Newer dependencies

DNN_models.py

@@ -257,9 +257,9 @@ def variational_AE(dims, act='relu', init='glorot_uniform', output_act = False,
 
     vae.compile(optimizer='adam', )
 
-    vae.metrics_tensors.append(K.mean(reconstruction_loss))
+    vae.metrics.append(K.mean(reconstruction_loss))
     vae.metrics_names.append("recon_loss")
-    vae.metrics_tensors.append(K.mean(beta * kl_loss))
+    vae.metrics.append(K.mean(beta * kl_loss))
     vae.metrics_names.append("kl_loss")
 
     return vae, encoder, decoder

README.md

@@ -19,15 +19,15 @@ DeepMicro is a deep representation learning framework exploiting various autoenc
 ```
 **Step 4:** Install required packages, then install tensorflow.
 ```
-~$ pip install --upgrade pip && pip install numpy==1.16.2 && pip install pandas==0.24.2 && pip install scipy==1.2.1 && pip install scikit-learn==0.20.3 && pip install matplotlib==3.0.3 && pip install psutil==5.6.1 && pip install keras==2.2.4
+~$ pip install --upgrade pip && pip install numpy==1.23.5 pandas==1.5.3 scipy==1.10.0 scikit-learn==1.1.1 matplotlib==3.1.3 psutil==5.9.4 keras==2.7.0
 ```
 * If your machine is *not* equipped with GPU, install tensorflow CPU version 
   ```
   ~$ pip install tensorflow==1.13.1
   ```
 * If it is equipped with GPU, then install tensorflow GPU version
   ```
-  ~$ pip install tensorflow-gpu==1.13.1
+  ~$ pip install tensorflow-gpu==2.7.0
   ```
 **Step 5:** Run DeepMicro, printing out its usage.
 ```