CCSD#

Here is the CCSD class to run the training and/or sampling pipeline.

ccsd.py: Code for the CCSD class for training and/or sampling.

class ccsd.diffusion.CCSD(type: str, config: str, folder: str = './', comment: str = '', seed: int = 42)[source]#

Bases: object

CCSD class for training and/or sampling.

__init__(type: str, config: str, folder: str = './', comment: str = '', seed: int = 42) → None[source]#

Initialize the CCSD class.

Parameters:

  • type (str) – Type of experiment. Choose from [“train”, “sample”].

  • config (str) – Path of config file

  • folder (str, optional) – Directory to save the results, load checkpoints, load config, etc. Defaults to “./”.

  • comment (str, optional) – A single line comment for the experiment. Defaults to “”.

  • seed (int, optional) – Random seed for reproducibility. Defaults to 42.

run() → None[source]#

Run the code for training and/or sampling.

Raises:

ValueError – raise and error the experiment type is not one of [train, sample].

is_trained() → bool[source]#

Check if the CCSD model is trained.

Returns:

True if the model is trained, False otherwise.

Return type:

bool

get_trainer() → Trainer[source]#

Get the trainer object.

Returns:

Trainer object.

Return type:

Trainer

get_sampler() → Sampler[source]#

Get the sampler object.

Returns:

Sampler object.

Return type:

Sampler

get_config() → EasyDict[source]#

Get the config object.

Returns:

Config object.

Return type:

EasyDict