我不知道為什么當我運行下面的代碼時這個錯誤不斷出現
CNN.fit(X_train_vector, y_train, epochs=10)
我的 CNN 代碼是這樣的：
CNN = tf.keras.models.Sequential()
CNN.add(tf.keras.layers.Conv1D(120, kernel_size=3, padding='valid', activation='relu', input_shape = (21367, 9000)))
CNN.add(tf.keras.layers.MaxPooling1D(2))
CNN.add(tf.keras.layers.Dropout(0.2))
CNN.add(tf.keras.layers.Flatten())
CNN.add(tf.keras.layers.Dense(200, activation='relu'))
CNN.add(tf.keras.layers.Dense(20, activation='relu'))
CNN.add(tf.keras.layers.Dense(1, activation='softmax'))
我的“X_train_vector”有一個形狀：
(21367, 9000)
我的“y_train”有一個形狀：
(21367, 1)
我得到的錯誤：
Epoch 1/10
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-108-895976bf38cd> in <module>()
----> 1 CNN.fit(X_train_vector, y_train, epochs=10)
1 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/func_graph.py in autograph_handler(*args, **kwargs)
1145 except Exception as e: # pylint:disable=broad-except
1146 if hasattr(e, "ag_error_metadata"):
-> 1147 raise e.ag_error_metadata.to_exception(e)
1148 else:
1149 raise
ValueError: in user code:
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1021, in train_function *
return step_function(self, iterator)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1010, in step_function **
outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1000, in run_step **
outputs = model.train_step(data)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 859, in train_step
y_pred = self(x, training=True)
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 67, in error_handler
raise e.with_traceback(filtered_tb) from None
File "/usr/local/lib/python3.7/dist-packages/keras/engine/input_spec.py", line 264, in assert_input_compatibility
raise ValueError(f'Input {input_index} of layer "{layer_name}" is '
ValueError: Input 0 of layer "sequential_13" is incompatible with the layer: expected shape=(None, 21367, 9000), found shape=(None, 9000)
我嘗試了幾種解決方案，包括將我的第一行 CNN 更改為：
CNN.add(tf.keras.layers.Conv1D(120, kernel_size=3, padding='valid', activation='relu', input_shape = (9000)))
但運行它說：
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-109-dd8d734d0a9f> in <module>()
1 CNN = tf.keras.models.Sequential()
----> 2 CNN.add(tf.keras.layers.Conv1D(120, kernel_size=3, padding='valid', activation='relu', input_shape = (9000)))
3 CNN.add(tf.keras.layers.MaxPooling1D(2))
4 CNN.add(tf.keras.layers.Dropout(0.2))
5 CNN.add(tf.keras.layers.Flatten())
3 frames
/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py in __init__(self, trainable, name, dtype, dynamic, **kwargs)
441 else:
442 batch_size = None
--> 443 batch_input_shape = (batch_size,) tuple(kwargs['input_shape'])
444 self._batch_input_shape = batch_input_shape
445
TypeError: 'int' object is not iterable
誰能幫我。我一直在尋找兩天的解決方案，它應該按照我嘗試的方式作業。我犯了一個錯誤嗎？請告訴我。提前致謝。
uj5u.com熱心網友回復：
輸入陣列應具有形狀(None, shape_0, shape_1)，其中None表示批量大小，并(shape_0, shape_1)表示特征的形狀。所以，你應該重塑你的輸入陣列：
X_train_vector = X_train_vector.reshape(-1, 9000, 1)
而且您在構建模型時實際上不需要指定批量大小，因此請將其洗掉并僅用(9000, 1)作input_shape. 試試這個：
CNN = tf.keras.models.Sequential()
CNN.add(tf.keras.layers.Conv1D(120, kernel_size=3, padding='valid', activation='relu', input_shape = (9000, 1)))
CNN.add(tf.keras.layers.MaxPooling1D(2))
CNN.add(tf.keras.layers.Dropout(0.2))
CNN.add(tf.keras.layers.Flatten())
CNN.add(tf.keras.layers.Dense(200, activation='relu'))
CNN.add(tf.keras.layers.Dense(20, activation='relu'))
CNN.add(tf.keras.layers.Dense(1, activation='softmax'))
這應該可以解決問題，同樣的錯誤不會再次出現。
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