ВНИМАНИЕ: тензорный поток: модель была построена с формой (нет, 66, 200, 3). ⇐ Python

[Anonymous]

У меня есть следующий код, который генерирует ошибку относительно фигуры:

Код: Выделить всё

from keras.layers import Dense, Activation
from keras import Sequential
from keras.models import load_model
from tensorflow.keras.optimizers import Adam
import tensorflow
import keras
from tensorflow.python.keras.layers import Input, Dense
from tensorflow.keras.optimizers import Adam
from keras.layers import Convolution2D, MaxPooling2D, Dropout, Flatten, Dense

def nvidia_model():
model = Sequential()
model.add(Convolution2D(24,(5,5), strides=(2, 2), input_shape=(66, 200, 3), activation='relu'))
model.add(Convolution2D(36, (5,5), strides=(2, 2), activation='relu'))
model.add(Convolution2D(48, (5,5), strides=(2, 2), activation='relu'))
model.add(Convolution2D(64, (3,3), activation='relu'))
model.add(Convolution2D(64, (3,3), activation='relu'))
model.add(Flatten())
model.add(Dense(100, activation = 'relu'))
model.add(Dense(50, activation = 'relu'))
model.add(Dense(10, activation = 'relu'))
model.add(Dense(1))

optimizer = Adam(learning_rate=1e-3)
model.compile(loss='mse', optimizer=optimizer)
return model

model = nvidia_model()
print(model.summary())

history = model.fit(X_train, y_train, epochs=30,validation_data=(X_valid,y_valid),batch_size=100,verbose=1,shuffle=1)

Однако при обучении первой эпохи я получаю ошибку, которую публикую ниже:

Код: Выделить всё

Epoch 1/30
WARNING:tensorflow:Model was constructed with shape (None, 66, 200, 3) for input KerasTensor(type_spec=TensorSpec(shape=(None, 66, 200, 3), dtype=tf.float32, name='conv2d_5_input'), name='conv2d_5_input', description="created by layer 'conv2d_5_input'"), but it was called on an input with incompatible shape (None,).
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
 in ()
----> 1 history = model.fit(X_train, y_train, epochs=30,validation_data=(X_valid,y_valid),batch_size=100,verbose=1,shuffle=1)

1 frames
/usr/local/lib/python3.7/dist-packages/keras/engine/training.py in tf__train_function(iterator)
13                 try:
14                     do_return = True
---> 15                     retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
16                 except:
17                     do_return = False

ValueError: in user code:

File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1160, in train_function  *
return step_function(self, iterator)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1146, 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 1135, in run_step  **
outputs = model.train_step(data)
File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 993, in train_step
y_pred = self(x, training=True)
File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 70, 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 251, in assert_input_compatibility
f'Input {input_index} of layer "{layer_name}" '

ValueError: Exception encountered when calling layer "sequential_1" "                 f"(type Sequential).

Input 0 of layer "conv2d_5" is incompatible with the layer: expected min_ndim=4, found ndim=1. Full shape received: (None,)

Call arguments received by layer "sequential_1" "                 f"(type Sequential):
• inputs=tf.Tensor(shape=(None,), dtype=string)
• training=True
• mask=None

Я также добавил опубликованный здесь код в Codeshare, чтобы вы могли видеть мой код. Можете ли вы помочь мне понять, что происходит? Спасибо за помощь.

Подробнее здесь: https://stackoverflow.com/questions/732 ... e-66-200-3