Skip to content

Commit f3b437b

Browse files
vfdev-5vfdev-5
committed
Updated FBResearchLogger example doctring
1 parent d772953 commit f3b437b

File tree

1 file changed

+57
-3
lines changed

1 file changed

+57
-3
lines changed

‎ignite/handlers/fbresearch_logger.py‎

Lines changed: 57 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -30,10 +30,64 @@ class FBResearchLogger:
3030
.. code-block:: python
3131
3232
import logging
33-
from ignite.handlers.fbresearch_logger import *
3433
35-
logger = FBResearchLogger(logger=logging.Logger(__name__), show_output=True)
36-
logger.attach(trainer, name="Train", every=10, optimizer=my_optimizer)
34+
import torch
35+
import torch.nn as nn
36+
import torch.optim as optim
37+
38+
from ignite.engine import create_supervised_trainer, Events
39+
from ignite.handlers.fbresearch_logger import FBResearchLogger
40+
from ignite.utils import setup_logger
41+
42+
model = nn.Linear(10, 5)
43+
opt = optim.SGD(model.parameters(), lr=0.001)
44+
criterion = nn.CrossEntropyLoss()
45+
46+
data = [(torch.rand(4, 10), torch.randint(0, 5, size=(4, ))) for _ in range(100)]
47+
48+
trainer = create_supervised_trainer(
49+
model, opt, criterion, output_transform=lambda x, y, y_pred, loss: {"total_loss": loss.item()}
50+
)
51+
52+
logger = setup_logger("trainer", level=logging.INFO)
53+
logger = FBResearchLogger(logger=logger, show_output=True)
54+
logger.attach(trainer, name="Train", every=20, optimizer=opt)
55+
56+
trainer.run(data, max_epochs=4)
57+
58+
Output:
59+
60+
.. code-block:: text
61+
62+
2024-04-22 12:05:47,843 trainer INFO: Train: start epoch [1/4]
63+
... Epoch [1/4] [20/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.5999 Iter time: 0.0008 s Data prep ..
64+
... Epoch [1/4] [40/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.9297 Iter time: 0.0008 s Data prep ..
65+
... Epoch [1/4] [60/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.9985 Iter time: 0.0008 s Data prep ..
66+
... Epoch [1/4] [80/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.9785 Iter time: 0.0008 s Data prep ..
67+
... Epoch [1/4] [100/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.6211 Iter time: 0.0008 s Data prep .
68+
... Train: Epoch [1/4] Total time: 0:00:00 (0.0008 s / it)
69+
... Train: start epoch [2/4]
70+
... Epoch [2/4] [19/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.5981 Iter time: 0.0009 s Data prep ..
71+
... Epoch [2/4] [39/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.9013 Iter time: 0.0008 s Data prep ..
72+
... Epoch [2/4] [59/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.9811 Iter time: 0.0008 s Data prep ..
73+
... Epoch [2/4] [79/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.9434 Iter time: 0.0008 s Data prep ..
74+
... Epoch [2/4] [99/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.6116 Iter time: 0.0008 s Data prep ..
75+
... Train: Epoch [2/4] Total time: 0:00:00 (0.0009 s / it)
76+
... Train: start epoch [3/4]
77+
... Epoch [3/4] [18/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.5972 Iter time: 0.0008 s Data prep ..
78+
... Epoch [3/4] [38/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.8753 Iter time: 0.0008 s Data prep ..
79+
... Epoch [3/4] [58/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.9657 Iter time: 0.0009 s Data prep ..
80+
... Epoch [3/4] [78/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.9112 Iter time: 0.0008 s Data prep ..
81+
... Epoch [3/4] [98/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.6035 Iter time: 0.0008 s Data prep ..
82+
... Train: Epoch [3/4] Total time: 0:00:00 (0.0009 s / it)
83+
... Train: start epoch [4/4]
84+
... Epoch [4/4] [17/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.5969 Iter time: 0.0008 s Data prep ..
85+
... Epoch [4/4] [37/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.8516 Iter time: 0.0008 s Data prep ..
86+
... Epoch [4/4] [57/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.9521 Iter time: 0.0008 s Data prep ..
87+
... Epoch [4/4] [77/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.8816 Iter time: 0.0008 s Data prep ..
88+
... Epoch [4/4] [97/100]: ETA: 0:00:00 lr: 0.00100 total_loss: 1.5966 Iter time: 0.0009 s Data prep ..
89+
... Train: Epoch [4/4] Total time: 0:00:00 (0.0009 s / it)
90+
... Train: run completed Total time: 0:00:00
3791
"""
3892

3993
def __init__(self, logger: Any, delimiter: str = " ", show_output: bool = False):

0 commit comments

Comments
 (0)