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Defined in tensorflow/contrib/data/python/ops/error_ops.py.

Creates a Dataset from another Dataset and silently ignores any errors. (deprecated)

THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use tf.data.experimental.ignore_errors().

Use this transformation to produce a dataset that contains the same elements as the input, but silently drops any elements that caused an error. For example:

dataset = tf.data.Dataset.from_tensor_slices([1., 2., 0., 4.])

# Computing `tf.check_numerics(1. / 0.)` will raise an InvalidArgumentError.
dataset = dataset.map(lambda x: tf.check_numerics(1. / x, "error"))

# Using `ignore_errors()` will drop the element that causes an error.
dataset =
    dataset.apply(tf.contrib.data.ignore_errors())  # ==> { 1., 0.5, 0.2 }


A Dataset transformation function, which can be passed to tf.data.Dataset.apply.