List of files or patterns of file paths containing
Example records. See tf.io.gfile.glob for pattern rules.
batch_size
An int or scalar Tensor specifying the batch size to use.
features
A dict mapping feature keys to FixedLenFeature or
VarLenFeature values.
randomize_input
Whether the input should be randomized.
num_epochs
Integer specifying the number of times to read through the
dataset. If None, cycles through the dataset forever. NOTE - If specified,
creates a variable that must be initialized, so call
tf.compat.v1.local_variables_initializer() and run the op in a session.
queue_capacity
Capacity for input queue.
reader_num_threads
The number of threads to read examples. In order to have
predictable and repeatable order of reading and enqueueing, such as in
prediction and evaluation mode, reader_num_threads should be 1.
name
Name of resulting op.
Returns
A dict of Tensor or SparseTensor objects for each in features.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2020-10-01 UTC."],[],[]]