tfdv.set_domain

tfdv.set_domain(
    schema,
    feature_path,
    domain
)

Sets the domain for the input feature in the schema.

If the input feature already has a domain, it is overwritten with the newly provided input domain. This method cannot be used to add a new global domain.

Args:

  • schema: A Schema protocol buffer.
  • feature_path: The name of the feature whose domain needs to be set. If a FeatureName is passed, a one-step FeaturePath will be constructed and used. For example, "my_feature" -> types.FeaturePath(["my_feature"])
  • domain: A domain protocol buffer (one of IntDomain, FloatDomain, StringDomain or BoolDomain) or the name of a global string domain present in the input schema. Example: python >>> from tensorflow_metadata.proto.v0 import schema_pb2 >>> import tensorflow_data_validation as tfdv >>> schema = schema_pb2.Schema() >>> schema.feature.add(name='feature') # Setting a int domain. >>> int_domain = schema_pb2.IntDomain(min=3, max=5) >>> tfdv.set_domain(schema, "feature", int_domain) # Setting a string domain. >>> str_domain = schema_pb2.StringDomain(value=['one', 'two', 'three']) >>> tfdv.set_domain(schema, "feature", str_domain)

Raises:

  • TypeError: If the input schema or the domain is not of the expected type.
  • ValueError: If an invalid global string domain is provided as input.