Merge pull request #5134 from FederatedAI/develop-1.11.3

Update 1.11.3 to Master
FederatedAI · Sep 8, 2023 · 5fdc5cf · 5fdc5cf
2 parents 8767db5 + 1f3e579
commit 5fdc5cf
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diff --git a/.gitmodules b/.gitmodules
@@ -1,12 +1,12 @@
 [submodule "fateboard"]
 	path = fateboard
 	url = https://github.com/FederatedAI/FATE-Board.git
-	branch = v1.11.1
+	branch = v1.11.2
 [submodule "eggroll"]
 	path = eggroll
 	url = https://github.com/WeBankFinTech/eggroll.git
-	branch = v2.5.1
+	branch = v2.5.2
 [submodule "fateflow"]
 	path = fateflow
 	url = https://github.com/FederatedAI/FATE-Flow.git
-	branch = v1.11.1
+	branch = v1.11.2
diff --git a/README.md b/README.md
@@ -50,7 +50,7 @@ Deploying FATE to multiple nodes to achieve scalability, reliability and managea
 - [EggRoll](https://github.com/WeBankFinTech/eggroll): A simple high-performance computing framework for (federated) machine learning.
 - [AnsibleFATE](https://github.com/FederatedAI/AnsibleFATE): A tool to optimize and automate the configuration and deployment operations via Ansible.
 - [FATE-Builder](https://github.com/FederatedAI/FATE-Builder): A tool to build package and docker image for FATE and KubeFATE.
-- [FATE-LLM](https://github.com/FederatedAI/FATE-LLM/blob/main/README.md)
+- [FATE-LLM](https://github.com/FederatedAI/FATE-LLM/blob/main/README.md) : A framework to support federated learning for large language models(LLMs).
 ## Documentation 
 
 ### FATE Design 

diff --git a/RELEASE.md b/RELEASE.md
@@ -1,3 +1,10 @@
+## Release 1.11.3
+### Major Features and Improvements
+> FederatedML
+* FedAVGTrainer update code strcuture: support OffsitetTuningTrainer
+* FedAVGTrainer update log format: report batch progress instead of batch index
+
+
 ## Release 1.11.2
 ### Major Features and Improvements
 > FederatedML

diff --git a/deploy/cluster-deploy/doc/fate_on_spark/fate_on_spark_deployment_guide.zh.md b/deploy/cluster-deploy/doc/fate_on_spark/fate_on_spark_deployment_guide.zh.md
@@ -183,7 +183,7 @@ wget https://webank-ai-1251170195.cos.ap-guangzhou.myqcloud.com/fate/${version}/
 scp *.tar.gz app@192.168.0.1:/data/projects/install
 scp *.tar.gz app@192.168.0.2:/data/projects/install
 ```
-注意: 当前文档需要部署的FATE version>=1.7.0，${version}替换为如1.11.2，不带v字符
+注意: 当前文档需要部署的FATE version>=1.7.0，${version}替换为如1.11.3，不带v字符
 ### 5.2 操作系统参数检查
 
 **在目标服务器（192.168.0.1 192.168.0.2 192.168.0.3）app用户下执行**

diff --git a/deploy/standalone-deploy/README.md b/deploy/standalone-deploy/README.md
@@ -41,7 +41,7 @@ export version={FATE version for this deployment}
 example:
 
 ```bash
-export version=1.11.2
+export version=1.11.3
 ```
 
 ### 2.2 Pulling mirrors

diff --git a/deploy/standalone-deploy/README.zh.md b/deploy/standalone-deploy/README.zh.md
@@ -35,13 +35,13 @@
 设置部署所需环境变量(注意, 通过以下方式设置的环境变量仅在当前终端会话有效, 若打开新的终端会话, 如重新登录或者新窗口, 请重新设置)
 
 ```bash
-export version={本次部署的FATE版本号, 如1.11.2}
+export version={本次部署的FATE版本号, 如1.11.3}
 ```
 
 样例:
 
