def __init__(self, freq=None, first=0, tag='', log_to_file=None, rank=None, gen_heartbeat=False, num_epochs=300,
test_freq=None, test_first=0):
'''
Constructor.
'''
if freq is None:
freq = sys.maxsize
if test_freq is None:
test_freq = sys.maxsize
super(ProgressPrinter, self).__init__(freq, first, test_freq, test_first)
self.loss_since_start = 0
self.metric_since_start = 0
self.samples_since_start = 0
self.updates_since_start = 0
self.loss_since_last = 0
self.metric_since_last = 0
self.samples_since_last = 0
self.total_updates = 0
self.epochs = 0
self.freq = freq
self.first = first
self.test_freq = test_freq
self.tag = '' if not tag else "[{}] ".format(tag)
self.epoch_start_time = time.time()
self.progress_timer_time = 0
self.log_to_file = log_to_file
self.gen_heartbeat = gen_heartbeat
self.num_epochs = num_epochs
# print out data about CNTK build
cntk_py.print_built_info()
self.logfilename = None
if self.log_to_file is not None:
self.logfilename = self.log_to_file
if rank is not None:
self.logfilename = self.logfilename + 'rank' + str(rank)
# print to stdout
print("Redirecting log to file " + self.logfilename)
with open(self.logfilename, "w") as logfile:
logfile.write(self.logfilename + "\n")
self.___logprint('CNTKCommandTrainInfo: train : ' + str(num_epochs))
self.___logprint('CNTKCommandTrainInfo: CNTKNoMoreCommands_Total : ' + str(num_epochs))
self.___logprint('CNTKCommandTrainBegin: train')
if freq == 0:
self.___logprint(' average since average since examples')
self.___logprint(' loss last metric last ')
self.___logprint(' ------------------------------------------------------')
def __init__(self,
freq=None,
first=0,
tag='',
log_to_file=None,
rank=None,
gen_heartbeat=False,
num_epochs=300,
test_freq=None,
test_first=0):
'''
Constructor.
Args:
freq (`int` or `None`, default `None`): determines how often
printing will occur. The value of 0 means an geometric
schedule (1,2,4,...). A value > 0 means a arithmetic schedule
(a log print for minibatch number: ``freq``, a log print for minibatch number: 2*``freq``,
a log print for minibatch number: 3*``freq``,...), and a value of None means no per-minibatch log.
first (`int`, default 0): Only start logging after the minibatch number is greater or equal to ``first``.
tag (`string`, default EmptyString): prepend minibatch log lines with your own string
log_to_file (`string` or `None`, default `None`): if None, output log data to stdout.
If a string is passed, the string is path to a file for log data.
rank (`int` or `None`, default `None`): set this to distributed.rank if you are using distributed
parallelism -- each rank's log will go to separate file.
gen_heartbeat (`bool`, default `False`): If True output a progress message every 10 seconds or so to stdout.
num_epochs (`int`, default 300): The total number of epochs to be trained. Used for some metadata.
This parameter is optional.
test_freq (`int` or `None`, default `None`): similar to ``freq``, but applies to printing intermediate
test results.
test_first (`int`, default 0): similar to ``first``, but applies to printing intermediate test results.
'''
if freq is None:
freq = sys.maxsize
if test_freq is None:
test_freq = sys.maxsize
super(ProgressPrinter, self).__init__(freq, first, test_freq,
test_first)
self.loss_since_start = 0
self.metric_since_start = 0
self.samples_since_start = 0
self.updates_since_start = 0
self.loss_since_last = 0
self.metric_since_last = 0
self.samples_since_last = 0
self.total_updates = 0
self.epochs = 0
self.freq = freq
self.first = first
self.test_freq = test_freq
self.tag = '' if not tag else "[{}] ".format(tag)
self.epoch_start_time = time.time()
self.progress_timer_time = 0
self.log_to_file = log_to_file
self.gen_heartbeat = gen_heartbeat
self.num_epochs = num_epochs
# print out data about CNTK build
cntk_py.print_built_info()
self.logfilename = None
if self.log_to_file is not None:
self.logfilename = self.log_to_file
if rank is not None:
self.logfilename = self.logfilename + 'rank' + str(rank)
# print to stdout
print("Redirecting log to file " + self.logfilename)
with open(self.logfilename, "w") as logfile:
logfile.write(self.logfilename + "\n")
self.___logprint('CNTKCommandTrainInfo: train : ' +
str(num_epochs))
self.___logprint(
'CNTKCommandTrainInfo: CNTKNoMoreCommands_Total : ' +
str(num_epochs))
self.___logprint('CNTKCommandTrainBegin: train')
if freq == 0:
self.___logprint(
' average since average since examples')
self.___logprint(
' loss last metric last ')
self.___logprint(
' ------------------------------------------------------')
def __init__(self, freq=None, first=0, tag='', log_to_file=None, rank=None, gen_heartbeat=False, num_epochs=None,
test_freq=None, test_first=0, metric_is_pct=True, distributed_freq=None, distributed_first=0):
'''
Constructor.
