auto-lint code

binaries.json

@@ -139,4 +139,4 @@
             }
         ]
     }
-}
+}

ivy/compiler/compiler.py

@@ -16,14 +16,16 @@ def source_to_source(
     as well e.g. (source="torch_frontend", target="ivy") or (source="torch_frontend", target="tensorflow") etc.
 
     Args:
+    ----
         object: The object (class/function) to be translated.
         source (str, optional): The source framework. Defaults to 'torch'.
         target (str, optional): The target framework. Defaults to 'torch_frontend'.
         profiling: Whether to add performance profiling.
 
     Returns:
-        The translated object."""
-
+    -------
+    The translated object.
+    """
     from ._compiler import source_to_source as _source_to_source
 
     return _source_to_source(
@@ -54,7 +56,8 @@ def trace_graph(
     params_v=None,
     v=None
 ):
-    """Takes `fn` and traces it into a more efficient composition of backend operations.
+    """Takes `fn` and traces it into a more efficient composition of backend
+    operations.
 
     Parameters
     ----------
@@ -124,8 +127,8 @@ def trace_graph(
     >>> start = time.time()
     >>> graph(x)
     >>> print(time.time() - start)
-    0.0001785755157470703"""
-
+    0.0001785755157470703
+    """
     from ._compiler import trace_graph as _trace_graph
 
     return _trace_graph(
@@ -189,8 +192,8 @@ def transpile(
 
     Returns
     -------
-    Either a transpiled Graph or a non-initialized LazyGraph."""
-
+    Either a transpiled Graph or a non-initialized LazyGraph.
+    """
     from ._compiler import transpile as _transpile
 
     return _transpile(

ivy/functional/frontends/torch/linalg.py

@@ -21,15 +21,15 @@ def cholesky(input, *, upper=False, out=None):
 )
 def cholesky_ex(input, *, upper=False, check_errors=False, out=None):
     try:
-        results = namedtuple("cholesky_ex", ['L', 'info'])
+        results = namedtuple("cholesky_ex", ["L", "info"])
         matrix = ivy.cholesky(input, upper=upper, out=out)
         info = ivy.zeros(input.shape[:-2], dtype=ivy.int32)
         return results(matrix, info)
     except RuntimeError as e:
         if check_errors:
             raise RuntimeError(e) from e
         else:
-            results = namedtuple("cholesky_ex", ['L', 'info'])
+            results = namedtuple("cholesky_ex", ["L", "info"])
             matrix = input * math.nan
             info = ivy.ones(input.shape[:-2], dtype=ivy.int32)
             return results(matrix, info)

ivy/functional/ivy/general.py

@@ -2879,15 +2879,9 @@ def set_item(
     ivy.array([[ 0, -1, 20],
            [10, 10, 10]])
     """
-
     # TODO: we may be able to remove this logic by instead tracing _parse_query as a node in the graph??
-    if (
-        isinstance(query, (list, tuple)) and
-        any([
-            q is Ellipsis or (
-                isinstance(q, slice) and q.stop is None
-            ) for q in query
-        ])
+    if isinstance(query, (list, tuple)) and any(
+        [q is Ellipsis or (isinstance(q, slice) and q.stop is None) for q in query]
     ):
         # use numpy for item setting when an ellipsis or unbounded slice is present,
         # as they would otherwise cause static dim sizes to be traced into the graph