fix the gpu_id bug

hub_module/modules/image/keypoint_detection/hand_pose_localization/model.py

@@ -7,9 +7,9 @@ __all__ = ['Model']
 
 class Model():
     # 初始化函数
-    def __init__(self, modelpath, use_gpu):
+    def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined=True):
         # 加载模型预测器
-        self.predictor = self.load_model(modelpath, use_gpu)
+        self.predictor = self.load_model(modelpath, use_gpu, use_mkldnn, combined)
 
         # 获取模型的输入输出
         self.input_names = self.predictor.get_input_names()
@@ -18,31 +18,33 @@ class Model():
         self.output_tensor = self.predictor.get_output_tensor(self.output_names[0])
 
     # 模型加载函数
-    def load_model(self, modelpath, use_gpu):
+    def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
         # 对运行位置进行配置
         if use_gpu:
             try:
-                places = os.environ["CUDA_VISIBLE_DEVICES"]
-                places = int(places[0])
-            except Exception as e:
-                print('Error: %s. Please set the environment variables "CUDA_VISIBLE_DEVICES".' % e)
+                int(os.environ.get('CUDA_VISIBLE_DEVICES'))
+            except Exception:
+                print('Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.')
                 use_gpu = False
                 
-        # 预训练模型路径
+        # 加载模型参数
+        if combined:
             model = os.path.join(modelpath, "__model__")
             params = os.path.join(modelpath, "__params__")
-
-        # 加载模型参数
             config = AnalysisConfig(model, params)
+        else:
+            config = AnalysisConfig(modelpath)
 
         # 设置参数
         if use_gpu:   
-            config.enable_use_gpu(100, places)
+            config.enable_use_gpu(100, 0)
         else:
             config.disable_gpu()
+            if use_mkldnn:
                 config.enable_mkldnn()
         config.disable_glog_info()
         config.switch_ir_optim(True)
+        config.enable_memory_optim()
         config.switch_use_feed_fetch_ops(False)
         config.switch_specify_input_names(True)
         
@@ -58,7 +60,8 @@ class Model():
 
         # 遍历输入数据进行预测
         for input_data in input_datas:
-            self.input_tensor.copy_from_cpu(input_data)
+            inputs = input_data.copy()
+            self.input_tensor.copy_from_cpu(inputs)
             self.predictor.zero_copy_run()
             output = self.output_tensor.copy_to_cpu()
             outputs.append(output)

hub_module/modules/image/keypoint_detection/hand_pose_localization/module.py

-# coding=utf-8
 import os
 
 from paddlehub import Module
@@ -22,7 +21,7 @@ class Hand_Pose_Localization(Module):
         self.model_path = os.path.join(self.directory, "hand_pose_localization")
 
         # 加载模型
-        self.model = Model(self.model_path, use_gpu)     
+        self.model = Model(self.model_path, use_gpu=use_gpu, use_mkldnn=False, combined=True)       
     
     # 关键点检测函数
     def keypoint_detection(

hub_module/modules/image/style_transfer/UGATIT_100w/model.py

@@ -7,9 +7,9 @@ __all__ = ['Model']
 
 class Model():
     # 初始化函数
-    def __init__(self, modelpath, use_gpu):
+    def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined=True):
         # 加载模型预测器
-        self.predictor = self.load_model(modelpath, use_gpu)
+        self.predictor = self.load_model(modelpath, use_gpu, use_mkldnn, combined)
 
         # 获取模型的输入输出
         self.input_names = self.predictor.get_input_names()
@@ -18,24 +18,30 @@ class Model():
         self.output_tensor = self.predictor.get_output_tensor(self.output_names[0])
 
     # 模型加载函数
-    def load_model(self, modelpath, use_gpu):
+    def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
         # 对运行位置进行配置
         if use_gpu:
             try:
-                places = os.environ["CUDA_VISIBLE_DEVICES"]
-                places = int(places[0])
-            except Exception as e:
-                print('Error: %s. Please set the environment variables "CUDA_VISIBLE_DEVICES".' % e)
+                int(os.environ.get('CUDA_VISIBLE_DEVICES'))
+            except Exception:
+                print('Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.')
                 use_gpu = False
                 
