Add nvtx annotatations to groupby methods (#12941)

Not sure if not annotating these was an oversight during implementation...

Authors:
  - Lawrence Mitchell (https://github.com/wence-)
  - Ray Douglass (https://github.com/raydouglass)
  - Bradley Dice (https://github.com/bdice)

Approvers:
  - Bradley Dice (https://github.com/bdice)

URL: #12941

python/cudf/cudf/core/groupby/groupby.py

@@ -326,6 +326,7 @@ def groups(self):
             zip(group_names.to_pandas(), grouped_index._split(offsets[1:-1]))
         )
 
+    @_cudf_nvtx_annotate
     def get_group(self, name, obj=None):
         """
         Construct DataFrame from group with provided name.
@@ -363,6 +364,7 @@ def get_group(self, name, obj=None):
 
         return obj.loc[self.groups[name]]
 
+    @_cudf_nvtx_annotate
     def size(self):
         """
         Return the size of each group.
@@ -377,6 +379,7 @@ def size(self):
             .agg("size")
         )
 
+    @_cudf_nvtx_annotate
     def cumcount(self):
         """
         Return the cumulative count of keys in each group.
@@ -392,6 +395,7 @@ def cumcount(self):
             .agg("cumcount")
         )
 
+    @_cudf_nvtx_annotate
     def rank(
         self,
         method="average",
@@ -781,6 +785,7 @@ def tail(self, n: int = 5, *, preserve_order: bool = True):
             n, take_head=False, preserve_order=preserve_order
         )
 
+    @_cudf_nvtx_annotate
     def nth(self, n):
         """
         Return the nth row from each group.
@@ -790,6 +795,7 @@ def nth(self, n):
 
         return result[sizes > n]
 
+    @_cudf_nvtx_annotate
     def ngroup(self, ascending=True):
         """
         Number each group from 0 to the number of groups - 1.
@@ -1086,6 +1092,7 @@ def _normalize_aggs(
         ]
         return column_names, columns, normalized_aggs
 
+    @_cudf_nvtx_annotate
     def pipe(self, func, *args, **kwargs):
         """
         Apply a function `func` with arguments to this GroupBy
@@ -1140,6 +1147,7 @@ def pipe(self, func, *args, **kwargs):
         """
         return cudf.core.common.pipe(self, func, *args, **kwargs)
 
+    @_cudf_nvtx_annotate
     def _jit_groupby_apply(
         self, function, group_names, offsets, group_keys, grouped_values, *args
     ):
@@ -1161,6 +1169,7 @@ def _jit_groupby_apply(
         result[None] = result.pop(0)
         return result
 
+    @_cudf_nvtx_annotate
     def _iterative_groupby_apply(
         self, function, group_names, offsets, group_keys, grouped_values, *args
     ):
@@ -1198,6 +1207,7 @@ def _iterative_groupby_apply(
                 result.index = cudf.MultiIndex._from_data(index_data)
         return result
 
+    @_cudf_nvtx_annotate
     def apply(self, function, *args, engine="cudf"):
         """Apply a python transformation function over the grouped chunk.
 
@@ -1319,6 +1329,7 @@ def mult(df):
             result = result.sort_index()
         return result
 
+    @_cudf_nvtx_annotate
     def apply_grouped(self, function, **kwargs):
         """Apply a transformation function over the grouped chunk.
 
@@ -1457,6 +1468,7 @@ def rolling_avg(val, avg):
         kwargs.update({"chunks": offsets})
         return grouped_values.apply_chunks(function, **kwargs)
 
+    @_cudf_nvtx_annotate
     def _broadcast(self, values):
         """
         Broadcast the results of an aggregation to the group
@@ -1480,6 +1492,7 @@ def _broadcast(self, values):
             values.index = self.obj.index
         return values
 
+    @_cudf_nvtx_annotate
     def transform(self, function):
         """Apply an aggregation, then broadcast the result to the group size.
 
