flytekit.extras.tensorflow.TensorFlowRecordsDirTransformer#
- class flytekit.extras.tensorflow.TensorFlowRecordsDirTransformer[source]#
TypeTransformer that supports serialising and deserialising to and from TFRecord directory. https://www.tensorflow.org/tutorials/load_data/tfrecord
Methods
- assert_type(t, v)#
- Parameters
t (Type[flytekit.core.type_engine.T]) –
v (flytekit.core.type_engine.T) –
- get_literal_type(t)[source]#
Converts the python type to a Flyte LiteralType
- Parameters
t (Type[flytekit.types.directory.types.FlyteDirectory.__class_getitem__.<locals>._SpecificFormatDirectoryClass]) –
- Return type
- guess_python_type(literal_type)[source]#
Converts the Flyte LiteralType to a python object type.
- Parameters
literal_type (flytekit.models.types.LiteralType) –
- Return type
Type[flytekit.types.directory.types.FlyteDirectory.__class_getitem__.<locals>._SpecificFormatDirectoryClass]
- to_html(ctx, python_val, expected_python_type)#
Converts any python val (dataframe, int, float) to a html string, and it will be wrapped in the HTML div
- Parameters
python_val (flytekit.core.type_engine.T) –
expected_python_type (Type[flytekit.core.type_engine.T]) –
- Return type
- to_literal(ctx, python_val, python_type, expected)[source]#
Converts a given python_val to a Flyte Literal, assuming the given python_val matches the declared python_type. Implementers should refrain from using type(python_val) instead rely on the passed in python_type. If these do not match (or are not allowed) the Transformer implementer should raise an AssertionError, clearly stating what was the mismatch :param ctx: A FlyteContext, useful in accessing the filesystem and other attributes :param python_val: The actual value to be transformed :param python_type: The assumed type of the value (this matches the declared type on the function) :param expected: Expected Literal Type
- Parameters
python_val (flytekit.types.directory.types.FlyteDirectory.__class_getitem__.<locals>._SpecificFormatDirectoryClass) –
python_type (Type[flytekit.types.directory.types.FlyteDirectory.__class_getitem__.<locals>._SpecificFormatDirectoryClass]) –
expected (flytekit.models.types.LiteralType) –
- Return type
- to_python_value(ctx, lv, expected_python_type)[source]#
Converts the given Literal to a Python Type. If the conversion cannot be done an AssertionError should be raised :param ctx: FlyteContext :param lv: The received literal Value :param expected_python_type: Expected native python type that should be returned
- Parameters
expected_python_type (Type[flytekit.types.directory.types.FlyteDirectory.__class_getitem__.<locals>._SpecificFormatDirectoryClass]) –
- Return type
tensorflow.python.data.ops.readers.TFRecordDatasetV2
Attributes
- TENSORFLOW_FORMAT = 'TensorFlowRecord'#
- name#
- python_type#
This returns the python type
- type_assertions_enabled#
Indicates if the transformer wants type assertions to be enabled at the core type engine layer