diff --git a/tests/st/fl/cross_silo_lenet/config.json b/tests/st/fl/cross_silo_lenet/config.json
new file mode 100644
index 00000000000..37ac6edfb25
--- /dev/null
+++ b/tests/st/fl/cross_silo_lenet/config.json
@@ -0,0 +1,6 @@
+{
+    "recovery": {
+        "storge_type": 1,
+        "storage_file_path": "recovery.json"
+    }
+}
\ No newline at end of file
diff --git a/tests/st/fl/cross_silo_lenet/finish_cross_silo_lenet.py b/tests/st/fl/cross_silo_lenet/finish_cross_silo_lenet.py
new file mode 100644
index 00000000000..489a8671961
--- /dev/null
+++ b/tests/st/fl/cross_silo_lenet/finish_cross_silo_lenet.py
@@ -0,0 +1,29 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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 argparse
+import subprocess
+
+parser = argparse.ArgumentParser(description="Finish test_cross_silo_lenet.py case")
+parser.add_argument("--scheduler_port", type=int, default=8113)
+
+args, _ = parser.parse_known_args()
+scheduler_port = args.scheduler_port
+
+cmd = "pid=`ps -ef|grep \"scheduler_port=" + str(scheduler_port) + "\" "
+cmd += " | grep -v \"grep\" | grep -v \"finish\" |awk '{print $2}'` && "
+cmd += "for id in $pid; do kill -9 $id && echo \"killed $id\"; done"
+
+subprocess.call(['bash', '-c', cmd])
diff --git a/tests/st/fl/cross_silo_lenet/run_cross_silo_lenet_sched.py b/tests/st/fl/cross_silo_lenet/run_cross_silo_lenet_sched.py
new file mode 100644
index 00000000000..48e79094476
--- /dev/null
+++ b/tests/st/fl/cross_silo_lenet/run_cross_silo_lenet_sched.py
@@ -0,0 +1,54 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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 argparse
+import subprocess
+
+parser = argparse.ArgumentParser(description="Run test_cross_silo_lenet.py case")
+parser.add_argument("--device_target", type=str, default="CPU")
+parser.add_argument("--server_mode", type=str, default="FEDERATED_LEARNING")
+parser.add_argument("--worker_num", type=int, default=1)
+parser.add_argument("--server_num", type=int, default=2)
+parser.add_argument("--scheduler_ip", type=str, default="127.0.0.1")
+parser.add_argument("--scheduler_port", type=int, default=8113)
+parser.add_argument("--scheduler_manage_port", type=int, default=11202)
+parser.add_argument("--config_file_path", type=str, default="")
+
+args, _ = parser.parse_known_args()
+device_target = args.device_target
+server_mode = args.server_mode
+worker_num = args.worker_num
+server_num = args.server_num
+scheduler_ip = args.scheduler_ip
+scheduler_port = args.scheduler_port
+scheduler_manage_port = args.scheduler_manage_port
+config_file_path = args.config_file_path
+
+cmd_sched = "execute_path=$(pwd) && self_path=$(dirname \"${script_self}\") && rm -rf ${execute_path}/scheduler/ &&"
+cmd_sched += "mkdir ${execute_path}/scheduler/ &&"
+cmd_sched += "cd ${execute_path}/scheduler/ || exit && export GLOG_v=1 &&"
+cmd_sched += "python ${self_path}/../test_cross_silo_lenet.py"
+cmd_sched += " --device_target=" + device_target
+cmd_sched += " --server_mode=" + server_mode
+cmd_sched += " --ms_role=MS_SCHED"
+cmd_sched += " --worker_num=" + str(worker_num)
+cmd_sched += " --server_num=" + str(server_num)
+cmd_sched += " --config_file_path=" + str(config_file_path)
+cmd_sched += " --scheduler_ip=" + scheduler_ip
+cmd_sched += " --scheduler_port=" + str(scheduler_port)
+cmd_sched += " --scheduler_manage_port=" + str(scheduler_manage_port)
+cmd_sched += " > scheduler.log 2>&1 &"
+
+subprocess.call(['bash', '-c', cmd_sched])
