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Unified configuration for metrics (#726)

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* Show description of metrics during analysis
    * Use --include-cols Description show the Description column in analyze mode (this is hidden by default)
    * Remove tips field from analysis config

* Align metric names in analysis config and documentation

* Add unified config utils/unified_config.yaml

* Add python script utils/split_config.py to auto generate analysis configuration and documentation metrics description
   * Add test case to ensure unified config is older than auto-generated config
   * Auto generate analysis config and documentation metrics description

* Update CONTRIBUTING.md to add instructions to build documentation assets
    * Add docker image and compose file to build documentation

* Update CHANGELOG and Documentation

* Use jinja template instead of hardcoding metric tables in documentation

[ROCm/rocprofiler-compute commit: bb44e90b2d]
This commit is contained in:
vedithal-amd
2025-07-25 14:01:34 -04:00
committed by GitHub
parent dcdadfd37d
commit 354fe5f52c
232 changed files with 44409 additions and 22480 deletions
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projects/rocprofiler-compute/src/utils/tty.py
+26 -7
View File
@@ -23,6 +23,7 @@
##############################################################################el
import copy
import textwrap
from pathlib import Path
import pandas as pd
@@ -51,8 +52,21 @@ def string_multiple_lines(source, width, max_rows):
def get_table_string(df, transpose=False, decimal=2):
"""
Convert DataFrame to a formatted table string, wrapping specified columns.
"""
df_to_show = df.transpose() if transpose else df
wrap_columns = ["Description"]
wrap_width = 40
for col in wrap_columns:
if col in df_to_show.columns:
df_to_show[col] = (
df_to_show[col]
.astype(str)
.apply(lambda x: textwrap.fill(x, width=wrap_width))
)
return tabulate(
df.transpose() if transpose else df,
df_to_show,
headers="keys",
tablefmt="fancy_grid",
floatfmt="." + str(decimal) + "f",
@@ -118,6 +132,10 @@ def show_all(args, runs, archConfigs, output, profiling_config, roof_plot=None):
int(convert_metric_id_to_panel_info(metric_id)[0])
for metric_id in filter_panel_ids
]
if args.include_cols:
hidden_cols = list(set(config.HIDDEN_COLUMNS_CLI) - set(args.include_cols))
else:
hidden_cols = config.HIDDEN_COLUMNS_CLI
for panel_id, panel in archConfigs.panel_configs.items():
# Skip panels that don't support baseline comparison
@@ -196,12 +214,14 @@ def show_all(args, runs, archConfigs, output, profiling_config, roof_plot=None):
df = pd.DataFrame(index=base_df.index)
for header in list(base_df.keys()):
# For raw csv table, columns cannot be filtered
# If columns are filtered, then skip the headers not in filtered columns
if (
(not args.cols)
or (args.cols and base_df.columns.get_loc(header) in args.cols)
or (type == "raw_csv_table")
type == "raw_csv_table"
or not args.cols
or base_df.columns.get_loc(header) in args.cols
):
if header in config.HIDDEN_COLUMNS:
if header in hidden_cols:
pass
elif header not in comparable_columns:
if (
@@ -236,8 +256,7 @@ def show_all(args, runs, archConfigs, output, profiling_config, roof_plot=None):
cur_df = convert_time_columns(cur_df, args.time_unit)
if (type == "raw_csv_table") or (
type == "metric_table"
and (not header in config.HIDDEN_COLUMNS)
type == "metric_table" and (not header in hidden_cols)
):
if run != base_run:
# calc percentage over the baseline