diff --git a/tests/st/serving/client_example.py b/tests/st/serving/client_example.py index c5b9c7ef46a460be08b13d8bbe95a009354cc069..560dd72c0766700db2fab145c1f1bcf963f33f89 100644 --- a/tests/st/serving/client_example.py +++ b/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) diff --git a/tests/st/serving/generate_model.py b/tests/st/serving/generate_model.py index 807862715d66cca1fffe417f8251b7f78dbca8e4..142ff91587f5b798219d2f3e25fd4c384fdaac95 100644 --- a/tests/st/serving/generate_model.py +++ b/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() diff --git a/tests/st/serving/serving.sh b/tests/st/serving/serving.sh index 1b77db34d57b4d1fa6426349273a759368469944..ac9644eafd0371afd8fcd83a4068863063e9d397 100644 --- a/tests/st/serving/serving.sh +++ b/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