Tensorflow GPU 启动时间长
Tensorflow GPU long startup time
我有这个问题，我知道很多人都听说过。我从配备 GTX 1050 Ti 的笔记本电脑升级到配备 RTX 3060 Ti 的 PC。我是 Anaconda 虚拟环境中的 运行 一切。我已经将我的环境从笔记本电脑复制到 PC。现在 TensorFlow GPU 需要很长时间才能启动。即使我写了两行代码：
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())
需要很多时间（30多分钟）。同样的事情在我的 GTX 1050 Ti 笔记本电脑上也能完美运行。
我尝试了很多东西：
- 在另一个环境中重新安装每个包（当然，相同的版本——我使用的是 TF 2.1、cudnn 7.6.5、cudatoolkit 10.1.243）。
- 在我的程序之前放几行代码（我尝试了 10 多种不同的可能性）。
- 正在重新安装清理 GPU 驱动程序。
TensorFlow启动后，RTX 3060 Ti运行正常，训练速度非常快。
我在谷歌上搜索了很多，但我看到现在还有很多人在我的地方，所以我预计不会很快得到答复:)。
无论如何，如果有人设法找到答案，请与我分享！提前致谢，祝您有美好的一天！
P.S。如果您需要代码或控制台日志，请在这里。我写了一个快速的 MNIST 程序：
from tensorflow.keras.datasets import mnist
from tensorflow.keras.utils import to_categorical
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Conv2D
from tensorflow.keras.layers import MaxPooling2D
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import Flatten
from tensorflow.keras.optimizers import SGD
from numpy import mean
from numpy import std
from matplotlib import pyplot as plt
from sklearn.model_selection import KFold
# Load and prepare the train and test set
def load_dataset():
# Load the dataset
(trainX, trainY), (testX, testY) = mnist.load_data()
# Reshape the dataset to have a single channel
trainX = trainX.reshape((trainX.shape[0], 28, 28, 1))
testX = testX.reshape((testX.shape[0], 28, 28, 1))
# One hot encode target values
trainY = to_categorical(trainY)
testY = to_categorical(testY)
return trainX, trainY, testX, testY
# Scale pixels
def prep_pixels(train, test):
# Convert from integers to float
train_norm = train.astype('float32')
test_norm = test.astype('float32')
# Normalize to range 0-1
train_norm = train_norm / 255.0
test_norm = test_norm / 255.0
return train_norm, test_norm
# Define the CNN classifier
def define_classifier():
# Build the structure
classifier = Sequential()
classifier.add(Conv2D(32, (3, 3), activation = 'relu', input_shape = (28, 28, 1)))
classifier.add(MaxPooling2D(pool_size = (2, 2)))
classifier.add(Conv2D(64, (3, 3), activation = 'relu'))
classifier.add(Conv2D(64, (3, 3), activation = 'relu'))
classifier.add(MaxPooling2D((2, 2)))
classifier.add(Flatten())
classifier.add(Dense(100, activation = 'relu'))
classifier.add(Dense(10, activation = 'softmax'))
# Compile the model
classifier.compile(optimizer = SGD(lr = 0.01, momentum = 0.9), loss = 'categorical_crossentropy',
metrics = ['accuracy'])
return classifier
# Evaluate the classifier using the K-Fold Cross-Validation
def evaluate_classifier(dataX, dataY, n_folds = 5):
scores, histories = list(), list()
# Prepare Cross-Validation
kfold = KFold(n_folds, shuffle = True, random_state = 1)
# Enumerate splits
for trainX_i, testX_i in kfold.split(dataX):
# Define classifier
classifier = define_classifier()
# Select rows for train and test
trainX, trainY, testX, testY = dataX[trainX_i], dataY[trainX_i], dataX[testX_i], dataY[testX_i]
# Fit the classifier
history = classifier.fit(trainX, trainY, batch_size = 32, epochs = 10,
validation_data = (testX, testY), verbose = 1)
# Evaluate the classifier
_, acc = classifier.evaluate(testX, testY, verbose = 1)
print('> ACC: %.3f' % (acc * 100.0))
# Store history, accuracy
scores.append(acc)
histories.append(history)
return scores, histories
# Plot learning curves
def visualise_learning(histories):
for i in range(len(histories)):
plt.tight_layout()
# Plot LOSS
plt.subplot(2, 1, 1)
plt.title('Cross-Entropy Loss')
plt.plot(histories[i].history['loss'], color = 'blue', label = 'train')
plt.plot(histories[i].history['val_loss'], color = 'orange', label = 'test')
# Plot ACCURACY
plt.subplot(2, 1, 2)
plt.title('Classification Accuracy')
plt.plot(histories[i].history['accuracy'], color = 'blue', label = 'train')
plt.plot(histories[i].history['val_accuracy'], color = 'orange', label = 'test')
plt.show()
# Summarize classifier performance
def summarize_performance(scores):
print('Accuracy: mean=%.3f std=%.3f, n=%d' % (mean(scores) * 100, std(scores) * 100, len(scores)))
# Run all parts together
def run():
trainX, trainY, testX, testY = load_dataset()
trainX, testX = prep_pixels(trainX, testX)
scores, histories = evaluate_classifier(trainX, trainY)
visualise_learning(histories)
summarize_performance(scores)
def save_model():
trainX, trainY, testX, testY = load_dataset()
trainX, testX = prep_pixels(trainX, testX)
classifier = define_classifier()
classifier.fit(trainX, trainY, epochs = 25, batch_size = 32, verbose = 1)
classifier.save('final_classifier.h5')
##############################################################################################################
