serving st time optimization

tests/st/serving/client_example.py

@@ -24,7 +24,7 @@ import mindspore.dataset as de
 from mindspore import Tensor, context
 from mindspore import log as logger
 from tests.st.networks.models.bert.src.bert_model import BertModel
-from .generate_model import AddNet, bert_net_cfg
+from .generate_model import bert_net_cfg
 
 context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
 
@@ -32,32 +32,6 @@ random.seed(1)
 np.random.seed(1)
 de.config.set_seed(1)
 
-def test_add():
-    channel = grpc.insecure_channel('localhost:5500')
-    stub = ms_service_pb2_grpc.MSServiceStub(channel)
-    request = ms_service_pb2.PredictRequest()
-
-    x = request.data.add()
-    x.tensor_shape.dims.extend([4])
-    x.tensor_type = ms_service_pb2.MS_FLOAT32
-    x.data = (np.ones([4]).astype(np.float32)).tobytes()
-
-    y = request.data.add()
-    y.tensor_shape.dims.extend([4])
-    y.tensor_type = ms_service_pb2.MS_FLOAT32
-    y.data = (np.ones([4]).astype(np.float32)).tobytes()
-
-    result = stub.Predict(request)
-    result_np = np.frombuffer(result.result[0].data, dtype=np.float32).reshape(result.result[0].tensor_shape.dims)
-    print("ms client received: ")
-    print(result_np)
-
-    net = AddNet()
-    net_out = net(Tensor(np.ones([4]).astype(np.float32)), Tensor(np.ones([4]).astype(np.float32)))
-    print("add net out: ")
-    print(net_out)
-    assert np.allclose(net_out.asnumpy(), result_np, 0.001, 0.001, equal_nan=True)
-
 def test_bert():
     MAX_MESSAGE_LENGTH = 0x7fffffff
     input_ids = np.random.randint(0, 1000, size=(2, 32), dtype=np.int32)

tests/st/serving/generate_model.py

@@ -15,11 +15,9 @@
 
 import random
 import numpy as np
-import mindspore.nn as nn
 import mindspore.common.dtype as mstype
 import mindspore.dataset as de
 from mindspore import Tensor, context
-from mindspore.ops import operations as P
 from mindspore.train.serialization import export
 from tests.st.networks.models.bert.src.bert_model import BertModel, BertConfig
 
@@ -50,20 +48,6 @@ random.seed(1)
 np.random.seed(1)
 de.config.set_seed(1)
 
-class AddNet(nn.Cell):
-    def __init__(self):
-        super(AddNet, self).__init__()
-        self.add = P.TensorAdd()
-
-    def construct(self, x_, y_):
-        return self.add(x_, y_)
-
-def export_add_model():
-    net = AddNet()
-    x = np.ones(4).astype(np.float32)
-    y = np.ones(4).astype(np.float32)
-    export(net, Tensor(x), Tensor(y), file_name='add.mindir', file_format='MINDIR')
-
 def export_bert_model():
     input_ids = np.random.randint(0, 1000, size=(2, 32), dtype=np.int32)
     segment_ids = np.zeros((2, 32), dtype=np.int32)
@@ -73,5 +57,4 @@ def export_bert_model():
            file_name='bert.mindir', file_format='MINDIR')
 
 if __name__ == '__main__':
-    export_add_model()
     export_bert_model()

tests/st/serving/serving.sh

@@ -41,7 +41,7 @@ prepare_model()
   python3 generate_model.py &> generate_model_serving.log
   echo "### end to generate mode for serving test ###"
   result=`ls -l | grep -E '*mindir' | grep -v ".log" | wc -l`
-  if [ ${result} -ne 2 ]
+  if [ ${result} -ne 1 ]
   then
     cat generate_model_serving.log
     echo "### generate model for serving test failed ###" && exit 1
@@ -98,13 +98,6 @@ pytest_serving()
   echo "### $1 client end ###"
 }
 
-test_add_model()
-{
-  start_service 5500 add.mindir ${ENV_DEVICE_ID}
-  pytest_serving test_add
-  clean_pid
-}
-
 test_bert_model()
 {
   start_service 5500 bert.mindir ${ENV_DEVICE_ID}
@@ -115,5 +108,4 @@ test_bert_model()
 echo "-----serving start-----"
 rm -rf ms_serving *.log *.mindir *.dat ${CURRPATH}/model ${CURRPATH}/kernel_meta
 prepare_model
-test_add_model
 test_bert_model