diff --git a/tests/st/fl/cross_silo_lenet/run_cross_silo_lenet_server.py b/tests/st/fl/cross_silo_lenet/run_cross_silo_lenet_server.py
new file mode 100644
index 00000000000..81b33faae92
--- /dev/null
+++ b/tests/st/fl/cross_silo_lenet/run_cross_silo_lenet_server.py
@@ -0,0 +1,115 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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 argparse
+import subprocess
+
+parser = argparse.ArgumentParser(description="Run test_cross_silo_lenet.py case")
+parser.add_argument("--device_target", type=str, default="CPU")
+parser.add_argument("--server_mode", type=str, default="FEDERATED_LEARNING")
+parser.add_argument("--worker_num", type=int, default=1)
+parser.add_argument("--server_num", type=int, default=2)
+parser.add_argument("--scheduler_ip", type=str, default="127.0.0.1")
+parser.add_argument("--scheduler_port", type=int, default=8113)
+parser.add_argument("--fl_server_port", type=int, default=6666)
+parser.add_argument("--start_fl_job_threshold", type=int, default=1)
+parser.add_argument("--start_fl_job_time_window", type=int, default=3000)
+parser.add_argument("--update_model_ratio", type=float, default=1.0)
+parser.add_argument("--update_model_time_window", type=int, default=3000)
+parser.add_argument("--fl_name", type=str, default="Lenet")
+parser.add_argument("--fl_iteration_num", type=int, default=25)
+parser.add_argument("--client_epoch_num", type=int, default=20)
+parser.add_argument("--client_batch_size", type=int, default=32)
+parser.add_argument("--client_learning_rate", type=float, default=0.1)
+parser.add_argument("--local_server_num", type=int, default=-1)
+parser.add_argument("--config_file_path", type=str, default="")
+parser.add_argument("--encrypt_type", type=str, default="NOT_ENCRYPT")
+# parameters for encrypt_type='DP_ENCRYPT'
+parser.add_argument("--dp_eps", type=float, default=50.0)
+parser.add_argument("--dp_delta", type=float, default=0.01)  # 1/worker_num
+parser.add_argument("--dp_norm_clip", type=float, default=1.0)
+# parameters for encrypt_type='PW_ENCRYPT'
+parser.add_argument("--share_secrets_ratio", type=float, default=1.0)
+parser.add_argument("--cipher_time_window", type=int, default=300000)
+parser.add_argument("--reconstruct_secrets_threshold", type=int, default=3)
+
+args, _ = parser.parse_known_args()
+device_target = args.device_target
+server_mode = args.server_mode
+worker_num = args.worker_num
+server_num = args.server_num
+scheduler_ip = args.scheduler_ip
+scheduler_port = args.scheduler_port
+fl_server_port = args.fl_server_port
+start_fl_job_threshold = args.start_fl_job_threshold
+start_fl_job_time_window = args.start_fl_job_time_window
+update_model_ratio = args.update_model_ratio
+update_model_time_window = args.update_model_time_window
+fl_name = args.fl_name
+fl_iteration_num = args.fl_iteration_num
+client_epoch_num = args.client_epoch_num
+client_batch_size = args.client_batch_size
+client_learning_rate = args.client_learning_rate
+local_server_num = args.local_server_num
+config_file_path = args.config_file_path
+encrypt_type = args.encrypt_type
+share_secrets_ratio = args.share_secrets_ratio
+cipher_time_window = args.cipher_time_window
+reconstruct_secrets_threshold = args.reconstruct_secrets_threshold
+dp_eps = args.dp_eps
+dp_delta = args.dp_delta
+dp_norm_clip = args.dp_norm_clip
+
+if local_server_num == -1:
+    local_server_num = server_num
+
+assert local_server_num <= server_num, "The local server number should not be bigger than total server number."
