def _iter_scalars(run, args):
from guild import index2 as indexlib # slightly expensive
for s in indexlib.iter_run_scalars(run):
key = _s_key(s)
val = _s_val(s)
step = _s_step(s)
if args.json:
yield key, (val, step)
else:
yield key, "%f (step %i)" % (_s_val(s), _s_step(s))
def _print_run_info(item, output=False, scalars=False):
for name in RUN_DETAIL:
print("%s: %s" % (name, item.fmt.get(name, "")))
print("flags:", end="")
print(run_util.format_attr(item.run.get("flags", "")))
if scalars:
print("scalars:")
for s in indexlib.iter_run_scalars(item.run):
print(" %s: %f (step %i)" %
(s["tag"], s["last_val"], s["last_step"]))
if output:
print("output:")
for line in run_util.iter_output(item.run):
print(" %s" % line, end="")
def _run_scalar_data(run):
data = {}
step = None
last_step = None
for s in indexlib.iter_run_scalars(run):
key = s["tag"]
data[key] = s["last_val"]
last_step = s["last_step"]
if key == "loss":
step = last_step
if data:
if step is None:
step = last_step
data["step"] = step
return data
def _runs_scalars(runs):
data = []
cols = [
"run",
"prefix",
"tag",
"first_val",
"first_step",
"last_val",
"last_step",
"min_val",
"min_step",
"max_val",
"max_step",
"avg_val",
"count",
"total",
]
for run in runs:
for s in indexlib.iter_run_scalars(run):
data.append(s)
return pd.DataFrame(data, columns=cols)
def _iter_scalars(run):
for s in indexlib.iter_run_scalars(run):
yield "%s: %f (step %i)" % (_s_key(s), _s_val(s), _s_step(s))
def _iter_scalars(run):
from guild import index2 as indexlib # slightly expensive
for s in indexlib.iter_run_scalars(run):
yield "%s: %f (step %i)" % (_s_key(s), _s_val(s), _s_step(s))
def _runs_scalars(runs):
data = []
for run in runs:
for s in indexlib.iter_run_scalars(run):
data.append(s)
return pd.DataFrame(data)
