update for ci

apache · Aug 21, 2024 · d9ccd83 · d9ccd83
1 parent ae02e4e
commit d9ccd83
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Showing 4 changed files with 13 additions and 39 deletions.
diff --git a/docs/reference/api/python/ndarray.rst b/docs/reference/api/python/ndarray.rst
diff --git a/docs/reference/api/python/runtime/runtime.rst b/docs/reference/api/python/runtime/runtime.rst
@@ -19,5 +19,4 @@ tvm.runtime
 -----------
 .. automodule:: tvm.runtime
    :members:
-   :imported-members:
    :exclude-members: NDArray
diff --git a/python/tvm/relax/transform/transform.py b/python/tvm/relax/transform/transform.py
@@ -391,8 +391,8 @@ def ConvertToDataflow(min_size: int = 2) -> tvm.ir.transform.Pass:
 
     Note: ConvertToDataflow may need to be called first.
 
-    Params
-    ------
+    Parameters
+    ----------
     min_size: int
         The minimum number of consecutive dataflow bindings
         the pass needs to extract a new block.
@@ -647,13 +647,8 @@ def BindParams(
     func_name: str
         The function name to be bound
 
-    params : Dict[
-                Union[str,relax.Var],
-                Union[tvm.runtime.NDArray, np.ndarray],
-             ]
-
-        The map from parameter or parameter name to constant
-        tensors.
+    params: Dict[Union[str,relax.Var], Union[tvm.runtime.NDArray, np.ndarray]]
+        The map from parameter or parameter name to constant tensors.
 
     Returns
     -------
@@ -994,16 +989,16 @@ def LiftTransformParams(shared_transform: Union[bool, List[str]] = False) -> tvm
         Indicates how the parameter transformation function will be produced
 
         - `False` (default): A separate parameter transformation function will be
-        produced for each function with the `"num_input"` attribute.
+          produced for each function with the `"num_input"` attribute.
 
         - `True`: A single parameter transformation function will be produced,
-        containing the preprocessing steps common across all functions with
-        the `"num_input"` attribute.
+          containing the preprocessing steps common across all functions with
+          the `"num_input"` attribute.
 
         - List[str]: A single parameter transformation function will be produced,
-        containing the preprocessing steps common across each function whose
-        name is in the list.  Passing a list of all functions with the `"num_input"`
-        attribute or an empty list is equivalent to passing `True`.
+          containing the preprocessing steps common across each function whose
+          name is in the list.  Passing a list of all functions with the `"num_input"`
+          attribute or an empty list is equivalent to passing `True`.
 
     Returns
     -------
@@ -1219,7 +1214,7 @@ def MetaScheduleTuneIRMod(
        maximum number of trials per task
     op_names: Optional[List[str]]
        A list of operator names to specify which op to tune. When it is None, all operators
-        are tuned.
+       are tuned.
 
     Returns
     -------

diff --git a/python/tvm/runtime/profiling/__init__.py b/python/tvm/runtime/profiling/__init__.py
@@ -230,6 +230,7 @@ def profile_function(mod, dev, collectors, func_name=None, warmup_iters=10):
     -------
 
     .. code-block: python
+
         f = tvm.build(my_func, target="llvm", name="my_func")
         prof = tvm.runtime.profiling.profile_function(
             f,
@@ -247,7 +248,7 @@ def profile_function(mod, dev, collectors, func_name=None, warmup_iters=10):
         Device to run the function on.
 
     collectors: List[MetricCollector]
-        :py:class:`MetricCollector`s which will collect performance information.
+        :py:class:`MetricCollector` which will collect performance information.
     func_name: Optional[str]
         Name of the function in `mod` to profile. Defaults to the `entry_name` of `mod`.
     warmup_iters: int