Fix np.object_ deprecations (triton-inference-server#5184)

* Fix np.object_ deprecations * Review comment
shixiaoyu321 · Dec 20, 2022 · e4e25d1 · e4e25d1
1 parent 580c062
commit e4e25d1
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Showing 4 changed files with 25 additions and 16 deletions.
diff --git a/qa/L0_backend_python/python_test.py b/qa/L0_backend_python/python_test.py
@@ -297,7 +297,9 @@ def test_unicode(self):
         model_name = "string"
         shape = [1]
 
-        for i in range(3):
+        # The first run will use np.bytes_ and the second run will use
+        # np.object_
+        for i in range(2):
             with self._shm_leak_detector.Probe() as shm_probe:
                 with httpclient.InferenceServerClient(
                         "localhost:8000") as client:
@@ -328,7 +330,10 @@ def test_string(self):
         model_name = "string_fixed"
         shape = [1]
 
-        for i in range(6):
+        # Test different string outputs. This test will send 4 requests to the
+        # backend. The model will return 4 responses (np.object_ and np.bytes) *
+        # (empty output and fixed output)
+        for i in range(4):
             with self._shm_leak_detector.Probe() as shm_probe:
                 with httpclient.InferenceServerClient(
                         "localhost:8000") as client:

diff --git a/qa/L0_string_io/string_client_test.py b/qa/L0_string_io/string_client_test.py
@@ -1,5 +1,5 @@
 #!/usr/bin/env python
-# Copyright (c) 2019-2020, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2019-2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
 # modification, are permitted provided that the following conditions
@@ -148,7 +148,7 @@ def _test_str_dtype(self, client, model_name, dtype=np.object_):
         self._test_infer_non_unicode(model_name, client, in0_bytes)
 
     def _test_bytes(self, model_name):
-        dtypes = [np.object_, np.object, np.bytes_]
+        dtypes = [np.object_, np.bytes_]
 
         # This clients will fail for binary_data=False when the binary input
         # is not UTF-8 encodable. They should work for other cases however.

diff --git a/qa/python_models/string/model.py b/qa/python_models/string/model.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2021-2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
 # modification, are permitted provided that the following conditions
@@ -35,7 +35,7 @@ class TritonPythonModel:
 
     def initialize(self, args):
         self._index = 0
-        self._dtypes = [np.bytes_, np.object_, np.object]
+        self._dtypes = [np.bytes_, np.object_]
 
     def execute(self, requests):
         responses = []

diff --git a/qa/python_models/string_fixed/model.py b/qa/python_models/string_fixed/model.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
+# Copyright 2021-2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
 # modification, are permitted provided that the following conditions
@@ -35,21 +35,25 @@ class TritonPythonModel:
 
     def initialize(self, args):
         self._index = 0
-        self._dtypes = [np.bytes_, np.object_, np.object]
+        self._dtypes = [np.bytes_, np.object_]
 
     def execute(self, requests):
+        # Create four different responses (empty string or fixed string) * (two
+        # datatypes)
         responses = []
         for _ in requests:
-            if self._index % 2 == 0:
+            if self._index == 0:
                 out_tensor_0 = pb_utils.Tensor(
-                    "OUTPUT0",
-                    np.array(['123456'], dtype=self._dtypes[self._index % 3]))
-            else:
-                # Test sending strings with no elements
+                    "OUTPUT0", np.array(['123456'], dtype=self._dtypes[0]))
+            elif self._index == 1:
                 out_tensor_0 = pb_utils.Tensor(
-                    "OUTPUT0", np.array([],
-                                        dtype=self._dtypes[self._index % 3]))
-
+                    "OUTPUT0", np.array([], dtype=self._dtypes[1]))
+            elif self._index == 2:
+                out_tensor_0 = pb_utils.Tensor(
+                    "OUTPUT0", np.array(['123456'], dtype=self._dtypes[0]))
+            elif self._index == 3:
+                out_tensor_0 = pb_utils.Tensor(
+                    "OUTPUT0", np.array([], dtype=self._dtypes[1]))
             self._index += 1
             responses.append(pb_utils.InferenceResponse([out_tensor_0]))
         return responses