def get_raw_strings(dataset, options):
"""
:param Dataset dataset:
:param options: argparse.Namespace
:return: list of (seq tag, string)
:rtype: list[(str,str)]
"""
refs = []
start_time = time.time()
seq_len_stats = Stats()
seq_idx = options.startseq
if options.endseq < 0:
options.endseq = float("inf")
interactive = Util.is_tty() and not log.verbose[5]
print("Iterating over %r." % dataset, file=log.v2)
while dataset.is_less_than_num_seqs(seq_idx) and seq_idx <= options.endseq:
dataset.load_seqs(seq_idx, seq_idx + 1)
complete_frac = dataset.get_complete_frac(seq_idx)
start_elapsed = time.time() - start_time
try:
num_seqs_s = str(dataset.num_seqs)
except NotImplementedError:
try:
num_seqs_s = "~%i" % dataset.estimated_num_seqs
except TypeError: # a number is required, not NoneType
num_seqs_s = "?"
progress_prefix = "%i/%s" % (seq_idx, num_seqs_s,)
progress = "%s (%.02f%%)" % (progress_prefix, complete_frac * 100)
if complete_frac > 0:
total_time_estimated = start_elapsed / complete_frac
remaining_estimated = total_time_estimated - start_elapsed
progress += " (%s)" % hms(remaining_estimated)
seq_tag = dataset.get_tag(seq_idx)
assert isinstance(seq_tag, str)
ref = dataset.get_data(seq_idx, options.key)
if isinstance(ref, numpy.ndarray):
assert ref.shape == () or (ref.ndim == 1 and ref.dtype == numpy.uint8)
if ref.shape == ():
ref = ref.flatten()[0] # get the entry itself (str or bytes)
else:
ref = ref.tobytes()
if isinstance(ref, bytes):
ref = ref.decode("utf8")
assert isinstance(ref, str)
seq_len_stats.collect([len(ref)])
refs.append((seq_tag, ref))
if interactive:
Util.progress_bar_with_time(complete_frac, prefix=progress_prefix)
elif log.verbose[5]:
print(progress_prefix, "seq tag %r, ref len %i chars" % (seq_tag, len(ref)))
seq_idx += 1
print("Done. Num seqs %i. Total time %s." % (
seq_idx, hms(time.time() - start_time)), file=log.v1)
print("More seqs which we did not dumped: %s." % (
dataset.is_less_than_num_seqs(seq_idx),), file=log.v1)
seq_len_stats.dump(stream_prefix="Seq-length %r " % (options.key,), stream=log.v2)
return refs
def get_raw_strings(dataset, options):
"""
:param Dataset dataset:
:param options: argparse.Namespace
:return: list of (seq tag, string)
:rtype: list[(str,str)]
"""
refs = []
start_time = time.time()
seq_len_stats = Stats()
seq_idx = options.startseq
if options.endseq < 0:
options.endseq = float("inf")
interactive = Util.is_tty() and not log.verbose[5]
print("Iterating over %r." % dataset, file=log.v2)
while dataset.is_less_than_num_seqs(seq_idx) and seq_idx <= options.endseq:
dataset.load_seqs(seq_idx, seq_idx + 1)
complete_frac = dataset.get_complete_frac(seq_idx)
start_elapsed = time.time() - start_time
try:
num_seqs_s = str(dataset.num_seqs)
except NotImplementedError:
try:
num_seqs_s = "~%i" % dataset.estimated_num_seqs
except TypeError: # a number is required, not NoneType
num_seqs_s = "?"
