fix gpu info tab, add nvidia-ml-py

Dockerfile

@@ -49,6 +49,8 @@ RUN pip3 install --no-cache-dir torch==$TORCH_VERSION -r requirements_styletts2.
 RUN pip3 install --no-cache-dir torch==$TORCH_VERSION -r requirements_vall_e.txt
 RUN pip3 install --no-cache-dir torch==$TORCH_VERSION -r requirements_maha_tts.txt
 RUN pip3 install --no-cache-dir torch==$TORCH_VERSION -r requirements_stable_audio.txt
+# RUN pip3 install --no-cache-dir torch==$TORCH_VERSION hydra-core==1.3.2
+RUN pip3 install --no-cache-dir torch==$TORCH_VERSION nvidia-ml-py
 
 # Build the React UI
 RUN cd react-ui && npm install && npm run build

installer_scripts/js/initializeApp.js

@@ -203,6 +203,7 @@ async function updateDependencies(optional = true) {
   tryInstall("-r requirements_stable_audio.txt", "Stable Audio");
   // reinstall hydra-core==1.3.2 because of fairseq
   tryInstall("hydra-core==1.3.2", "hydra-core fix due to fairseq");
+  tryInstall("nvidia-ml-py", "nvidia-ml-py");
   savePipPackagesVersion(newPipPackagesVersion);
 }
 

installer_scripts/versions.json

@@ -1,5 +1,5 @@
 {
-    "version": "0.0.3",
+    "version": "0.1.0",
     "pip_packages": 4,
     "npm_packages": 3,
     "react_ui": 3

tts_webui/utils/gpu_info_tab.py

@@ -26,6 +26,23 @@ def get_gpu_info():
     return [get_gpu_info_idx(idx) for idx in range(device_count)]
 
 
+def get_pynvml_fields(idx=0):
+    # check if pynvml is installed
+    try:
+        # import pynvml
+        return {
+            "temperature": torch.cuda.temperature(idx),
+            "power_draw": torch.cuda.power_draw(idx) / 1000,
+            "utilization": torch.cuda.utilization(idx),
+        }
+    # except ImportError:
+    except:
+        return {
+            "temperature": 0,
+            "power_draw": 0,
+            "utilization": 0,
+        }
+
 def get_gpu_info_idx(idx=0):
     return {
         "torch_version": torch.__version__,
@@ -43,9 +60,7 @@ def get_gpu_info_idx(idx=0):
         "multi_processor_count": torch.cuda.get_device_properties(
             idx
         ).multi_processor_count,
-        "temperature": torch.cuda.temperature(idx),
-        "power_draw": torch.cuda.power_draw(idx) / 1000,
-        "utilization": torch.cuda.utilization(idx),
+        **get_pynvml_fields(idx),
     }