形状失配模型InceptionResNetV2 & weigts

Question

我使用InceptionResNetV2进行图像分类&使用回复权重。但要犯错误：

ValueError:您正在尝试将包含449层的权重文件加载到一个具有448层的模型中。

img_ht = 96
img_wid = 96
img_chnl = 3

import tensorflow as tf
from tensorflow import keras
from keras_preprocessing.image import ImageDataGenerator

train_generator = train_datagen.flow_from_directory(
    directory = "../input/cassava-disease/train/train/",
subset="training",
batch_size = 49,
seed=42,
shuffle=False,
class_mode="categorical",
target_size=(img_ht, img_wid))

valid_generator = train_datagen.flow_from_directory(
directory = "../input/cassava-disease/train/train/",
subset="validation",
batch_size=49,
seed=42,
shuffle=False,
class_mode="categorical",
target_size = (img_ht, img_wid))

from keras.applications import InceptionResNetV2 as InceptionResNetV2

base_model = keras.applications.InceptionResNetV2(input_shape=(img_ht, img_wid, 3), 
                                         include_top = False, 
                                         weights = "../input/inception/inception_resnet_v2_weights_tf_dim_ordering_tf_kernels.h5")

base_model.trainable = False
print(base_model.summary())

Answer 1

找到答案了。这是因为行-> include_top = False。

python &机器学习的新技术