Class Trainable
Defined in tensorflow/contrib/learn/python/learn/trainable.py
.
Interface for objects that are trainable by, e.g., Experiment
.
THIS CLASS IS DEPRECATED.
Methods
tf.contrib.learn.Trainable.fit
fit(
x=None,
y=None,
input_fn=None,
steps=None,
batch_size=None,
monitors=None,
max_steps=None
)
Trains a model given training data x
predictions and y
labels.
Args:
x
: Matrix of shape [n_samples, n_features...] or the dictionary of Matrices. Can be iterator that returns arrays of features or dictionary of arrays of features. The training input samples for fitting the model. If set,input_fn
must beNone
.y
: Vector or matrix [n_samples] or [n_samples, n_outputs] or the dictionary of same. Can be iterator that returns array of labels or dictionary of array of labels. The training label values (class labels in classification, real numbers in regression). If set,input_fn
must beNone
. 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 -Tensor
or dictionary of string feature name toTensor
. labels -Tensor
or dictionary ofTensor
with labels. If input_fn is set,x
,y
, andbatch_size
must beNone
.steps
: Number of steps for which to train model. IfNone
, train forever. 'steps' works incrementally. If you call two times fit(steps=10) then training occurs in total 20 steps. If you don't want to have incremental behavior please setmax_steps
instead. If set,max_steps
must beNone
.batch_size
: minibatch size to use on the input, defaults to first dimension ofx
. Must beNone
ifinput_fn
is provided.monitors
: List ofBaseMonitor
subclass instances. Used for callbacks inside the training loop.max_steps
: Number of total steps for which to train model. IfNone
, train forever. If set,steps
must beNone
.Two calls to
fit(steps=100)
means 200 training iterations. On the other hand, two calls tofit(max_steps=100)
means that the second call will not do any iteration since first call did all 100 steps.
Returns:
self
, for chaining.