         # 加载模型参数
+        if combined:
+            model = os.path.join(modelpath, "__model__")
+            params = os.path.join(modelpath, "__params__")
+            config = AnalysisConfig(model, params)
+        else:
             config = AnalysisConfig(modelpath)
 
         # 设置参数
         if use_gpu:   
-            config.enable_use_gpu(100, places)
+            config.enable_use_gpu(100, 0)
         else:
             config.disable_gpu()
+            if use_mkldnn:
+                config.enable_mkldnn()
         config.disable_glog_info()
         config.switch_ir_optim(True)
         config.enable_memory_optim()

hub_module/modules/image/style_transfer/UGATIT_100w/module.py

@@ -21,7 +21,7 @@ class UGATIT_100w(Module):
         self.model_path = os.path.join(self.directory, "UGATIT_100w")
 
         # 加载模型
-        self.model = Model(self.model_path, use_gpu)     
+        self.model = Model(self.model_path, use_gpu=use_gpu, use_mkldnn=False, combined=False) 
     
     # 关键点检测函数
     def style_transfer(

hub_module/modules/image/style_transfer/UGATIT_83w/model.py

@@ -7,9 +7,9 @@ __all__ = ['Model']
 
 class Model():
     # 初始化函数
-    def __init__(self, modelpath, use_gpu):
+    def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined=True):
         # 加载模型预测器
-        self.predictor = self.load_model(modelpath, use_gpu)
+        self.predictor = self.load_model(modelpath, use_gpu, use_mkldnn, combined)
 
         # 获取模型的输入输出
         self.input_names = self.predictor.get_input_names()
@@ -18,24 +18,30 @@ class Model():
         self.output_tensor = self.predictor.get_output_tensor(self.output_names[0])
 
     # 模型加载函数
-    def load_model(self, modelpath, use_gpu):
+    def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
         # 对运行位置进行配置
         if use_gpu:
             try:
-                places = os.environ["CUDA_VISIBLE_DEVICES"]
-                places = int(places[0])
-            except Exception as e:
-                print('Error: %s. Please set the environment variables "CUDA_VISIBLE_DEVICES".' % e)
+                int(os.environ.get('CUDA_VISIBLE_DEVICES'))
+            except Exception:
+                print('Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.')
                 use_gpu = False
                 
         # 加载模型参数
+        if combined:
+            model = os.path.join(modelpath, "__model__")
+            params = os.path.join(modelpath, "__params__")
+            config = AnalysisConfig(model, params)
+        else:
             config = AnalysisConfig(modelpath)
 
         # 设置参数
         if use_gpu:   
-            config.enable_use_gpu(100, places)
+            config.enable_use_gpu(100, 0)
         else:
             config.disable_gpu()
+            if use_mkldnn:
+                config.enable_mkldnn()
         config.disable_glog_info()
         config.switch_ir_optim(True)
         config.enable_memory_optim()

hub_module/modules/image/style_transfer/UGATIT_83w/module.py

@@ -21,7 +21,7 @@ class UGATIT_83w(Module):
         self.model_path = os.path.join(self.directory, "UGATIT_83w")
 
         # 加载模型
-        self.model = Model(self.model_path, use_gpu)     
+        self.model = Model(self.model_path, use_gpu=use_gpu, use_mkldnn=False, combined=False)     
     
     # 关键点检测函数
     def style_transfer(

hub_module/modules/image/style_transfer/UGATIT_92w/model.py

@@ -7,9 +7,9 @@ __all__ = ['Model']
 
 class Model():
     # 初始化函数
-    def __init__(self, modelpath, use_gpu):
+    def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined=True):
         # 加载模型预测器
-        self.predictor = self.load_model(modelpath, use_gpu)
+        self.predictor = self.load_model(modelpath, use_gpu, use_mkldnn, combined)
 
         # 获取模型的输入输出
         self.input_names = self.predictor.get_input_names()
@@ -18,24 +18,30 @@ class Model():
         self.output_tensor = self.predictor.get_output_tensor(self.output_names[0])
 
     # 模型加载函数
-    def load_model(self, modelpath, use_gpu):
+    def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
         # 对运行位置进行配置
         if use_gpu:
             try:
-                places = os.environ["CUDA_VISIBLE_DEVICES"]
-                places = int(places[0])
-            except Exception as e:
-                print('Error: %s. Please set the environment variables "CUDA_VISIBLE_DEVICES".' % e)
+                int(os.environ.get('CUDA_VISIBLE_DEVICES'))
+            except Exception:
+                print('Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.')
                 use_gpu = False
                 
