General spell check and typo fixing

Co-authored-by: Nick Curtis <nicholas.curtis@amd.com>
Signed-off-by: colramos-amd <colramos@amd.com>

src/utils/file_io.py

@@ -101,7 +101,7 @@ def create_df_kernel_top_stats(
         # NB: support ignoring the 1st n dispatched execution by '> n'
         #     The better way may be parsing python slice string
         if ">" in filter_dispatch_ids[0]:
-            m = re.match("\> (\d+)", filter_dispatch_ids[0])
+            m = re.match(r"\> (\d+)", filter_dispatch_ids[0])
             df = df[df["Dispatch_ID"] > int(m.group(1))]
         else:
             df = df.loc[df["Dispatch_ID"].astype(str).isin(filter_dispatch_ids)]

src/utils/parser.py

@@ -784,7 +784,7 @@ def eval_metric(dfs, dfs_type, sys_info, soc_spec, raw_pmc_df, debug):
                                         print("~" * 40)
                                     except TypeError:
                                         print(
-                                            "skipping entry. Encounterd a missing counter"
+                                            "skipping entry. Encountered a missing counter"
                                         )
                                         print(expr, " has been assigned to None")
                                         print(np.nan)
@@ -794,7 +794,7 @@ def eval_metric(dfs, dfs_type, sys_info, soc_spec, raw_pmc_df, debug):
                                             == "'NoneType' object has no attribute 'get'"
                                         ):
                                             print(
-                                                "skipping entry. Encounterd a missing csv"
+                                                "skipping entry. Encountered a missing csv"
                                             )
                                             print(np.nan)
                                         else:

src/utils/roofline_calc.py

@@ -184,9 +184,9 @@ def calc_ceilings(roofline_parameters, dtype, benchmark_data):
 # -------------------------------------------------------------------------------------
 #                              Overlay application performance
 # -------------------------------------------------------------------------------------
-# Calculate relevent metrics for ai calculation
+# Calculate relevant metrics for ai calculation
 def calc_ai(sort_type, ret_df):
-    """Given counter data, caclulate arithmetic intensity for each kernel in the application.
+    """Given counter data, calculate arithmetic intensity for each kernel in the application.
     """
     df = ret_df["pmc_perf"]
     # Sort by top kernels or top dispatches?