i

recommend-model-produce/src/main/python/tools/inferv2.py

@@ -1,4 +1,6 @@
 import os
+import sys
+import numpy as np
 __dir__ = os.path.dirname(os.path.abspath(__file__))
 sys.path.append(__dir__)
 from utils.oss_client import HangZhouOSSClient
@@ -27,7 +29,7 @@ def main():
 
     init_model_path = "/app/output_model_dssm"
     client = HangZhouOSSClient("art-recommend")
-    oss_object_name = self.config.get("runner.oss_object_name", "dyp/model.tar.gz")
+    oss_object_name = "dyp/dssm.tar.gz"
     client.get_object_to_file(oss_object_name, "model.tar.gz")
     compress.uncompress_tar("model.tar.gz", init_model_path)
     assert os.path.exists(init_model_path)
@@ -46,7 +48,7 @@ def main():
     input_handle = predictor.get_input_handle(input_names[0])
 
     # 设置输入
-    fake_input = np.random.randn(1, 157).astype("float32")
+    fake_input = np.abs(np.random.randn(1, 157).astype("float32"))
     input_handle.reshape([1, 157])
     input_handle.copy_from_cpu(fake_input)
 
@@ -57,8 +59,8 @@ def main():
     output_names = predictor.get_output_names()
     output_handle = predictor.get_output_handle(output_names[0])
     output_data = output_handle.copy_to_cpu() # numpy.ndarray类型
-    print("Output data size is {}".format(output_data.size))
-    print("Output data shape is {}".format(output_data.shape))
+    print("Output data size is {}".format(output_data))
+    print("Output data shape is {}".format(fake_input))
 
 if __name__ == "__main__":
-    main()
+    main()