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当我运行这个程序时，我没有得到模型执行细节，也没有错误。我的问题是，尽管没有报告错误，为什么我没有得到有关模型执行的任何详细信息？以下是代码和输出：

编码：

import tensorflow as tf
import keras_tuner as kt
from tensorflow import keras
#from kerastuner import RandomSearch
#from kerastuner.engine.hyperparameters import HyperParameters
import os
import cv2
import pandas as pd
import numpy as np
from tensorflow.keras.utils import to_categorical
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import train_test_split
print(kt.__version__)


f= pd.read_csv('CELLS_ALL.csv')
Labels= f['labels']
path_dir = 'C:\\Users\\Tusneem\\PycharmProjects\\imageDataGen\\images\\'
img_all = []
for i in os.listdir(path_dir):
   img_sig = cv2.imread(path_dir+i)
   img_sig = cv2.resize(img_sig, (50, 50))
   img_all.append(img_sig)
x = np.array(img_all, dtype="float") / 255.0
le = LabelEncoder()
y = le.fit_transform(Labels)
y = to_categorical(y)
print(y)


(trainX, testX, trainY, testY) = train_test_split(x, y, test_size=0.20, random_state=42)

# for cnn images should me of shape (len(training,size,size, channel)

trainX= trainX.reshape(len(trainX),50,50,3)
testX = testX.reshape(len(testX),50,50,3)

print(trainX.shape)
print(trainY.shape)


def build_model(hp):
    model = keras.Sequential()
    model.add(keras.layers.Conv2D(
            hp.Int('conv_1_filter', min_value=32, max_value=128, step=20),
            hp.Choice('conv_1_kernel', values=[3, 5]),
            activation='relu',
            input_shape=(50, 50, 3)))
    model.add(keras.layers.Conv2D(
            hp.Int('conv_2_filter', min_value=32, max_value=64, step=20),
            hp.Choice('conv_2_kernel', values=[3, 5]),
            activation='relu'))
    model.add(keras.layers.Flatten())
    model.add(keras.layers.Dense(
            hp.Int('dense_1_units', min_value=32, max_value=64, step=20),
            activation='relu'
        ))
    model.add(keras.layers.Dense(15, activation='softmax'))

    model.compile(optimizer=keras.optimizers.Adam(hp.Choice('learning_rate', values=[1e-2, 1e-3])),
                  loss='categorical_crossentropy',
                  metrics=['accuracy'])
    return model
#parse_categorical_crossentropy


tuner_search= kt.RandomSearch(build_model,
                          objective='val_accuracy',
                          max_trials=5) #,directory='tune',project_name="cnn model tunning"

tuner_search.search(trainX,trainY,epochs=3,validation=(testX,testY))
#best_model = tuner_search.get_best_models()[0]

我得到的输出：

2021-08-28 20:05:31.957461: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] 成功打开动态库 cudart64_110.dll

tensorflow/core/common_runtime/gpu/gpu_device.cc:1418] 创建了 TensorFlow 设备（/job:localhost/replica:0/task:0/device:GPU:0 具有 6003 MB 内存）-> 物理 GPU（设备：0，名称：采用 Max-Q 设计的 GeForce RTX 2070，pci 总线 ID：0000:01:00.0，计算能力：7.5）

Process finished with exit code 0
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