AI Model Efficiency Toolkit
tf-torch-cpu_1.26.1
Quantization User Guide
Use Cases
AIMET Quantization Features
AIMET Quantization Workflow
Debugging Guidelines
Compression User Guide
Overview
Use Case
Compression ratio selection
Visualization
Overview
Design
Compression
Starting a Bokeh Server Session:
How to use the tool
Model Compression
Weight SVD
Spatial SVD
Channel Pruning
Overall Procedure
Channel Selection
Winnowing
Weight Reconstruction
Optional techniques to get better compression results
Rank Rounding
Per-layer Fine-tuning
FAQs
References
API Documentation
AIMET APIs for PyTorch
PyTorch Model Quantization API
PyTorch Model Compression API
Introduction
Top-level API for Compression
Greedy Selection Parameters
TAR Selection Parameters
Spatial SVD Configuration
Weight SVD Configuration
Channel Pruning Configuration
Configuration Definitions
Code Examples
PyTorch Model Visualization API for Compression
Top-level API Compression
Code Examples
PyTorch Model Visualization API for Quantization
Top-level API Quantization
Code Examples
AIMET APIs for TensorFlow
TensorFlow Model Guidelines
TensorFlow Model Quantization API
TensorFlow Model Compression API
Introduction
Top-level API for Compression
Greedy Selection Parameters
Spatial SVD Configuration
Channel Pruning Configuration
Configuration Definitions
Code Examples
Weight SVD Top-level API
Code Examples for Weight SVD
TensorFlow Model Visualization API for Quantization
Top-level API for Visualization of Weight tensors
Code Examples for Visualization of Weight tensors
Using AIMET Tensorflow APIs with Keras Models
Introduction
APIs
Code Example
Utility Functions
AIMET APIs for Keras
Keras Model Quantization API
AIMET APIs for ONNX
ONNX Model Quantization API
Indices and tables
Examples Documentation
Browse the notebooks
Running the notebooks
Install Jupyter
Download the Example notebooks and related code
Run the notebooks
AI Model Efficiency Toolkit
Index
Index
A
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B
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C
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D
|
E
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F
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G
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L
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M
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N
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O
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P
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Q
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R
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S
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T
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U
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V
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W
A
ActivationType (class in aimet_common.defs)
AdaroundParameters (class in aimet_tensorflow.adaround.adaround_weight)
,
[1]
(class in aimet_torch.adaround.adaround_weight)
analytical_bias_correction_per_layer() (in module aimet_tensorflow.bias_correction.BiasCorrection)
analyze() (aimet_tensorflow.quant_analyzer.QuantAnalyzer method)
(aimet_torch.quant_analyzer.QuantAnalyzer method)
apply() (aimet_tensorflow.auto_quant.AutoQuant method)
(aimet_torch.auto_quant.AutoQuant method)
apply_adaround() (in module aimet_tensorflow.adaround.adaround_weight.Adaround)
(in module aimet_torch.adaround.adaround_weight.Adaround)
auto (aimet_tensorflow.defs.ChannelPruningParameters.Mode attribute)
(aimet_tensorflow.defs.SpatialSvdParameters.Mode attribute)
(aimet_torch.defs.ChannelPruningParameters.Mode attribute)
(aimet_torch.defs.SpatialSvdParameters.Mode attribute)
(aimet_torch.defs.WeightSvdParameters.Mode attribute)
AutoQuant (class in aimet_tensorflow.auto_quant)
(class in aimet_torch.auto_quant)
(class in aimet_torch.auto_quant_v2)
B
bias_correction_per_layer() (in module aimet_tensorflow.bias_correction.BiasCorrection)
