Update client.py

Author: wanghongtao007

examples/add_sub/client.py

@@ -1,82 +1,35 @@
-# Copyright 2020-2021, 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
-# are met:
-#  * Redistributions of source code must retain the above copyright
-#    notice, this list of conditions and the following disclaimer.
-#  * Redistributions in binary form must reproduce the above copyright
-#    notice, this list of conditions and the following disclaimer in the
-#    documentation and/or other materials provided with the distribution.
-#  * Neither the name of NVIDIA CORPORATION nor the names of its
-#    contributors may be used to endorse or promote products derived
-#    from this software without specific prior written permission.
-#
-# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
-# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
-# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-# PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR
-# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
-# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
-# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
-# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
-# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
-# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
-# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
-import sys
-
-import numpy as np
-import tritonclient.http as httpclient
 from tritonclient.utils import *
+import tritonclient.http as httpclient
+import numpy as np
+
+triton_url = "localhost:8000"
+model_name = "openpom_model"
 
-model_name = "add_sub"
-shape = [4]
+smiles = ["CC(=O)OC1=CC=CC=C1C(=O)O"]
+input_data = np.array(smiles, dtype=object).reshape(1, 1)
 
-with httpclient.InferenceServerClient("localhost:8000") as client:
-    input0_data = np.random.rand(*shape).astype(np.float32)
-    input1_data = np.random.rand(*shape).astype(np.float32)
+with httpclient.InferenceServerClient(triton_url) as client:
     inputs = [
         httpclient.InferInput(
-            "INPUT0", input0_data.shape, np_to_triton_dtype(input0_data.dtype)
-        ),
-        httpclient.InferInput(
-            "INPUT1", input1_data.shape, np_to_triton_dtype(input1_data.dtype)
-        ),
+            name="SMILES",
+            shape=input_data.shape,
+            datatype="BYTES"
+        )
     ]
-
-    inputs[0].set_data_from_numpy(input0_data)
-    inputs[1].set_data_from_numpy(input1_data)
+    inputs[0].set_data_from_numpy(input_data)
 
     outputs = [
-        httpclient.InferRequestedOutput("OUTPUT0"),
-        httpclient.InferRequestedOutput("OUTPUT1"),
+        httpclient.InferRequestedOutput("OUTPUT", binary_data=True)
     ]
+    print("Type of outputs[0]:", type(outputs[0]))
+    print("Outputs:", outputs)
 
-    response = client.infer(model_name, inputs, request_id=str(1), outputs=outputs)
-
-    result = response.get_response()
-    output0_data = response.as_numpy("OUTPUT0")
-    output1_data = response.as_numpy("OUTPUT1")
-
-    print(
-        "INPUT0 ({}) + INPUT1 ({}) = OUTPUT0 ({})".format(
-            input0_data, input1_data, output0_data
-        )
+    response = client.infer(
+        model_name=model_name,
+        inputs=inputs,
+        outputs=outputs
     )
-    print(
-        "INPUT0 ({}) - INPUT1 ({}) = OUTPUT1 ({})".format(
-            input0_data, input1_data, output1_data
-        )
-    )
-
-    if not np.allclose(input0_data + input1_data, output0_data):
-        print("add_sub example error: incorrect sum")
-        sys.exit(1)
-
-    if not np.allclose(input0_data - input1_data, output1_data):
-        print("add_sub example error: incorrect difference")
-        sys.exit(1)
 
-    print("PASS: add_sub")
-    sys.exit(0)
+    embeddings = response.as_numpy("OUTPUT")
+    print("shape:", embeddings.shape)
+    print("embedding vector: \n", embeddings[0])