import os os.environ['TF_CPP_MIN_LOG_LEVEL']='2' import os from tensorflow import keras import matplotlib.pyplot as plt import numpy as np import tensorflow as tf from sklearn.model_selection import train_test_split from tensorflow.keras import Model from tensorflow.keras.layers import Conv2D, BatchNormalization, Activation, MaxPool2D, Dropout, Flatten, Dense np.set_printoptions(threshold=np.inf) from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense from tensorflow.keras.utils import plot_model # 创建模型 model = Sequential() model.add(Conv2D(6, (3, 3), activation='relu', padding='same', input_shape=(3, 1024, 1))) model.add(Conv2D(16, (3, 3), activation='relu'), padding='same') model.add(MaxPooling2D((2, 2))) model.add(Dropout(0.1)) model.add(Flatten()) model.add(Dense(1024, activation='relu')) model.add(Dropout(0.2)) model.add(Dense(225, activation='sigmoid')) # 输出模型结构图表 plot_model(model, show_shapes=True) TypeError: add() got an unexpected keyword argument 'padding'

在第6行和第7行中，您的代码中有一些语法错误。请注意在第6行中，由于缺少右括号，导致第7行的参数被视为model.add()函数的参数，而不是Conv2D()函数的参数。此外，在第7行中，您意外地在Conv2D()函数的括号之外使用了一个逗号。因此，您可以将代码更改如下所示：

import os
os.environ['TF_CPP_MIN_LOG_LEVEL']='2'
import os
from tensorflow import keras
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
from sklearn.model_selection import train_test_split
from tensorflow.keras import Model
from tensorflow.keras.layers import Conv2D, BatchNormalization, Activation, MaxPool2D, Dropout, Flatten, Dense
np.set_printoptions(threshold=np.inf)

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense
from tensorflow.keras.utils import plot_model

# 创建模型
model = Sequential()
model.add(Conv2D(6, (3, 3), activation='relu', padding='same', input_shape=(3, 1024, 1)))
model.add(Conv2D(16, (3, 3), activation='relu', padding='same'))
model.add(MaxPooling2D((2, 2)))
model.add(Dropout(0.1))
model.add(Flatten())
model.add(Dense(1024, activation='relu'))
model.add(Dropout(0.2))
model.add(Dense(225, activation='sigmoid'))

# 输出模型结构图表
plot_model(model, show_shapes=True)

请注意，在第6行和第7行中，我们已经修复了语法错误，并将输入参数放在正确的位置。现在，代码应该可以正常运行，输出模型结构图表。