 ```bash
-export version=1.11.2
+export version=1.11.3
 ```
 
 ### 2.2 拉取镜像

diff --git a/doc/federatedml_component/README.md b/doc/federatedml_component/README.md
@@ -40,7 +40,6 @@ provide:
 | [Homo-LR](logistic_regression.md)                                             | HomoLR                       | Build homo logistic regression model through multiple parties.                                                                        | Table, values are instances.                      | Table, values are instances.                                                                          |                                                      | Logistic Regression Model, consists of model-meta and model-param.      |
 | [Homo-NN](homo_nn.md)                                                         | HomoNN                       | Build homo neural network model through multiple parties.                                                                             | Table, values are instances.                      | Table, values are instances.                                                                          |                                                      | Neural Network Model, consists of model-meta and model-param.           |
 | [Hetero Secure Boosting](ensemble.md)                                         | HeteroSecureBoost            | Build hetero secure boosting model through multiple parties                                                                           | Table, values are instances.                      | Table, values are instances.                                                                          |                                                      | SecureBoost Model, consists of model-meta and model-param.              |
-| [Hetero Fast Secure Boosting](ensemble.md)                                    | HeteroFastSecureBoost        | Build hetero secure boosting model through multiple parties in layered/mix manners.                                                   | Table, values are instances.                      | Table, values are instances.                                                                          |                                                      | FastSecureBoost Model, consists of model-meta and model-param.          |
 | [Evaluation](evaluation.md)                                                   | Evaluation                   | Output the model evaluation metrics for user.                                                                                         | Table(s), values are instances.                   |                                                                                                       |                                                      |                                                                         |
 | [Hetero Pearson](correlation.md)                                              | HeteroPearson                | Calculate hetero correlation of features from different parties.                                                                      | Table, values are instances.                      |                                                                                                       |                                                      |                                                                         |
 | [Hetero-NN](hetero_nn.md)                                                     | HeteroNN                     | Build hetero neural network model.                                                                                                    | Table, values are instances.                      | Table, values are instances.                                                                          |                                                      | Hetero Neural Network Model, consists of model-meta and model-param.    |

diff --git a/doc/federatedml_component/README.zh.md b/doc/federatedml_component/README.zh.md
@@ -30,7 +30,6 @@ Federatedml模块包括许多常见机器学习算法联邦化实现。所有模
 | [Homo-LR](logistic_regression.md)                                             | HomoLR                  | 通过多方构建横向逻辑回归模块。                                                                                     | Table, 值为Instance             |                                                                                                   |                                         | Logistic回归模型，由模型本身和模型参数组成  |
 | [Homo-NN](homo_nn.md)                                                         | HomoNN                  | 通过多方构建横向神经网络模块。                                                                                     | Table, 值为Instance             |                                                                                                   |                                         | 神经网络模型，由模型本身和模型参数组成        |
 | [Hetero Secure Boosting](ensemble.md)                                         | HeteroSecureBoost       | 通过多方构建纵向Secure Boost模块。                                                                             | Table，值为Instance              |                                                                                                   |                                         | SecureBoost模型，由模型本身和模型参数组成 |
-| [Hetero Fast Secure Boosting](ensemble.md)                                    | HeteroFastSecureBoost   | 使用分层/混合模式快速构建树模型                                                                                    | Table，值为Instance              | Table，值为Instance                                                                                  |                                         | FastSecureBoost模型          |
 | [Evaluation](evaluation.md)                                                   | Evaluation              | 为用户输出模型评估指标。                                                                                        | Table(s), 值为Instance          |                                                                                                   |                                         |                            |
 | [Hetero Pearson](correlation.md)                                              | HeteroPearson           | 计算来自不同方的特征的Pearson相关系数。                                                                             | Table, 值为Instance             |                                                                                                   |                                         |                            |
 | [Hetero-NN](hetero_nn.md)                                                     | HeteroNN                | 构建纵向神经网络模块。                                                                                         | Table, 值为Instance             |                                                                                                   |                                         | 纵向神经网络模型                   |

diff --git a/eggroll b/eggroll
