sparsezoo package

Submodules

sparsezoo.main module

Script to download a model from sparse zoo

Download objects from the SparseZoo

positional arguments:

{download,search}

optional arguments:
-h, --help

show this help message and exit

[–sub-architecture SUB_ARCHITECTURE] [–framework FRAMEWORK] [–repo REPO] [–dataset DATASET] [–training-scheme TRAINING_SCHEME] [–optim-name OPTIM_NAME] [–optim-category OPTIM_CATEGORY] [–optim-target OPTIM_TARGET] [–release-version RELEASE_VERSION] [–page PAGE] [–page-length PAGE_LENGTH]

Search for objects from the repo.

optional arguments:
-h, --help

show this help message and exit

--domain DOMAIN

The domain of the model the object belongs to; e.g. cv, nlp

--sub-domain SUB_DOMAIN

The sub domain of the model the object belongs to; e.g. classification, segmentation

--architecture ARCHITECTURE

The architecture of the model the object belongs to; e.g. resnet_v1, mobilenet_v1

--sub-architecture SUB_ARCHITECTURE

The sub architecture (scaling factor) of the model the object belongs to; e.g. 50, 101, 152

--framework FRAMEWORK

The framework the model the object belongs to was trained on; e.g. pytorch, tensorflow

--repo REPO

The source repo for the model the object belongs to; e.g. sparseml, torchvision

--dataset DATASET

The dataset the model the object belongs to was trained on; e.g. imagenet, cifar10

--training-scheme TRAINING_SCHEME

The training scheme used on the model the object belongs to if any; e.g. augmented

--optim-name OPTIM_NAME

The name describing the optimization of the model the object belongs to, e.g. base, pruned, pruned_quant

--optim-category OPTIM_CATEGORY

The degree of optimization of the model the object belongs to; e.g. none, conservative (~100 baseline metric), moderate (>=99 baseline metric), aggressive (<99 baseline metric)

--optim-target OPTIM_TARGET

The deployment target of optimization of the model the object belongs to; e.g. edge, deepsparse, deepsparse_throughput, gpu

--release-version RELEASE_VERSION

the max release version of the model in semantic version format

--page PAGE

The page of search results to view

--page-length PAGE_LENGTH

The amount of search results per page to view

[–sub-architecture SUB_ARCHITECTURE] –framework FRAMEWORK –repo REPO –dataset DATASET [–training-scheme TRAINING_SCHEME] –optim-name OPTIM_NAME –optim-category OPTIM_CATEGORY [–optim-target OPTIM_TARGET] [–release-version RELEASE_VERSION] [–save-dir SAVE_DIR]

Download a specific model from the repo.

optional arguments:
-h, --help

show this help message and exit

--domain DOMAIN

The domain of the model the object belongs to; e.g. cv, nlp

--sub-domain SUB_DOMAIN

The sub domain of the model the object belongs to; e.g. classification, segmentation

--architecture ARCHITECTURE

The architecture of the model the object belongs to; e.g. resnet_v1, mobilenet_v1

--sub-architecture SUB_ARCHITECTURE

The sub architecture (scaling factor) of the model the object belongs to; e.g. 50, 101, 152

--framework FRAMEWORK

The framework the model the object belongs to was trained on; e.g. pytorch, tensorflow

--repo REPO

The source repo for the model the object belongs to; e.g. sparseml, torchvision

--dataset DATASET

The dataset the model the object belongs to was trained on; e.g. imagenet, cifar10

--training-scheme TRAINING_SCHEME

The training scheme used on the model the object belongs to if any; e.g. augmented

--optim-name OPTIM_NAME

The name describing the optimization of the model the object belongs to, e.g. base, pruned, pruned_quant

--optim-category OPTIM_CATEGORY

The degree of optimization of the model the object belongs to; e.g. none, conservative (~100 baseline metric), moderate (>=99 baseline metric), aggressive (<99 baseline metric)

--optim-target OPTIM_TARGET

The deployment target of optimization of the model the object belongs to; e.g. edge, deepsparse, deepsparse_throughput, gpu

--release-version RELEASE_VERSION

the max release version of the model in semantic version format

--save-dir SAVE_DIR

The directory to save the model files in, defaults to the cwd with the model description as a sub folder

sparsezoo.main.main()[source]

Module contents