# make a prediction for a new image.
from tensorflow.keras.preprocessing.image import load_img
from tensorflow.keras.preprocessing.image import img_to_array
from tensorflow.keras.models import load_model
# load and prepare the image
def load_image(filename):
# load the image
img = load_img(filename, grayscale=True, target_size=(28, 28))
# convert to array
img = img_to_array(img)
# reshape into a single sample with 1 channel
img = img.reshape(1, 28, 28, 1)
# prepare pixel data
img = img.astype('float32')
img = img / 255.0
return img
# load an image and predict the class
def run_example():
# load the image
img = load_image('image.png')
# load model
model = load_model('final_classifier.h5')
# predict the class
digit = model.predict_classes(img)
print(digit[0])
# entry point, run the example
#run_example()
run()
这是控制台日志：
Python 3.7.9 (default, Aug 31 2020, 17:10:11) [MSC v.1916 64 bit (AMD64)]
Type "copyright", "credits" or "license" for more information.
IPython 7.19.0 -- An enhanced Interactive Python.
runcell(0, 'C:/Python/Projects/Handwritten Digit Recognition/digit_recognizer.py')
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.395981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:31.430370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:31.452057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:31.659034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:31.837570: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.055598: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.056116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.395981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:31.430370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:31.452057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:31.659034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:31.837570: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.055598: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.056116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:32.652696: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2021-01-14 13:47:32.655023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:32.655039: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:32.655046: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:32.655051: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:32.655057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:32.655062: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:32.655067: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.655072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.655095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.395981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:31.430370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:31.452057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:31.659034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:31.837570: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.055598: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.056116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:32.652696: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2021-01-14 13:47:32.655023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:32.655039: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:32.655046: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:32.655051: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:32.655057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:32.655062: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:32.655067: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.655072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.655095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:50:57.038023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-14 13:50:57.038040: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] 0
2021-01-14 13:50:57.038045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0: N
2021-01-14 13:50:57.039526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6699 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3060 Ti, pci bus id: 0000:01:00.0, compute capability: 8.6)
Train on 48000 samples, validate on 12000 samples
Epoch 1/10
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.395981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:31.430370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:31.452057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:31.659034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:31.837570: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.055598: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.056116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:32.652696: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2021-01-14 13:47:32.655023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:32.655039: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:32.655046: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:32.655051: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:32.655057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:32.655062: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:32.655067: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.655072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.655095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:50:57.038023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-14 13:50:57.038040: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] 0
2021-01-14 13:50:57.038045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0: N
2021-01-14 13:50:57.039526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6699 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3060 Ti, pci bus id: 0000:01:00.0, compute capability: 8.6)
2021-01-14 13:50:57.563527: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.395981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:31.430370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:31.452057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:31.659034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:31.837570: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.055598: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.056116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:32.652696: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2021-01-14 13:47:32.655023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:32.655039: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:32.655046: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:32.655051: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:32.655057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:32.655062: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:32.655067: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.655072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.655095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:50:57.038023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-14 13:50:57.038040: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] 0
2021-01-14 13:50:57.038045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0: N
2021-01-14 13:50:57.039526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6699 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3060 Ti, pci bus id: 0000:01:00.0, compute capability: 8.6)
2021-01-14 13:50:57.563527: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:52:17.763274: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
7232/48000 [===>..........................] - ETA: 1:21:26 - loss: 2.3010 - accuracy: 0.1114
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.395981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:31.430370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:31.452057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:31.659034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:31.837570: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.055598: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.056116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:32.652696: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2021-01-14 13:47:32.655023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:32.655039: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:32.655046: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:32.655051: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:32.655057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:32.655062: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:32.655067: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.655072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.655095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:50:57.038023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-14 13:50:57.038040: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] 0
2021-01-14 13:50:57.038045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0: N
2021-01-14 13:50:57.039526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6699 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3060 Ti, pci bus id: 0000:01:00.0, compute capability: 8.6)
2021-01-14 13:50:57.563527: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:52:17.763274: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 14:05:23.645822: W tensorflow/stream_executor/gpu/redzone_allocator.cc:312] Internal: Invoking GPU asm compilation is supported on Cuda non-Windows platforms only
Relying on driver to perform ptx compilation. This message will be only logged once.
