Python ValueError:层sequential_37的输入0与层不兼容：预期ndim=3，发现ndim=2。收到完整形状：[无，15]

我已经尽了我所知的一切努力。 此外，输入的所有组合_dim=15已经存在。如果有人能帮我

print(x_train.shape)
print(y_train.shape)
print(x_test.shape)
print(y_test.shape)

（233941,15）

（233941,1）

（100261、15）

（100261，）

我已经使用input_dim=（233941,15）和input_dim=（233941,1）完成了测试。但我还是找不到问题。 我的问题可能在数据集部分吗

from keras.models import Sequential
from keras.layers import Dense
from keras.layers import Dense, Dropout, LSTM
model = Sequential()
model.add(LSTM(100, input_dim=15, return_sequences=True))
model.add(Dropout(0.3))

model.add(LSTM(50, return_sequences = True))
model.add(Dropout(0.3))
#3 camada
model.add(LSTM(50, return_sequences = True))
model.add(Dropout(0.3))

model.add(LSTM(units = 50))
model.add(Dropout(0.3))

model.add(Dense(1, activation='sigmoid'))

# Compile model
model.compile(optimizer = 'adam', loss = 'mean_squared_error',
                  metrics = ['mean_absolute_error'])
# Fit the model
model.fit(x_train,y_train,epochs=100, validation_data=(x_test,y_test))

纪元1/100
---------------------------------------------------------------------------
ValueError回溯（最近一次调用上次）
在（）
21指标=[“平均绝对误差]）
22#适合模型
--->23模型拟合（x_序列，y_序列，历元=100，验证数据=（x_检验，y_检验））
10帧
/包装器中的usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/func_graph.py（*args，**kwargs）
971例外情况为e:#pylint:disable=broad except
972如果hasattr（e，“AGU错误元数据”）：
-->973将e.ag\u错误\u元数据引发到\u异常（e）
974其他：
975提高
ValueError:在用户代码中：
/usr/local/lib/python3.6/dist包/tensorflow/python/keras/engine/training.py:806 train_函数*
返回步骤_函数（self、迭代器）
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:796-step_函数**
输出=模型。分配策略。运行（运行步骤，参数=（数据，）
/usr/local/lib/python3.6/dist包/tensorflow/python/distribute/distribute_lib.py:1211运行
返回self.\u扩展。为每个\u副本调用\u（fn，args=args，kwargs=kwargs）
/usr/local/lib/python3.6/dist包/tensorflow/python/distribute/distribute_lib.py:2585调用每个副本
返回自我。为每个副本（fn、ARG、kwargs）调用
/usr/local/lib/python3.6/dist-packages/tensorflow/python/distribute/distribute\u-lib.py:2945\u为每个复制副本调用
返回fn（*args，**kwargs）
/usr/local/lib/python3.6/dist包/tensorflow/python/keras/engine/training.py:789运行步骤**
输出=型号列车步进（数据）
/usr/local/lib/python3.6/dist包/tensorflow/python/keras/engine/training.py:747 train_步骤
y_pred=self（x，training=True）
/usr/local/lib/python3.6/dist包/tensorflow/python/keras/engine/base\u layer.py:976\u调用__
（姓名）
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/input\u spec.py:180断言\u输入\u兼容性
str（x.shape.as_list（））
ValueError:层sequential_37的输入0与层不兼容：预期ndim=3，发现ndim=2。收到完整形状：[无，15]

正如Marco Certliani在评论中提到的，您需要为RNN正确设置输入格式，因为您提到的错误是三维的

以下是输入张量的表示形式：

---

这意味着您的3D张量的形状为（批量大小、时间步长、输入维度）。

您必须排列数据以适应RNN。。。您的输入必须是三维的，而目前它只是二维的

Epoch 1/100
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-79-2e6c4d489e38> in <module>()
     21                   metrics = ['mean_absolute_error'])
     22 # Fit the model
---> 23 model.fit(x_train,y_train,epochs=100, validation_data=(x_test,y_test))

10 frames
/usr/local/lib/python3.6/dist-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:

    /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:806 train_function  *
        return step_function(self, iterator)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:796 step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/distribute/distribute_lib.py:1211 run
        return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/distribute/distribute_lib.py:2585 call_for_each_replica
        return self._call_for_each_replica(fn, args, kwargs)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/distribute/distribute_lib.py:2945 _call_for_each_replica
        return fn(*args, **kwargs)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:789 run_step  **
        outputs = model.train_step(data)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:747 train_step
        y_pred = self(x, training=True)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py:976 __call__
        self.name)
    /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/input_spec.py:180 assert_input_compatibility
        str(x.shape.as_list()))

    ValueError: Input 0 of layer sequential_37 is incompatible with the layer: expected ndim=3, found ndim=2. Full shape received: [None, 15]