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[skip ci] Doctest for Accuracy #2287

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480bf48
Added doctest for Accuracy
Chandan-h-509 Oct 22, 2021
a413232
Lint fixes
Chandan-h-509 Oct 22, 2021
92d485e
Added default evaluator
Chandan-h-509 Oct 23, 2021
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25 changes: 25 additions & 0 deletions ignite/metrics/accuracy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -126,6 +126,31 @@ def thresholded_output_transform(output):
device: specifies which device updates are accumulated on. Setting the metric's
device to be the same as your ``update`` arguments ensures the ``update`` method is non-blocking. By
default, CPU.

Examples:
To use with ``Engine`` and ``process_function``, simply attach the metric instance to the engine.
The output of the engine's ``process_function`` needs to be in the format of
``(y_pred, y)`` or ``{'y_pred': y_pred, 'y': y, ...}``. If not, ``output_tranform`` can be added
to the metric to transform the output into the form expected by the metric.

``y_pred`` and ``y`` should have the same shape.

.. testcode::

def process_function(engine, batch):
y_pred, y = batch
return y_pred, y
engine = Engine(process_function)
metric = Accuracy()
metric.attach(engine, 'accuracy')
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@vfdev-5 vfdev-5 Oct 22, 2021

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I think we could create a default evaluator as above and hide this part of code from the user ?

cc @ydcjeff

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@Chandan-h-509 Chandan-h-509 Oct 22, 2021

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I feel it would be good to have this part of the code so that it remains transparent.
Could you also explain the alternative that you are proposing?

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@vfdev-5 vfdev-5 Oct 22, 2021

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There is a way to define a global context using this:

ignite/docs/source/conf.py

Lines 344 to 353 in 74dabca

doctest_global_setup = """
import torch
from torch import nn, optim
from ignite.engine import *
from ignite.handlers import *
from ignite.metrics import *
from ignite.utils import *
manual_seed(666)

preds = torch.Tensor([[1,0,0,1]])
target = torch.Tensor([[1,0,0,0]])
state = engine.run([[preds, target]])
print(state.metrics['accuracy'])

.. testoutput::

0.75
"""

def __init__(
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