Some TFX components use a description of your input data called a schema. The schema is an instance of schema.proto. It can specify data types for feature values, whether a feature has to be present in all examples, allowed value ranges, and other properties. A SchemaGen pipeline component will automatically generate a schema by inferring types, categories, and ranges from the training data.
- Consumes: statistics from a StatisticsGen component
- Emits: Data schema proto
Here's an excerpt from a schema proto:
...
feature {
name: "age"
value_count {
min: 1
max: 1
}
type: FLOAT
presence {
min_fraction: 1
min_count: 1
}
}
feature {
name: "capital-gain"
value_count {
min: 1
max: 1
}
type: FLOAT
presence {
min_fraction: 1
min_count: 1
}
}
...
The following TFX libraries use the schema:
- TensorFlow Data Validation
- TensorFlow Transform
- TensorFlow Model Analysis
In a typical TFX pipeline SchemaGen generates a schema, which is consumed by the other pipeline components. However, the auto-generated schema is best-effort and only tries to infer basic properties of the data. It is expected that developers review and modify it as needed.
The modified schema can be brought back into the pipeline using ImportSchemaGen component. The SchemaGen component for the initial schema generation can be removed and all downstream components can use the output of ImportSchemaGen. It is also recommended to add ExampleValidator using the imported schema to examine the training data continuously.
SchemaGen and TensorFlow Data Validation
SchemaGen makes extensive use of TensorFlow Data Validation for inferring a schema.
Using the SchemaGen Component
For the initial schema generation
A SchemaGen pipeline component is typically very easy to deploy and requires little customization. Typical code looks like this:
schema_gen = tfx.components.SchemaGen(
statistics=stats_gen.outputs['statistics'])
More details are available in the SchemaGen API reference.
For the reviewed schema import
Add ImportSchemaGen component to the pipeline to bring the reviewed schema definition into the pipeline.
schema_gen = tfx.components.ImportSchemaGen(
schema_file='/some/path/schema.pbtxt')
The schema_file should be a full path to the text protobuf file.
More details are available in the ImportSchemaGen API reference.