我正试图在RTX 3070 GPU上训练我的tensorflow模型。我使用的是一个anaconda虚拟环境，提示显示GPU已成功检测到，并且没有显示任何错误或警告，但每当模型开始训练时，它都会使用CPU。
我的蟒蛇提示：
2020-11-28 19:38:17.373117: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2020-11-28 19:38:17.378626: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2020-11-28 19:38:17.378679: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2020-11-28 19:38:17.381802: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2020-11-28 19:38:17.382739: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2020-11-28 19:38:17.389401: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2020-11-28 19:38:17.391830: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2020-11-28 19:38:17.392332: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2020-11-28 19:38:17.392422: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1866] Adding visible gpu devices: 0
2020-11-28 19:38:26.072912: 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
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2020-11-28 19:38:26.073904: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1724] Found device 0 with properties:
pciBusID: 0000:08:00.0 name: GeForce RTX 3070 computeCapability: 8.6
coreClock: 1.725GHz coreCount: 46 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2020-11-28 19:38:26.073984: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2020-11-28 19:38:26.074267: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2020-11-28 19:38:26.074535: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2020-11-28 19:38:26.074775: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2020-11-28 19:38:26.075026: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2020-11-28 19:38:26.075275: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll
2020-11-28 19:38:26.075646: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2020-11-28 19:38:26.075871: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2020-11-28 19:38:26.076139: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1866] Adding visible gpu devices: 0
2020-11-28 19:38:26.738596: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1265] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-11-28 19:38:26.738680: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1271] 0
2020-11-28 19:38:26.739375: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1284] 0: N
2020-11-28 19:38:26.740149: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1410] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6589 MB memory) -> physical GPU (device: 0, name: GeForce RTX 3070, pci bus id: 0000:08:00.0, compute capability: 8.6)
2020-11-28 19:38:26.741055: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2020-11-28 19:38:28.028828: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:126] None of the MLIR optimization passes are enabled (registered 2)
2020-11-28 19:38:32.428408: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2020-11-28 19:38:33.305827: I tensorflow/stream_executor/cuda/cuda_dnn.cc:344] Loaded cuDNN version 8004
2020-11-28 19:38:33.753275: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2020-11-28 19:38:34.603341: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2020-11-28 19:38:34.610934: I tensorflow/stream_executor/cuda/cuda_blas.cc:1838] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.
我的型号代码：
inputs = keras.Input(shape=(None,), dtype="int32")
x = layers.Embedding(max_features, 128)(inputs)
x = layers.Bidirectional(layers.LSTM(64, return_sequences=True))(x)
x = layers.Bidirectional(layers.LSTM(64))(x)
outputs = layers.Dense(1, activation="sigmoid")(x)
model = keras.Model(inputs, outputs)
model.compile("adam", "binary_crossentropy", metrics=["accuracy"])
model.fit(x_train, y_train, batch_size=32, epochs=2, validation_data=(x_val, y_val))
我正在使用：
- tensorflow夜间gpu 2.5.0.dev20201111(安装在anaconda虚拟环境上(
- CUDA 11.1(CUDA_111.1.1_456.81(
- CUDNN v8.0.4.30(适用于CUDA 11.1(
- python 3.8
我知道我的GPU没有被使用，因为它的利用率是1%，而我的CPU是60%，它的顶级进程是python。
有人能帮我使用GPU进行模型训练吗？
很可能您将Tensorflow用于CPU，而不是GPU。做一个"；pip卸载tensorflow"；以及"；pip安装tensorflow gpu"；以安装适合于利用GPU的一个。