+
+for i in range(local_server_num):
+    cmd_server = "execute_path=$(pwd) && self_path=$(dirname \"${script_self}\") && "
+    cmd_server += "rm -rf ${execute_path}/server_" + str(i) + "/ &&"
+    cmd_server += "mkdir ${execute_path}/server_" + str(i) + "/ &&"
+    cmd_server += "cd ${execute_path}/server_" + str(i) + "/ || exit && export GLOG_v=1 &&"
+    cmd_server += "python ${self_path}/../test_cross_silo_lenet.py"
+    cmd_server += " --device_target=" + device_target
+    cmd_server += " --server_mode=" + server_mode
+    cmd_server += " --ms_role=MS_SERVER"
+    cmd_server += " --worker_num=" + str(worker_num)
+    cmd_server += " --server_num=" + str(server_num)
+    cmd_server += " --scheduler_ip=" + scheduler_ip
+    cmd_server += " --scheduler_port=" + str(scheduler_port)
+    cmd_server += " --fl_server_port=" + str(fl_server_port + i)
+    cmd_server += " --start_fl_job_threshold=" + str(start_fl_job_threshold)
+    cmd_server += " --start_fl_job_time_window=" + str(start_fl_job_time_window)
+    cmd_server += " --update_model_ratio=" + str(update_model_ratio)
+    cmd_server += " --update_model_time_window=" + str(update_model_time_window)
+    cmd_server += " --fl_name=" + fl_name
+    cmd_server += " --fl_iteration_num=" + str(fl_iteration_num)
+    cmd_server += " --config_file_path=" + str(config_file_path)
+    cmd_server += " --client_epoch_num=" + str(client_epoch_num)
+    cmd_server += " --client_batch_size=" + str(client_batch_size)
+    cmd_server += " --client_learning_rate=" + str(client_learning_rate)
+    cmd_server += " --encrypt_type=" + str(encrypt_type)
+    cmd_server += " --share_secrets_ratio=" + str(share_secrets_ratio)
+    cmd_server += " --cipher_time_window=" + str(cipher_time_window)
+    cmd_server += " --reconstruct_secrets_threshold=" + str(reconstruct_secrets_threshold)
+    cmd_server += " --dp_eps=" + str(dp_eps)
+    cmd_server += " --dp_delta=" + str(dp_delta)
+    cmd_server += " --dp_norm_clip=" + str(dp_norm_clip)
+    cmd_server += " > server.log 2>&1 &"
+
+    import time
+    time.sleep(0.3)
+    subprocess.call(['bash', '-c', cmd_server])
diff --git a/tests/st/fl/cross_silo_lenet/run_cross_silo_lenet_worker.py b/tests/st/fl/cross_silo_lenet/run_cross_silo_lenet_worker.py
new file mode 100644
index 00000000000..b2e14650bcf
--- /dev/null
+++ b/tests/st/fl/cross_silo_lenet/run_cross_silo_lenet_worker.py
@@ -0,0 +1,70 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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 argparse
+import subprocess
+
+parser = argparse.ArgumentParser(description="Run test_cross_silo_lenet.py case")
+parser.add_argument("--device_target", type=str, default="GPU")
+parser.add_argument("--server_mode", type=str, default="FEDERATED_LEARNING")
+parser.add_argument("--worker_num", type=int, default=1)
+parser.add_argument("--server_num", type=int, default=2)
+parser.add_argument("--scheduler_ip", type=str, default="127.0.0.1")
+parser.add_argument("--scheduler_port", type=int, default=8113)
+parser.add_argument("--fl_iteration_num", type=int, default=25)
+parser.add_argument("--client_epoch_num", type=int, default=20)
+parser.add_argument("--worker_step_num_per_iteration", type=int, default=65)
+parser.add_argument("--local_worker_num", type=int, default=-1)
+parser.add_argument("--config_file_path", type=str, default="")
+
+args, _ = parser.parse_known_args()
+device_target = args.device_target
+server_mode = args.server_mode
+worker_num = args.worker_num
+server_num = args.server_num
+scheduler_ip = args.scheduler_ip
+scheduler_port = args.scheduler_port
+fl_iteration_num = args.fl_iteration_num
+client_epoch_num = args.client_epoch_num
+worker_step_num_per_iteration = args.worker_step_num_per_iteration
+local_worker_num = args.local_worker_num
+config_file_path = args.config_file_path
+
+if local_worker_num == -1:
+    local_worker_num = worker_num
+
+assert local_worker_num <= worker_num, "The local worker number should not be bigger than total worker number."
