modelverse/performance/utils.py

import unittest
import sys
import os

import sys
import time
import json
import urllib
import urllib2
import subprocess
import signal
import random
import operator

sys.path.append("interface/HUTN")
sys.path.append("scripts")
from hutn_compiler.compiler import main as do_compile
from check_objects import to_recompile

USERNAME = "test_task"
PARALLEL_PUSH = True

BOOTSTRAP_FOLDER_NAME = "bootstrap"
CURRENT_FOLDER_NAME = "performance"

PORTS = set()

OPTIMIZATION_LEVEL_LEGACY_INTERPRETER = "legacy-interpreter"
OPTIMIZATION_LEVEL_INTERPRETER = "interpreter"
OPTIMIZATION_LEVEL_BASELINE_JIT = "baseline-jit"
OPTIMIZATION_LEVEL_BASELINE_JIT_NO_THUNKS = "baseline-jit,no-thunks"
OPTIMIZATION_LEVEL_FAST_JIT = "fast-jit"
OPTIMIZATION_LEVEL_ADAPTIVE_JIT_FAVOR_LARGE_FUNCTIONS = "adaptive-jit-favor-large-functions"
OPTIMIZATION_LEVEL_ADAPTIVE_JIT_FAVOR_SMALL_FUNCTIONS = "adaptive-jit-favor-small-functions"
OPTIMIZATION_LEVEL_ADAPTIVE_JIT_FAVOR_LOOPS = "adaptive-jit-favor-loops"
ALL_OPTIMIZATION_LEVELS = [
    OPTIMIZATION_LEVEL_LEGACY_INTERPRETER,
    OPTIMIZATION_LEVEL_INTERPRETER,
    OPTIMIZATION_LEVEL_BASELINE_JIT,
    OPTIMIZATION_LEVEL_BASELINE_JIT_NO_THUNKS,
    OPTIMIZATION_LEVEL_FAST_JIT,
    OPTIMIZATION_LEVEL_ADAPTIVE_JIT_FAVOR_LARGE_FUNCTIONS,
    OPTIMIZATION_LEVEL_ADAPTIVE_JIT_FAVOR_SMALL_FUNCTIONS,
    OPTIMIZATION_LEVEL_ADAPTIVE_JIT_FAVOR_LOOPS
]

class ModelverseTerminated(Exception):
    """An exception that tells the task that the Modelverse has terminated."""
    pass

def get_code_folder_name():
    """Gets the name of the code folder."""
    return '%s/code' % CURRENT_FOLDER_NAME

def get_free_port():
    """Gets a unique new port."""
    while 1:
        port = random.randint(10000, 20000)
        # Check if this port is in the set of ports.
        if port not in PORTS:
            # We have found a unique port. Add it to the set and return.
            PORTS.add(port)
            return port

def execute(scriptname, parameters=None, wait=False):
    """Runs a script."""
    if os.name not in ["nt", "posix"]:
        # Stop now, as we would have no clue on how to kill its subtree
        raise Exception("Unknown OS version: " + str(os.name))

    command = [sys.executable, "scripts/%s.py" % scriptname] + (
        [] if parameters is None else parameters)

    if wait:
        return subprocess.call(command, shell=False)
    else:
        return subprocess.Popen(command, shell=False)

def kill(process):
    """Kills the given process."""
    if os.name == "nt":
        subprocess.call(["taskkill", "/F", "/T", "/PID", "%i" % process.pid])
    elif os.name == "posix":
        subprocess.call(["pkill", "-P", "%i" % process.pid])

def set_input_data(address, data):
    """Sets the Modelverse program's input data."""
    if data is not None:
        urllib2.urlopen(
            urllib2.Request(
                address,
                urllib.urlencode(
                    {"op": "set_input", "data": json.dumps(data), "taskname": USERNAME})),
            timeout=10).read()
    else:
        return []

def compile_file(address, mod_filename, filename, mode, proc):
    """Compiles the given file."""
    # Load in the file required
    try:
        timeout_val = 240
        taskname = str(random.random())
        while 1:
            proc2 = execute(
                "compile", [address, mod_filename, taskname, filename, mode], wait=False)

            if proc.returncode is not None:
                # Modelverse has already terminated, which isn't a good sign!
                raise Exception("Modelverse died!")

