# `Jido.Evolve.Evolvable.HParams`
[🔗](https://github.com/agentjido/jido_evolve/blob/v1.0.0/lib/jido_evolve/evolvable/hparams.ex#L1)

Evolvable protocol implementation for hyperparameter maps.

Supports schema-driven evolution of mixed-type parameters:
- Floats with linear or log-scale bounds
- Integers with min/max bounds
- Enums (categorical choices)
- Lists of values with length constraints

## Schema Format

Bounds can be specified as either ranges (`min..max`) or tuples (`{min, max}`).
Note: Ranges only work for integer bounds (Elixir requirement). Use tuples for float bounds.

    %{
      learning_rate: {:float, {1.0e-5, 1.0e-1}, :log},
      hidden_layers: {:list, {:int, 16..256}, length: {1, 3}},
      dropout_rate: {:float, {0.0, 0.6}, :linear},
      activation: {:enum, [:relu, :tanh, :gelu]},
      batch_size: {:enum, [16, 32, 64, 128]}
    }

## Usage

    schema = %{learning_rate: {:float, {0.001, 0.1}, :log}}
    hparams = Jido.Evolve.Evolvable.HParams.new(schema)
    # => %{learning_rate: 0.0032}

# `new`

Creates a new random hyperparameter map from a schema.

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*Consult [api-reference.md](api-reference.md) for complete listing*