fix resnet inference demo link (#1339)

Author: ZhaoqiongZ

AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/ResNet50_Inference.ipynb

@@ -65,7 +65,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!wget https://raw.githubusercontent.com/intel/intel-extension-for-pytorch/master/examples/resnet50.py"
+    "!wget https://raw.githubusercontent.com/intel/intel-extension-for-pytorch/master/examples/cpu/inference/resnet50_general_inference_script.py"
    ]
   },
   {
@@ -111,7 +111,7 @@
     "source $ONEAPI_INSTALL/setvars.sh --force > /dev/null 2>&1\n",
     "source activate pytorch\n",
     "echo \"########## Executing the run\"\n",
-    "DNNL_VERBOSE=1 python resnet50.py > infer_rn50_cpu.csv\n",
+    "DNNL_VERBOSE=1 python resnet50_general_inference_script.py > infer_rn50_cpu.csv\n",
     "echo \"########## Done with the run\""
    ]
   },
@@ -175,7 +175,7 @@
     "source $ONEAPI_INSTALL/setvars.sh --force > /dev/null 2>&1\n",
     "source activate pytorch\n",
     "echo \"########## Executing the run\"\n",
-    "DNNL_VERBOSE=1 python resnet50.py > infer_rn50_gpu.csv\n",
+    "DNNL_VERBOSE=1 python resnet50_general_inference_script_gpu.py > infer_rn50_gpu.csv\n",
     "echo \"########## Done with the run\""
    ]
   },

AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/codes_for_ipynb/gpu.patch

@@ -1,32 +1,18 @@
-diff --git a/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/Intel_Extension_For_PyTorch_Hello_World.py b/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/Intel_Extension_For_PyTorch_Hello_World.py
-index 00eb371b..a3ded045 100755
---- a/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/Intel_Extension_For_PyTorch_Hello_World.py
-+++ b/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/Intel_Extension_For_PyTorch_Hello_World.py
-@@ -75,7 +75,7 @@ def main():
-     3. crite: Criterion function to minimize loss
-     '''
-     model = TestModel()
--    model = model.to(memory_format=torch.channels_last)
-+    model = model.to("xpu", memory_format=torch.channels_last)
-     optim = torch.optim.SGD(model.parameters(), lr=0.01)
-     crite = nn.MSELoss(reduction='sum')
+diff --git a/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/resnet50_general_inference_script.py b/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/resnet50_general_inference_script_gpu.py
+similarity index 92%
+rename from AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/resnet50_general_inference_script.py
+rename to AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/resnet50_general_inference_script_gpu.py
+index dae594af..edd0fcb3 100644
+--- a/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/resnet50_general_inference_script.py
++++ b/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/resnet50_general_inference_script_gpu.py
+@@ -23,8 +23,8 @@ def main(args):
 
-@@ -104,7 +104,8 @@ def main():
-         '''
-         model.train()
-         for batch_index, (data, y_ans) in enumerate(trainLoader):
--            data = data.to(memory_format=torch.channels_last)
-+            data = data.to("xpu", memory_format=torch.channels_last)
-+            y_ans = y_ans.to("xpu", memory_format=torch.channels_last)
-             optim.zero_grad()
-             y = model(data)
-             loss = crite(y, y_ans)
-@@ -116,7 +117,7 @@ def main():
-         '''
-         model.eval()
-         for batch_index, data in enumerate(testLoader):
--            data = data.to(memory_format=torch.channels_last)
-+            data = data.to("xpu", memory_format=torch.channels_last)
-             y = model(data)
+   import intel_extension_for_pytorch as ipex
 
- if __name__ == '__main__':
+-  model = model.to(memory_format=torch.channels_last)
+-  data = data.to(memory_format=torch.channels_last)
++  model = model.to("xpu",memory_format=torch.channels_last)
++  data = data.to("xpu",memory_format=torch.channels_last)
+ 
+   if args.dtype == 'float32':
+     model = ipex.optimize(model, dtype=torch.float32)

AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/codes_for_py/gpu.patch

@@ -0,0 +1,32 @@
+diff --git a/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/Intel_Extension_For_PyTorch_Hello_World.py b/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/Intel_Extension_For_PyTorch_Hello_World.py
+index 00eb371b..a3ded045 100755
+--- a/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/Intel_Extension_For_PyTorch_Hello_World.py
++++ b/AI-and-Analytics/Getting-Started-Samples/Intel_Extension_For_PyTorch_GettingStarted/Intel_Extension_For_PyTorch_Hello_World.py
+@@ -75,7 +75,7 @@ def main():
+     3. crite: Criterion function to minimize loss
+     '''
+     model = TestModel()
+-    model = model.to(memory_format=torch.channels_last)
++    model = model.to("xpu", memory_format=torch.channels_last)
+     optim = torch.optim.SGD(model.parameters(), lr=0.01)
+     crite = nn.MSELoss(reduction='sum')
+ 
+@@ -104,7 +104,8 @@ def main():
+         '''
+         model.train()
+         for batch_index, (data, y_ans) in enumerate(trainLoader):
+-            data = data.to(memory_format=torch.channels_last)
++            data = data.to("xpu", memory_format=torch.channels_last)
++            y_ans = y_ans.to("xpu", memory_format=torch.channels_last)
+             optim.zero_grad()
+             y = model(data)
+             loss = crite(y, y_ans)
+@@ -116,7 +117,7 @@ def main():
+         '''
+         model.eval()
+         for batch_index, data in enumerate(testLoader):
+-            data = data.to(memory_format=torch.channels_last)
++            data = data.to("xpu", memory_format=torch.channels_last)
+             y = model(data)
+ 
+ if __name__ == '__main__':