            while proc2.returncode is None:
                time.sleep(0.01)
                proc2.poll()
                timeout_val -= 0.01
                if timeout_val < 0:
                    kill(proc2)
                    print("Compilation timeout expired!")
                    return False

            if proc2.returncode != 2:
                break

        # Make sure everything stopped correctly
        assert proc2.returncode == 0
        if proc2.returncode != 0:
            return False
    except:
        raise
    finally:
        try:
            kill(proc2)
        except UnboundLocalError:
            pass

def run_file(files, parameters, mode, handle_output, optimization_level=None):
    """Compiles the given sequence of files, feeds them the given input in the given mode,
       and handles their output."""
    # Resolve file
    import os.path

    time.sleep(0.01)
    port = get_free_port()
    address = "http://127.0.0.1:%i" % port
    try:
        # Run Modelverse server
        modelverse_args = [str(port)]
        if optimization_level is not None:
            modelverse_args.append('--kernel=%s' % optimization_level)
        proc = execute("run_local_modelverse", modelverse_args, wait=False)

        threads = []
        mod_files = []
        for filename in files:
            if os.path.isfile("%s/%s" % (get_code_folder_name(), filename)):
                mod_filename = "%s/%s" % (get_code_folder_name(), filename)
            elif os.path.isfile("%s/%s" % (BOOTSTRAP_FOLDER_NAME, filename)):
                mod_filename = "%s/%s" % (BOOTSTRAP_FOLDER_NAME, filename)
            else:
                raise Exception("File not found: %s" % filename)
            mod_files.append(mod_filename)

        to_compile = to_recompile(address, mod_files)

        for mod_filename in to_compile:
            if PARALLEL_PUSH:
                import threading
                threads.append(
                    threading.Thread(
                        target=compile_file,
                        args=[address, mod_filename, mod_filename, mode, proc]))
                threads[-1].start()
            else:
                compile_file(address, mod_filename, mod_filename, mode, proc)

        if PARALLEL_PUSH:
            for t in threads:
                t.join()

        if mode[-1] == "O":
            # Fire up the linker
            val = execute("link_and_load", [address, USERNAME] + mod_files, wait=True)
            if val != 0:
                raise Exception("Linking error")

        # Send the request ...
        set_input_data(address, parameters)

        # ... and wait for replies
        while 1:
            val = urllib2.urlopen(
                urllib2.Request(
                    address,
                    urllib.urlencode({"op": "get_output", "taskname": USERNAME})),
                timeout=240).read()
            val = json.loads(val)

            if proc.returncode is not None:
                # Modelverse has terminated. This may or may not be what we want.
                raise ModelverseTerminated()

            if not handle_output(val):
                return

        # All passed!
        return
    except:
        raise
    finally:
        try:
            kill(proc)
        except UnboundLocalError:
            pass

def run_file_to_completion(files, parameters, mode):
    """Compiles the given sequence of files, feeds them the given input in the given mode,
       and then collects and returns output."""
    results = []
    def handle_output(output):
        """Appends the given output to the list of results."""
        results.append(output)
        return True

    try:
        run_file(files, parameters, mode, handle_output)
    except ModelverseTerminated:
        return results

def run_file_fixed_output_count(files, parameters, mode, output_count, optimization_level=None):
    """Compiles the given sequence of files, feeds them the given input in the given mode,
       and then collects and returns a fixed number of outputs."""
    results = []
    def handle_output(output):
        """Appends the given output to the list of results."""
        if len(results) < output_count:
            results.append(output)
            return True
        else:
            return False

    run_file(files, parameters, mode, handle_output, optimization_level)
    return results

def run_file_single_output(files, parameters, mode, optimization_level=None):
    """Compiles the given sequence of files, feeds them the given input in the given mode,
       and then collects and returns a single output."""
    return run_file_fixed_output_count(files, parameters, mode, 1, optimization_level)[0]

def run_perf_test(files, parameters, optimization_level, n_iterations=1):
    """Compiles the given sequence of files, feeds them the given input in the given mode,
       and then collects their output. This process is repeated n_iterations times. The
       return value is the average of all outputs."""
    result = 0.0
    for _ in xrange(n_iterations):
        result += float(
            run_file_single_output(
                files, parameters + [0], 'CO',
                optimization_level)) / float(n_iterations)
    return result

def format_output(output):
    """Formats the output of `run_file_to_completion` as a string."""
    return '\n'.join(output)

def define_perf_test(target_class, test_function, optimization_level):
    """Defines a performance test in the given class. The performance test calls the given function
       at the given optimization level."""
    setattr(
        target_class,
        'test_%s' % optimization_level.replace('-', '_').lower(),
        lambda self: test_function(self, optimization_level))

def define_perf_tests(target_class, test_function):
    """Defines performance tests in the given class. Each test calls the given function."""
    for optimization_level in ALL_OPTIMIZATION_LEVELS:
        define_perf_test(target_class, test_function, optimization_level)

DEFAULT_PERF_FILE_NAME = 'perf_data.txt'

def write_perf_to_file(test_name, optimization_level, result, file_name=DEFAULT_PERF_FILE_NAME):
    """Writes performance data to a file."""
    with open(file_name, "a") as perf_file:
        perf_file.write('%s:%s:%f\n' % (test_name, optimization_level, result))

def parse_perf_data(file_name):
    """Parses the performance data in the given file."""
    results = {}
    with open(file_name, 'r') as perf_file:
        for line in perf_file.readlines():
            test_name, optimization_level, result = line.strip().split(':')
            if optimization_level not in results:
                results[optimization_level] = []
            results[optimization_level].append((test_name, result))
    return sorted(results.items(), key=operator.itemgetter(1))