#!/usr/bin/env python3 import itertools import sys import pytest import numpy as np import pandas as pd def test_multi_agent_support( input_samples_csv: pd.DataFrame, input_kernel_trace_csv: pd.DataFrame, input_agent_info_csv: pd.DataFrame, ): transpose_kernel_source_line_start = 137 transpose_kernel_source_line_end = 145 mi2xx_mi3xx_agents_df = input_agent_info_csv[ input_agent_info_csv["Name"].apply( lambda name: name == "gfx90a" or name.startswith("gfx94") ) ] # Extract samples that originates from know code object it samples_df = input_samples_csv[input_samples_csv["Dispatch_Id"] != 0].copy() # Determine the agent on which sample was generated samples_df["Agent_Id"] = ( samples_df["Dispatch_Id"] .map(input_kernel_trace_csv.set_index("Dispatch_Id")["Agent_Id"]) .astype(np.uint64) ) sampled_agents = samples_df["Agent_Id"].unique() sampled_agents_num = len(sampled_agents) # all agents must be sampled assert sampled_agents_num == len(mi2xx_mi3xx_agents_df) # separate samples per agents grouped_samples_per_agent = samples_df.groupby("Agent_Id") for agent_id, agent_samples_df in grouped_samples_per_agent: sampled_dispatches = agent_samples_df["Dispatch_Id"].unique() # at least 1 sampled dispatch per agent assert len(sampled_dispatches) >= 1 # extract decoded samples that are mapped to the transpose.cpp file transpose_samples_df = samples_df[ samples_df["Instruction_Comment"].apply( lambda comment: "transpose-all-agents.cpp" in comment ) ].copy() # determine the line number for each sample transpose_samples_df["Source_Line_Num"] = transpose_samples_df[ "Instruction_Comment" ].apply(lambda source_line: int(source_line.split(":")[-1])) # assert that line belongs to a kernel range assert ( (transpose_samples_df["Source_Line_Num"] >= transpose_kernel_source_line_start) & (transpose_samples_df["Source_Line_Num"] <= transpose_kernel_source_line_end) ).all() if __name__ == "__main__": exit_code = pytest.main(["-x", __file__] + sys.argv[1:]) sys.exit(exit_code)