@@ -1534,6 +1547,7 @@ def rolling(self, *args, **kwargs):
         """
         return cudf.core.window.rolling.RollingGroupby(self, *args, **kwargs)
 
+    @_cudf_nvtx_annotate
     def count(self, dropna=True):
         """Compute the number of values in each column.
 
@@ -1548,6 +1562,7 @@ def func(x):
 
         return self.agg(func)
 
+    @_cudf_nvtx_annotate
     def describe(self, include=None, exclude=None):
         """
         Generate descriptive statistics that summarizes the central tendency,
@@ -1619,6 +1634,7 @@ def describe(self, include=None, exclude=None):
         )
         return res
 
+    @_cudf_nvtx_annotate
     def corr(self, method="pearson", min_periods=1):
         """
         Compute pairwise correlation of columns, excluding NA/null values.
@@ -1680,6 +1696,7 @@ def corr(self, method="pearson", min_periods=1):
             lambda x: x.corr(method, min_periods), "Correlation"
         )
 
+    @_cudf_nvtx_annotate
     def cov(self, min_periods=0, ddof=1):
         """
         Compute the pairwise covariance among the columns of a DataFrame,
@@ -1854,6 +1871,7 @@ def _cov_or_corr(self, func, method_name):
 
         return res
 
+    @_cudf_nvtx_annotate
     def var(self, ddof=1):
         """Compute the column-wise variance of the values in each group.
 
@@ -1869,6 +1887,7 @@ def func(x):
 
         return self.agg(func)
 
+    @_cudf_nvtx_annotate
     def std(self, ddof=1):
         """Compute the column-wise std of the values in each group.
 
@@ -1884,6 +1903,7 @@ def func(x):
 
         return self.agg(func)
 
+    @_cudf_nvtx_annotate
     def quantile(self, q=0.5, interpolation="linear"):
         """Compute the column-wise quantiles of the values in each group.
 
@@ -1901,14 +1921,17 @@ def func(x):
 
         return self.agg(func)
 
+    @_cudf_nvtx_annotate
     def collect(self):
         """Get a list of all the values for each column in each group."""
         return self.agg("collect")
 
+    @_cudf_nvtx_annotate
     def unique(self):
         """Get a list of the unique values for each column in each group."""
         return self.agg("unique")
 
+    @_cudf_nvtx_annotate
     def diff(self, periods=1, axis=0):
         """Get the difference between the values in each group.
 
@@ -1945,6 +1968,7 @@ def _scan_fill(self, method: str, limit: int) -> DataFrameOrSeries:
         result = self._mimic_pandas_order(result)
         return result._copy_type_metadata(values)
 
+    @_cudf_nvtx_annotate
     def pad(self, limit=None):
         """Forward fill NA values.
 
@@ -1981,6 +2005,7 @@ def ffill(self, limit=None):
 
         return self._scan_fill("ffill", limit)
 
+    @_cudf_nvtx_annotate
     def backfill(self, limit=None):
         """Backward fill NA values.
 
@@ -2015,6 +2040,7 @@ def bfill(self, limit=None):
 
         return self._scan_fill("bfill", limit)
 
+    @_cudf_nvtx_annotate
     def fillna(
         self,
         value=None,
@@ -2078,6 +2104,7 @@ def fillna(
             value=value, inplace=inplace, axis=axis, limit=limit
         )
 
+    @_cudf_nvtx_annotate
     def shift(self, periods=1, freq=None, axis=0, fill_value=None):
         """
         Shift each group by ``periods`` positions.
@@ -2133,6 +2160,7 @@ def shift(self, periods=1, freq=None, axis=0, fill_value=None):
         result = self._mimic_pandas_order(result)
         return result._copy_type_metadata(values)
 
+    @_cudf_nvtx_annotate
     def pct_change(
         self, periods=1, fill_method="ffill", axis=0, limit=None, freq=None
     ):