PR #3 autograph -> autogl

rename autograph to autogl

autogl/datasets/__init__.py

@@ -17,7 +17,7 @@ DATASET_DICT = {}
 
 def register_dataset(name):
     """
-    New dataset types can be added to autograph with the :func:`register_dataset`
+    New dataset types can be added to autogl with the :func:`register_dataset`
     function decorator.
 
     For example::
@@ -37,7 +37,7 @@ def register_dataset(name):
             pyg and not issubclass(cls, torch_geometric.data.Dataset)
         ):
             raise ValueError(
-                "Dataset ({}: {}) must extend autograph.data.Dataset".format(
+                "Dataset ({}: {}) must extend autogl.data.Dataset".format(
                     name, cls.__name__
                 )
             )
@@ -106,17 +106,6 @@ from .utils import (
     graph_get_split,
 )
 
-"""
-# automatically import any Python files in the datasets/ directory
-for file in os.listdir(os.path.dirname(__file__)):
-    if file.endswith(".py") and not file.startswith("_"):
-        dataset_name = file[: file.find(".py")]
-        if not pyg and dataset_name.startswith("pyg"):
-            continue
-        module = importlib.import_module("autograph.datasets." + dataset_name)
-"""
-
-
 def build_dataset(args, path="~/.cache-autogl/"):
     path = osp.join(path, "data", args.dataset)
     path = os.path.expanduser(path)

autogl/datasets/utils.py

@@ -168,7 +168,7 @@ def random_splits_mask_class(
 
 
 def graph_cross_validation(dataset, n_splits=10, shuffle=True, random_seed=42):
-    r"""Cross validation for graph classification data, returning one fold with specific idx in autograph.datasets or pyg.Dataloader(default)
+    r"""Cross validation for graph classification data, returning one fold with specific idx in autogl.datasets or pyg.Dataloader(default)
 
     Parameters
     ----------
@@ -315,7 +315,7 @@ def graph_get_split(dataset, mask="train", is_loader=True, batch_size=128):
         return with which dataset/dataloader
 
     is_loader : bool
-        return with autograph.datasets or pyg.Dataloader
+        return with autogl.datasets or pyg.Dataloader
 
     batch_size : int
         batch_size for generateing Dataloader
@@ -332,7 +332,7 @@ def graph_get_split(dataset, mask="train", is_loader=True, batch_size=128):
 
 '''
 def graph_cross_validation(dataset, n_splits = 10, shuffle = True, random_seed = 42, fold_idx = 0, batch_size = 32, dataloader = True):
-    r"""Cross validation for graph classification data, returning one fold with specific idx in autograph.datasets or pyg.Dataloader(default)
+    r"""Cross validation for graph classification data, returning one fold with specific idx in autogl.datasets or pyg.Dataloader(default)
 
     Parameters
     ----------
@@ -355,7 +355,7 @@ def graph_cross_validation(dataset, n_splits = 10, shuffle = True, random_seed =
         batch_size for generateing Dataloader
 
     dataloader : bool
-        return with autograph.datasets or pyg.Dataloader
+        return with autogl.datasets or pyg.Dataloader
     """
     skf = StratifiedKFold(n_splits=n_splits, shuffle = shuffle, random_state = random_seed)
     idx_list = []

autogl/module/model/__init__.py

@@ -17,13 +17,6 @@ def register_model(name):
 
     return register_model_cls
 
-
-# automatically import any Python files in this directory
-# for file in os.listdir(os.path.dirname(__file__)):
-#     if file.endswith(".py") and not file.startswith("_"):
-#         file_name = file[: file.find(".py")]
-#         module = importlib.import_module("autograph.module.model." + file_name)
-
 from .base import BaseModel
 from .topkpool import AutoTopkpool
 from .graphsage import AutoSAGE

autogl/module/train/__init__.py

@@ -36,16 +36,6 @@ def register_evaluate(*name):
 
     return register_evaluate_cls
 
-
-"""
-# automatically import any Python files in this directory
-for file in os.listdir(os.path.dirname(__file__)):
-    if file.endswith(".py") and not file.startswith("_"):
-        file_name = file[: file.find(".py")]
-        module = importlib.import_module("autograph.module.train." + file_name)
-"""
-
-
 def get_feval(feval):
     if isinstance(feval, str):
         return EVALUATE_DICT[feval]

autogl/module/train/graph_classification.py

@@ -214,7 +214,7 @@ class GraphClassificationTrainer(BaseTrainer):
 
         Returns
         -------
-        self: ``autograph.train.GraphClassificationTrainer``
+        self: ``autogl.train.GraphClassificationTrainer``
             A reference of current trainer.
 
         """
@@ -289,7 +289,7 @@ class GraphClassificationTrainer(BaseTrainer):
 
         Returns
         -------
-        self: ``autograph.train.GraphClassificationTrainer``
+        self: ``autogl.train.GraphClassificationTrainer``
             A reference of current trainer.
 
         """
@@ -507,7 +507,7 @@ class GraphClassificationTrainer(BaseTrainer):
 
         Returns
         -------
-        self: ``autograph.train.GraphClassificationTrainer``
+        self: ``autogl.train.GraphClassificationTrainer``
             A new instance of trainer.
 
         """

autogl/module/train/node_classification.py

@@ -191,7 +191,7 @@ class NodeClassificationTrainer(BaseTrainer):
 
         Returns
         -------
-        self: ``autograph.train.NodeClassificationTrainer``
+        self: ``autogl.train.NodeClassificationTrainer``
             A reference of current trainer.
 
         """
@@ -261,7 +261,7 @@ class NodeClassificationTrainer(BaseTrainer):
 
         Returns
         -------
-        self: ``autograph.train.NodeClassificationTrainer``
+        self: ``autogl.train.NodeClassificationTrainer``
             A reference of current trainer.
 
         """
@@ -456,7 +456,7 @@ class NodeClassificationTrainer(BaseTrainer):
 
         Returns
         -------
-        self: ``autograph.train.NodeClassificationTrainer``
+        self: ``autogl.train.NodeClassificationTrainer``
             A new instance of trainer.
 
         """