[DOCS-74] Fixes shortdocs (wandb#2094)

Co-authored-by: ariG23498 <[email protected]>

wandb/apis/public.py

@@ -715,7 +715,7 @@ def __repr__(self):
 
 
 class Project(Attrs):
-    """A project is a namespace for runs"""
+    """A project is a namespace for runs."""
 
     def __init__(self, client, entity, project, attrs):
         super(Project, self).__init__(dict(attrs))
@@ -1401,15 +1401,20 @@ def __repr__(self):
 
 
 class Sweep(Attrs):
-    """A set of runs associated with a sweep
-    Instantiate with:
-      api.sweep(sweep_path)
+    """A set of runs associated with a sweep.
+
+    Examples:
+        Instantiate with:
+        ```
+        api = wandb.Api()
+        sweep = api.sweep(path/to/sweep)
+        ```
 
     Attributes:
-        runs (`Runs`): list of runs
-        id (str): sweep id
-        project (str): name of project
-        config (str): dictionary of sweep configuration
+        runs: (`Runs`) list of runs
+        id: (str) sweep id
+        project: (str) name of project
+        config: (str) dictionary of sweep configuration
     """
 
     QUERY = gql(
@@ -1582,7 +1587,7 @@ def __repr__(self):
 
 
 class Files(Paginator):
-    """Files is an iterable collection of `File` objects."""
+    """An iterable collection of `File` objects."""
 
     QUERY = gql(
         """
@@ -2569,6 +2574,8 @@ def ref_url(self):
 
 class Artifact(artifacts.Artifact):
     """
+    A wandb Artifact.
+
     An artifact that has been logged, including all its attributes, links to the runs
     that use it, and a link to the run that logged it.
 

wandb/sdk/wandb_artifacts.py

@@ -77,11 +77,12 @@ def __init__(self, entry: ArtifactEntry, obj: data_types.WBValue):
 
 class Artifact(ArtifactInterface):
     """
+    Flexible and lightweight building block for dataset and model versioning.
+
     Constructs an empty artifact whose contents can be populated using its
     `add` family of functions. Once the artifact has all the desired files,
     you can call `wandb.log_artifact()` to log it.
 
-
     Arguments:
         name: (str) A human-readable name for this artifact, which is how you
             can identify this artifact in the UI or reference it in `use_artifact`

wandb/sdk/wandb_run.py

@@ -178,11 +178,12 @@ def join(self) -> None:
 
 class Run(object):
     """
-    The run object corresponds to a single execution of your script,
-    typically this is an ML experiment. Create a run with `wandb.init()`.
+    A unit of computation logged by wandb. Typically this is an ML experiment.
 
-    In distributed training, use `wandb.init()` to create a run for each process,
-    and set the group argument to organize runs into a larger experiment.
+    Create a run with `wandb.init()`.
+
+    In distributed training, use `wandb.init()` to create a run for
+    each process, and set the group argument to organize runs into a larger experiment.
 
     Currently there is a parallel Run object in the wandb.Api. Eventually these
     two objects will be merged.

wandb/sdk/wandb_summary.py

@@ -81,8 +81,9 @@ def update(self, d: t.Dict):
 
 class Summary(SummaryDict):
     """
-    Summary tracks single values for each run. By default, summary is set to the
-    last value of History.
+    Tracks single values for each metric for each run.
+
+    By default, a metric's summary is the last value of its History.
 
     For example, `wandb.log({'accuracy': 0.9})` will add a new step to History and
     update Summary to the latest value. In some cases, it's more useful to have

wandb/sdk_py27/wandb_artifacts.py

@@ -77,11 +77,12 @@ def __init__(self, entry, obj):
 
 class Artifact(ArtifactInterface):
     """
+    Flexible and lightweight building block for dataset and model versioning.
+
     Constructs an empty artifact whose contents can be populated using its
     `add` family of functions. Once the artifact has all the desired files,
     you can call `wandb.log_artifact()` to log it.
 
-
     Arguments:
         name: (str) A human-readable name for this artifact, which is how you
             can identify this artifact in the UI or reference it in `use_artifact`

wandb/sdk_py27/wandb_run.py

@@ -178,11 +178,12 @@ def join(self):
 
 class Run(object):
     """
-    The run object corresponds to a single execution of your script,
-    typically this is an ML experiment. Create a run with `wandb.init()`.
+    A unit of computation logged by wandb. Typically this is an ML experiment.
 
-    In distributed training, use `wandb.init()` to create a run for each process,
-    and set the group argument to organize runs into a larger experiment.
+    Create a run with `wandb.init()`.
+
+    In distributed training, use `wandb.init()` to create a run for
+    each process, and set the group argument to organize runs into a larger experiment.
 
     Currently there is a parallel Run object in the wandb.Api. Eventually these
     two objects will be merged.

wandb/sdk_py27/wandb_summary.py

@@ -81,8 +81,9 @@ def update(self, d):
 
 class Summary(SummaryDict):
     """
-    Summary tracks single values for each run. By default, summary is set to the
-    last value of History.
+    Tracks single values for each metric for each run.
+
+    By default, a metric's summary is the last value of its History.
 
     For example, `wandb.log({'accuracy': 0.9})` will add a new step to History and
     update Summary to the latest value. In some cases, it's more useful to have