SWDEV-499989: Conversion Script to change counter collection output format from v3 to v1 (#107)
* SWDEV-499989: Add script to convert rocprofv3 counter collection output format to that of v1
* Add logging and argparsing
* Dropping duplicated counters in pmc multiple lines
* Adding test for conversion
* moving conversion script to test files
* copy conversion script from scripts folder
[ROCm/rocprofiler-sdk commit: c77596b703]
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υποβολή
0608bbb4db
+156
@@ -0,0 +1,156 @@
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#!/usr/bin/env python3
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import os
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import pandas as pd
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import argparse
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import logging
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def read_csv(file_path):
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df = pd.DataFrame()
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try:
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df = pd.read_csv(file_path)
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except Exception as e:
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logging.info(f"Error reading {file_path}: {e}")
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raise
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return df
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def get_counter_collection_files(root_path):
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file_paths = []
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for root, _, files in os.walk(root_path):
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if "pmc_" in root:
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for file in files:
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if file.endswith("counter_collection.csv"):
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file_path = os.path.join(root, file)
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file_paths.append(file_path)
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return file_paths
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def get_combined_df(args):
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files_list = []
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for input in args.input:
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if os.path.isfile(input):
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files_list.append(input)
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elif os.path.isdir(input):
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files_list.extend(get_counter_collection_files(input))
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if not files_list:
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raise ValueError("Valid Input files not found")
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logging.info(f"Processing files: {files_list}")
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combined_df = pd.DataFrame()
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for file in files_list:
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combined_df = pd.concat([combined_df, read_csv(file)], ignore_index=True)
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return combined_df
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def write_to_file(df, args):
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logging.info(f"Saving output file to : {args.output}")
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directory, file_path = os.path.split(args.output)
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if directory:
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os.makedirs(directory, exist_ok=True)
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df.to_csv(args.output, index=False)
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def main(args):
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logging.basicConfig(level=args.loglevel)
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input_df = get_combined_df(args)
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# Validate
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columns = [
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"Correlation_Id",
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"Dispatch_Id",
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"Agent_Id",
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"Queue_Id",
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"Process_Id",
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"Thread_Id",
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"Grid_Size",
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"Kernel_Id",
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"Kernel_Name",
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"Workgroup_Size",
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"LDS_Block_Size",
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"Scratch_Size",
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"VGPR_Count",
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"SGPR_Count",
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"Counter_Name",
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"Counter_Value",
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"Start_Timestamp",
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"End_Timestamp",
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]
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for col in input_df.columns:
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if col not in columns:
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logging.debug(f"Unexpected column {col} found in rocprofv3 input file")
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non_index_columns = [
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"Correlation_Id",
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"Start_Timestamp",
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"End_Timestamp",
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"Process_Id",
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"Thread_Id",
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"Kernel_Id",
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]
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# Convert
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indexes = [
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"Dispatch_Id",
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"Agent_Id",
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"Grid_Size",
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"Kernel_Name",
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"LDS_Block_Size",
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"Queue_Id",
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"SGPR_Count",
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"Scratch_Size",
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"VGPR_Count",
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"Workgroup_Size",
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]
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# Drop duplicate counters in multiple PMC lines
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input_df.drop_duplicates(
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subset=indexes + ["Counter_Name"], keep="first", inplace=True
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)
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pivoted_data = input_df.pivot_table(
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index=indexes, columns="Counter_Name", values="Counter_Value", aggfunc="sum"
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).reset_index()
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# Save
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write_to_file(pivoted_data, args)
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def parse_args():
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"-i",
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"--input",
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help="Rocprofv3 Counter Collection input files and/or directories containing `*counter_collection.csv` files",
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nargs="+",
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default=[],
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required=True,
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)
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parser.add_argument(
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"-o",
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"--output",
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help="Rocprofv1 formatted output file name",
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default=None,
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type=str,
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required=True,
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)
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parser.add_argument(
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"-d",
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"--debug",
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help="Debug Logs",
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action="store_const",
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dest="loglevel",
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const=logging.DEBUG,
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default=logging.WARNING,
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)
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parser.add_argument(
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"-v",
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"--verbose",
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help="Verbose Logs",
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action="store_const",
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dest="loglevel",
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const=logging.INFO,
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)
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return parser.parse_args()
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if __name__ == "__main__":
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main(parse_args())
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