progress_prefix = "%i/%s" % (seq_idx, num_seqs_s,)
progress = "%s (%.02f%%)" % (progress_prefix, complete_frac * 100)
if complete_frac > 0:
total_time_estimated = start_elapsed / complete_frac
remaining_estimated = total_time_estimated - start_elapsed
progress += " (%s)" % hms(remaining_estimated)
seq_tag = dataset.get_tag(seq_idx)
assert isinstance(seq_tag, str)
ref = dataset.get_data(seq_idx, options.key)
if isinstance(ref, numpy.ndarray):
assert ref.shape == () or (ref.ndim == 1 and ref.dtype == numpy.uint8)
if ref.shape == ():
ref = ref.flatten()[0] # get the entry itself (str or bytes)
else:
ref = ref.tobytes()
if isinstance(ref, bytes):
ref = ref.decode("utf8")
assert isinstance(ref, str)
seq_len_stats.collect([len(ref)])
refs.append((seq_tag, ref))
if interactive:
Util.progress_bar_with_time(complete_frac, prefix=progress_prefix)
elif log.verbose[5]:
print(progress_prefix, "seq tag %r, ref len %i chars" % (seq_tag, len(ref)))
seq_idx += 1
print("Done. Num seqs %i. Total time %s." % (
seq_idx, hms(time.time() - start_time)), file=log.v1)
print("More seqs which we did not dumped: %s." % (
dataset.is_less_than_num_seqs(seq_idx),), file=log.v1)
seq_len_stats.dump(stream_prefix="Seq-length %r " % (options.key,), stream=log.v2)
return refs
def analyze_dataset(options):
"""
:param options: argparse.Namespace
"""
print("Epoch: %i" % options.epoch, file=log.v3)
print("Dataset keys:", dataset.get_data_keys(), file=log.v3)
print("Dataset target keys:", dataset.get_target_list(), file=log.v3)
assert options.key in dataset.get_data_keys()
terminal_width, _ = Util.terminal_size()
show_interactive_process_bar = (log.verbose[3] and (not log.verbose[5]) and terminal_width >= 0)
start_time = time.time()
num_seqs_stats = Stats()
if options.endseq < 0:
options.endseq = float("inf")
recurrent = True
used_data_keys = dataset.get_data_keys()
batch_size = config.typed_value('batch_size', 1)
max_seqs = config.int('max_seqs', -1)
seq_drop = config.float('seq_drop', 0.0)
max_seq_length = config.typed_value('max_seq_length', None) or config.float('max_seq_length', 0)
max_pad_size = config.typed_value("max_pad_size", None)
batches = dataset.generate_batches(
recurrent_net=recurrent,
batch_size=batch_size,
max_seqs=max_seqs,
max_seq_length=max_seq_length,
max_pad_size=max_pad_size,
seq_drop=seq_drop,
used_data_keys=used_data_keys)
step = 0
total_num_seqs = 0
total_num_frames = NumbersDict()
total_num_used_frames = NumbersDict()
try:
while batches.has_more():
# See FeedDictDataProvider.
batch, = batches.peek_next_n(1)
assert isinstance(batch, Batch)
if batch.start_seq > options.endseq:
break
dataset.load_seqs(batch.start_seq, batch.end_seq)
complete_frac = batches.completed_frac()
start_elapsed = time.time() - start_time
try:
num_seqs_s = str(dataset.num_seqs)
except NotImplementedError:
try:
num_seqs_s = "~%i" % dataset.estimated_num_seqs
except TypeError: # a number is required, not NoneType
num_seqs_s = "?"
progress_prefix = "%i/%s" % (batch.start_seq, num_seqs_s)
progress = "%s (%.02f%%)" % (progress_prefix, complete_frac * 100)
if complete_frac > 0:
total_time_estimated = start_elapsed / complete_frac
remaining_estimated = total_time_estimated - start_elapsed
progress += " (%s)" % hms(remaining_estimated)
batch_max_time = NumbersDict.max([seq.frame_length for seq in batch.seqs]) * len(batch.seqs)
batch_num_used_frames = sum([seq.frame_length for seq in batch.seqs], NumbersDict())
total_num_seqs += len(batch.seqs)
num_seqs_stats.collect(numpy.array([len(batch.seqs)]))
total_num_frames += batch_max_time
total_num_used_frames += batch_num_used_frames
print(
"%s, batch %i, num seqs %i, frames %s, used %s (%s)" % (
progress, step, len(batch.seqs),
batch_max_time, batch_num_used_frames, batch_num_used_frames / batch_max_time),
file=log.v5)
if show_interactive_process_bar:
Util.progress_bar_with_time(complete_frac, prefix=progress_prefix)
step += 1
batches.advance(1)
finally:
print("Done. Total time %s. More seqs which we did not dumped: %s" % (
hms(time.time() - start_time), batches.has_more()), file=log.v2)
print("Dataset epoch %i, order %r." % (dataset.epoch, dataset.seq_ordering))
print("Num batches (steps): %i" % step, file=log.v1)
print("Num seqs: %i" % total_num_seqs, file=log.v1)
num_seqs_stats.dump(stream=log.v1, stream_prefix="Batch num seqs ")
for key in used_data_keys:
print("Data key %r:" % key, file=log.v1)
print(" Num frames: %s" % total_num_frames[key], file=log.v1)
print(" Num used frames: %s" % total_num_used_frames[key], file=log.v1)
print(" Fraction used frames: %s" % (total_num_used_frames / total_num_frames)[key], file=log.v1)
dataset.finish_epoch()
def dump_dataset(dataset, options):
"""
:type dataset: Dataset.Dataset
:param options: argparse.Namespace
"""
print("Epoch: %i" % options.epoch, file=log.v3)
dataset.init_seq_order(epoch=options.epoch)
print("Dataset keys:", dataset.get_data_keys(), file=log.v3)
print("Dataset target keys:", dataset.get_target_list(), file=log.v3)
assert options.key in dataset.get_data_keys()
if options.get_num_seqs:
print("Get num seqs.")
