tfdv.set_domain

Sets the domain for the input feature in the schema.

tfdv.set_domain(
    schema: schema_pb2.Schema,
    feature_path: tfdv.FeaturePath,
    domain: Any
) -> None

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.

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 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) ```


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<tr><th colspan="2"><h2 class="add-link">Raises</h2></th></tr>

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<td>
`TypeError`<a id="TypeError"></a>
</td>
<td>
If the input schema or the domain is not of the expected type.
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<td>
`ValueError`<a id="ValueError"></a>
</td>
<td>
If an invalid global string domain is provided as input.
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