tf.estimator.inputs.numpy_input_fn
tf.estimator.inputs.numpy_input_fn
tf.estimator.inputs.numpy_input_fn
numpy_input_fn( x, y=None, batch_size=128, num_epochs=1, shuffle=None, queue_capacity=1000, num_threads=1 )
Defined in tensorflow/python/estimator/inputs/numpy_io.py
.
Returns input function that would feed dict of numpy arrays into the model.
This returns a function outputting features
and target
based on the dict of numpy arrays. The dict features
has the same keys as the x
.
Example:
age = np.arange(4) * 1.0 height = np.arange(32, 36) x = {'age': age, 'height': height} y = np.arange(-32, -28) with tf.Session() as session: input_fn = numpy_io.numpy_input_fn( x, y, batch_size=2, shuffle=False, num_epochs=1)
Args:
-
x
: dict of numpy array object. -
y
: numpy array object.None
if absent. -
batch_size
: Integer, size of batches to return. -
num_epochs
: Integer, number of epochs to iterate over data. IfNone
will run forever. -
shuffle
: Boolean, if True shuffles the queue. Avoid shuffle at prediction time. -
queue_capacity
: Integer, size of queue to accumulate. -
num_threads
: Integer, number of threads used for reading and enqueueing. In order to have predicted and repeatable order of reading and enqueueing, such as in prediction and evaluation mode,num_threads
should be 1.
Returns:
Function, that has signature of ()->(dict of features
, target
)
Raises:
-
ValueError
: if the shape ofy
mismatches the shape of values inx
(i.e., values inx
have same shape). -
TypeError
:x
is not a dict orshuffle
is not bool.
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/estimator/inputs/numpy_input_fn