'''
if freq is None:
freq = sys.maxsize
if test_freq is None:
test_freq = sys.maxsize
if distributed_freq is None:
distributed_freq = sys.maxsize
super(ProgressPrinter, self).__init__(freq, first, test_freq, test_first, distributed_freq, distributed_first)
self.loss_since_start = 0
self.metric_since_start = 0
self.samples_since_start = 0
self.updates_since_start = 0
self.loss_since_last = 0
self.metric_since_last = 0
self.samples_since_last = 0
self.total_updates = 0
self.epochs = 0
self.freq = freq
self.first = first
self.test_freq = test_freq
self.tag = '' if not tag else "[{}] ".format(tag)
self.epoch_start_time = time.time()
self.progress_timer_time = 0
self.log_to_file = log_to_file
self.gen_heartbeat = gen_heartbeat
self.num_epochs = num_epochs
self.metric_is_pct = metric_is_pct
if metric_is_pct:
self.metric_multiplier = 100.0
else:
self.metric_multiplier = 1.0
self.__disown__()
# print out data about CNTK build
# TODO: this is for internal purposes, so find better way
cntk_py.print_built_info()
self.logfilename = None
if self.log_to_file is not None:
self.logfilename = self.log_to_file
if rank is not None:
self.logfilename = self.logfilename + 'rank' + str(rank)
# print to stdout
print("Redirecting log to file " + self.logfilename)
with open(self.logfilename, "w") as logfile:
logfile.write(self.logfilename + "\n")
self.___logprint('CNTKCommandTrainInfo: train : ' + str(num_epochs if num_epochs is not None else 300))
self.___logprint('CNTKCommandTrainInfo: CNTKNoMoreCommands_Total : ' + str(num_epochs if num_epochs is not None else 300))
self.___logprint('CNTKCommandTrainBegin: train')
if freq == 0:
self.___logprint(' average since average since examples')
self.___logprint(' loss last metric last ')
self.___logprint(' ------------------------------------------------------')
def __init__(self,
freq=None,
first=0,
tag='',
log_to_file=None,
rank=None,
gen_heartbeat=False,
num_epochs=300,
tensorboard_log_dir=None,
model=None):
'''
Constructor. The optional ``freq`` parameter determines how often
printing will occur. The value of 0 means an geometric
schedule (1,2,4,...). A value > 0 means a arithmetic schedule
(freq, 2*freq, 3*freq,...), and a value of None means no per-minibatch log.
set log_to_file if you want the output to go file instead of stdout.
set rank to distributed.rank if you are using distibuted parallelism -- each rank's log will go to seperate file.
'''
from sys import maxsize
if freq is None:
freq = maxsize
self.loss_since_start = 0
self.metric_since_start = 0
self.samples_since_start = 0
self.updates_since_start = 0
self.loss_since_last = 0
self.metric_since_last = 0
self.samples_since_last = 0
self.total_updates = 0
self.epochs = 0
self.freq = freq
self.first = first
self.tag = '' if not tag else "[{}] ".format(tag)
self.epoch_start_time = time.time()
self.progress_timer_time = 0
self.log_to_file = log_to_file
self.rank = rank
self.gen_heartbeat = gen_heartbeat
self.num_epochs = num_epochs
self.trainer = None
# print out data about CNTK build
print_built_info()