+
+for i in range(local_worker_num):
+    cmd_worker = "execute_path=$(pwd) && self_path=$(dirname \"${script_self}\") && "
+    cmd_worker += "rm -rf ${execute_path}/worker_" + str(i) + "/ &&"
+    cmd_worker += "mkdir ${execute_path}/worker_" + str(i) + "/ &&"
+    cmd_worker += "cd ${execute_path}/worker_" + str(i) + "/ || exit && export GLOG_v=1 && "
+    cmd_worker += "export CUDA_VISIBLE_DEVICES=" + str(i) +" && "
+    cmd_worker += "python ${self_path}/../test_cross_silo_lenet.py"
+    cmd_worker += " --device_target=" + device_target
+    cmd_worker += " --server_mode=" + server_mode
+    cmd_worker += " --ms_role=MS_WORKER"
+    cmd_worker += " --worker_num=" + str(worker_num)
+    cmd_worker += " --server_num=" + str(server_num)
+    cmd_worker += " --scheduler_ip=" + scheduler_ip
+    cmd_worker += " --scheduler_port=" + str(scheduler_port)
+    cmd_worker += " --config_file_path=" + str(config_file_path)
+    cmd_worker += " --fl_iteration_num=" + str(fl_iteration_num)
+    cmd_worker += " --client_epoch_num=" + str(client_epoch_num)
+    cmd_worker += " --worker_step_num_per_iteration=" + str(worker_step_num_per_iteration)
+    cmd_worker += " > worker.log 2>&1 &"
+
+    subprocess.call(['bash', '-c', cmd_worker])
diff --git a/tests/st/fl/cross_silo_lenet/src/cell_wrapper.py b/tests/st/fl/cross_silo_lenet/src/cell_wrapper.py
new file mode 100644
index 00000000000..2f8053d435d
--- /dev/null
+++ b/tests/st/fl/cross_silo_lenet/src/cell_wrapper.py
@@ -0,0 +1,46 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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.
+# ============================================================================
+
+from mindspore.ops import functional as F
+from mindspore.ops import operations as P
+from mindspore.nn import TrainOneStepCell
+
+class TrainOneStepCellForFLWorker(TrainOneStepCell):
+    """
+    Wraps the network with federated learning operators in worker.
+    """
+    def __init__(self, network, optimizer, sens=1.0, batch_size=32):
+        super(TrainOneStepCellForFLWorker, self).__init__(network, optimizer, sens)
+        self.batch_size = batch_size
+        self.start_fl_job = P.StartFLJob(batch_size)
+        self.update_model = P.UpdateModel()
+        self.get_model = P.GetModel()
+        self.depend = P.Depend()
+
+    def construct(self, *inputs):
+        start_fl_job = self.start_fl_job()
+        inputs = self.depend(inputs, start_fl_job)
+
+        loss = self.network(*inputs)
+        sens = F.fill(loss.dtype, loss.shape, self.sens)
+        grads = self.grad(self.network, self.weights)(*inputs, sens)
+        grads = self.grad_reducer(grads)
+        loss = self.depend(loss, self.optimizer(grads))
+
+        self.update_model(self.weights)
+        get_model = self.get_model(self.weights)
+
+        loss = self.depend(loss, get_model)
+        return loss
diff --git a/tests/st/fl/cross_silo_lenet/src/model.py b/tests/st/fl/cross_silo_lenet/src/model.py
new file mode 100644
index 00000000000..aba4940499e
--- /dev/null
+++ b/tests/st/fl/cross_silo_lenet/src/model.py
@@ -0,0 +1,72 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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 mindspore.nn as nn
+from mindspore.common.initializer import TruncatedNormal
+
+def conv(in_channels, out_channels, kernel_size, stride=1, padding=0):
+    """weight initial for conv layer"""
+    weight = weight_variable()
+    return nn.Conv2d(
+        in_channels,
+        out_channels,
+        kernel_size=kernel_size,
+        stride=stride,