         # 加载模型参数
+        if combined:
+            model = os.path.join(modelpath, "__model__")
+            params = os.path.join(modelpath, "__params__")
+            config = AnalysisConfig(model, params)
+        else:
             config = AnalysisConfig(modelpath)
 
         # 设置参数
         if use_gpu:   
-            config.enable_use_gpu(100, places)
+            config.enable_use_gpu(100, 0)
         else:
             config.disable_gpu()
+            if use_mkldnn:
+                config.enable_mkldnn()
         config.disable_glog_info()
         config.switch_ir_optim(True)
         config.enable_memory_optim()

hub_module/modules/image/style_transfer/UGATIT_92w/module.py

@@ -21,7 +21,7 @@ class UGATIT_92w(Module):
         self.model_path = os.path.join(self.directory, "UGATIT_92w")
 
         # 加载模型
-        self.model = Model(self.model_path, use_gpu)     
+        self.model = Model(self.model_path, use_gpu=use_gpu, use_mkldnn=False, combined=False)  
     
     # 关键点检测函数
     def style_transfer(

hub_module/modules/image/style_transfer/animegan_v1_hayao_60/model.py

@@ -7,9 +7,9 @@ __all__ = ['Model']
 
 class Model():
     # 初始化函数
-    def __init__(self, modelpath, use_gpu):
+    def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined=True):
         # 加载模型预测器
-        self.predictor = self.load_model(modelpath, use_gpu)
+        self.predictor = self.load_model(modelpath, use_gpu, use_mkldnn, combined)
 
         # 获取模型的输入输出
         self.input_names = self.predictor.get_input_names()
@@ -18,24 +18,29 @@ class Model():
         self.output_tensor = self.predictor.get_output_tensor(self.output_names[0])
 
     # 模型加载函数
-    def load_model(self, modelpath, use_gpu):
+    def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
         # 对运行位置进行配置
         if use_gpu:
             try:
-                places = os.environ["CUDA_VISIBLE_DEVICES"]
-                places = int(places[0])
-            except Exception as e:
-                print('Error: %s. Please set the environment variables "CUDA_VISIBLE_DEVICES".' % e)
+                int(os.environ.get('CUDA_VISIBLE_DEVICES'))
+            except Exception:
+                print('Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.')
                 use_gpu = False
                 
         # 加载模型参数
+        if combined:
+            model = os.path.join(modelpath, "__model__")
+            params = os.path.join(modelpath, "__params__")
+            config = AnalysisConfig(model, params)
+        else:
             config = AnalysisConfig(modelpath)
 
         # 设置参数
         if use_gpu:   
-            config.enable_use_gpu(100, places)
+            config.enable_use_gpu(100, 0)
         else:
             config.disable_gpu()
+            if use_mkldnn:
                 config.enable_mkldnn()
         config.disable_glog_info()
         config.switch_ir_optim(True)
@@ -55,7 +60,8 @@ class Model():
 
         # 遍历输入数据进行预测
         for input_data in input_datas:
-            self.input_tensor.copy_from_cpu(input_data)
+            inputs = input_data.copy()
+            self.input_tensor.copy_from_cpu(inputs)
             self.predictor.zero_copy_run()
             output = self.output_tensor.copy_to_cpu()
             outputs.append(output)

hub_module/modules/image/style_transfer/animegan_v1_hayao_60/module.py

@@ -21,7 +21,7 @@ class Animegan_V1_Hayao_60(Module):
         self.model_path = os.path.join(self.directory, "animegan_v1_hayao_60")
 
         # 加载模型
-        self.model = Model(self.model_path, use_gpu)     
+        self.model = Model(self.model_path, use_gpu=use_gpu, use_mkldnn=False, combined=False)     
     
     # 关键点检测函数
     def style_transfer(

hub_module/modules/image/style_transfer/animegan_v2_hayao_64/model.py

@@ -7,9 +7,9 @@ __all__ = ['Model']
 
 class Model():
     # 初始化函数
-    def __init__(self, modelpath, use_gpu):
+    def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined=True):
         # 加载模型预测器
-        self.predictor = self.load_model(modelpath, use_gpu)
+        self.predictor = self.load_model(modelpath, use_gpu, use_mkldnn, combined)
 