print("estimated_num_seqs: %r" % dataset.estimated_num_seqs)
try:
print("num_seqs: %r" % dataset.num_seqs)
except Exception as exc:
print("num_seqs exception %r, which is valid, so we count." % exc)
seq_idx = 0
if dataset.get_target_list():
default_target = dataset.get_target_list()[0]
else:
default_target = None
while dataset.is_less_than_num_seqs(seq_idx):
dataset.load_seqs(seq_idx, seq_idx + 1)
if seq_idx % 10000 == 0:
if default_target:
targets = dataset.get_targets(default_target, seq_idx)
postfix = " (targets = %r...)" % (targets[:10],)
else:
postfix = ""
print("%i ...%s" % (seq_idx, postfix))
seq_idx += 1
print("accumulated num seqs: %i" % seq_idx)
print("Done.")
return
dump_file = None
if options.type == "numpy":
print("Dump files: %r*%r" % (options.dump_prefix, options.dump_postfix), file=log.v3)
elif options.type == "stdout":
print("Dump to stdout", file=log.v3)
if options.stdout_limit is not None:
Util.set_pretty_print_default_limit(options.stdout_limit)
numpy.set_printoptions(
threshold=sys.maxsize if options.stdout_limit == float("inf") else int(options.stdout_limit))
if options.stdout_as_bytes:
Util.set_pretty_print_as_bytes(options.stdout_as_bytes)
elif options.type == "print_tag":
print("Dump seq tag to stdout", file=log.v3)
elif options.type == "dump_tag":
dump_file = open("%sseq-tags.txt" % options.dump_prefix, "w")
print("Dump seq tag to file: %s" % (dump_file.name,), file=log.v3)
elif options.type == "dump_seq_len":
dump_file = open("%sseq-lens.txt" % options.dump_prefix, "w")
print("Dump seq lens to file: %s" % (dump_file.name,), file=log.v3)
dump_file.write("{\n")
elif options.type == "print_shape":
print("Dump shape to stdout", file=log.v3)
elif options.type == "plot":
print("Plot.", file=log.v3)
elif options.type == "interactive":
print("Interactive debug shell.", file=log.v3)
elif options.type == "null":
print("No dump.")
else:
raise Exception("unknown dump option type %r" % options.type)
start_time = time.time()
stats = Stats() if (options.stats or options.dump_stats) else None
seq_len_stats = {key: Stats() for key in dataset.get_data_keys()}
seq_idx = options.startseq
if options.endseq < 0:
options.endseq = float("inf")
while dataset.is_less_than_num_seqs(seq_idx) and seq_idx <= options.endseq:
dataset.load_seqs(seq_idx, seq_idx + 1)
complete_frac = dataset.get_complete_frac(seq_idx)
start_elapsed = time.time() - start_time
try:
num_seqs_s = str(dataset.num_seqs)
except NotImplementedError:
try:
num_seqs_s = "~%i" % dataset.estimated_num_seqs
except TypeError: # a number is required, not NoneType
num_seqs_s = "?"
