def plot_mem_conv50(config, local_dir, logs, iters):
def smoother(ss):
return ss.ewm(span=15).mean()
df, _, fig = pl.memory_usage(logs,
iter_times=iters[0:10],
mem_type='GPU_0_bfc',
smoother=smoother)
return fig
def plot_mem_ptbL(config, local_dir, logs, iters):
def smoother(ss):
return ss
df, _, fig = pl.memory_usage(logs,
iter_times=iters[0:10],
mem_type='GPU_0_bfc',
smoother=smoother)
return fig
def plot_mem_resnet50_25(config, local_dir, logs, iters):
def smoother(ss, ss2):
print('{}, {}, {}'.format(ss.min(), ss.max(), ss2.mean()))
return ss
# return ss.ewm(span=15).mean()
df, _, fig = pl.memory_usage(logs,
iter_times=iters[0:10],
mem_type='GPU_0_bfc',
smoother=smoother)
return fig
def plot_mem_resnet152_75(config, local_dir, logs, iters):
def smoother(ss, ss2):
print('{}, {}, {}'.format(ss.min(), ss.max(), ss2.mean()))
return ss
# return ss.ewm(span=15).mean()
df, _, fig = pl.memory_usage(logs,
ends=iters[0][1],
show_avg=False,
mem_type='GPU_0_bfc')
fig.set_size_inches(3.45, 1.75, forward=True)
return fig
def plot_nested_doll_mix5_samelength(config, local_dir, logs, iters):
with mpl.style.context(('color5')):
pf.preprocess(local_dir)
perfdf = pf.load_file(os.path.join(local_dir, 'sessiter.output'))
fig = plt.figure()
spec = mpl.gridspec.GridSpec(2, 1, height_ratios=[1, 3])
spec.update(hspace=0.2, left=0.18, right=.98, top=.8, bottom=0.22)
ax0 = fig.add_subplot(spec[0])
ax1 = fig.add_subplot(spec[1], sharex=ax0)
plt.setp(ax0.get_xticklabels(), visible=False)
df, _ = pf.session_counters(perfdf, colnames=['scheduled'], ax=ax0)
def smoother(ss):
sampled = ss.resample('50ms').interpolate(method='time')
print("previous len: {} now: {}".format(len(ss), len(sampled)))
return sampled
df, _, _ = pl.memory_usage(logs,
mem_type='GPU_0_bfc',
per_sess=True,
ax=ax1,
show_avg=False,
smoother=smoother)
ax0.set_title('Scheduled Tasks')
ax0.legend().set_visible(False)
handles, labels = ax1.get_legend_handles_labels()
ax1.legend(handles=handles,
labels=[
'alexnet_100', 'overfeat_50', 'googlenet_50',
"inception3_25", "resnet50_50"
],
ncol=3,
loc='upper center',
bbox_to_anchor=(0.48, -0.19),
frameon=False)
ax0.set_ylabel('# of Tasks')
ax1.set_xlabel('Time (s)')
ax1.set_title('Memory Usage')
ax1.tick_params(axis='x', labelsize=8)
ax1.tick_params(axis='y', labelsize=8)
ax0.tick_params(axis='y', labelsize=8)
return fig
def plot_fair20(config, local_dir, logs, iters):
with mpl.style.context(('grayscale20')):
def smoother(ss):
sampled = ss.resample('500us').interpolate(method='time')
print("previous len: {} now: {}".format(len(ss), len(sampled)))
return sampled
df, _, fig = pl.memory_usage(logs,
mem_type='GPU_0_bfc',
per_sess=True,
show_avg=False)
ax = fig.axes[-1]
ax.legend().remove()
ax.set_title('Memory Usage')
# ax.set_title('resnet50_50 of 265,180,170,100 iterations')
fig.tight_layout(pad=0)
# fig.adjust(right=.98, top=.85, left=.2, bottom=.2)
return fig
def plot_case_bigsmall_wc(config, local_dir, logs, iters):
pf.preprocess(local_dir)
perfdf = pf.load_file(os.path.join(local_dir, 'sessiter.output'))
fig = plt.figure()
spec = mpl.gridspec.GridSpec(2, 1, height_ratios=[1, 3])
spec.update(hspace=0.2, left=0.16, right=.98, top=.8, bottom=0.18)
ax0 = fig.add_subplot(spec[0])
ax1 = fig.add_subplot(spec[1], sharex=ax0)
plt.setp(ax0.get_xticklabels(), visible=False)
df, _ = pf.session_counters(perfdf, colnames=['scheduled'], ax=ax0)
def smoother(ss):
sampled = ss.resample('500us').interpolate(method='time')
print("previous len: {} now: {}".format(len(ss), len(sampled)))
return sampled
df, _, _ = pl.memory_usage(logs,
mem_type='GPU_0_bfc',
per_sess=True,
ax=ax1,
show_avg=False,
smoother=smoother)
ax0.legend().set_visible(False)
handles, labels = ax1.get_legend_handles_labels()
ax1.legend(handles=handles,
labels=['alexnet_100', 'inception3_25'],
ncol=2,
loc='upper center',
bbox_to_anchor=(0.5, -0.2),
frameon=False)
ax0.set_ylabel('Scheduled\nTasks')
ax1.set_xlabel('Time (s)')
ax1.set_xlim([0, 115 * 1e9])
ax1.tick_params(axis='x', labelsize=8)
ax1.tick_params(axis='y', labelsize=8)
ax0.tick_params(axis='y', labelsize=8)
return fig