         # 获取模型的输入输出
         self.input_names = self.predictor.get_input_names()
@@ -18,24 +18,29 @@ class Model():
         self.output_tensor = self.predictor.get_output_tensor(self.output_names[0])
 
     # 模型加载函数
-    def load_model(self, modelpath, use_gpu):
+    def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
         # 对运行位置进行配置
         if use_gpu:
             try:
-                places = os.environ["CUDA_VISIBLE_DEVICES"]
-                places = int(places[0])
-            except Exception as e:
-                print('Error: %s. Please set the environment variables "CUDA_VISIBLE_DEVICES".' % e)
+                int(os.environ.get('CUDA_VISIBLE_DEVICES'))
+            except Exception:
+                print('Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.')
                 use_gpu = False
                 
         # 加载模型参数
+        if combined:
+            model = os.path.join(modelpath, "__model__")
+            params = os.path.join(modelpath, "__params__")
+            config = AnalysisConfig(model, params)
+        else:
             config = AnalysisConfig(modelpath)
 
         # 设置参数
         if use_gpu:   
-            config.enable_use_gpu(100, places)
+            config.enable_use_gpu(100, 0)
         else:
             config.disable_gpu()
+            if use_mkldnn:
                 config.enable_mkldnn()
         config.disable_glog_info()
         config.switch_ir_optim(True)
@@ -55,7 +60,8 @@ class Model():
 
         # 遍历输入数据进行预测
         for input_data in input_datas:
-            self.input_tensor.copy_from_cpu(input_data)
+            inputs = input_data.copy()
+            self.input_tensor.copy_from_cpu(inputs)
             self.predictor.zero_copy_run()
             output = self.output_tensor.copy_to_cpu()
             outputs.append(output)

hub_module/modules/image/style_transfer/animegan_v2_hayao_64/module.py

@@ -21,7 +21,7 @@ class Animegan_V2_Hayao_64(Module):
         self.model_path = os.path.join(self.directory, "animegan_v2_hayao_64")
 
         # 加载模型
-        self.model = Model(self.model_path, use_gpu)     
+        self.model = Model(self.model_path, use_gpu=use_gpu, use_mkldnn=False, combined=False)     
     
     # 关键点检测函数
     def style_transfer(

hub_module/modules/image/style_transfer/animegan_v2_hayao_99/model.py

@@ -7,9 +7,9 @@ __all__ = ['Model']
 
 class Model():
     # 初始化函数
-    def __init__(self, modelpath, use_gpu):
+    def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined=True):
         # 加载模型预测器
-        self.predictor = self.load_model(modelpath, use_gpu)
+        self.predictor = self.load_model(modelpath, use_gpu, use_mkldnn, combined)
 
         # 获取模型的输入输出
         self.input_names = self.predictor.get_input_names()
@@ -18,24 +18,29 @@ class Model():
         self.output_tensor = self.predictor.get_output_tensor(self.output_names[0])
 
     # 模型加载函数
-    def load_model(self, modelpath, use_gpu):
+    def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
         # 对运行位置进行配置
         if use_gpu:
             try:
-                places = os.environ["CUDA_VISIBLE_DEVICES"]
-                places = int(places[0])
-            except Exception as e:
-                print('Error: %s. Please set the environment variables "CUDA_VISIBLE_DEVICES".' % e)
+                int(os.environ.get('CUDA_VISIBLE_DEVICES'))
+            except Exception:
+                print('Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.')
                 use_gpu = False
                 
         # 加载模型参数
+        if combined:
+            model = os.path.join(modelpath, "__model__")
+            params = os.path.join(modelpath, "__params__")
+            config = AnalysisConfig(model, params)
+        else:
             config = AnalysisConfig(modelpath)
 
         # 设置参数
         if use_gpu:   
-            config.enable_use_gpu(100, places)
+            config.enable_use_gpu(100, 0)
         else:
             config.disable_gpu()
+            if use_mkldnn:
                 config.enable_mkldnn()
         config.disable_glog_info()
         config.switch_ir_optim(True)
@@ -55,7 +60,8 @@ class Model():
 
