as_datatype_enum
---> 97   ctx.ensure_initialized()
     98   return ops.EagerTensor(value, ctx.device_name, dtype)
     99 

F:\Anaconda3\lib\site-packages\tensorflow\python\eager\context.py in ensure_initialized(self)
    509       opts = pywrap_tfe.TFE_NewContextOptions()
    510       try:
--> 511         config_str = self.config.SerializeToString()
    512         pywrap_tfe.TFE_ContextOptionsSetConfig(opts, config_str)
    513         if self._device_policy is not None:

F:\Anaconda3\lib\site-packages\tensorflow\python\eager\context.py in config(self)
    928     """Return the ConfigProto with all runtime deltas applied."""
    929     # Ensure physical devices have been discovered and config has been imported
--> 930     self._initialize_physical_devices()
    931 
    932     config = config_pb2.ConfigProto()

F:\Anaconda3\lib\site-packages\tensorflow\python\eager\context.py in _initialize_physical_devices(self)
   1251         return
   1252 
-> 1253       devs = pywrap_tfe.TF_ListPhysicalDevices()
   1254       self._physical_devices = [
   1255           PhysicalDevice(name=d.decode(),

InternalError: failed to get compute capability major for device: UNKNOWN ERROR (1); 0