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plot_timings
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def plot_timings(loader, n_batches, model_time=0.2, max_time=2.5): | |
fig, ax = plt.subplots() | |
ax.set_axisbelow(True) | |
ax.yaxis.grid(which="major", color='black', linewidth=1) | |
zero_time = time.time() | |
worker_ids = {} | |
worker_count = count() | |
for result in islice(loader, n_batches): | |
start = time.time() | |
time.sleep(model_time) | |
end = time.time() | |
# check if already batched | |
if isinstance(result[0], torch.Tensor): | |
result = zip(*result) | |
batch = [] | |
for item in result: | |
data, worker, t1, t2 = tuple(map(scalar, item)) | |
# fix worker position in plot | |
if worker != -1: | |
if worker not in worker_ids: | |
worker_ids[worker] = next(worker_count) | |
worker = worker_ids[worker] | |
plot_time_box(data, worker, t1-zero_time, t2-zero_time, ax) | |
batch.append(data) | |
batch_str = ",".join(map(str, batch)) | |
plot_time_box(batch_str, -1, start-zero_time, end-zero_time, ax, color='firebrick') | |
max_worker = len(worker_ids) - 1 | |
ax.set_xlim(0, max_time) | |
ax.set_ylim(-1.5, max_worker + 0.5) | |
ax.set_xticks(np.arange(0, max_time, 0.2)) | |
ax.set_yticks(np.arange(-1, max_worker+1, 1)) | |
ax.set_yticklabels([]) | |
ax.tick_params(axis='y', colors=(0,0,0,0)) | |
fig.set_figwidth(16) | |
fig.set_figheight((max_worker + 2) * 0.5) | |
ax.xaxis.label.set_color('gray') | |
ax.tick_params(axis='x', colors='gray') | |
for spine in ax.spines.values(): | |
spine.set_edgecolor((0,0,0,0)) | |
def scalar(x): | |
return x.item() if hasattr(x, 'item') else x | |
def plot_time_box(data, worker, t1, t2, ax, color='steelblue'): | |
x = t1 | |
y = worker - 0.25 | |
w = t2 - t1 | |
h = 0.6 | |
rect = Rectangle((x, y), w, h, linewidth=2, edgecolor='black',facecolor=color) | |
ax.add_patch(rect) | |
ax.text(x + (w * 0.5), y + (h * 0.5), str(data), va='center', ha='center', color='white', weight='bold') |
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