update examples and examples doc (#1460)

Author: jingxu10

docs/tutorials/examples.md

@@ -0,0 +1,9 @@
+cmake_minimum_required(VERSION 3.0 FATAL_ERROR)
+project(example-app)
+
+find_package(IPEX REQUIRED)
+
+add_executable(example-app example-app.cpp)
+target_link_libraries(example-app "${TORCH_LIBRARIES}")
+
+set_property(TARGET example-app PROPERTY CXX_STANDARD 14)

examples/cpu/inference/cpp/CMakeLists.txt

@@ -0,0 +1,23 @@
+#include <torch/script.h>
+#include <iostream>
+#include <memory>
+
+int main(int argc, const char* argv[]) {
+    torch::jit::script::Module module;
+    try {
+        module = torch::jit::load(argv[1]);
+    }
+    catch (const c10::Error& e) {
+        std::cerr << "error loading the model\n";
+        return -1;
+    }
+
+    std::vector<torch::jit::IValue> inputs;
+    torch::Tensor input = torch::rand({1,3,224,224});
+    inputs.push_back(input);
+
+    at::Tensor output = module.forward(inputs).toTensor();
+    std::cout << output_tensor.slice(/*dim=*/1, /*start=*/0, /*end=*/5) << std::endl;
+
+    return 0;
+}

examples/cpu/inference/cpp/example-app.cpp

@@ -0,0 +1,14 @@
+#!/usr/bin/env python
+# encoding: utf-8
+
+import torch
+import torchvision
+
+model =  torchvision.models.resnet50(pretrained=True)
+model.eval()
+
+input = torch.rand(1, 3, 224, 224)
+model = torch.jit.trace(model, input, check_trace=False)
+
+model.save('resnet50.pt')
+print("save mode to: resnet50.pt")

examples/cpu/inference/cpp/model_gen.py

@@ -14,7 +14,5 @@
 model = ipex.optimize(model, dtype=torch.bfloat16)
 ######################################################
 
-with torch.no_grad():
-  with torch.cpu.amp.autocast():
-    model(data)
-    
+with torch.no_grad(), torch.cpu.amp.autocast():
+  model(data)

…ference/BERT_general_inference_script.py …/python/bert_general_inference_script.pyexamples/cpu/inference/BERT_general_inference_script.py renamed to examples/cpu/inference/python/bert_general_inference_script.py examples/cpu/inference/BERT_general_inference_script.py renamed to examples/cpu/inference/python/bert_general_inference_script.py

@@ -16,4 +16,4 @@
 ######################################################
 
 with torch.no_grad():
-    model(data)
+  model(data)

…e/BERT_imperative_mode_inference_bf16.py …n/bert_imperative_mode_inference_bf16.pyexamples/cpu/inference/BERT_imperative_mode_inference_bf16.py renamed to examples/cpu/inference/python/bert_imperative_mode_inference_bf16.py examples/cpu/inference/BERT_imperative_mode_inference_bf16.py renamed to examples/cpu/inference/python/bert_imperative_mode_inference_bf16.py

@@ -14,10 +14,9 @@
 model = ipex.optimize(model, dtype=torch.bfloat16)
 ######################################################
 
-with torch.no_grad():
-  with torch.cpu.amp.autocast():
-    d = torch.randint(vocab_size, size=[batch_size, seq_length])
-    model = torch.jit.trace(model, (d,), check_trace=False, strict=False)
-    model = torch.jit.freeze(model)
+with torch.no_grad(), torch.cpu.amp.autocast():
+  d = torch.randint(vocab_size, size=[batch_size, seq_length])
+  model = torch.jit.trace(model, (d,), check_trace=False, strict=False)
+  model = torch.jit.freeze(model)
 
-    model(data)
+  model(data)