当我运行此功能时：
def run_lstm(x_train,x_test,y_train,y_test):
model = tf.keras.models.Sequential()
model.add(tf.keras.layers.LSTM(500))
# model.add(tf.keras.layers.Dropout(0.5))
model.add(tf.keras.layers.Dense(18, activation='sigmoid'))
model.compile(loss='binary_crossentropy',
optimizer='rmsprop',
metrics=['accuracy'])
model.fit(x_train, y_train, batch_size=32, epochs=10, validation_data=(x_test,y_test))
score = model.evaluate(x_test, y_test)
print('Test loss:', score[0])
print('Test accuracy:', score[1])
我收到此错误：
Traceback (most recent call last):
File "/Users/khaled/Documents/GitHub/deep-learning-for-human-activity-recognition-using-skeleton-datasets/train.py", line 294, in <module>
run_lstm(x_train, x_test, y_train, y_test)
File "/Users/khaled/Documents/GitHub/deep-learning-for-human-activity-recognition-using-skeleton-datasets/train.py", line 277, in run_lstm
model.fit(x_train, y_train, batch_size=32, epochs=10, validation_data=(x_test,y_test))
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py", line 1509, in fit
validation_split=validation_split)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py", line 993, in _standardize_user_data
class_weight, batch_size)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py", line 1029, in _standardize_weights
self._set_inputs(x)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/training/checkpointable/base.py", line 426, in _method_wrapper
method(self, *args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py", line 1222, in _set_inputs
self.build(input_shape=input_shape)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/keras/engine/sequential.py", line 222, in build
layer.build(shape)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/keras/utils/tf_utils.py", line 149, in wrapper
output_shape = fn(instance, input_shape)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/keras/layers/recurrent.py", line 552, in build
self.cell.build(step_input_shape)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/keras/utils/tf_utils.py", line 149, in wrapper
output_shape = fn(instance, input_shape)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/keras/layers/recurrent.py", line 1934, in build
constraint=self.kernel_constraint)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 586, in add_weight
aggregation=aggregation)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/training/checkpointable/base.py", line 591, in _add_variable_with_custom_getter
**kwargs_for_getter)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1986, in make_variable
aggregation=aggregation)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variables.py", line 145, in __call__
return cls._variable_call(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variables.py", line 141, in _variable_call
aggregation=aggregation)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variables.py", line 120, in <lambda>
previous_getter = lambda **kwargs: default_variable_creator(None, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py", line 2434, in default_variable_creator
import_scope=import_scope)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/variables.py", line 147, in __call__
return super(VariableMetaclass, cls).__call__(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/resource_variable_ops.py", line 297, in __init__
constraint=constraint)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/resource_variable_ops.py", line 411, in _init_from_args
initial_value(), name="initial_value", dtype=dtype)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1970, in <lambda>
shape, dtype=dtype, partition_info=partition_info)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/tensorflow/python/ops/init_ops.py", line 470, in __call__
scale /= max(1., (fan_in + fan_out) / 2.)
TypeError: unsupported operand type(s) for +: 'NoneType' and 'int'
我应该改变什么？
谢谢。
答案 0 :(得分：1)
我通过在代码中添加两行来解决了这个问题：
x_train = x_train.reshape(x_train.shape[0], x_train.shape[1], 1)
x_test = x_test.reshape(x_test.shape[0], x_test.shape[1], 1)
函数将是：
def run_lstm(x_train,x_test,y_train,y_test):
x_train = x_train.reshape(x_train.shape[0], x_train.shape[1], 1)
x_test = x_test.reshape(x_test.shape[0], x_test.shape[1], 1)
model = tf.keras.models.Sequential()
model.add(tf.keras.layers.LSTM(50))
# model.add(tf.keras.layers.Dropout(0.5))
# model.add(tf.keras.layers.Flatten())
model.add(tf.keras.layers.Dense(18, activation='sigmoid'))
model.compile(loss='binary_crossentropy',
optimizer='rmsprop',
metrics=['accuracy'])
model.fit(x_train, y_train, batch_size=300, epochs=2, validation_data=(x_test,y_test))
score = model.evaluate(x_test, y_test)
print('Test loss:', score[0])
print('Test accuracy:', score[1])