48000/48000 [==============================] - 869s 18ms/sample - loss: 2.3019 - accuracy: 0.1101 - val_loss: 2.3014 - val_accuracy: 0.1144
在“Adding visible gpu devices: 0”行之后打开动态库花了很多时间。
GTX 1050 Ti 卡基于 Pascal 兼容 CUDA version start with 8.x 的架构，其中 RTX 3060 Ti 卡基于 Ampere 兼容的架构CUDA version start with 11.x.
因此您的 gpu 卡兼容的 tensorflow 版本是 2.4.0，cuDNN 是 8.0。
感谢 njuffa CUDNN support matrix and insights. You can check tensorflow tested build configurations for windows and Linux。
我有这个问题，我知道很多人都听说过。我从配备 GTX 1050 Ti 的笔记本电脑升级到配备 RTX 3060 Ti 的 PC。我是 Anaconda 虚拟环境中的 运行 一切。我已经将我的环境从笔记本电脑复制到 PC。现在 TensorFlow GPU 需要很长时间才能启动。即使我写了两行代码：
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())
需要很多时间（30多分钟）。同样的事情在我的 GTX 1050 Ti 笔记本电脑上也能完美运行。 我尝试了很多东西：
- 在另一个环境中重新安装每个包（当然，相同的版本——我使用的是 TF 2.1、cudnn 7.6.5、cudatoolkit 10.1.243）。
- 在我的程序之前放几行代码（我尝试了 10 多种不同的可能性）。
- 正在重新安装清理 GPU 驱动程序。
TensorFlow启动后，RTX 3060 Ti运行正常，训练速度非常快。 我在谷歌上搜索了很多，但我看到现在还有很多人在我的地方，所以我预计不会很快得到答复:)。
无论如何，如果有人设法找到答案，请与我分享！提前致谢，祝您有美好的一天！
P.S。如果您需要代码或控制台日志，请在这里。我写了一个快速的 MNIST 程序：
from tensorflow.keras.datasets import mnist
from tensorflow.keras.utils import to_categorical
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Conv2D
from tensorflow.keras.layers import MaxPooling2D
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import Flatten
from tensorflow.keras.optimizers import SGD
from numpy import mean
from numpy import std
from matplotlib import pyplot as plt
from sklearn.model_selection import KFold
# Load and prepare the train and test set
def load_dataset():
# Load the dataset
(trainX, trainY), (testX, testY) = mnist.load_data()
# Reshape the dataset to have a single channel
trainX = trainX.reshape((trainX.shape[0], 28, 28, 1))
testX = testX.reshape((testX.shape[0], 28, 28, 1))
# One hot encode target values
trainY = to_categorical(trainY)
testY = to_categorical(testY)
return trainX, trainY, testX, testY
# Scale pixels
def prep_pixels(train, test):
# Convert from integers to float
train_norm = train.astype('float32')
test_norm = test.astype('float32')
# Normalize to range 0-1
train_norm = train_norm / 255.0
test_norm = test_norm / 255.0
return train_norm, test_norm
# Define the CNN classifier
def define_classifier():
# Build the structure
classifier = Sequential()
classifier.add(Conv2D(32, (3, 3), activation = 'relu', input_shape = (28, 28, 1)))
classifier.add(MaxPooling2D(pool_size = (2, 2)))
classifier.add(Conv2D(64, (3, 3), activation = 'relu'))
classifier.add(Conv2D(64, (3, 3), activation = 'relu'))
classifier.add(MaxPooling2D((2, 2)))
classifier.add(Flatten())
classifier.add(Dense(100, activation = 'relu'))
classifier.add(Dense(10, activation = 'softmax'))
# Compile the model
classifier.compile(optimizer = SGD(lr = 0.01, momentum = 0.9), loss = 'categorical_crossentropy',
metrics = ['accuracy'])
return classifier
# Evaluate the classifier using the K-Fold Cross-Validation
def evaluate_classifier(dataX, dataY, n_folds = 5):
scores, histories = list(), list()