         # 遍历输入数据进行预测
         for input_data in input_datas:
-            self.input_tensor.copy_from_cpu(input_data)
+            inputs = input_data.copy()
+            self.input_tensor.copy_from_cpu(inputs)
             self.predictor.zero_copy_run()
             output = self.output_tensor.copy_to_cpu()
             outputs.append(output)

hub_module/modules/image/style_transfer/animegan_v2_hayao_99/module.py

@@ -21,7 +21,7 @@ class Animegan_V2_Hayao_99(Module):
         self.model_path = os.path.join(self.directory, "animegan_v2_hayao_99")
 
         # 加载模型
-        self.model = Model(self.model_path, use_gpu)     
+        self.model = Model(self.model_path, use_gpu=use_gpu, use_mkldnn=False, combined=False)    
     
     # 关键点检测函数
     def style_transfer(

hub_module/modules/image/style_transfer/animegan_v2_paprika_54/model.py

@@ -7,9 +7,9 @@ __all__ = ['Model']
 
 class Model():
     # 初始化函数
-    def __init__(self, modelpath, use_gpu):
+    def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined=True):
         # 加载模型预测器
-        self.predictor = self.load_model(modelpath, use_gpu)
+        self.predictor = self.load_model(modelpath, use_gpu, use_mkldnn, combined)
 
         # 获取模型的输入输出
         self.input_names = self.predictor.get_input_names()
@@ -18,24 +18,29 @@ class Model():
         self.output_tensor = self.predictor.get_output_tensor(self.output_names[0])
 
     # 模型加载函数
-    def load_model(self, modelpath, use_gpu):
+    def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
         # 对运行位置进行配置
         if use_gpu:
             try:
-                places = os.environ["CUDA_VISIBLE_DEVICES"]
-                places = int(places[0])
-            except Exception as e:
-                print('Error: %s. Please set the environment variables "CUDA_VISIBLE_DEVICES".' % e)
+                int(os.environ.get('CUDA_VISIBLE_DEVICES'))
+            except Exception:
+                print('Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.')
                 use_gpu = False
                 
         # 加载模型参数
+        if combined:
+            model = os.path.join(modelpath, "__model__")
+            params = os.path.join(modelpath, "__params__")
+            config = AnalysisConfig(model, params)
+        else:
             config = AnalysisConfig(modelpath)
 
         # 设置参数
         if use_gpu:   
-            config.enable_use_gpu(100, places)
+            config.enable_use_gpu(100, 0)
         else:
             config.disable_gpu()
+            if use_mkldnn:
                 config.enable_mkldnn()
         config.disable_glog_info()
         config.switch_ir_optim(True)
@@ -55,7 +60,8 @@ class Model():
 
         # 遍历输入数据进行预测
         for input_data in input_datas:
-            self.input_tensor.copy_from_cpu(input_data)
+            inputs = input_data.copy()
+            self.input_tensor.copy_from_cpu(inputs)
             self.predictor.zero_copy_run()
             output = self.output_tensor.copy_to_cpu()
             outputs.append(output)

hub_module/modules/image/style_transfer/animegan_v2_paprika_54/module.py

@@ -21,7 +21,7 @@ class Animegan_V2_Paprika_54(Module):
         self.model_path = os.path.join(self.directory, "animegan_v2_paprika_54")
 
         # 加载模型
-        self.model = Model(self.model_path, use_gpu)     
+        self.model = Model(self.model_path, use_gpu=use_gpu, use_mkldnn=False, combined=False)    
     
     # 关键点检测函数
     def style_transfer(

hub_module/modules/image/style_transfer/animegan_v2_paprika_74/model.py

@@ -7,9 +7,9 @@ __all__ = ['Model']
 
 class Model():
     # 初始化函数
-    def __init__(self, modelpath, use_gpu):
+    def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined=True):
         # 加载模型预测器
-        self.predictor = self.load_model(modelpath, use_gpu)
+        self.predictor = self.load_model(modelpath, use_gpu, use_mkldnn, combined)
 
         # 获取模型的输入输出
         self.input_names = self.predictor.get_input_names()
@@ -18,24 +18,29 @@ class Model():
         self.output_tensor = self.predictor.get_output_tensor(self.output_names[0])
 