# Create TensorBoardFileWriter if the path to a log directory was provided.
self.tensorboard_writer = None
if tensorboard_log_dir is not None:
tb_run_name = tag.lower() if tag else ''
if self.rank is not None:
tb_run_name += 'rank' + str(self.rank)
if tb_run_name:
tensorboard_log_dir = os.path.join(tensorboard_log_dir,
tb_run_name)
self.tensorboard_writer = TensorBoardFileWriter(
tensorboard_log_dir, model)
self.logfilename = None
if self.log_to_file is not None:
self.logfilename = self.log_to_file
if self.rank != None:
self.logfilename = self.logfilename + 'rank' + str(self.rank)
# print to stdout
print("Redirecting log to file " + self.logfilename)
with open(self.logfilename, "w") as logfile:
logfile.write(self.logfilename + "\n")
self.___logprint('CNTKCommandTrainInfo: train : ' +
str(num_epochs))
self.___logprint(
'CNTKCommandTrainInfo: CNTKNoMoreCommands_Total : ' +
str(num_epochs))
self.___logprint('CNTKCommandTrainBegin: train')
if freq == 0:
self.___logprint(
' average since average since examples')
self.___logprint(
' loss last metric last ')
self.___logprint(
' ------------------------------------------------------')
def __init__(self, freq=None, first=0, tag='', log_to_file=None, rank=None, gen_heartbeat=False, num_epochs=300,
test_freq=None, test_first=0):
'''
Constructor.
Args:
freq (`int` or `None`, default `None`): determines how often
printing will occur. The value of 0 means an geometric
schedule (1,2,4,...). A value > 0 means a arithmetic schedule
(a log print for minibatch number: ``freq``, a log print for minibatch number: 2*``freq``,
a log print for minibatch number: 3*``freq``,...), and a value of None means no per-minibatch log.
first (`int`, default 0): Only start logging after the minibatch number is greater or equal to ``first``.
tag (`string`, default EmptyString): prepend minibatch log lines with your own string
log_to_file (`string` or `None`, default `None`): if None, output log data to stdout.
If a string is passed, the string is path to a file for log data.
rank (`int` or `None`, default `None`): set this to distributed.rank if you are using distributed
parallelism -- each rank's log will go to separate file.
gen_heartbeat (`bool`, default `False`): If True output a progress message every 10 seconds or so to stdout.
num_epochs (`int`, default 300): The total number of epochs to be trained. Used for some metadata.
This parameter is optional.
test_freq (`int` or `None`, default `None`): similar to ``freq``, but applies to printing intermediate
test results.
test_first (`int`, default 0): similar to ``first``, but applies to printing intermediate test results.
'''
if freq is None:
freq = sys.maxsize
if test_freq is None:
test_freq = sys.maxsize
super(ProgressPrinter, self).__init__(freq, first, test_freq, test_first)
self.loss_since_start = 0
self.metric_since_start = 0
self.samples_since_start = 0
self.updates_since_start = 0
self.loss_since_last = 0
self.metric_since_last = 0
self.samples_since_last = 0
self.total_updates = 0
self.epochs = 0
self.freq = freq
self.first = first
self.test_freq = test_freq
self.tag = '' if not tag else "[{}] ".format(tag)
self.epoch_start_time = time.time()
self.progress_timer_time = 0
self.log_to_file = log_to_file
self.gen_heartbeat = gen_heartbeat
self.num_epochs = num_epochs
# print out data about CNTK build
cntk_py.print_built_info()
self.logfilename = None
if self.log_to_file is not None:
self.logfilename = self.log_to_file
if rank is not None:
self.logfilename = self.logfilename + 'rank' + str(rank)
# print to stdout
print("Redirecting log to file " + self.logfilename)
with open(self.logfilename, "w") as logfile:
logfile.write(self.logfilename + "\n")
self.___logprint('CNTKCommandTrainInfo: train : ' + str(num_epochs))
self.___logprint('CNTKCommandTrainInfo: CNTKNoMoreCommands_Total : ' + str(num_epochs))
self.___logprint('CNTKCommandTrainBegin: train')
if freq == 0:
self.___logprint(' average since average since examples')
self.___logprint(' loss last metric last ')
self.___logprint(' ------------------------------------------------------')
