Add api ref for mf task and context

doc/source/index.rst

@@ -24,3 +24,4 @@ Welcome to FederatedScope's documentation!
    gfl.rst
    autotune.rst
    attack.rst
+   mf.rst

doc/source/mf.rst

@@ -0,0 +1,26 @@
+Federated Matrix Factorization Module References
+=======================
+
+federatedscope.mf.dataset
+-----------------------
+
+.. automodule:: federatedscope.mf.dataset
+    :members:
+
+federatedscope.mf.model
+-----------------------
+
+.. automodule:: federatedscope.mf.model
+    :members:
+
+federatedscope.mf.dataloader
+-----------------------
+
+.. automodule:: federatedscope.mf.dataloader
+    :members:
+
+federatedscope.mf.trainer
+-----------------------
+
+.. automodule:: federatedscope.mf.trainer
+    :members:

enviroment/requirements-torch1.10-application.txt

@@ -6,7 +6,7 @@ scikit-learn
 pytorch==1.10.1
 torchvision==0.11.2
 torchaudio==0.10.1
-cudatoolkit==11.3.1
+cudatoolkit
 wandb
 tensorboard
 tensorboardX

federatedscope/core/trainers/__init__.py

@@ -1,4 +1,15 @@
 from federatedscope.core.trainers.trainer import Trainer, GeneralTorchTrainer
 from federatedscope.core.trainers.trainer_pFedMe import wrap_pFedMeTrainer
+from federatedscope.core.trainers.context import Context
+from federatedscope.core.trainers.trainer_fedprox import wrap_fedprox_trainer
+from federatedscope.core.trainers.trainer_nbafl import wrap_nbafl_trainer, wrap_nbafl_server
 
-__all__ = ['Trainer', 'GeneralTorchTrainer', 'wrap_pFedMeTrainer']
+__all__ = [
+    'Trainer',
+    'Context',
+    'GeneralTorchTrainer',
+    'wrap_pFedMeTrainer',
+    'wrap_fedprox_trainer',
+    'wrap_nbafl_trainer',
+    'wrap_nbafl_server'
+]

federatedscope/mf/dataloader/__init__.py

@@ -1,3 +1,6 @@
-from federatedscope.mf.dataloader.dataloader import load_mf_dataset
+from federatedscope.mf.dataloader.dataloader import load_mf_dataset, MFDataLoader
 
-__all__ = ['load_mf_dataset']
+__all__ = [
+    'load_mf_dataset',
+    'MFDataLoader'
+]

federatedscope/mf/dataloader/dataloader.py

@@ -16,7 +16,7 @@
 
 
 def load_mf_dataset(config=None):
-    """Return dataset of matrix factorization
+    """Return the dataset of matrix factorization
 
     Format:
         {
@@ -66,7 +66,7 @@ def load_mf_dataset(config=None):
 class MFDataLoader(object):
     """DataLoader for MF dataset
 
-    Arguments:
+    Args:
         data (csc_matrix): sparse MF dataset
         batch_size (int): the size of batch data
         shuffle (bool): shuffle the dataset
@@ -150,6 +150,8 @@ def __len__(self):
     def __next__(self, theta=None):
         """Get the next batch of data
 
+        Args:
+            theta (int): the maximal number of ratings for each user
         """
         idx_end = self._idx_cur + self.batch_size
         if self._idx_cur == len(

federatedscope/mf/dataset/__init__.py

@@ -1,8 +1,13 @@
-from os.path import dirname, basename, isfile, join
-import glob
+from federatedscope.mf.dataset.movielens import *
 
-modules = glob.glob(join(dirname(__file__), "*.py"))
 __all__ = [
-    basename(f)[:-3] for f in modules
-    if isfile(f) and not f.endswith('__init__.py')
+    'VMFDataset',
+    'HMFDataset',
+    'MovieLensData',
+    'MovieLens1M',
+    'MovieLens10M',
+    'VFLMovieLens1M',
+    'HFLMovieLens1M',
+    'VFLMovieLens10M',
+    'HFLMovieLens10M'
 ]

federatedscope/mf/model/__init__.py

@@ -1,8 +1,9 @@
-from os.path import dirname, basename, isfile, join
-import glob
+from federatedscope.mf.model.model import BasicMFNet, VMFNet, HMFNet
+from federatedscope.mf.model.model_builder import get_mfnet
 
-modules = glob.glob(join(dirname(__file__), "*.py"))
 __all__ = [
-    basename(f)[:-3] for f in modules
-    if isfile(f) and not f.endswith('__init__.py')
-]
+    "get_mfnet",
+    "BasicMFNet",
+    "VMFNet",
+    "HMFNet"
+]

federatedscope/mf/trainer/__init__.py

@@ -1,8 +1,10 @@
-from os.path import dirname, basename, isfile, join
-import glob
+from federatedscope.mf.trainer.trainer import MFTrainer
+from federatedscope.mf.trainer.trainer_sgdmf import wrap_MFTrainer, init_sgdmf_ctx, embedding_clip, hook_on_batch_backward
 
-modules = glob.glob(join(dirname(__file__), "*.py"))
 __all__ = [
-    basename(f)[:-3] for f in modules
-    if isfile(f) and not f.endswith('__init__.py')
+    'MFTrainer',
+    'wrap_MFTrainer',
+    'init_sgdmf_ctx',
+    'embedding_clip',
+    'hook_on_batch_backward'
 ]