+        padding=padding,
+        weight_init=weight,
+        has_bias=False,
+        pad_mode="valid",
+    )
+
+
+def fc_with_initialize(input_channels, out_channels):
+    """weight initial for fc layer"""
+    weight = weight_variable()
+    bias = weight_variable()
+    return nn.Dense(input_channels, out_channels, weight, bias)
+
+
+def weight_variable():
+    """weight initial"""
+    return TruncatedNormal(0.02)
+
+
+class LeNet5(nn.Cell):
+    def __init__(self, num_class=10, channel=3):
+        super(LeNet5, self).__init__()
+        self.num_class = num_class
+        self.conv1 = conv(channel, 6, 5)
+        self.conv2 = conv(6, 16, 5)
+        self.fc1 = fc_with_initialize(16 * 5 * 5, 120)
+        self.fc2 = fc_with_initialize(120, 84)
+        self.fc3 = fc_with_initialize(84, self.num_class)
+        self.relu = nn.ReLU()
+        self.max_pool2d = nn.MaxPool2d(kernel_size=2, stride=2)
+        self.flatten = nn.Flatten()
+
+    def construct(self, x):
+        x = self.conv1(x)
+        x = self.relu(x)
+        x = self.max_pool2d(x)
+        x = self.conv2(x)
+        x = self.relu(x)
+        x = self.max_pool2d(x)
+        x = self.flatten(x)
+        x = self.fc1(x)
+        x = self.relu(x)
+        x = self.fc2(x)
+        x = self.relu(x)
+        x = self.fc3(x)
+        return x
diff --git a/tests/st/fl/cross_silo_lenet/test_cross_silo_lenet.py b/tests/st/fl/cross_silo_lenet/test_cross_silo_lenet.py
new file mode 100644
index 00000000000..b2745c21e4e
--- /dev/null
+++ b/tests/st/fl/cross_silo_lenet/test_cross_silo_lenet.py
@@ -0,0 +1,135 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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 argparse
+import numpy as np
+
+import mindspore.context as context
+import mindspore.nn as nn
+from mindspore import Tensor
+from mindspore.nn import WithLossCell
+from src.cell_wrapper import TrainOneStepCellForFLWorker
+from src.model import LeNet5
+
+parser = argparse.ArgumentParser(description="test_cross_silo_lenet")
+parser.add_argument("--device_target", type=str, default="GPU")
+parser.add_argument("--server_mode", type=str, default="FEDERATED_LEARNING")
+parser.add_argument("--ms_role", type=str, default="MS_WORKER")
+parser.add_argument("--worker_num", type=int, default=1)
+parser.add_argument("--server_num", type=int, default=1)
+parser.add_argument("--scheduler_ip", type=str, default="127.0.0.1")
+parser.add_argument("--scheduler_port", type=int, default=8113)
+parser.add_argument("--fl_server_port", type=int, default=6666)
+parser.add_argument("--start_fl_job_threshold", type=int, default=1)
+parser.add_argument("--start_fl_job_time_window", type=int, default=3000)
+parser.add_argument("--update_model_ratio", type=float, default=1.0)
+parser.add_argument("--update_model_time_window", type=int, default=3000)
+parser.add_argument("--fl_name", type=str, default="Lenet")
+parser.add_argument("--fl_iteration_num", type=int, default=25)
+parser.add_argument("--client_epoch_num", type=int, default=20)
+parser.add_argument("--client_batch_size", type=int, default=32)
+parser.add_argument("--client_learning_rate", type=float, default=0.1)
+parser.add_argument("--worker_step_num_per_iteration", type=int, default=65)
+parser.add_argument("--scheduler_manage_port", type=int, default=11202)
+parser.add_argument("--config_file_path", type=str, default="")
+parser.add_argument("--encrypt_type", type=str, default="NOT_ENCRYPT")
+# parameters for encrypt_type='DP_ENCRYPT'
+parser.add_argument("--dp_eps", type=float, default=50.0)