bias_fold() (in module aimet_tensorflow.cross_layer_equalization.HighBiasFold)
,
[1]
(in module aimet_tensorflow.keras.cross_layer_equalization.HighBiasFold)
,
[1]
(in module aimet_torch.cross_layer_equalization.HighBiasFold)
,
[1]
BiasCorrectionParams() (in module aimet_tensorflow.bias_correction)
C
channel_pruning (aimet_common.defs.CompressionScheme attribute)
ChannelPruningParameters (class in aimet_tensorflow.defs)
(class in aimet_torch.defs)
ChannelPruningParameters.AutoModeParams (class in aimet_tensorflow.defs)
(class in aimet_torch.defs)
ChannelPruningParameters.ManualModeParams (class in aimet_tensorflow.defs)
(class in aimet_torch.defs)
ChannelPruningParameters.Mode (class in aimet_tensorflow.defs)
(class in aimet_torch.defs)
check_model_arch() (in module aimet_torch.arch_checker.arch_checker.ArchChecker)
ClsSetInfo (class in aimet_tensorflow.cross_layer_equalization)
(class in aimet_tensorflow.keras.cross_layer_equalization)
(class in aimet_torch.cross_layer_equalization)
ClsSetInfo.ClsSetLayerPairInfo (class in aimet_tensorflow.cross_layer_equalization)
(class in aimet_tensorflow.keras.cross_layer_equalization)
(class in aimet_torch.cross_layer_equalization)
compress_model() (aimet_tensorflow.compress.ModelCompressor static method)
(aimet_torch.compress.ModelCompressor static method)
compress_net() (aimet_tensorflow.svd.Svd method)
CompressionScheme (class in aimet_common.defs)
compute_encodings() (aimet_onnx.quantsim.QuantizationSimModel method)
(aimet_tensorflow.keras.quantsim.QuantizationSimModel method)
(aimet_tensorflow.quantsim.QuantizationSimModel method)
(aimet_torch.quantsim.QuantizationSimModel method)
ConvBnInfoType (class in aimet_common.bias_correction)
correct_bias() (in module aimet_tensorflow.bias_correction.BiasCorrection)
(in module aimet_torch.bias_correction)
CostMetric (class in aimet_common.defs)
D
display_comp_ratio_plot() (aimet_torch.visualize_serialized_data.VisualizeCompression method)
display_eval_scores() (aimet_torch.visualize_serialized_data.VisualizeCompression method)
E
enable_per_layer_mse_loss() (aimet_torch.quant_analyzer.QuantAnalyzer method)
equalize_model() (in module aimet_onnx.cross_layer_equalization)
(in module aimet_tensorflow.cross_layer_equalization)
(in module aimet_tensorflow.keras.cross_layer_equalization)
(in module aimet_torch.cross_layer_equalization)
export() (aimet_onnx.quantsim.QuantizationSimModel method)
(aimet_tensorflow.keras.quantsim.QuantizationSimModel method)
(aimet_tensorflow.quantsim.QuantizationSimModel method)
(aimet_torch.quantsim.QuantizationSimModel method)
F
fold_all_batch_norms() (in module aimet_tensorflow.batch_norm_fold)
(in module aimet_tensorflow.keras.batch_norm_fold)
(in module aimet_torch.batch_norm_fold)
fold_all_batch_norms_to_scale() (in module aimet_tensorflow.batch_norm_fold)
(in module aimet_tensorflow.keras.batch_norm_fold)
(in module aimet_torch.batch_norm_fold)
fold_given_batch_norms() (in module aimet_tensorflow.batch_norm_fold)
(in module aimet_tensorflow.keras.batch_norm_fold)
(in module aimet_torch.batch_norm_fold)
G
get_quant_scheme_candidates() (aimet_torch.auto_quant_v2.AutoQuant method)
GreedySelectionParameters (class in aimet_common.defs)
L
load_checkpoint() (aimet_torch.quantsim method)
load_keras_model_multi_gpu() (in module aimet_tensorflow.utils.convert_tf_sess_to_keras)
load_tf_sess_variables_to_keras_single_gpu() (in module aimet_tensorflow.utils.convert_tf_sess_to_keras)
M
mac (aimet_common.defs.CostMetric attribute)
manual (aimet_tensorflow.defs.ChannelPruningParameters.Mode attribute)
(aimet_tensorflow.defs.SpatialSvdParameters.Mode attribute)
(aimet_torch.defs.ChannelPruningParameters.Mode attribute)
(aimet_torch.defs.SpatialSvdParameters.Mode attribute)
(aimet_torch.defs.WeightSvdParameters.Mode attribute)
map_cls_sets_to_new_session() (aimet_tensorflow.cross_layer_equalization.ClsSetInfo static method)
memory (aimet_common.defs.CostMetric attribute)
ModelCompressor (class in aimet_tensorflow.compress)