# Prepare Cross-Validation
kfold = KFold(n_folds, shuffle = True, random_state = 1)
# Enumerate splits
for trainX_i, testX_i in kfold.split(dataX):
# Define classifier
classifier = define_classifier()
# Select rows for train and test
trainX, trainY, testX, testY = dataX[trainX_i], dataY[trainX_i], dataX[testX_i], dataY[testX_i]
# Fit the classifier
history = classifier.fit(trainX, trainY, batch_size = 32, epochs = 10,
validation_data = (testX, testY), verbose = 1)
# Evaluate the classifier
_, acc = classifier.evaluate(testX, testY, verbose = 1)
print('> ACC: %.3f' % (acc * 100.0))
# Store history, accuracy
scores.append(acc)
histories.append(history)
return scores, histories
# Plot learning curves
def visualise_learning(histories):
for i in range(len(histories)):
plt.tight_layout()
# Plot LOSS
plt.subplot(2, 1, 1)
plt.title('Cross-Entropy Loss')
plt.plot(histories[i].history['loss'], color = 'blue', label = 'train')
plt.plot(histories[i].history['val_loss'], color = 'orange', label = 'test')
# Plot ACCURACY
plt.subplot(2, 1, 2)
plt.title('Classification Accuracy')
plt.plot(histories[i].history['accuracy'], color = 'blue', label = 'train')
plt.plot(histories[i].history['val_accuracy'], color = 'orange', label = 'test')
plt.show()
# Summarize classifier performance
def summarize_performance(scores):
print('Accuracy: mean=%.3f std=%.3f, n=%d' % (mean(scores) * 100, std(scores) * 100, len(scores)))
# Run all parts together
def run():
trainX, trainY, testX, testY = load_dataset()
trainX, testX = prep_pixels(trainX, testX)
scores, histories = evaluate_classifier(trainX, trainY)
visualise_learning(histories)
summarize_performance(scores)
def save_model():
trainX, trainY, testX, testY = load_dataset()
trainX, testX = prep_pixels(trainX, testX)
classifier = define_classifier()
classifier.fit(trainX, trainY, epochs = 25, batch_size = 32, verbose = 1)
classifier.save('final_classifier.h5')
##############################################################################################################
# make a prediction for a new image.
from tensorflow.keras.preprocessing.image import load_img
from tensorflow.keras.preprocessing.image import img_to_array
from tensorflow.keras.models import load_model
# load and prepare the image
def load_image(filename):
# load the image
img = load_img(filename, grayscale=True, target_size=(28, 28))
# convert to array
img = img_to_array(img)
# reshape into a single sample with 1 channel
img = img.reshape(1, 28, 28, 1)
# prepare pixel data
img = img.astype('float32')
img = img / 255.0
return img
# load an image and predict the class
def run_example():
# load the image
img = load_image('image.png')
# load model
model = load_model('final_classifier.h5')
# predict the class
digit = model.predict_classes(img)
print(digit[0])
# entry point, run the example
#run_example()
run()
这是控制台日志：
Python 3.7.9 (default, Aug 31 2020, 17:10:11) [MSC v.1916 64 bit (AMD64)]
Type "copyright", "credits" or "license" for more information.