diff --git a/fate.env b/fate.env
@@ -1,7 +1,7 @@
-FATE=1.11.2
-FATEFlow=1.11.1
-FATEBoard=1.11.1
-EGGROLL=2.5.1
+FATE=1.11.3
+FATEFlow=1.11.2
+FATEBoard=1.11.2
+EGGROLL=2.5.2
 CENTOS=7.2
 UBUNTU=16.04
 PYTHON=3.8

diff --git a/fateboard b/fateboard
diff --git a/fateflow b/fateflow
diff --git a/python/fate_client/pipeline/component/homo_nn.py b/python/fate_client/pipeline/component/homo_nn.py
@@ -44,7 +44,8 @@
         'loss': None,
         'optimizer': None,
         'nn_define': None,
-        'ds_config': None
+        'ds_config': None,
+        'server_init': False
     }
 except Exception as e:
     print(e)
@@ -65,7 +66,10 @@ class HomoNN(FateComponent):
     torch_seed, global random seed
     loss, loss function from fate_torch
     optimizer, optimizer from fate_torch
+    ds_config, config for deepspeed
     model, a fate torch sequential defining the model structure
+    server_init, whether to initialize the model, loss and optimizer on server, if configs are provided, they will be used.  In
+                 current version this option is specially designed for offsite-tuning
     """
 
     @extract_explicit_parameter
@@ -82,7 +86,9 @@ def __init__(self,
                  loss=None,
                  optimizer: OptimizerType = None,
                  ds_config: dict = None,
-                 model: Sequential = None, **kwargs):
+                 model: Sequential = None,
+                 server_init: bool = False,
+                 **kwargs):
 
         explicit_parameters = copy.deepcopy(DEFAULT_PARAM_DICT)
         if 'name' not in kwargs["explict_parameters"]:
@@ -94,8 +100,15 @@ def __init__(self,
         self.input = Input(self.name, data_type="multi")
         self.output = Output(self.name, data_type='single')
         self._module_name = "HomoNN"
-        self._updated = {'trainer': False, 'dataset': False,
-                         'torch_seed': False, 'loss': False, 'optimizer': False, 'model': False}
+        self._updated = {
+            'trainer': False,
+            'dataset': False,
+            'torch_seed': False,
+            'loss': False,
+            'optimizer': False,
+            'model': False,
+            'ds_config': False,
+            'server_init': False}
         self._set_param(kwargs["explict_parameters"])
         self._check_parameters()
 

diff --git a/python/fate_client/pipeline/component/nn/backend/torch/cust.py b/python/fate_client/pipeline/component/nn/backend/torch/cust.py
@@ -3,9 +3,12 @@
 from pipeline.component.nn.backend.torch.base import FateTorchLayer, FateTorchLoss
 import difflib
 
+ML_PATH = 'federatedml.nn'
+LLM_PATH = "fate_llm"
 
-MODEL_PATH = None
-LOSS_PATH = None
+LLM_MODEL_PATH = '{}.model_zoo'.format(LLM_PATH)
+MODEL_PATH = '{}.model_zoo'.format(ML_PATH)
+LOSS_PATH = '{}.loss'.format(ML_PATH)
 
 
 def str_simi(str_a, str_b):
@@ -45,9 +48,14 @@ class CustModel(FateTorchLayer, nn.Module):
 
     def __init__(self, module_name, class_name, **kwargs):
         super(CustModel, self).__init__()
-        assert isinstance(module_name, str), 'name must be a str, specify the module in the model_zoo'
-        assert isinstance(class_name, str), 'class name must be a str, specify the class in the module'
-        self.param_dict = {'module_name': module_name, 'class_name': class_name, 'param': kwargs}
+        assert isinstance(
+            module_name, str), 'name must be a str, specify the module in the model_zoo'
+        assert isinstance(
+            class_name, str), 'class name must be a str, specify the class in the module'
+        self.param_dict = {
+            'module_name': module_name,
+            'class_name': class_name,
+            'param': kwargs}
         self._model = None
 
     def init_model(self):
@@ -62,11 +70,18 @@ def forward(self, x):
     def get_pytorch_model(self, module_path=None):
 
         if module_path is None:
-            return get_class(
-                self.param_dict['module_name'],
-                self.param_dict['class_name'],
-                self.param_dict['param'],
-                MODEL_PATH)
+            try:
+                return get_class(
+                    self.param_dict['module_name'],
+                    self.param_dict['class_name'],
+                    self.param_dict['param'],
+                    MODEL_PATH)
+            except BaseException:
+                return get_class(
+                    self.param_dict['module_name'],
+                    self.param_dict['class_name'],
+                    self.param_dict['param'],
+                    LLM_MODEL_PATH)
         else:
             return get_class(
                 self.param_dict['module_name'],

diff --git a/python/fate_client/pyproject.toml b/python/fate_client/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "fate_client"
-version = "1.11.2"
+version = "1.11.3"
 description = "Clients for FATE, including flow_client and pipeline"
 authors = ["FederatedAI <contact@FedAI.org>"]
 license = "Apache-2.0"

diff --git a/python/fate_client/setup.py b/python/fate_client/setup.py
@@ -48,7 +48,7 @@
 
 setup_kwargs = {
     "name": "fate-client",
-    "version": "1.11.2",
+    "version": "1.11.3",
     "description": "Clients for FATE, including flow_client and pipeline",
     "long_description": "FATE Client\n===========\n\nTools for interacting with FATE.\n\nquick start\n-----------\n\n1. (optional) create virtual env\n\n   .. code-block:: bash\n\n      python -m venv venv\n      source venv/bin/activate\n\n\n2. install FATE Client\n\n   .. code-block:: bash\n\n      pip install fate-client\n\n\nPipeline\n========\n\nA high-level python API that allows user to design, start,\nand query FATE jobs in a sequential manner. For more information,\nplease refer to this `guide <./pipeline/README.rst>`__\n\nInitial Configuration\n---------------------\n\n1. Configure server information\n\n   .. code-block:: bash\n\n      # configure values in pipeline/config.yaml\n      # use real ip address to configure pipeline\n      pipeline init --ip 127.0.0.1 --port 9380 --log-directory ./logs\n\n\nFATE Flow Command Line Interface (CLI) v2\n=========================================\n\nA command line interface providing series of commands for user to design, start,\nand query FATE jobs. For more information, please refer to this `guide <./flow_client/README.rst>`__\n\nInitial Configuration\n---------------------\n\n1. Configure server information\n\n   .. code-block:: bash\n\n      # configure values in conf/service_conf.yaml\n      flow init -c /data/projects/fate/conf/service_conf.yaml\n      # use real ip address to initialize cli\n      flow init --ip 127.0.0.1 --port 9380\n\n",
     "author": "FederatedAI",

diff --git a/python/fate_test/pyproject.toml b/python/fate_test/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "fate_test"
-version = "1.11.2"
+version = "1.11.3"
 description = "test tools for FATE"
 authors = ["FederatedAI <contact@FedAI.org>"]
 license = "Apache-2.0"