progress_prefix = "%i/%s" % (seq_idx, num_seqs_s)
progress = "%s (%.02f%%)" % (progress_prefix, complete_frac * 100)
if complete_frac > 0:
total_time_estimated = start_elapsed / complete_frac
remaining_estimated = total_time_estimated - start_elapsed
progress += " (%s)" % hms(remaining_estimated)
if options.type == "print_tag":
print("seq %s tag:" % (progress if log.verbose[2] else progress_prefix), dataset.get_tag(seq_idx))
elif options.type == "dump_tag":
print("seq %s tag:" % (progress if log.verbose[2] else progress_prefix), dataset.get_tag(seq_idx))
dump_file.write("%s\n" % dataset.get_tag(seq_idx))
elif options.type == "dump_seq_len":
seq_len = dataset.get_seq_length(seq_idx)[options.key]
print(
"seq %s tag:" % (progress if log.verbose[2] else progress_prefix),
dataset.get_tag(seq_idx), "%r len:" % options.key, seq_len)
dump_file.write("%r: %r,\n" % (dataset.get_tag(seq_idx), seq_len))
else:
data = dataset.get_data(seq_idx, options.key)
if options.type == "numpy":
numpy.savetxt("%s%i.data%s" % (options.dump_prefix, seq_idx, options.dump_postfix), data)
elif options.type == "stdout":
print("seq %s tag:" % progress, dataset.get_tag(seq_idx))
print("seq %s data:" % progress, pretty_print(data))
elif options.type == "print_shape":
print("seq %s data shape:" % progress, data.shape)
elif options.type == "plot":
plot(data)
for target in dataset.get_target_list():
targets = dataset.get_targets(target, seq_idx)
if options.type == "numpy":
numpy.savetxt("%s%i.targets.%s%s" % (options.dump_prefix, seq_idx, target, options.dump_postfix), targets, fmt='%i')
elif options.type == "stdout":
extra = ""
if target in dataset.labels and len(dataset.labels[target]) > 1:
assert dataset.can_serialize_data(target)
extra += " (%r)" % dataset.serialize_data(key=target, data=targets)
print("seq %i target %r: %s%s" % (seq_idx, target, pretty_print(targets), extra))
elif options.type == "print_shape":
print("seq %i target %r shape:" % (seq_idx, target), targets.shape)
if options.type == "interactive":
from Debug import debug_shell
debug_shell(locals())
seq_len = dataset.get_seq_length(seq_idx)
for key in dataset.get_data_keys():
seq_len_stats[key].collect([seq_len[key]])
if stats:
stats.collect(data)
if options.type == "null":
Util.progress_bar_with_time(complete_frac, prefix=progress_prefix)
seq_idx += 1
print("Done. Total time %s. More seqs which we did not dumped: %s" % (
hms_fraction(time.time() - start_time), dataset.is_less_than_num_seqs(seq_idx)), file=log.v2)
for key in dataset.get_data_keys():
seq_len_stats[key].dump(stream_prefix="Seq-length %r " % key, stream=log.v2)
if stats:
stats.dump(output_file_prefix=options.dump_stats, stream_prefix="Data %r " % options.key, stream=log.v1)
if options.type == "dump_seq_len":
dump_file.write("}\n")
if dump_file:
print("Dumped to file:", dump_file.name, file=log.v2)
dump_file.close()
def dump_dataset(dataset, options):
"""
:type dataset: Dataset.Dataset
:param options: argparse.Namespace
"""
print("Epoch: %i" % options.epoch, file=log.v3)
dataset.init_seq_order(epoch=options.epoch)
print("Dataset keys:", dataset.get_data_keys(), file=log.v3)
print("Dataset target keys:", dataset.get_target_list(), file=log.v3)
assert options.key in dataset.get_data_keys()
if options.get_num_seqs:
print("Get num seqs.")
print("estimated_num_seqs: %r" % dataset.estimated_num_seqs)
try:
print("num_seqs: %r" % dataset.num_seqs)
except Exception as exc:
print("num_seqs exception %r, which is valid, so we count." % exc)
seq_idx = 0
if dataset.get_target_list():
default_target = dataset.get_target_list()[0]
else:
default_target = None
while dataset.is_less_than_num_seqs(seq_idx):
dataset.load_seqs(seq_idx, seq_idx + 1)
if seq_idx % 10000 == 0:
if default_target:
targets = dataset.get_targets(default_target, seq_idx)
postfix = " (targets = %r...)" % (targets[:10], )
else:
postfix = ""
print("%i ...%s" % (seq_idx, postfix))
seq_idx += 1
print("accumulated num seqs: %i" % seq_idx)
print("Done.")
