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Fix unaligned args in api_docs/python/tf/contrib/learn/Evaluable (#10423)

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This commit fixes unaligned args in api_docs/python/tf/contrib/learn/Evaluable

Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
This commit is contained in:
Yong Tang 2017-06-06 16:56:18 -07:00 committed by Jonathan Hseu
parent ed47ecf2dc
commit 8b065bc109
1 changed files with 11 additions and 12 deletions
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23
tensorflow/contrib/learn/python/learn/evaluable.py
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@ -60,19 +60,19 @@ class Evaluable(object):
Args:
x: Matrix of shape [n_samples, n_features...] or dictionary of many matrices
containing the input samples for fitting the model. Can be iterator that returns
arrays of features or dictionary of array of features. If set, `input_fn` must
be `None`.
containing the input samples for fitting the model. Can be iterator that returns
arrays of features or dictionary of array of features. If set, `input_fn` must
be `None`.
y: Vector or matrix [n_samples] or [n_samples, n_outputs] containing the
label values (class labels in classification, real numbers in
regression) or dictionary of multiple vectors/matrices. Can be iterator
that returns array of targets or dictionary of array of targets. If set,
`input_fn` must be `None`. Note: For classification, label values must
be integers representing the class index (i.e. values from 0 to
n_classes-1).
label values (class labels in classification, real numbers in
regression) or dictionary of multiple vectors/matrices. Can be iterator
that returns array of targets or dictionary of array of targets. If set,
`input_fn` must be `None`. Note: For classification, label values must
be integers representing the class index (i.e. values from 0 to
n_classes-1).
input_fn: Input function returning a tuple of:
features - Dictionary of string feature name to `Tensor` or `Tensor`.
labels - `Tensor` or dictionary of `Tensor` with labels.
features - Dictionary of string feature name to `Tensor` or `Tensor`.
labels - `Tensor` or dictionary of `Tensor` with labels.
If input_fn is set, `x`, `y`, and `batch_size` must be `None`. If
`steps` is not provided, this should raise `OutOfRangeError` or
`StopIteration` after the desired amount of data (e.g., one epoch) has
@ -90,7 +90,6 @@ class Evaluable(object):
friendly names for the metric to a `MetricSpec` object defining which
model outputs to evaluate against which labels with which metric
function.
Metric ops should support streaming, e.g., returning `update_op` and
`value` tensors. For example, see the options defined in
`../../../metrics/python/ops/metrics_ops.py`.