#!/usr/bin/env python3

import json
import argparse
import os
from sys import argv as sysargs
from sys import version_info as python_version
from sys import exit as sys_exit
import pandas as pd
from datetime import datetime
import venv
import shutil

if (python_version[0] < 3) or (python_version[0] < 3
                               and python_version[1] < 6):
    raise Exception("Please utilize Python version 3.6 and above. Exiting...")


def parse_args():
    parser = argparse.ArgumentParser(
        description="Parser for MIGraphX ROCTX Markers")
    parser.add_argument('--json-path',
                        type=str,
                        metavar='json-path',
                        help='Path to json file')
    parser.add_argument('--out',
                        type=str,
                        metavar='out',
                        help='Output directory for run.')
    parser.add_argument(
        '--study-name',
        type=str,
        metavar='study-name',
        help='Study-name is used for naming the output CSV file.')
    parser.add_argument('--repeat',
                        type=int,
                        metavar='repeat',
                        help='Defines number of runs.',
                        default=2)
    parser.add_argument('--parse',
                        default=False,
                        action='store_true',
                        help='Parses given JSON file.')
    parser.add_argument('--clean',
                        default=False,
                        action='store_true',
                        help='Removes temporary paths')
    parser.add_argument('--run',
                        type=str,
                        metavar='run',
                        help='Enables run and fetches run configs.')
    parser.add_argument('--debug', default=False, action='store_true')

    args = parser.parse_args()
    return args


args = parse_args()
if not len(sysargs) > 1:
    raise Exception("No arg is passed. Exiting...")


def parse(file):
    with open(file, "r") as read_file:
        data = json.load(read_file)

    #Get marker names and first marker's time
    list_names = []
    first_marker = True
    first_marker_time = 0
    for i in data:
        if (i):
            if ("Marker start:" in i['name']) and (
                    i['name'] not in list_names):
                list_names.append(i['name'])
                if first_marker:
                    first_marker_time = i['ts']
                    first_marker = False

    if (args.debug):
        print(f"FIRST MARKER TIME DETERMINED: {first_marker_time}")

    if (first_marker_time == 0):
        raise ("FIRST MARKER TIME IS ZERO. EXITING...")

    kernel_launch_info = []  #kernel description
    kernel_launch_list = []  #kernel launch details
    kernel_launch_time = []  #kernel execution time
    for i in data:
        if (i and i.get('args')):
            try:
                if (("KernelExecution" in i['args']['desc'])
                        and (i['ts'] >= first_marker_time)):
                    kernel_launch_info.append(i['args']['desc'])
                    kernel_launch_list.append(i)
                    kernel_launch_time.append(int(i['dur']))
            except:
                continue

    max_index = kernel_launch_time.index(max(kernel_launch_time))
    max_kernel_info = kernel_launch_list[max_index]

    if (args.debug):
        with open('rocTX_kernel_launch_list.txt', 'w') as f:
            for i in kernel_launch_list:
                f.write(f'{i}')

    # Get timing information for each marker name
    list_times_per_names = []
    for name in list_names:
        temp_list = []
        for entry in data:
            if (entry) and (
                    name == entry['name']
            ):  # name can match on gpu or cpu side, for gpu, we need data from gpu markers.
                if (("gpu::" in name)
                        and ("UserMarker frame:" in entry['args']['desc'])
                    ):  #gpu side information
                    temp_list.append(int(entry.get('dur')))
                elif (("gpu::" not in name)
                      and ("Marker start:" in entry['args']['desc'])
                      ):  #cpu side information
                    temp_list.append(int(entry.get('dur')))
        list_times_per_names.append(temp_list)

    if (args.debug):
        print(list_times_per_names)

    sum_per_name = []  #TODO: refactor stat collection
    for list in list_times_per_names:
        sum_per_name.append(sum(list))

    count_per_name = []
    for list in list_times_per_names:
        try:
            count_per_name.append(len(list))
        except:
            count_per_name.append(0)

    max_per_name = []
    for list in list_times_per_names:
        try:
            max_per_name.append(max(list))
        except:
            max_per_name.append(0)

    min_per_name = []
    for list in list_times_per_names:
        try:
            min_per_name.append(min(list))
        except:
            min_per_name.append(0)

    max_index_per_name = []
    for list in list_times_per_names:
        try:
            max_index_per_name.append(list.index(max(list)))
        except:
            max_index_per_name.append(0)

    max_occur_per_name = []
    for list in list_times_per_names:
        try:
            max_occur_per_name.append(list.count(max(list)))
        except:
            max_occur_per_name.append(0)

    total_time = sum(sum_per_name)

    d = {
        'SUM': sum_per_name,
        'MIN': min_per_name,
        'MAX': max_per_name,
        'COUNT': count_per_name,
        'MAX_INDEX': max_index_per_name,
        'MAX_OCCUR': max_occur_per_name
    }
    df2 = pd.DataFrame(d)
    df2.index = list_names
    df2.sort_values(by=['SUM'], inplace=True, ascending=False)

    if (args.debug):
        print(df2)
        print(f"\nTOTAL TIME: {total_time} us")
    return df2, total_time, max_kernel_info


def run():
    repeat_count = args.repeat
    if (repeat_count == 0 or repeat_count == float('inf') or not repeat_count):
        raise Exception("REPEAT COUNT CANNOT BE ZERO/INFINITY/NULL")
    run_args = args.run
    #configurations
    configs = '--hip-trace --roctx-trace --flush-rate 10ms --timestamp on'
    output_dir = f"-d {args.out}"
    executable = f"/opt/rocm/bin/migraphx-driver roctx {run_args}"
    process_args = configs + ' ' + output_dir + ' ' + executable
    for i in range(repeat_count):
        os.system('rocprof ' + process_args)
    print("RUN COMPLETE.")