return
if options.type == "numpy":
print("Dump files: %r*%r" %
(options.dump_prefix, options.dump_postfix),
file=log.v3)
elif options.type == "stdout":
print("Dump to stdout", file=log.v3)
elif options.type == "print_shape":
print("Dump shape to stdout", file=log.v3)
elif options.type == "plot":
print("Plot.", file=log.v3)
elif options.type == "null":
print("No dump.")
else:
raise Exception("unknown dump option type %r" % options.type)
start_time = time.time()
stats = Stats() if (options.stats or options.dump_stats) else None
seq_len_stats = {key: Stats() for key in dataset.get_data_keys()}
seq_idx = options.startseq
if options.endseq < 0:
options.endseq = float("inf")
while dataset.is_less_than_num_seqs(seq_idx) and seq_idx <= options.endseq:
dataset.load_seqs(seq_idx, seq_idx + 1)
complete_frac = dataset.get_complete_frac(seq_idx)
start_elapsed = time.time() - start_time
try:
num_seqs_s = str(dataset.num_seqs)
except NotImplementedError:
try:
num_seqs_s = "~%i" % dataset.estimated_num_seqs
except TypeError: # a number is required, not NoneType
num_seqs_s = "?"
progress_prefix = "%i/%s" % (seq_idx, num_seqs_s)
progress = "%s (%.02f%%)" % (progress_prefix, complete_frac * 100)
if complete_frac > 0:
total_time_estimated = start_elapsed / complete_frac
remaining_estimated = total_time_estimated - start_elapsed
progress += " (%s)" % hms(remaining_estimated)
data = dataset.get_data(seq_idx, options.key)
if options.type == "numpy":
numpy.savetxt(
"%s%i.data%s" %
(options.dump_prefix, seq_idx, options.dump_postfix), data)
elif options.type == "stdout":
print("seq %s data:" % progress, pretty_print(data))
elif options.type == "print_shape":
print("seq %s data shape:" % progress, data.shape)
elif options.type == "plot":
plot(data)
for target in dataset.get_target_list():
targets = dataset.get_targets(target, seq_idx)
if options.type == "numpy":
numpy.savetxt("%s%i.targets.%s%s" %
(options.dump_prefix, seq_idx, target,
options.dump_postfix),
targets,
fmt='%i')
elif options.type == "stdout":
print("seq %i target %r:" % (seq_idx, target),
pretty_print(targets))
elif options.type == "print_shape":
print("seq %i target %r shape:" % (seq_idx, target),
targets.shape)
seq_len = dataset.get_seq_length(seq_idx)
for key in dataset.get_data_keys():
seq_len_stats[key].collect([seq_len[key]])
if stats:
stats.collect(data)
if options.type == "null":
Util.progress_bar_with_time(complete_frac, prefix=progress_prefix)
seq_idx += 1
print("Done. Total time %s. More seqs which we did not dumped: %s" %
(hms(time.time() - start_time),
dataset.is_less_than_num_seqs(seq_idx)),
file=log.v1)
for key in dataset.get_data_keys():
seq_len_stats[key].dump(stream_prefix="Seq-length %r " % key,
stream=log.v2)
if stats:
stats.dump(output_file_prefix=options.dump_stats,
stream_prefix="Data %r " % options.key,
stream=log.v2)
def dump_dataset(dataset, options):
"""
:type dataset: Dataset.Dataset
:param options: argparse.Namespace
"""
print("Epoch: %i" % options.epoch, file=log.v3)
dataset.init_seq_order(epoch=options.epoch)
print("Dataset keys:", dataset.get_data_keys(), file=log.v3)
print("Dataset target keys:", dataset.get_target_list(), file=log.v3)
assert options.key in dataset.get_data_keys()
if options.get_num_seqs:
print("Get num seqs.")
print("estimated_num_seqs: %r" % dataset.estimated_num_seqs)
try:
print("num_seqs: %r" % dataset.num_seqs)
except Exception as exc:
print("num_seqs exception %r, which is valid, so we count." % exc)
seq_idx = 0
if dataset.get_target_list():
default_target = dataset.get_target_list()[0]
else:
default_target = None
while dataset.is_less_than_num_seqs(seq_idx):
dataset.load_seqs(seq_idx, seq_idx + 1)
if seq_idx % 10000 == 0:
if default_target:
targets = dataset.get_targets(default_target, seq_idx)
postfix = " (targets = %r...)" % (targets[:10],)
else:
postfix = ""
print("%i ...%s" % (seq_idx, postfix))
seq_idx += 1
print("accumulated num seqs: %i" % seq_idx)
print("Done.")
