gigl.common.beam.BetterWriteToTFRecord

class gigl.common.beam.better_tfrecordio.BetterWriteToTFRecord(file_path_prefix: str, transformed_metadata: DatasetMetadata | AsSingleton | None = None, file_name_suffix: str | None = '.tfrecord', compression_type: str | None = 'auto', max_bytes_per_shard: int | None = 200000000, num_shards: int | None = 0)

Bases: PTransform

Transform for writing to TFRecord sinks.

Methods

__init__	Initialize BetterWriteToTFRecord transform.
annotations
default_label
default_type_hints
display_data	Returns the display data associated to a pipeline component.
expand
from_runner_api
get_resource_hints
get_type_hints	Gets and/or initializes type hints for this object.
get_windowing	Returns the window function to be associated with transform's output.
infer_output_type
register_urn
runner_api_requires_keyed_input
to_runner_api
to_runner_api_parameter
to_runner_api_pickled
type_check_inputs
type_check_inputs_or_outputs
type_check_outputs
with_input_types	Annotates the input type of a PTransform with a type-hint.
with_output_types	Annotates the output type of a PTransform with a type-hint.
with_resource_hints	Adds resource hints to the PTransform.

__init__(file_path_prefix: str, transformed_metadata: DatasetMetadata | AsSingleton | None = None, file_name_suffix: str | None = '.tfrecord', compression_type: str | None = 'auto', max_bytes_per_shard: int | None = 200000000, num_shards: int | None = 0)

Initialize BetterWriteToTFRecord transform.

We improve the default WriteToTFRecord implementation by first simplifying needed params, adding functionality to cap the max bytes per shard. And, adding support for both easily serializing generic protobuff messages and tf.train.Example messages with capacity to specify deferred (computed at runtime) tft.tf_metadata.dataset_metadata.DatasetMetadata.

Args:

file_path_prefix (str): The file path to write to. The files written will begin

with this prefix, followed by a shard identifier, and end in a common extension, if given by file_name_suffix.

transformed_metadata (Optional[Union[dataset_metadata.DatasetMetadata, apache_beam.pvalue.AsSingleton]]):

Useful for encoding tf.train.Example, when reading a TFTransform fn (dataset_metadata.DatasetMetadata) or when building it for the first time (apache_beam.pvalue.AsSingleton[dataset_metadata.DatasetMetadata]). Defaults to None, meaning a generic protobuf message is assumed which will be encoded using SerializeToString().

file_name_suffix (str, optional): Suffix for the files written. Defaults to “.tfrecord”. compression_type (str, optional): Used to handle compressed output files. Typical value

is CompressionTypes.AUTO, in which case the file_path’s extension will be used to detect the compression.

max_bytes_per_shard (int, optional): The data is sharded into separate files to promote

faster/distributed writes. This parameter controls the max size of these shards. Defaults to int(2e8), or ~200 Mb.

num_shards (int, optional): The number of files (shards) used for output. If not set,

the service will decide on the optimal number of shards based off of max_bytes_per_shard. WARNING: Constraining the number of shards is likely to reduce the performance of a pipeline - only use if you know what you are doing.

classmethod __init_subclass__(*args, **kwargs)

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__or__(right)

Used to compose PTransforms, e.g., ptransform1 | ptransform2.

__repr__()

Return repr(self).

__ror__(left, label=None)

Used to apply this PTransform to non-PValues, e.g., a tuple.

__str__()

Return str(self).

__weakref__

list of weak references to the object (if defined)

display_data() → dict

Returns the display data associated to a pipeline component.

It should be reimplemented in pipeline components that wish to have static display data.

Returns:

Dict[str, Any]: A dictionary containing key:value pairs. The value might be an integer, float or string value; a DisplayDataItem for values that have more data (e.g. short value, label, url); or a HasDisplayData instance that has more display data that should be picked up. For example:

{
  'key1': 'string_value',
  'key2': 1234,
  'key3': 3.14159265,
  'key4': DisplayDataItem('apache.org', url='http://apache.org'),
  'key5': subComponent
}

get_type_hints()

Gets and/or initializes type hints for this object.

If type hints have not been set, attempts to initialize type hints in this order: - Using self.default_type_hints(). - Using self.__class__ type hints.

get_windowing(inputs: Any) → Windowing

Returns the window function to be associated with transform’s output.

By default most transforms just return the windowing function associated with the input PCollection (or the first input if several).

with_input_types(input_type_hint)

Annotates the input type of a PTransform with a type-hint.

Args:

input_type_hint (type): An instance of an allowed built-in type, a custom

class, or an instance of a TypeConstraint.

Raises:

TypeError: If input_type_hint is not a valid type-hint.

See apache_beam.typehints.typehints.validate_composite_type_param() for further details.

Returns:

PTransform: A reference to the instance of this particular PTransform object. This allows chaining type-hinting related methods.

with_output_types(type_hint)

Annotates the output type of a PTransform with a type-hint.

Args:

type_hint (type): An instance of an allowed built-in type, a custom class,

or a TypeConstraint.

Raises:

TypeError: If type_hint is not a valid type-hint. See

validate_composite_type_param() for further details.

Returns:

PTransform: A reference to the instance of this particular PTransform object. This allows chaining type-hinting related methods.

with_resource_hints(**kwargs) → PTransform

Adds resource hints to the PTransform.

Resource hints allow users to express constraints on the environment where the transform should be executed. Interpretation of the resource hints is defined by Beam Runners. Runners may ignore the unsupported hints.

Args:

**kwargs: key-value pairs describing hints and their values.

Raises:

ValueError: if provided hints are unknown to the SDK. See

apache_beam.transforms.resources for a list of known hints.

Returns:

PTransform: A reference to the instance of this particular PTransform object.