函数调用栈：train_function（当运行keras简单例子）
Function call stack: train_function (when running keras simple example)
我正在使用以下环境：
ubuntu: 18.04
python: 3.8.9
tensorflow: 2.4.1
nvidia-smi: Driver Version: 465.19.01 CUDA Version: 11.3
cat /usr/local/cuda/include/cudnn_version.h | grep CUDNN_MAJOR -A 2:
#define CUDNN_MAJOR 8
#define CUDNN_MINOR 2
#define CUDNN_PATCHLEVEL 0
我正在尝试 运行 简单示例（我从：https://keras.io/examples/vision/mnist_convnet/ 中获取）
print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))
return 1
我正在运行宁此代码：
# Model / data parameters
num_classes = 10
input_shape = (28, 28, 1)
# the data, split between train and test sets
(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()
# Scale images to the [0, 1] range
x_train = x_train.astype("float32") / 255
x_test = x_test.astype("float32") / 255
# Make sure images have shape (28, 28, 1)
x_train = np.expand_dims(x_train, -1)
x_test = np.expand_dims(x_test, -1)
print("x_train shape:", x_train.shape)
print(x_train.shape[0], "train samples")
print(x_test.shape[0], "test samples")
# convert class vectors to binary class matrices
y_train = keras.utils.to_categorical(y_train, num_classes)
y_test = keras.utils.to_categorical(y_test, num_classes)
model = keras.Sequential(
[
keras.Input(shape=input_shape),
layers.Conv2D(32, kernel_size=(3, 3), activation="relu"),
layers.MaxPooling2D(pool_size=(2, 2)),
layers.Conv2D(64, kernel_size=(3, 3), activation="relu"),
layers.MaxPooling2D(pool_size=(2, 2)),
layers.Flatten(),
layers.Dropout(0.5),
layers.Dense(num_classes, activation="softmax"),
]
)
batch_size = 128
epochs = 15
model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=["accuracy"])
model.fit(x_train, y_train, batch_size=batch_size, epochs=epochs, validation_split=0.1)
并获得输出（和错误）：
2021-05-05 10:27:56.954764: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-05-05 10:27:57.588546: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-05-05 10:27:57.589040: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2021-05-05 10:27:57.620509: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:57.620805: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 2080 computeCapability: 7.5
coreClock: 1.71GHz coreCount: 46 deviceMemorySize: 7.79GiB deviceMemoryBandwidth: 417.23GiB/s
2021-05-05 10:27:57.620821: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-05-05 10:27:57.622539: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-05-05 10:27:57.622566: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-05-05 10:27:57.623220: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-05-05 10:27:57.623371: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-05-05 10:27:57.625233: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-05-05 10:27:57.625626: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2021-05-05 10:27:57.625716: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-05-05 10:27:57.625783: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:57.626097: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:57.626415: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
Num GPUs Available: 1
Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz
11493376/11490434 [==============================] - 1s 0us/step
x_train shape: (60000, 28, 28, 1)
60000 train samples
10000 test samples
2021-05-05 10:27:59.125675: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-05-05 10:27:59.125985: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-05-05 10:27:59.126111: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:59.126471: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 2080 computeCapability: 7.5
coreClock: 1.71GHz coreCount: 46 deviceMemorySize: 7.79GiB deviceMemoryBandwidth: 417.23GiB/s
2021-05-05 10:27:59.126496: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-05-05 10:27:59.126509: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-05-05 10:27:59.126517: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-05-05 10:27:59.126526: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-05-05 10:27:59.126534: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-05-05 10:27:59.126543: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-05-05 10:27:59.126551: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2021-05-05 10:27:59.126559: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-05-05 10:27:59.126596: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:59.126878: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:59.127132: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-05-05 10:27:59.127154: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-05-05 10:27:59.502912: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-05-05 10:27:59.502935: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
2021-05-05 10:27:59.502940: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
2021-05-05 10:27:59.503071: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:59.503409: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:59.503717: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:59.504006: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6846 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080, pci bus id: 0000:01:00.0, compute capability: 7.5)
2021-05-05 10:27:59.671068: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-05-05 10:27:59.690822: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 3199980000 Hz
Epoch 1/15
2021-05-05 10:27:59.949178: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-05-05 10:28:00.250994: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-05-05 10:28:00.252453: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-05-05 10:28:00.852411: W tensorflow/core/framework/op_kernel.cc:1763] OP_REQUIRES failed at conv_ops.cc:1106 : Not found: No algorithm worked!