return
if options.type == "numpy":
print("Dump files: %r*%r" % (options.dump_prefix, options.dump_postfix), file=log.v3)
elif options.type == "stdout":
print("Dump to stdout", file=log.v3)
if options.stdout_limit is not None:
Util.set_pretty_print_default_limit(options.stdout_limit)
numpy.set_printoptions(
threshold=sys.maxsize if options.stdout_limit == float("inf") else int(options.stdout_limit))
if options.stdout_as_bytes:
Util.set_pretty_print_as_bytes(options.stdout_as_bytes)
elif options.type == "print_tag":
print("Dump seq tag to stdout", file=log.v3)
elif options.type == "print_shape":
print("Dump shape to stdout", file=log.v3)
elif options.type == "plot":
print("Plot.", file=log.v3)
elif options.type == "null":
print("No dump.")
else:
raise Exception("unknown dump option type %r" % options.type)
start_time = time.time()
stats = Stats() if (options.stats or options.dump_stats) else None
seq_len_stats = {key: Stats() for key in dataset.get_data_keys()}
seq_idx = options.startseq
if options.endseq < 0:
options.endseq = float("inf")
while dataset.is_less_than_num_seqs(seq_idx) and seq_idx <= options.endseq:
dataset.load_seqs(seq_idx, seq_idx + 1)
complete_frac = dataset.get_complete_frac(seq_idx)
start_elapsed = time.time() - start_time
try:
num_seqs_s = str(dataset.num_seqs)
except NotImplementedError:
try:
num_seqs_s = "~%i" % dataset.estimated_num_seqs
except TypeError: # a number is required, not NoneType
num_seqs_s = "?"
progress_prefix = "%i/%s" % (seq_idx, num_seqs_s)
progress = "%s (%.02f%%)" % (progress_prefix, complete_frac * 100)
if complete_frac > 0:
total_time_estimated = start_elapsed / complete_frac
remaining_estimated = total_time_estimated - start_elapsed
progress += " (%s)" % hms(remaining_estimated)
if options.type == "print_tag":
print("seq %s tag:" % (progress if log.verbose[2] else progress_prefix), dataset.get_tag(seq_idx))
else:
data = dataset.get_data(seq_idx, options.key)
if options.type == "numpy":
numpy.savetxt("%s%i.data%s" % (options.dump_prefix, seq_idx, options.dump_postfix), data)
elif options.type == "stdout":
print("seq %s tag:" % progress, dataset.get_tag(seq_idx))
print("seq %s data:" % progress, pretty_print(data))
elif options.type == "print_shape":
print("seq %s data shape:" % progress, data.shape)
elif options.type == "plot":
plot(data)
for target in dataset.get_target_list():
targets = dataset.get_targets(target, seq_idx)
if options.type == "numpy":
numpy.savetxt("%s%i.targets.%s%s" % (options.dump_prefix, seq_idx, target, options.dump_postfix), targets, fmt='%i')
elif options.type == "stdout":
extra = ""
if target in dataset.labels and len(dataset.labels[target]) > 1:
labels = dataset.labels[target]
if len(labels) < 1000 and all([len(l) == 1 for l in labels]):
join_str = ""
else:
join_str = " "
extra += " (%r)" % join_str.join(map(dataset.labels[target].__getitem__, targets))
print("seq %i target %r: %s%s" % (seq_idx, target, pretty_print(targets), extra))
elif options.type == "print_shape":
print("seq %i target %r shape:" % (seq_idx, target), targets.shape)
seq_len = dataset.get_seq_length(seq_idx)
for key in dataset.get_data_keys():
seq_len_stats[key].collect([seq_len[key]])
if stats:
stats.collect(data)
if options.type == "null":
Util.progress_bar_with_time(complete_frac, prefix=progress_prefix)
seq_idx += 1
print("Done. Total time %s. More seqs which we did not dumped: %s" % (
hms(time.time() - start_time), dataset.is_less_than_num_seqs(seq_idx)), file=log.v2)
for key in dataset.get_data_keys():
seq_len_stats[key].dump(stream_prefix="Seq-length %r " % key, stream=log.v2)
if stats:
stats.dump(output_file_prefix=options.dump_stats, stream_prefix="Data %r " % options.key, stream=log.v1)