IPython 7.19.0 -- An enhanced Interactive Python.
runcell(0, 'C:/Python/Projects/Handwritten Digit Recognition/digit_recognizer.py')
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.395981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:31.430370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:31.452057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:31.659034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:31.837570: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.055598: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.056116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.395981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:31.430370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:31.452057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:31.659034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:31.837570: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.055598: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.056116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:32.652696: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2021-01-14 13:47:32.655023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:32.655039: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:32.655046: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:32.655051: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:32.655057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:32.655062: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:32.655067: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.655072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.655095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.395981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:31.430370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:31.452057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:31.659034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:31.837570: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.055598: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.056116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:32.652696: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2021-01-14 13:47:32.655023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:32.655039: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:32.655046: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:32.655051: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:32.655057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:32.655062: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:32.655067: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.655072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.655095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:50:57.038023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-14 13:50:57.038040: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] 0
2021-01-14 13:50:57.038045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0: N
2021-01-14 13:50:57.039526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6699 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3060 Ti, pci bus id: 0000:01:00.0, compute capability: 8.6)
Train on 48000 samples, validate on 12000 samples
Epoch 1/10
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.395981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:31.430370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:31.452057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:31.659034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:31.837570: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.055598: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.056116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:32.652696: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2021-01-14 13:47:32.655023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:32.655039: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:32.655046: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:32.655051: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:32.655057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:32.655062: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:32.655067: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.655072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.655095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:50:57.038023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-14 13:50:57.038040: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] 0
2021-01-14 13:50:57.038045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0: N
2021-01-14 13:50:57.039526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6699 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3060 Ti, pci bus id: 0000:01:00.0, compute capability: 8.6)
2021-01-14 13:50:57.563527: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.395981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:31.430370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:31.452057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:31.659034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:31.837570: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.055598: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.056116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:32.652696: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2021-01-14 13:47:32.655023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:32.655039: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:32.655046: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:32.655051: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:32.655057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:32.655062: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:32.655067: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.655072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.655095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:50:57.038023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-14 13:50:57.038040: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] 0
2021-01-14 13:50:57.038045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0: N
2021-01-14 13:50:57.039526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6699 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3060 Ti, pci bus id: 0000:01:00.0, compute capability: 8.6)
2021-01-14 13:50:57.563527: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:52:17.763274: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
7232/48000 [===>..........................] - ETA: 1:21:26 - loss: 2.3010 - accuracy: 0.1114
2021-01-14 13:47:28.396292: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.018731: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library nvcuda.dll
2021-01-14 13:47:31.041720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:31.041751: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:31.395981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:31.430370: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:31.452057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:31.659034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:31.837570: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.055598: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.056116: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:47:32.652696: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
2021-01-14 13:47:32.655023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1555] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 3060 Ti computeCapability: 8.6
coreClock: 1.8GHz coreCount: 38 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2021-01-14 13:47:32.655039: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_101.dll
2021-01-14 13:47:32.655046: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:47:32.655051: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cufft64_10.dll
2021-01-14 13:47:32.655057: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library curand64_10.dll
2021-01-14 13:47:32.655062: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusolver64_10.dll
2021-01-14 13:47:32.655067: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cusparse64_10.dll
2021-01-14 13:47:32.655072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 13:47:32.655095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1697] Adding visible gpu devices: 0
2021-01-14 13:50:57.038023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1096] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-14 13:50:57.038040: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] 0
2021-01-14 13:50:57.038045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] 0: N
2021-01-14 13:50:57.039526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1241] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6699 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3060 Ti, pci bus id: 0000:01:00.0, compute capability: 8.6)
2021-01-14 13:50:57.563527: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cublas64_10.dll
2021-01-14 13:52:17.763274: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudnn64_7.dll
2021-01-14 14:05:23.645822: W tensorflow/stream_executor/gpu/redzone_allocator.cc:312] Internal: Invoking GPU asm compilation is supported on Cuda non-Windows platforms only
Relying on driver to perform ptx compilation. This message will be only logged once.
48000/48000 [==============================] - 869s 18ms/sample - loss: 2.3019 - accuracy: 0.1101 - val_loss: 2.3014 - val_accuracy: 0.1144
在“Adding visible gpu devices: 0”行之后打开动态库花了很多时间。
GTX 1050 Ti 卡基于 Pascal 兼容 CUDA version start with 8.x 的架构，其中 RTX 3060 Ti 卡基于 Ampere 兼容的架构CUDA version start with 11.x.
因此您的 gpu 卡兼容的 tensorflow 版本是 2.4.0，cuDNN 是 8.0。
感谢 njuffa CUDNN support matrix and insights. You can check tensorflow tested build configurations for windows and Linux。