save_pretrained for serializing config.

[sayakpaul]

What does this PR do?

Follow-up of #11539.

Test code:

from diffusers.modular_pipelines import PipelineBlock

block = PipelineBlock.from_pretrained(
    "diffusers-internal-dev/modular-depth-block-sayak", trust_remote_code=True
)
block.save_pretrained("dummy")

Currently, it serializes the config.json. I think we agreed to manually save the block module that implements the custom block. It looks like so:

{
  "_class_name": "DepthProcessorBlock",
  "_component_names": [
    "depth_processor"
  ],
  "_diffusers_version": "0.34.0.dev0",
  "auto_map": {
    "PipelineBlock": "block.DepthProcessorBlock"
  }
}

diffusers-cli custom_blocks can also do the work. More details:
#11603 (comment)

More about the CLI stuff

Currently, for custom blocks, we need the block implementation module (say block.py), and the config.json, and an optional requirements.txt. @DN6 suggested a good idea over chat.

We let the user implement block.py (or any other module name) inside a folder. We then provide a CLI tool (diffusers-cli init-block ...) that would be run from the folder and spit out the following:

├── block.py
├── config.json
└── requirements.txt

So, the config.json will be created by the CLI command itself.

There will be some reasonable defaults to serialize a desired config.json file but we will also expose certain CLI args to let the users take fine-grained control (would come in handy in case there are multiple block implementations and scripts).

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[sayakpaul]

@DN6 I pushed an initial version of the diffusers-cli command we chatted about yesterday. Could you PTAL?

Provided you have implemented a block.py in a directory called custom_blocks, run:

diffusers-cli custom_blocks

And then it should spit out:

config.json
requirements.txt
block.py (should already be present)

This is a rough proposal, happy to iterate further.