想在R语言环境下使用tensorflow进行深度学习时，需要：安装tensorflow包: install.packages(‘tensorflow’)
安装tensorflow：install_tensorflow()

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此时会提示安装miniconda3. 而由于miniconda服务器问题，在R中下载miniconda总是超时无法连接。
这时要直接从官网下载miniconda3.
下载exe文件安装以后，还需要对miniconda进行配置，否则依然无法安装tensorflow。

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从开始中打开anaconda prompt（miniconda3），进行配置：
conda create -n tensorflow2.6  ###当前tensorflow最高版本为2.6，自己安装时根据实际情况选择版本

然后会自动安装tensorflow环境：

Collecting package metadata (current_repodata.json): doneSolving environment: done ## Package Plan ##   environment location: C:\ProgramData\Miniconda3\envs\tensorflow2.6 Proceed ([y]/n)? y Preparing transaction: done Verifying transaction: done Executing transaction: done # # To activate this environment, use # #     $ conda activate tensorflow2.6

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再到R环境下安装tensorflow，就可以成功了。

运行mnist案例：

> network%>%fit(train_images,train_labels,epochs = 5,batch_size = 128)2021-10-10 10:59:22.750466: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2) Epoch 1/5 469/469 [==============================] - 6s 12ms/step - loss: 0.2524 - accuracy: 0.9269 Epoch 2/5 469/469 [==============================] - 6s 12ms/step - loss: 0.1019 - accuracy: 0.9695 Epoch 3/5 469/469 [==============================] - 6s 12ms/step - loss: 0.0679 - accuracy: 0.9797 Epoch 4/5 469/469 [==============================] - 6s 12ms/step - loss: 0.0495 - accuracy: 0.9850 Epoch 5/5 469/469 [==============================] - 6s 12ms/step - loss: 0.0367 - accuracy: 0.9891 > > metrics <- network %>% evaluate(test_images,test_labels) 313/313 [==============================] - 1s 2ms/step - loss: 0.0674 - accuracy: 0.9801 > metrics       loss   accuracy 0.06739952 0.98009998 > network %>% predict(test_images[1:5,]) %>% k_argmax() tf.Tensor([7 2 1 0 4], shape=(5,), dtype=int64)

模型精度98%，对测试数据的预测正确。