Bunch

experimental.network_dynamics.Bunch()

Dictionary with attribute access for parameters.

A JAX PyTree-compatible parameter container that allows both dict[‘key’] and dict.key access patterns. Designed for neural dynamics parameters with support for JAX transformations.

Examples: >>> params = Bunch(a=1.0, b=2.0) >>> params.a # attribute access 1.0 >>> params[‘b’] # dict access 2.0 >>> jax.tree.map(lambda x: x * 2, params) # JAX transformations Bunch(a=2.0, b=4.0)

Methods

Name	Description
copy	Create a shallow copy of the Bunch.

copy

experimental.network_dynamics.Bunch.copy()

Create a shallow copy of the Bunch.

# Bunch { #tvboptim.experimental.network_dynamics.Bunch }

```python
experimental.network_dynamics.Bunch()
```

Dictionary with attribute access for parameters.

A JAX PyTree-compatible parameter container that allows both dict['key']
and dict.key access patterns. Designed for neural dynamics parameters
with support for JAX transformations.

Examples:
    >>> params = Bunch(a=1.0, b=2.0)
    >>> params.a  # attribute access
    1.0
    >>> params['b']  # dict access
    2.0
    >>> jax.tree.map(lambda x: x * 2, params)  # JAX transformations
    Bunch(a=2.0, b=4.0)

## Methods

| Name | Description |
| --- | --- |
| [copy](#tvboptim.experimental.network_dynamics.Bunch.copy) | Create a shallow copy of the Bunch. |

### copy { #tvboptim.experimental.network_dynamics.Bunch.copy }

```python
experimental.network_dynamics.Bunch.copy()
```

Create a shallow copy of the Bunch.