(class in aimet_torch.compress)
ModuleCompRatioPair (class in aimet_tensorflow.defs)
(class in aimet_torch.defs)
N
no_activation (aimet_common.defs.ActivationType attribute)
O
optimize() (aimet_torch.auto_quant_v2.AutoQuant method)
P
post_training_percentile (aimet_common.defs.QuantScheme attribute)
,
[1]
,
[2]
,
[3]
post_training_tf (aimet_common.defs.QuantScheme attribute)
,
[1]
,
[2]
,
[3]
post_training_tf_enhanced (aimet_common.defs.QuantScheme attribute)
,
[1]
,
[2]
,
[3]
prepare_model() (in module aimet_tensorflow.keras.model_preparer)
(in module aimet_torch.model_preparer)
Q
QuantAnalyzer (class in aimet_tensorflow.quant_analyzer)
(class in aimet_torch.quant_analyzer)
QuantizationSimModel (class in aimet_onnx.quantsim)
(class in aimet_tensorflow.keras.quantsim)
(class in aimet_tensorflow.quantsim)
(class in aimet_torch.quantsim)
QuantParams (class in aimet_tensorflow.bias_correction)
(class in aimet_torch.quantsim)
QuantScheme (class in aimet_common.defs)
,
[1]
,
[2]
,
[3]
R
reestimate_bn_stats() (in module aimet_tensorflow.bn_reestimation)
(in module aimet_tensorflow.keras.bn_reestimation)
(in module aimet_torch.bn_reestimation)
relu (aimet_common.defs.ActivationType attribute)
relu6 (aimet_common.defs.ActivationType attribute)
run_inference() (aimet_torch.auto_quant_v2.AutoQuant method)
S
save_as_tf_module_multi_gpu() (in module aimet_tensorflow.utils.convert_tf_sess_to_keras)
save_checkpoint() (aimet_torch.quantsim method)
save_tf_session_single_gpu() (in module aimet_tensorflow.utils.convert_tf_sess_to_keras)
scale_cls_sets() (in module aimet_tensorflow.cross_layer_equalization.CrossLayerScaling)
(in module aimet_tensorflow.keras.cross_layer_equalization.CrossLayerScaling)
(in module aimet_torch.cross_layer_equalization.CrossLayerScaling)
scale_model() (in module aimet_tensorflow.cross_layer_equalization.CrossLayerScaling)
(in module aimet_tensorflow.keras.cross_layer_equalization.CrossLayerScaling)
(in module aimet_torch.cross_layer_equalization.CrossLayerScaling)
set_adaround_params() (aimet_tensorflow.auto_quant.AutoQuant method)
(aimet_torch.auto_quant.AutoQuant method)
(aimet_torch.auto_quant_v2.AutoQuant method)
set_export_params() (aimet_torch.auto_quant.AutoQuant method)
(aimet_torch.auto_quant_v2.AutoQuant method)
set_model_preparer_params() (aimet_torch.auto_quant_v2.AutoQuant method)
set_quant_scheme_candidates() (aimet_torch.auto_quant_v2.AutoQuant method)
spatial_svd (aimet_common.defs.CompressionScheme attribute)
SpatialSvdParameters (class in aimet_tensorflow.defs)
(class in aimet_torch.defs)
SpatialSvdParameters.AutoModeParams (class in aimet_tensorflow.defs)
(class in aimet_torch.defs)
SpatialSvdParameters.ManualModeParams (class in aimet_tensorflow.defs)
(class in aimet_torch.defs)
SpatialSvdParameters.Mode (class in aimet_tensorflow.defs)
(class in aimet_torch.defs)
Svd (class in aimet_tensorflow.svd)
T
TarRankSelectionParameters (class in aimet_torch.defs)
training_range_learning_with_tf_enhanced_init (aimet_common.defs.QuantScheme attribute)
,
[1]
,
[2]
,
[3]
training_range_learning_with_tf_init (aimet_common.defs.QuantScheme attribute)
,
[1]
,
[2]
,
[3]
U
update_keras_bn_ops_trainable_flag() (in module aimet_tensorflow.utils.graph)
V
visualize_changes_after_optimization() (in module aimet_torch.visualize_model)
visualize_relative_weight_ranges_single_layer() (in module aimet_tensorflow.plotting_utils)
visualize_relative_weight_ranges_to_identify_problematic_layers() (in module aimet_torch.visualize_model)
visualize_weight_ranges() (in module aimet_torch.visualize_model)
visualize_weight_ranges_single_layer() (in module aimet_tensorflow.plotting_utils)
VisualizeCompression (class in aimet_torch.visualize_serialized_data)
W
weight_svd (aimet_common.defs.CompressionScheme attribute)
WeightSvdParameters (class in aimet_torch.defs)
WeightSvdParameters.AutoModeParams (class in aimet_torch.defs)
WeightSvdParameters.ManualModeParams (class in aimet_torch.defs)
WeightSvdParameters.Mode (class in aimet_torch.defs)