Recommendation Compression

recommendation_compression(self, compression_method: ~netspresso.enums.compression.CompressionMethod, recommendation_method: ~netspresso.enums.compression.RecommendationMethod, recommendation_ratio: float, input_model_path: str, output_dir: str, input_shapes: ~typing.List[~typing.Dict[str, int]], framework: ~netspresso.enums.model.Framework = Framework.PYTORCH, options: ~netspresso.clients.compressor.v2.schemas.compression.base.RecommendationOptions = RecommendationOptions(reshape_channel_axis=-1, policy=<Policy.AVERAGE: 'average'>, layer_norm=<LayerNorm.STANDARD_SCORE: 'standard_score'>, group_policy=<GroupPolicy.AVERAGE: 'average'>, step_size=2, step_op=<StepOp.ROUND: 'round'>, reverse=False, min_num_of_value=8), dataset_path: str | None = None) → CompressorMetadata

Compress a recommendation-based model using the given compression and recommendation methods.

Parameters:

compression_method (CompressionMethod) – The selected compression method.
recommendation_method (RecommendationMethod) – The selected recommendation method.
recommendation_ratio (float) – The compression ratio recommended by the recommendation method.
input_model_path (str) – The file path where the model is located.
output_dir (str) – The local path to save the compressed model.
input_shapes (List[Dict[str, int]]) – Input shapes of the model.
framework (Framework, optional) – The framework of the model.
options (Options, optional) – The options for pruning method.
dataset_path (str, optional) – The path of the dataset used for nuclear norm compression method. Default is None.

Raises:

e – If an error occurs while performing recommendation compression.

Returns:

Compress metadata.

Return type:

CompressorMetadata

Details of Parameters

Compression Method

class CompressionMethod(value)[source]: An enumeration.

Available Compression Method

Name	Description
PR_L2	L2 Norm Pruning
PR_GM	GM Pruning
PR_NN	Nuclear Norm Pruning
PR_SNP	Structured Neuron-level Pruning
FD_TK	Tucker Decomposition
FD_SVD	Singular Value Decomposition

Example

from netspresso.enums import CompressionMethod

COMPRESSION_METHOD = CompressionMethod.PR_L2

Warning

Nuclear Norm is only supported in the Tensorflow-Keras framework.
Structured Neuron-level is only supported in the PyTorch and ONNX frameworks.

Note

Click on the link to learn more about the information. (Compression Method)

Recommendation Method

class RecommendationMethod(value)[source]: An enumeration.

Available Recommendation Method

Name	Description
SLAMP	Structured Layer-adaptive Sparsity for the Magnitude-based Pruning
VBMF	Variational Bayesian Matrix Factorization

Example

from netspresso.enums import RecommendationMethod

RECOMMENDATION_METHOD = RecommendationMethod.SLAMP

Note

If you selected PR_L2, PR_GM, PR_NN, PR_SNP for compression_method
- The recommended_method available is SLAMP.
If you selected FD_TK, FD_SVD for compression_method
- The recommended_method available is VBMF.

Recommendation Ratio

Note

SLAMP (Pruning ratio)
- Remove corresponding amounts of the filters. (e.g. 0.2 removes 20% of the filters in each layer)
- Available ranges
$0 <ratio < 1$
- Click the link for more information. (SLAMP)
VBMF (Calibration ratio)
- This function control compression level of model if the result of recommendation doesn’t meet the compression level user wants. Remained rank add or subtract (removed rank x calibration ratio) according to calibration ratio range.
- Available ranges
$https://latex.codecogs.com/svg.image?-1 \leq ratio \leq 1$
- Click the link for more information. (VBMF)

Options

Example

from netspresso.enums import Policy, LayerNorm, GroupPolicy
from netspresso.clients.compressor.v2.schemas import Options

OPTIONS = Options(
    policy=Policy.AVERAGE,
    layer_norm=LayerNorm.TSS_NORM,
    group_policy=GroupPolicy.COUNT,
    reshape_channel_axis=-1
)

Note

Click the link for more information. (Pruning Options)

Note

This parameter applies only to the Pruning Method (PR_L2, PR_GM, PR_NN, PR_SNP).

Example

from netspresso import NetsPresso
from netspresso.enums import CompressionMethod, RecommendationMethod


netspresso = NetsPresso(email="YOUR_EMAIL", password="YOUR_PASSWORD")

compressor = netspresso.compressor_v2()
compressed_model = compressor.recommendation_compression(
    compression_method=CompressionMethod.PR_L2,
    recommendation_method=RecommendationMethod.SLAMP,
    recommendation_ratio=0.5,
    input_model_path="./examples/sample_models/graphmodule.pt",
    output_dir="./outputs/compressed/graphmodule_recommend",
    input_shapes=[{"batch": 1, "channel": 3, "dimension": [224, 224]}],
)