def plotly_history_graph():
cli = tw.WatcherClient()
p = tw.plotly.line_plot.LinePlot(title='Demo')
s2 = cli.create_stream(event_name='ev_j',
expr='map(lambda v:(v.x, v.val), l)')
p.subscribe(s2, ytitle='ev_j', history_len=15)
p.show()
utils.wait_key()
def show_find_lr():
cli_train = tw.WatcherClient()
plot = tw.mpl.LinePlot()
train_batch_loss = cli_train.create_stream(
event_name='batch',
expr='lambda d:(d.tt.scheduler.get_lr()[0], d.metrics.batch_loss)')
plot.subscribe(train_batch_loss, xtitle='Epoch', ytitle='Loss')
utils.wait_key()
def plotly_line_graph():
cli = tw.WatcherClient()
s1 = cli.create_stream(event_name="ev_i",
expr='map(lambda v:(v.x, math.sqrt(v.val)), l)')
p = tw.plotly.line_plot.LinePlot()
p.subscribe(s1)
p.show()
utils.wait_key()
def dlc_show_rand_outputs():
cli = cli_train = tw.WatcherClient()
imgs = cli.create_stream(
event_name='batch',
expr=
"top(l, out_xform=pyt_img_img_out_xform, group_key=lambda x:'', topk=10, order='rnd')",
throttle=1)
img_plot = tw.mpl.ImagePlot()
img_plot.show(imgs, img_width=39, img_height=69, viz_img_scale=10)
utils.wait_key()
def plot_grads_plotly():
train_cli = tw.WatcherClient()
grads = train_cli.create_stream(event_name='batch',
expr='lambda d:grads_abs_mean(d.model)',
throttle=1)
p = tw.plotly.line_plot.LinePlot('Demo')
p.subscribe(grads,
xtitle='Layer',
ytitle='Gradients',
history_len=30,
new_on_eval=True)
utils.wait_key()
def img2img_rnd():
cli_train = tw.WatcherClient()
cli = tw.WatcherClient()
imgs = cli_train.create_stream(
event_name='batch',
expr=
"top(l, out_xform=pyt_img_img_out_xform, group_key=lambda x:'', topk=2, order='rnd')",
throttle=1)
img_plot = tw.mpl.ImagePlot()
img_plot.show(imgs, img_width=100, img_height=100, viz_img_scale=3, cols=1)
utils.wait_key()
def plot_grads():
train_cli = tw.WatcherClient()
grads = train_cli.create_stream(
event_name='batch',
expr=
'lambda d:agg_params(d.model, lambda p: p.grad.abs().mean().item())',
throttle=1)
p = tw.plotly.LinePlot('Demo')
p.subscribe(grads,
xtitle='Epoch',
ytitle='Gradients',
history_len=30,
new_on_eval=True)
utils.wait_key()
def show_stream():
cli = tw.WatcherClient()
print("Subscribing to event ev_i...")
s1 = cli.create_stream(event_name="ev_i",
expr='map(lambda v:math.sqrt(v.val), l)')
r1 = tw.TextVis(title='L1')
r1.subscribe(s1)
r1.show()
print("Subscribing to event ev_j...")
s2 = cli.create_stream(event_name="ev_j",
expr='map(lambda v:v.val*v.val, l)')
r2 = tw.TextVis(title='L2')
r2.subscribe(s2)
r2.show()
print("Waiting for key...")
utils.wait_key()
import tensorwatch as tw
import time
from tensorwatch.zmq_wrapper import ZmqWrapper
from tensorwatch import utils
class A:
def on_event(self, obj):
print(obj)
a = A()
utils.set_debug_verbosity(10)
sub = ZmqWrapper.Subscription(40859, "Topic1", a.on_event)
print("subscriber is waiting")
clisrv = ZmqWrapper.ClientServer(40860, False)
clisrv.send_obj("hello 1")
print('sleeping..')
time.sleep(10)
clisrv.send_obj("hello 2")
print('waiting for key..')
utils.wait_key()