     # 模型加载函数
-    def load_model(self, modelpath, use_gpu):
+    def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
         # 对运行位置进行配置
         if use_gpu:
             try:
-                places = os.environ["CUDA_VISIBLE_DEVICES"]
-                places = int(places[0])
-            except Exception as e:
-                print('Error: %s. Please set the environment variables "CUDA_VISIBLE_DEVICES".' % e)
+                int(os.environ.get('CUDA_VISIBLE_DEVICES'))
+            except Exception:
+                print('Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.')
                 use_gpu = False
                 
         # 加载模型参数
+        if combined:
+            model = os.path.join(modelpath, "__model__")
+            params = os.path.join(modelpath, "__params__")
+            config = AnalysisConfig(model, params)
+        else:
             config = AnalysisConfig(modelpath)
 
         # 设置参数
         if use_gpu:   
-            config.enable_use_gpu(100, places)
+            config.enable_use_gpu(100, 0)
         else:
             config.disable_gpu()
+            if use_mkldnn:
                 config.enable_mkldnn()
         config.disable_glog_info()
         config.switch_ir_optim(True)
@@ -55,7 +60,8 @@ class Model():
 
         # 遍历输入数据进行预测
         for input_data in input_datas:
-            self.input_tensor.copy_from_cpu(input_data)
+            inputs = input_data.copy()
+            self.input_tensor.copy_from_cpu(inputs)
             self.predictor.zero_copy_run()
             output = self.output_tensor.copy_to_cpu()
             outputs.append(output)

hub_module/modules/image/style_transfer/animegan_v2_paprika_74/module.py

@@ -21,7 +21,7 @@ class Animegan_V2_Paprika_74(Module):
         self.model_path = os.path.join(self.directory, "animegan_v2_paprika_74")
 
         # 加载模型
-        self.model = Model(self.model_path, use_gpu)     
+        self.model = Model(self.model_path, use_gpu=use_gpu, use_mkldnn=False, combined=False)    
     
     # 关键点检测函数
     def style_transfer(

hub_module/modules/image/style_transfer/animegan_v2_paprika_97/model.py

@@ -7,9 +7,9 @@ __all__ = ['Model']
 
 class Model():
     # 初始化函数
-    def __init__(self, modelpath, use_gpu):
+    def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined=True):
         # 加载模型预测器
-        self.predictor = self.load_model(modelpath, use_gpu)
+        self.predictor = self.load_model(modelpath, use_gpu, use_mkldnn, combined)
 
         # 获取模型的输入输出
         self.input_names = self.predictor.get_input_names()
@@ -18,24 +18,29 @@ class Model():
         self.output_tensor = self.predictor.get_output_tensor(self.output_names[0])
 
     # 模型加载函数
-    def load_model(self, modelpath, use_gpu):
+    def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
         # 对运行位置进行配置
         if use_gpu:
             try:
-                places = os.environ["CUDA_VISIBLE_DEVICES"]
-                places = int(places[0])
-            except Exception as e:
-                print('Error: %s. Please set the environment variables "CUDA_VISIBLE_DEVICES".' % e)
+                int(os.environ.get('CUDA_VISIBLE_DEVICES'))
+            except Exception:
+                print('Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.')
                 use_gpu = False
                 
         # 加载模型参数
+        if combined:
+            model = os.path.join(modelpath, "__model__")
+            params = os.path.join(modelpath, "__params__")
+            config = AnalysisConfig(model, params)
+        else:
             config = AnalysisConfig(modelpath)
 
         # 设置参数
         if use_gpu:   
-            config.enable_use_gpu(100, places)
+            config.enable_use_gpu(100, 0)
         else:
             config.disable_gpu()
+            if use_mkldnn:
                 config.enable_mkldnn()
         config.disable_glog_info()
         config.switch_ir_optim(True)
@@ -55,7 +60,8 @@ class Model():
 
         # 遍历输入数据进行预测
         for input_data in input_datas:
-            self.input_tensor.copy_from_cpu(input_data)
+            inputs = input_data.copy()
+            self.input_tensor.copy_from_cpu(inputs)
             self.predictor.zero_copy_run()
             output = self.output_tensor.copy_to_cpu()
             outputs.append(output)

hub_module/modules/image/style_transfer/animegan_v2_paprika_97/module.py

@@ -21,7 +21,7 @@ class Animegan_V2_Paprika_97(Module):
         self.model_path = os.path.join(self.directory, "animegan_v2_paprika_97")
 
