Registry¶

Available Registries¶

Registries are Flash internal key-value database to store a mapping between a name and a function.

In simple words, they are just advanced dictionary storing a function from a key string.

Registries help organize code and make the functions accessible all across the Flash codebase. Each Flash Task can have several registries as static attributes.

Currently, Flash uses internally registries only for backbones, but more components will be added.

1. Imports¶

from functools import partial

from flash import Task
from flash.core.registry import FlashRegistry

2. Init a Registry¶

It is good practice to associate one or multiple registry to a Task as follow:

# creating a custom `Task` with its own registry
class MyImageClassifier(Task):
    backbones = FlashRegistry("backbones")

    def __init__(
        self,
        backbone: str = "resnet18",
        pretrained: bool = True,
    ):
        ...

        self.backbone, self.num_features = self.backbones.get(backbone)(pretrained=pretrained)

3. Adding new functions¶

Your custom functions can be registered within a FlashRegistry as a decorator or directly.

# Option 1: Used with partial.
def fn(backbone: str, pretrained: bool = True):
    # Create backbone and backbone output dimension (`num_features`)
    backbone, num_features = None, None
    return backbone, num_features


# HINT 1: Use `from functools import partial` if you want to store some arguments.
MyImageClassifier.backbones(fn=partial(fn, backbone="my_backbone"), name="username/partial_backbone")


# Option 2: Using decorator.
@MyImageClassifier.backbones(name="username/decorated_backbone")
def fn(pretrained: bool = True):
    # Create backbone and backbone output dimension (`num_features`)
    backbone, num_features = None, None
    return backbone, num_features

4. Accessing registered functions¶

You can now access your function from your task!

# 3.b Optional: List available backbones
print(MyImageClassifier.available_backbones())

# 4. Build the model
model = MyImageClassifier(backbone="username/decorated_backbone")

Here’s the output:

['username/decorated_backbone', 'username/partial_backbone']

5. Pre-registered backbones¶

Flash provides populated registries containing lots of available backbones.

Example:

from flash.image.backbones import OBJ_DETECTION_BACKBONES
from flash.image.classification.backbones import IMAGE_CLASSIFIER_BACKBONES

print(IMAGE_CLASSIFIER_BACKBONES.available_keys())
""" out:
['adv_inception_v3', 'cspdarknet53', 'cspdarknet53_iabn', 430+.., 'xception71']
"""