你好，请问跑训练代码出现下面两个信息是什么意思？
1、None of the MLIR Optimization Passes are enabled
2、Couldn’t invoke ptxas.exe --version
代码是链接里的示例代码：कनवल्शनल न्यूरल नेटवर्क (सीएनएन) | TensorFlow Core
看起来是能用GPU训练，但是总感觉速度有问题。。跟机器用的是AMD的CPU有关系吗，CPU是5800x，显卡是3080ti，环境是tensorflow-gpu 2.5.0，python=3.8，cudatoolkit=11.3，cudnn=8.2。
具体信息如下：
2021-09-12 17:35:28.302826: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:176] None of the MLIR Optimization Passes are enabled (registered 2)
Epoch 1/10
2021-09-12 17:35:28.528250: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library cudnn64_8.dll
2021-09-12 17:35:28.954801: I tensorflow/stream_executor/cuda/cuda_dnn.cc:359] Loaded cuDNN version 8201
2021-09-12 17:35:29.577930: E tensorflow/core/platform/windows/subprocess.cc:287] Call to CreateProcess failed. Error code: 2
2021-09-12 17:35:29.578036: W tensorflow/stream_executor/gpu/asm_compiler.cc:56] Couldn’t invoke ptxas.exe --version
2021-09-12 17:35:29.582453: E tensorflow/core/platform/windows/subprocess.cc:287] Call to CreateProcess failed. Error code: 2
2021-09-12 17:35:29.582966: W tensorflow/stream_executor/gpu/redzone_allocator.cc:314] Internal: Failed to launch ptxas
Relying on driver to perform ptx compilation.
Modify $PATH to customize ptxas location.
This message will be only logged once.
2021-09-12 17:35:29.620691: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library cublas64_11.dll
2021-09-12 17:35:30.122407: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library cublasLt64_11.dll
2021-09-12 17:35:30.155622: I tensorflow/stream_executor/cuda/cuda_blas.cc:1838] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.
1563/1563 [==============================] - 7s 3ms/step - loss: 1.5276 - accuracy: 0.4408 - val_loss: 1.2432 - val_accuracy: 0.5580
Epoch 2/10
1563/1563 [==============================] - 4s 3ms/step - loss: 1.1622 - accuracy: 0.5898 - val_loss: 1.1072 - val_accuracy: 0.6117