def clean():
    shutil.rmtree('/tmp/rocm-profile-data/', ignore_errors=False)


def main():

    if (args.clean):
        clean()
        sys_exit()

    print("Initiating virtual environment...")
    builder = venv.EnvBuilder(clear=True, with_pip=True)
    builder.create('/tmp/rocm-profile-data/py/')
    python_bin = '/tmp/rocm-profile-data/py' + '/bin/python'
    file = args.json_path

    if (args.study_name):
        filename = args.study_name + ".csv"
    else:
        filename = "output" + datetime.now().strftime(
            "%Y_%m_%d-%I:%M:%S_%p") + ".csv"

    with open(filename, 'a') as f:
        f.write(f"{args.run}\n")

    if (args.run):
        curr = os.path.abspath(os.getcwd())
        rpd_path = '/tmp/rocm-profile-data/rocmProfileData/'
        if not os.path.exists(rpd_path):
            print("rocmProfileData DOES NOT EXIST. CLONING...")
            os.system(
                f"git clone https://github.com/ROCmSoftwarePlatform/rocmProfileData.git {rpd_path}"
            )
        os.chdir(rpd_path + "rocpd_python/")
        os.system(python_bin + ' -m pip install --upgrade pip')
        os.system(python_bin + ' setup.py install')
        os.chdir(curr)
        run()
        os.chdir(curr + f"/{args.out}/")
        out_path = os.popen(f"ls -td $PWD/*/*/ | head -{args.repeat}").read()
        print(f"\nFOLLOWING PATHS WILL BE PARSED:\n{out_path}")
        out_path = out_path.splitlines()
        df_tot = pd.DataFrame()
        tot_time = []
        max_kernel_info_list = []
        for path in out_path:
            path = path.strip('\n')
            print("\nPARSING OUTPUT PATH: " + path)
            os.chdir(path)
            os.system(
                f"{python_bin} -m rocpd.rocprofiler_import --ops_input_file hcc_ops_trace.txt --api_input_file hip_api_trace.txt --roctx_input_file roctx_trace.txt trace.rpd"
            )
            os.system(
                f"{python_bin} {rpd_path}/rpd2tracing.py trace.rpd trace.json")
            os.chdir(curr)
            df, total_time, path_max_kernel_info = parse(path + "trace.json")
            max_kernel_info_list.append(path_max_kernel_info)
            tot_time.append(total_time)
            df_tot = pd.merge(df_tot,
                              df,
                              how='outer',
                              left_index=True,
                              right_index=True)
            if (args.debug):
                print("JSON FILE PATH: " + path + "trace.json")

        df_tot.to_csv("rocTX_runs_dataframe.csv")
        if (args.debug):
            print(df_tot)

        tmp_sum = df_tot.loc[:, df_tot.columns.str.contains('SUM')].astype(int)
        tmp_min = df_tot.loc[:, df_tot.columns.str.contains('MIN')].astype(int)
        tmp_max = df_tot.loc[:, df_tot.columns.str.match("^MAX_.$")].astype(
            int)
        tmp_count = df_tot.loc[:, df_tot.columns.str.match("COUNT")].astype(
            int)

        tmp_sum['SUM_avg'] = tmp_sum.mean(axis=1).astype(int)
        tmp_min['MIN_avg'] = tmp_min.mean(axis=1).astype(int)
        tmp_max['MAX_avg'] = tmp_max.mean(axis=1).astype(int)

        df2 = tmp_sum['SUM_avg'].copy()
        df2 = pd.merge(df2,
                       tmp_min['MIN_avg'],
                       how='outer',
                       left_index=True,
                       right_index=True)
        df2 = pd.merge(df2,
                       tmp_max['MAX_avg'],
                       how='outer',
                       left_index=True,
                       right_index=True)
        df2 = pd.merge(df2,
                       tmp_count['COUNT_x'],
                       how='outer',
                       left_index=True,
                       right_index=True)
        df2.rename(columns={'COUNT_x': 'COUNT'}, inplace=True)
        df2 = df2.loc[:, ~df2.columns.duplicated(
        )]  #there will be many COUNT_x in df2
        df2.sort_values(by=['SUM_avg'], inplace=True, ascending=False)

        if (args.debug):
            pd.set_option('display.max_columns', None)
            print(df_tot)  #all data from all runs

        print("\n*** RESULTS ***")
        print(df2)
        out_time = sum(tot_time) / len(tot_time)
        print(f"\nAVG TOTAL TIME: {out_time} us\n")

        df2.to_csv(filename, mode='a')
        with open(filename, 'a') as f:
            f.write(f"AVG TOTAL TIME: {out_time} us\n")
        print(f"OUTPUT CSV FILE:\t{filename}")

        if (args.debug):
            #kernels that took the longest time printed
            for item in max_kernel_info_list:
                print(f"KERNEL NAME: {item['name']}\t\t{item['dur']}")

        with open('rocTX_kernel_timing_details.txt', 'w') as f:
            f.write(
                "MOST TIME CONSUMING KERNELS IN EACH ITERATION (EXPECTED TO BE SAME KERNEL):\n"
            )
            for i in max_kernel_info_list:
                f.write(f"KERNEL NAME: {i['name']}\t\t{i['dur']}\n")
        print("KERNEL TIMING DETAILS:\trocTX_kernel_timing_details.txt")
        print("ALL DATA FROM ALL RUNS:\trocTX_runs_dataframe.csv")

    elif (args.parse):
        if not (file):
            raise Exception("JSON PATH IS NOT PROVIDED FOR PARSING.")
        parse(file)
    else:
        raise Exception("PLEASE PROVIDE A COMMAND: RUN, PARSE, CLEAN")


if __name__ == "__main__":
    main()