Pownie/backgammon
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Merge branch 'master' into 'experimentation'

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# Conflicts:
#   main.py
This commit is contained in:
Christoffer Müller Madsen 2018-05-22 13:11:43 +00:00
commit 1fd6c35baa
1 changed files with 12 additions and 4 deletions
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16
main.py
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@ -2,6 +2,7 @@ import argparse
import sys import sys
import os import os
import time import time
import subprocess
# Parse command line arguments # Parse command line arguments
parser = argparse.ArgumentParser(description="Backgammon games") parser = argparse.ArgumentParser(description="Backgammon games")
@ -79,16 +80,18 @@ if not os.path.isdir(log_path):
# Define helper functions # Define helper functions
def log_train_outcome(outcome, diff_in_values, trained_eps = 0, log_path = os.path.join(model_path(), 'logs', "train.log")): def log_train_outcome(outcome, diff_in_values, trained_eps = 0, log_path = os.path.join(model_path(), 'logs', "train.log")):
commit = subprocess.run(['git', 'describe', '--first-parent', '--always'], stdout=subprocess.PIPE).stdout.decode('utf-8').rstrip()
format_vars = { 'trained_eps': trained_eps, format_vars = { 'trained_eps': trained_eps,
'count': len(outcome), 'count': len(outcome),
'sum': sum(outcome), 'sum': sum(outcome),
'mean': sum(outcome) / len(outcome), 'mean': sum(outcome) / len(outcome),
'time': int(time.time()), 'time': int(time.time()),
'average_diff_in_vals': diff_in_values 'average_diff_in_vals': diff_in_values
'commit': commit
} }
with open(log_path, 'a+') as f: with open(log_path, 'a+') as f:
f.write("{time};{trained_eps};{count};{sum};{mean};{average_diff_in_vals}".format(**format_vars) + "\n") f.write("{time};{trained_eps};{count};{sum};{mean};{average_diff_in_vals};{commit}".format(**format_vars) + "\n")
def log_eval_outcomes(outcomes, trained_eps = 0, log_path = os.path.join(model_path(), 'logs', "eval.log")): def log_eval_outcomes(outcomes, trained_eps = 0, log_path = os.path.join(model_path(), 'logs', "eval.log")):
@ -99,9 +102,12 @@ def log_eval_outcomes(outcomes, trained_eps = 0, log_path = os.path.join(model_p
:param log_path: :param log_path:
:return: :return:
""" """
commit = subprocess.run(['git', 'describe', '--first-parent', '--always'], stdout=subprocess.PIPE).stdout.decode('utf-8').rstrip()
for outcome in outcomes: for outcome in outcomes:
scores = outcome[1] scores = outcome[1]
format_vars = { 'trained_eps': trained_eps, format_vars = { 'commit': commit,
'trained_eps': trained_eps,
'method': outcome[0], 'method': outcome[0],
'count': len(scores), 'count': len(scores),
'sum': sum(scores), 'sum': sum(scores),
@ -109,9 +115,10 @@ def log_eval_outcomes(outcomes, trained_eps = 0, log_path = os.path.join(model_p
'time': int(time.time()) 'time': int(time.time())
} }
with open(log_path, 'a+') as f: with open(log_path, 'a+') as f:
f.write("{time};{method};{trained_eps};{count};{sum};{mean}".format(**format_vars) + "\n") f.write("{time};{method};{trained_eps};{count};{sum};{mean};{commit}".format(**format_vars) + "\n")
def log_bench_eval_outcomes(outcomes, log_path, index, time, trained_eps = 0): def log_bench_eval_outcomes(outcomes, log_path, index, time, trained_eps = 0):
commit = subprocess.run(['git', 'describe', '--first-parent', '--always'], stdout=subprocess.PIPE).stdout.decode('utf-8').rstrip()
for outcome in outcomes: for outcome in outcomes:
scores = outcome[1] scores = outcome[1]
format_vars = { 'trained_eps': trained_eps, format_vars = { 'trained_eps': trained_eps,
@ -121,9 +128,10 @@ def log_bench_eval_outcomes(outcomes, log_path, index, time, trained_eps = 0):
'mean': sum(scores) / len(scores), 'mean': sum(scores) / len(scores),
'time': time, 'time': time,
'index': index, 'index': index,
'commit': commit
} }
with open(log_path, 'a+') as f: with open(log_path, 'a+') as f:
f.write("{method};{count};{index};{time};{sum};{mean}".format(**format_vars) + "\n") f.write("{method};{count};{index};{time};{sum};{mean};{commit}".format(**format_vars) + "\n")
def find_board_rep(): def find_board_rep():
checkpoint_path = os.path.join(config['model_storage_path'], config['model']) checkpoint_path = os.path.join(config['model_storage_path'], config['model'])