rls2.4: fix coverity issue (#3191)

Author: blzheng

examples/cpu/llm/inference/distributed/run_generation_tp.py

@@ -292,7 +292,7 @@
 
     def load_image(image_file):
         if image_file.startswith("http://") or image_file.startswith("https://"):
-            response = requests.get(image_file, verify=False)
+            response = requests.get(image_file)
             image = Image.open(BytesIO(response.content)).convert("RGB")
         else:
             image = Image.open(image_file).convert("RGB")
@@ -400,7 +400,7 @@ def trace_handler(prof):
         if not hasattr(model.config, "token_latency"):
             model.config.token_latency = True
     if model_type == "git":
-        prompt = Image.open(requests.get(args.image_url, stream=True, verify=False).raw)
+        prompt = Image.open(requests.get(args.image_url, stream=True).raw)
         generate_kwargs.pop("min_new_tokens", None)
     elif model_type == "llava":
         if args.prompt is not None:

examples/cpu/llm/inference/distributed/run_generation_with_deepspeed.py

@@ -557,7 +557,7 @@ def write_checkpoints_json():
     from PIL import Image
     import requests
 
-    prompt = Image.open(requests.get(args.image_url, stream=True, verify=False).raw)
+    prompt = Image.open(requests.get(args.image_url, stream=True).raw)
     inputs = [prompt] * args.batch_size
     generate_kwargs.pop("min_new_tokens", None)
 elif model_type == "llava":
@@ -567,7 +567,7 @@ def write_checkpoints_json():
 
     def load_image(image_file):
         if image_file.startswith("http://") or image_file.startswith("https://"):
-            response = requests.get(image_file, verify=False)
+            response = requests.get(image_file)
             image = Image.open(BytesIO(response.content)).convert("RGB")
         else:
             image = Image.open(image_file).convert("RGB")

examples/cpu/llm/inference/single_instance/run_generation.py

@@ -239,7 +239,7 @@
 
     def load_image(image_file):
         if image_file.startswith("http://") or image_file.startswith("https://"):
-            response = requests.get(image_file, verify=False)
+            response = requests.get(image_file)
             image = Image.open(BytesIO(response.content)).convert("RGB")
         else:
             image = Image.open(image_file).convert("RGB")
@@ -299,7 +299,7 @@ def trace_handler(prof):
         if not hasattr(model.config, "token_latency"):
             model.config.token_latency = True
     if model_type == "git":
-        prompt = Image.open(requests.get(args.image_url, stream=True, verify=False).raw)
+        prompt = Image.open(requests.get(args.image_url, stream=True).raw)
         generate_kwargs.pop("min_new_tokens", None)
     elif model_type == "llava":
         if args.prompt is not None:

examples/cpu/llm/inference/single_instance/run_quantization.py

@@ -362,7 +362,7 @@
 
     def load_image(image_file):
         if image_file.startswith("http://") or image_file.startswith("https://"):
-            response = requests.get(image_file, verify=False)
+            response = requests.get(image_file)
             image = Image.open(BytesIO(response.content)).convert("RGB")
         else:
             image = Image.open(image_file).convert("RGB")
@@ -1154,7 +1154,7 @@ def calib_func(prepared_model):
             )
 
     if model.name == "git":
-        prompt = Image.open(requests.get(args.image_url, stream=True, verify=False).raw)
+        prompt = Image.open(requests.get(args.image_url, stream=True).raw)
     elif model.name == "llava":
         if args.prompt is not None:
             prompt = args.prompt