Traceback (most recent call last):
File "/home/ubadmin/PycharmProjects/AgeRecognision/main.py", line 19, in <module>
main()
File "/home/ubadmin/PycharmProjects/AgeRecognision/main.py", line 7, in main
if (0 == simpleExample.run()):
File "/home/ubadmin/PycharmProjects/AgeRecognision/SimpleExample.py", line 58, in run
model.fit(x_train, y_train, batch_size=batch_size, epochs=epochs, validation_split=0.1)
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1100, in fit
tmp_logs = self.train_function(iterator)
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 828, in __call__
result = self._call(*args, **kwds)
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 888, in _call
return self._stateless_fn(*args, **kwds)
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 2942, in __call__
return graph_function._call_flat(
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 1918, in _call_flat
return self._build_call_outputs(self._inference_function.call(
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 555, in call
outputs = execute.execute(
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/eager/execute.py", line 59, in quick_execute
tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.NotFoundError: No algorithm worked!
[[node sequential/conv2d/Conv2D (defined at /SimpleExample.py:58) ]] [Op:__inference_train_function_728]
Function call stack:
train_function
- 有什么问题？
- 如果
tf.config.experimental.list_physical_devices('GPU'))给出1，这是否表示GPU驱动程序（nvidia、cuda、cudnaa都可以？）
- 我该如何修复它以及 运行 这个简单的例子？
重启后一切正常！
貌似安装完cuda和tensorflow后不得不重启电脑
我正在使用以下环境：
ubuntu: 18.04
python: 3.8.9
tensorflow: 2.4.1
nvidia-smi: Driver Version: 465.19.01 CUDA Version: 11.3
cat /usr/local/cuda/include/cudnn_version.h | grep CUDNN_MAJOR -A 2:
#define CUDNN_MAJOR 8
#define CUDNN_MINOR 2
#define CUDNN_PATCHLEVEL 0
我正在尝试 运行 简单示例（我从：https://keras.io/examples/vision/mnist_convnet/ 中获取）
print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))
return 1
我正在运行宁此代码：
# Model / data parameters
num_classes = 10
input_shape = (28, 28, 1)
# the data, split between train and test sets
(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()
# Scale images to the [0, 1] range
x_train = x_train.astype("float32") / 255
x_test = x_test.astype("float32") / 255
# Make sure images have shape (28, 28, 1)
x_train = np.expand_dims(x_train, -1)
x_test = np.expand_dims(x_test, -1)
print("x_train shape:", x_train.shape)
print(x_train.shape[0], "train samples")
print(x_test.shape[0], "test samples")
# convert class vectors to binary class matrices
y_train = keras.utils.to_categorical(y_train, num_classes)
y_test = keras.utils.to_categorical(y_test, num_classes)
model = keras.Sequential(
[
keras.Input(shape=input_shape),
layers.Conv2D(32, kernel_size=(3, 3), activation="relu"),
layers.MaxPooling2D(pool_size=(2, 2)),
layers.Conv2D(64, kernel_size=(3, 3), activation="relu"),
layers.MaxPooling2D(pool_size=(2, 2)),
layers.Flatten(),
layers.Dropout(0.5),
layers.Dense(num_classes, activation="softmax"),
]
)
batch_size = 128
epochs = 15
model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=["accuracy"])
model.fit(x_train, y_train, batch_size=batch_size, epochs=epochs, validation_split=0.1)
并获得输出（和错误）：
2021-05-05 10:27:56.954764: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-05-05 10:27:57.588546: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-05-05 10:27:57.589040: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2021-05-05 10:27:57.620509: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:57.620805: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 2080 computeCapability: 7.5
coreClock: 1.71GHz coreCount: 46 deviceMemorySize: 7.79GiB deviceMemoryBandwidth: 417.23GiB/s
2021-05-05 10:27:57.620821: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-05-05 10:27:57.622539: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-05-05 10:27:57.622566: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-05-05 10:27:57.623220: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-05-05 10:27:57.623371: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-05-05 10:27:57.625233: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-05-05 10:27:57.625626: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2021-05-05 10:27:57.625716: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-05-05 10:27:57.625783: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:57.626097: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:57.626415: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
