[Serving]add ernie-3.0 demo (#399)

serving add ernie-3.0 demo

examples/text/ernie-3.0/serving/seq_cls_grpc_client.py

@@ -0,0 +1,149 @@
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import logging
+import numpy as np
+import time
+from typing import Optional
+
+from tritonclient import utils as client_utils
+from tritonclient.grpc import InferenceServerClient, InferInput, InferRequestedOutput, service_pb2_grpc, service_pb2
+
+LOGGER = logging.getLogger("run_inference_on_triton")
+
+
+class SyncGRPCTritonRunner:
+    DEFAULT_MAX_RESP_WAIT_S = 120
+
+    def __init__(
+            self,
+            server_url: str,
+            model_name: str,
+            model_version: str,
+            *,
+            verbose=False,
+            resp_wait_s: Optional[float]=None, ):
+        self._server_url = server_url
+        self._model_name = model_name
+        self._model_version = model_version
+        self._verbose = verbose
+        self._response_wait_t = self.DEFAULT_MAX_RESP_WAIT_S if resp_wait_s is None else resp_wait_s
+
+        self._client = InferenceServerClient(
+            self._server_url, verbose=self._verbose)
+        error = self._verify_triton_state(self._client)
+        if error:
+            raise RuntimeError(
+                f"Could not communicate to Triton Server: {error}")
+
+        LOGGER.debug(
+            f"Triton server {self._server_url} and model {self._model_name}:{self._model_version} "
+            f"are up and ready!")
+
+        model_config = self._client.get_model_config(self._model_name,
+                                                     self._model_version)
+        model_metadata = self._client.get_model_metadata(self._model_name,
+                                                         self._model_version)
+        LOGGER.info(f"Model config {model_config}")
+        LOGGER.info(f"Model metadata {model_metadata}")
+
+        self._inputs = {tm.name: tm for tm in model_metadata.inputs}
+        self._input_names = list(self._inputs)
+        self._outputs = {tm.name: tm for tm in model_metadata.outputs}
+        self._output_names = list(self._outputs)
+        self._outputs_req = [
+            InferRequestedOutput(name) for name in self._outputs
+        ]
+
+    def Run(self, inputs):
+        """
+        Args:
+            inputs: list, Each value corresponds to an input name of self._input_names
+        Returns:
+            results: dict, {name : numpy.array}
+        """
+        infer_inputs = []
+        for idx, data in enumerate(inputs):
+            data = np.array(
+                [[x.encode('utf-8')] for x in data], dtype=np.object_)
+            infer_input = InferInput(self._input_names[idx], [len(data), 1],
+                                     "BYTES")
+            infer_input.set_data_from_numpy(data)
+            infer_inputs.append(infer_input)
+
+        results = self._client.infer(
+            model_name=self._model_name,
+            model_version=self._model_version,
+            inputs=infer_inputs,
+            outputs=self._outputs_req,
+            client_timeout=self._response_wait_t, )
+        results = {name: results.as_numpy(name) for name in self._output_names}
+        return results
+
+    def _verify_triton_state(self, triton_client):
+        if not triton_client.is_server_live():
+            return f"Triton server {self._server_url} is not live"
+        elif not triton_client.is_server_ready():
+            return f"Triton server {self._server_url} is not ready"
+        elif not triton_client.is_model_ready(self._model_name,
+                                              self._model_version):
+            return f"Model {self._model_name}:{self._model_version} is not ready"
+        return None
+
+
+def test_tnews_dataset(runner):
+    from paddlenlp.datasets import load_dataset
+    dev_ds = load_dataset('clue', "tnews", splits='dev')
+
+    batches = []
+    labels = []
+    idx = 0
+    batch_size = 32
+    while idx < len(dev_ds):
+        data = []
+        label = []
+        for i in range(batch_size):
+            if idx + i >= len(dev_ds):
+                break
+            data.append(dev_ds[idx + i]["sentence"])
+            label.append(dev_ds[idx + i]["label"])
+        batches.append(data)
+        labels.append(np.array(label))
+        idx += batch_size
+
+    accuracy = 0
+    for i, data in enumerate(batches):
+        ret = runner.Run([data])
+        # print("ret:", ret)
+        accuracy += np.sum(labels[i] == ret["label"])
+    print("acc:", 1.0 * accuracy / len(dev_ds))
+
+
+if __name__ == "__main__":
+    from paddlenlp.datasets import load_dataset
+    dev_ds = load_dataset('clue', "tnews", splits='dev')
+    model_name = "ernie_seqcls"
+    model_version = "1"
+    url = "localhost:8001"
+    runner = SyncGRPCTritonRunner(url, model_name, model_version)
+    texts = [["你家拆迁，要钱还是要房？答案一目了然", "军嫂探亲拧包入住，部队家属临时来队房标准有了规定，全面落实！"], [
+        "区块链投资心得，能做到就不会亏钱",
+    ]]
+
+    for text in texts:
+        # input format:[input1, input2 ... inputn], n = len(self._input_names)
+        result = runner.Run([text])
+        print(result)
+
+    test_tnews_dataset(runner)