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tf.compat.v1.data.TFRecordDataset

A Dataset comprising records from one or more TFRecord files.

Inherits From: Dataset, Dataset

filenames A tf.string tensor or tf.data.Dataset containing one or more filenames.
compression_type (Optional.) A tf.string scalar evaluating to one of "" (no compression), "ZLIB", or "GZIP".
buffer_size (Optional.) A tf.int64 scalar representing the number of bytes in the read buffer. If your input pipeline is I/O bottlenecked, consider setting this parameter to a value 1-100 MBs. If None, a sensible default for both local and remote file systems is used.
num_parallel_reads (Optional.) A tf.int64 scalar representing the number of files to read in parallel. If greater than one, the records of files read in parallel are outputted in an interleaved order. If your input pipeline is I/O bottlenecked, consider setting this parameter to a value greater than one to parallelize the I/O. If None, files will be read sequentially.
name (Optional.) A name for the tf.data operation.

TypeError If any argument does not have the expected type.
ValueError If any argument does not have the expected shape.

element_spec The type specification of an element of this dataset.

dataset = tf.data.Dataset.from_tensor_slices([1, 2, 3])
dataset.element_spec
TensorSpec(shape=(), dtype=tf.int32, name=None)

For more information, read this guide.

output_classes Returns the class of each component of an element of this dataset. (deprecated)

output_shapes Returns the shape of each component of an element of this dataset. (deprecated)
output_types Returns the type of each component of an element of this dataset. (deprecated)

Methods

apply

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Applies a transformation function to this dataset.

apply enables chaining of custom Dataset transformations, which are represented as functions that take one Dataset argument and return a transformed Dataset.

dataset = tf.data.Dataset.range(100)
def dataset_fn(ds):
  return ds.filter(lambda x: x < 5)
dataset = dataset.apply(dataset_fn)
list(dataset.as_numpy_iterator())
[0, 1, 2, 3, 4]

Args
transformation_func A function that takes one Dataset argument and returns a Dataset.

Returns
Dataset The Dataset returned by applying transformation_func to this dataset.

as_numpy_iterator

View source

Returns an iterator which converts all elements of the dataset to numpy.

Use as_numpy_iterator to inspect the content of your dataset. To see element shapes and types, print d