每当我尝试在Python 3.7中使用KerasDropout函数时，我都会收到UnboundLocalError: local variable 'a' referenced before assignment。没有Dropout行的相同代码工作正常。
有谁知道如何在不使用 3.6 版本的情况下解决此问题？
谢谢！
我正在使用...
macOS 10.14.4
Python 3.7.3
Keras 2.2.4
TensorFlow 1.13.1
更新1：我包含与问题相关的代码段
def create_model(neurons, learn_rate):
model = Sequential()
model.add(Dense(neurons, input_shape=(100,), activation='sigmoid'))
model.add(Dropout(0.2))
model.add(Dense(5, activation='softmax'))
optimizer = SGD(lr=learn_rate)
model.compile(loss='sparse_categorical_crossentropy', optimizer=optimizer, metrics=['accuracy'])
return model
model=create_model(neurons=584, learn_rate=0.035)
model.fit(X_train, y_train, epochs=139);
score = model.evaluate(X_test, y_test);
print(score)
更新 2：我包括完整的回溯
---------------------------------------------------------------------------
UnboundLocalError Traceback (most recent call last)
<ipython-input-4-7807c02c4f54> in <module>
9 return model
10
---> 11 model=create_model(neurons=584, learn_rate=0.035)
12 model.fit(X_train, y_train, epochs=139);
13 score = model.evaluate(X_test, y_test);
<ipython-input-4-7807c02c4f54> in create_model(neurons, learn_rate)
2 model = Sequential()
3 model.add(Dense(neurons, input_shape=(100,), activation='sigmoid'))
----> 4 model.add(Dropout(0.2))
5 model.add(Dense(5, activation='softmax'))
6
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/keras/engine/sequential.py in add(self, layer)
179 self.inputs = network.get_source_inputs(self.outputs[0])
180 elif self.outputs:
--> 181 output_tensor = layer(self.outputs[0])
182 if isinstance(output_tensor, list):
183 raise TypeError('All layers in a Sequential model '
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/keras/engine/base_layer.py in __call__(self, inputs, **kwargs)
455 # Actually call the layer,
456 # collecting output(s), mask(s), and shape(s).
--> 457 output = self.call(inputs, **kwargs)
458 output_mask = self.compute_mask(inputs, previous_mask)
459
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/keras/layers/core.py in call(self, inputs, training)
124 seed=self.seed)
125 return K.in_train_phase(dropped_inputs, inputs,
--> 126 training=training)
127 return inputs
128
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py in in_train_phase(x, alt, training)
3103 """
3104 if training is None:
-> 3105 training = learning_phase()
3106 uses_learning_phase = True
3107 else:
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py in learning_phase()
133 phase = tf.placeholder_with_default(False,
134 shape=(),
--> 135 name='keras_learning_phase')
136 _GRAPH_LEARNING_PHASES[graph] = phase
137 return _GRAPH_LEARNING_PHASES[graph]
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/tensorflow/python/ops/array_ops.py in placeholder_with_default(input, shape, name)
2091 A `Tensor`. Has the same type as `input`.
2092 """
-> 2093 return gen_array_ops.placeholder_with_default(input, shape, name)
2094
2095
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/tensorflow/python/ops/gen_array_ops.py in placeholder_with_default(input, shape, name)
5923 shape = _execute.make_shape(shape, "shape")
5924 _, _, _op = _op_def_lib._apply_op_helper(
-> 5925 "PlaceholderWithDefault", input=input, shape=shape, name=name)
5926 _result = _op.outputs[:]
5927 _inputs_flat = _op.inputs
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py in _apply_op_helper(self, op_type_name, name, **keywords)
509 dtype=dtype,
510 as_ref=input_arg.is_ref,
--> 511 preferred_dtype=default_dtype)
512 except TypeError as err:
513 if dtype is None:
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in internal_convert_to_tensor(value, dtype, name, as_ref, preferred_dtype, ctx, accept_symbolic_tensors)
1173
1174 if ret is None:
-> 1175 ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
1176
1177 if ret is NotImplemented:
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py in _constant_tensor_conversion_function(v, dtype, name, as_ref)
302 as_ref=False):
303 _ = as_ref
--> 304 return constant(v, dtype=dtype, name=name)
305
306
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py in constant(value, dtype, shape, name)
243 """
244 return _constant_impl(value, dtype, shape, name, verify_shape=False,
--> 245 allow_broadcast=True)
246
247
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py in _constant_impl(value, dtype, shape, name, verify_shape, allow_broadcast)
281 tensor_util.make_tensor_proto(
282 value, dtype=dtype, shape=shape, verify_shape=verify_shape,
--> 283 allow_broadcast=allow_broadcast))
284 dtype_value = attr_value_pb2.AttrValue(type=tensor_value.tensor.dtype)
285 const_tensor = g.create_op(
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/tensorflow/python/framework/tensor_util.py in make_tensor_proto(values, dtype, shape, verify_shape, allow_broadcast)
571 raise TypeError(
572 "Element type not supported in TensorProto: %s" % numpy_dtype.name)
--> 573 append_fn(tensor_proto, proto_values)
574
575 return tensor_proto
tensorflow/python/framework/fast_tensor_util.pyx in tensorflow.python.framework.fast_tensor_util.AppendBoolArrayToTensorProto()
~/anaconda3/envs/deep-3.7/lib/python3.7/site-packages/numpy/lib/type_check.py in asscalar(***failed resolving arguments***)
545 warnings.warn('np.asscalar(a) is deprecated since NumPy v1.16, use '
546 'a.item() instead', DeprecationWarning, stacklevel=1)
--> 547 return a.item()
548
549 #-----------------------------------------------------------------------------
UnboundLocalError: local variable 'a' referenced before assignment
``
我发现安装pip install tf-nightly可以解决问题。