+parser.add_argument("--dp_delta", type=float, default=0.01)  # 1/worker_num
+parser.add_argument("--dp_norm_clip", type=float, default=1.0)
+# parameters for encrypt_type='PW_ENCRYPT'
+parser.add_argument("--share_secrets_ratio", type=float, default=1.0)
+parser.add_argument("--cipher_time_window", type=int, default=300000)
+parser.add_argument("--reconstruct_secrets_threshold", type=int, default=3)
+
+args, _ = parser.parse_known_args()
+device_target = args.device_target
+server_mode = args.server_mode
+ms_role = args.ms_role
+worker_num = args.worker_num
+server_num = args.server_num
+scheduler_ip = args.scheduler_ip
+scheduler_port = args.scheduler_port
+fl_server_port = args.fl_server_port
+start_fl_job_threshold = args.start_fl_job_threshold
+start_fl_job_time_window = args.start_fl_job_time_window
+update_model_ratio = args.update_model_ratio
+update_model_time_window = args.update_model_time_window
+fl_name = args.fl_name
+fl_iteration_num = args.fl_iteration_num
+client_epoch_num = args.client_epoch_num
+client_batch_size = args.client_batch_size
+client_learning_rate = args.client_learning_rate
+worker_step_num_per_iteration = args.worker_step_num_per_iteration
+scheduler_manage_port = args.scheduler_manage_port
+config_file_path = args.config_file_path
+encrypt_type = args.encrypt_type
+share_secrets_ratio = args.share_secrets_ratio
+cipher_time_window = args.cipher_time_window
+reconstruct_secrets_threshold = args.reconstruct_secrets_threshold
+dp_eps = args.dp_eps
+dp_delta = args.dp_delta
+dp_norm_clip = args.dp_norm_clip
+
+ctx = {
+    "enable_fl": True,
+    "server_mode": server_mode,
+    "ms_role": ms_role,
+    "worker_num": worker_num,
+    "server_num": server_num,
+    "scheduler_ip": scheduler_ip,
+    "scheduler_port": scheduler_port,
+    "fl_server_port": fl_server_port,
+    "start_fl_job_threshold": start_fl_job_threshold,
+    "start_fl_job_time_window": start_fl_job_time_window,
+    "update_model_ratio": update_model_ratio,
+    "update_model_time_window": update_model_time_window,
+    "fl_name": fl_name,
+    "fl_iteration_num": fl_iteration_num,
+    "client_epoch_num": client_epoch_num,
+    "client_batch_size": client_batch_size,
+    "client_learning_rate": client_learning_rate,
+    "worker_step_num_per_iteration": worker_step_num_per_iteration,
+    "scheduler_manage_port": scheduler_manage_port,
+    "config_file_path": config_file_path,
+    "share_secrets_ratio": share_secrets_ratio,
+    "cipher_time_window": cipher_time_window,
+    "reconstruct_secrets_threshold": reconstruct_secrets_threshold,
+    "dp_eps": dp_eps,
+    "dp_delta": dp_delta,
+    "dp_norm_clip": dp_norm_clip,
+    "encrypt_type": encrypt_type
+}
+
+context.set_context(mode=context.GRAPH_MODE, device_target=device_target, save_graphs=False)
+context.set_fl_context(**ctx)
+
+if __name__ == "__main__":
+    epoch = 50000
+    np.random.seed(0)
+    network = LeNet5(62)
+    criterion = nn.SoftmaxCrossEntropyWithLogits(sparse=True, reduction="mean")
+    net_opt = nn.Momentum(network.trainable_params(), 0.01, 0.9)
+    net_with_criterion = WithLossCell(network, criterion)
+    train_network = TrainOneStepCellForFLWorker(net_with_criterion, net_opt)
+    train_network.set_train()
+    losses = []
+
+    for _ in range(epoch):
+        data = Tensor(np.random.rand(32, 3, 32, 32).astype(np.float32))
+        label = Tensor(np.random.randint(0, 61, (32)).astype(np.int32))
+        loss = train_network(data, label).asnumpy()
+        losses.append(loss)
+    print(losses)