         # 加载模型
-        self.model = Model(self.model_path, use_gpu)     
+        self.model = Model(self.model_path, use_gpu=use_gpu, use_mkldnn=False, combined=False)    
     
     # 关键点检测函数
     def style_transfer(

hub_module/modules/image/style_transfer/animegan_v2_paprika_98/model.py

@@ -7,9 +7,9 @@ __all__ = ['Model']
 
 class Model():
     # 初始化函数
-    def __init__(self, modelpath, use_gpu):
+    def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined=True):
         # 加载模型预测器
-        self.predictor = self.load_model(modelpath, use_gpu)
+        self.predictor = self.load_model(modelpath, use_gpu, use_mkldnn, combined)
 
         # 获取模型的输入输出
         self.input_names = self.predictor.get_input_names()
@@ -18,24 +18,29 @@ class Model():
         self.output_tensor = self.predictor.get_output_tensor(self.output_names[0])
 
     # 模型加载函数
-    def load_model(self, modelpath, use_gpu):
+    def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
         # 对运行位置进行配置
         if use_gpu:
             try:
-                places = os.environ["CUDA_VISIBLE_DEVICES"]
-                places = int(places[0])
-            except Exception as e:
-                print('Error: %s. Please set the environment variables "CUDA_VISIBLE_DEVICES".' % e)
+                int(os.environ.get('CUDA_VISIBLE_DEVICES'))
+            except Exception:
+                print('Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.')
                 use_gpu = False
                 
         # 加载模型参数
+        if combined:
+            model = os.path.join(modelpath, "__model__")
+            params = os.path.join(modelpath, "__params__")
+            config = AnalysisConfig(model, params)
+        else:
             config = AnalysisConfig(modelpath)
 
         # 设置参数
         if use_gpu:   
-            config.enable_use_gpu(100, places)
+            config.enable_use_gpu(100, 0)
         else:
             config.disable_gpu()
+            if use_mkldnn:
                 config.enable_mkldnn()
         config.disable_glog_info()
         config.switch_ir_optim(True)
@@ -55,7 +60,8 @@ class Model():
 
         # 遍历输入数据进行预测
         for input_data in input_datas:
-            self.input_tensor.copy_from_cpu(input_data)
+            inputs = input_data.copy()
+            self.input_tensor.copy_from_cpu(inputs)
             self.predictor.zero_copy_run()
             output = self.output_tensor.copy_to_cpu()
             outputs.append(output)

hub_module/modules/image/style_transfer/animegan_v2_paprika_98/module.py

@@ -21,7 +21,7 @@ class Animegan_V2_Paprika_98(Module):
         self.model_path = os.path.join(self.directory, "animegan_v2_paprika_98")
 
         # 加载模型
-        self.model = Model(self.model_path, use_gpu)     
+        self.model = Model(self.model_path, use_gpu=use_gpu, use_mkldnn=False, combined=False)      
     
     # 关键点检测函数
     def style_transfer(

hub_module/modules/image/style_transfer/animegan_v2_shinkai_33/model.py

@@ -7,9 +7,9 @@ __all__ = ['Model']
 
 class Model():
     # 初始化函数
-    def __init__(self, modelpath, use_gpu):
+    def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined=True):
         # 加载模型预测器
-        self.predictor = self.load_model(modelpath, use_gpu)
+        self.predictor = self.load_model(modelpath, use_gpu, use_mkldnn, combined)
 
         # 获取模型的输入输出
         self.input_names = self.predictor.get_input_names()
@@ -18,24 +18,29 @@ class Model():
         self.output_tensor = self.predictor.get_output_tensor(self.output_names[0])
 
     # 模型加载函数
-    def load_model(self, modelpath, use_gpu):
+    def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
         # 对运行位置进行配置
         if use_gpu:
             try:
-                places = os.environ["CUDA_VISIBLE_DEVICES"]
-                places = int(places[0])
-            except Exception as e:
-                print('Error: %s. Please set the environment variables "CUDA_VISIBLE_DEVICES".' % e)
+                int(os.environ.get('CUDA_VISIBLE_DEVICES'))
+            except Exception:
+                print('Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.')
                 use_gpu = False
                 
         # 加载模型参数
+        if combined:
+            model = os.path.join(modelpath, "__model__")
+            params = os.path.join(modelpath, "__params__")
+            config = AnalysisConfig(model, params)
+        else:
             config = AnalysisConfig(modelpath)
 