Num GPUs Available: 1
Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz
11493376/11490434 [==============================] - 1s 0us/step
x_train shape: (60000, 28, 28, 1)
60000 train samples
10000 test samples
2021-05-05 10:27:59.125675: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-05-05 10:27:59.125985: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-05-05 10:27:59.126111: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:59.126471: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: NVIDIA GeForce RTX 2080 computeCapability: 7.5
coreClock: 1.71GHz coreCount: 46 deviceMemorySize: 7.79GiB deviceMemoryBandwidth: 417.23GiB/s
2021-05-05 10:27:59.126496: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-05-05 10:27:59.126509: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-05-05 10:27:59.126517: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-05-05 10:27:59.126526: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-05-05 10:27:59.126534: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-05-05 10:27:59.126543: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-05-05 10:27:59.126551: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2021-05-05 10:27:59.126559: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-05-05 10:27:59.126596: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:59.126878: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:59.127132: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
2021-05-05 10:27:59.127154: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-05-05 10:27:59.502912: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-05-05 10:27:59.502935: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
2021-05-05 10:27:59.502940: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
2021-05-05 10:27:59.503071: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:59.503409: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:59.503717: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:941] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-05-05 10:27:59.504006: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6846 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080, pci bus id: 0000:01:00.0, compute capability: 7.5)
2021-05-05 10:27:59.671068: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-05-05 10:27:59.690822: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 3199980000 Hz
Epoch 1/15
2021-05-05 10:27:59.949178: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-05-05 10:28:00.250994: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-05-05 10:28:00.252453: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-05-05 10:28:00.852411: W tensorflow/core/framework/op_kernel.cc:1763] OP_REQUIRES failed at conv_ops.cc:1106 : Not found: No algorithm worked!
Traceback (most recent call last):
File "/home/ubadmin/PycharmProjects/AgeRecognision/main.py", line 19, in <module>
main()
File "/home/ubadmin/PycharmProjects/AgeRecognision/main.py", line 7, in main
if (0 == simpleExample.run()):
File "/home/ubadmin/PycharmProjects/AgeRecognision/SimpleExample.py", line 58, in run
model.fit(x_train, y_train, batch_size=batch_size, epochs=epochs, validation_split=0.1)
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1100, in fit
tmp_logs = self.train_function(iterator)
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 828, in __call__
result = self._call(*args, **kwds)
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 888, in _call
return self._stateless_fn(*args, **kwds)
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 2942, in __call__
return graph_function._call_flat(
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 1918, in _call_flat
return self._build_call_outputs(self._inference_function.call(
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 555, in call
outputs = execute.execute(
File "/home/ubadmin/PycharmProjects/AgeRecognision/venv/lib/python3.8/site-packages/tensorflow/python/eager/execute.py", line 59, in quick_execute
tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.NotFoundError: No algorithm worked!
[[node sequential/conv2d/Conv2D (defined at /SimpleExample.py:58) ]] [Op:__inference_train_function_728]
Function call stack:
train_function
- 有什么问题？
- 如果
tf.config.experimental.list_physical_devices('GPU'))给出1，这是否表示GPU驱动程序（nvidia、cuda、cudnaa都可以？） - 我该如何修复它以及 运行 这个简单的例子？
重启后一切正常！ 貌似安装完cuda和tensorflow后不得不重启电脑