         # 设置参数
         if use_gpu:   
-            config.enable_use_gpu(100, places)
+            config.enable_use_gpu(100, 0)
         else:
             config.disable_gpu()
+            if use_mkldnn:
                 config.enable_mkldnn()
         config.disable_glog_info()
         config.switch_ir_optim(True)
@@ -55,7 +60,8 @@ class Model():
 
         # 遍历输入数据进行预测
         for input_data in input_datas:
-            self.input_tensor.copy_from_cpu(input_data)
+            inputs = input_data.copy()
+            self.input_tensor.copy_from_cpu(inputs)
             self.predictor.zero_copy_run()
             output = self.output_tensor.copy_to_cpu()
             outputs.append(output)

hub_module/modules/image/style_transfer/animegan_v2_shinkai_33/module.py

@@ -21,7 +21,7 @@ class Animegan_V2_Shinkai_33(Module):
         self.model_path = os.path.join(self.directory, "animegan_v2_shinkai_33")
 
         # 加载模型
-        self.model = Model(self.model_path, use_gpu)     
+        self.model = Model(self.model_path, use_gpu=use_gpu, use_mkldnn=False, combined=False)    
     
     # 关键点检测函数
     def style_transfer(

hub_module/modules/image/style_transfer/animegan_v2_shinkai_53/model.py

@@ -7,9 +7,9 @@ __all__ = ['Model']
 
 class Model():
     # 初始化函数
-    def __init__(self, modelpath, use_gpu):
+    def __init__(self, modelpath, use_gpu=False, use_mkldnn=True, combined=True):
         # 加载模型预测器
-        self.predictor = self.load_model(modelpath, use_gpu)
+        self.predictor = self.load_model(modelpath, use_gpu, use_mkldnn, combined)
 
         # 获取模型的输入输出
         self.input_names = self.predictor.get_input_names()
@@ -18,24 +18,29 @@ class Model():
         self.output_tensor = self.predictor.get_output_tensor(self.output_names[0])
 
     # 模型加载函数
-    def load_model(self, modelpath, use_gpu):
+    def load_model(self, modelpath, use_gpu, use_mkldnn, combined):
         # 对运行位置进行配置
         if use_gpu:
             try:
-                places = os.environ["CUDA_VISIBLE_DEVICES"]
-                places = int(places[0])
-            except Exception as e:
-                print('Error: %s. Please set the environment variables "CUDA_VISIBLE_DEVICES".' % e)
+                int(os.environ.get('CUDA_VISIBLE_DEVICES'))
+            except Exception:
+                print('Error! Unable to use GPU. Please set the environment variables "CUDA_VISIBLE_DEVICES=GPU_id" to use GPU.')
                 use_gpu = False
                 
         # 加载模型参数
+        if combined:
+            model = os.path.join(modelpath, "__model__")
+            params = os.path.join(modelpath, "__params__")
+            config = AnalysisConfig(model, params)
+        else:
             config = AnalysisConfig(modelpath)
 
         # 设置参数
         if use_gpu:   
-            config.enable_use_gpu(100, places)
+            config.enable_use_gpu(100, 0)
         else:
             config.disable_gpu()
+            if use_mkldnn:
                 config.enable_mkldnn()
         config.disable_glog_info()
         config.switch_ir_optim(True)
@@ -55,7 +60,8 @@ class Model():
 
         # 遍历输入数据进行预测
         for input_data in input_datas:
-            self.input_tensor.copy_from_cpu(input_data)
+            inputs = input_data.copy()
+            self.input_tensor.copy_from_cpu(inputs)
             self.predictor.zero_copy_run()
             output = self.output_tensor.copy_to_cpu()
             outputs.append(output)

hub_module/modules/image/style_transfer/animegan_v2_shinkai_53/module.py

@@ -21,7 +21,7 @@ class Animegan_V2_Shinkai_53(Module):
         self.model_path = os.path.join(self.directory, "animegan_v2_shinkai_53")
 
         # 加载模型
-        self.model = Model(self.model_path, use_gpu)     
+        self.model = Model(self.model_path, use_gpu=use_gpu, use_mkldnn=False, combined=False)    
     
     # 关键点检测函数
     def style_transfer(