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- autoapi/neural_compressor
- adaptor
- mxnet_utils
- util
- ox_utils
- calibration
- calibrator
- operators
- activation
- argmax
- attention
- binary_op
- concat
- conv
- direct_q8
- embed_layernorm
- gather
- gavgpool
- gemm
- lstm
- matmul
- maxpool
- norm
- ops
- pad
- pooling
- reduce
- resize
- split
- unary_op
- quantizer
- smooth_quant
- util
- weight_only
- tensorflow
- tf_utils
- graph_converter
- graph_converter_without_calib
- graph_rewriter
- bf16
- bf16_convert
- dequantize_cast_optimizer
- generic
- convert_add_to_biasadd
- convert_layout
- convert_leakyrelu
- convert_nan_to_random
- convert_placeholder_to_const
- dilated_contraction
- dummy_biasadd
- expanddims_optimizer
- fetch_weight_from_reshape
- fold_batch_norm
- fold_constant
- fuse_biasadd_add
- fuse_column_wise_mul
- fuse_conv_with_math
- fuse_decomposed_bn
- fuse_decomposed_in
- fuse_gelu
- fuse_layer_norm
- fuse_pad_with_conv
- fuse_pad_with_fp32_conv
- fuse_reshape_transpose
- graph_cse_optimizer
- grappler_pass
- insert_print_node
- move_squeeze_after_relu
- pre_optimize
- remove_training_nodes
- rename_batch_norm
- strip_equivalent_nodes
- strip_unused_nodes
- switch_optimizer
- graph_base
- int8
- freeze_fake_quant
- freeze_value
- freeze_value_without_calib
- fuse_conv_redundant_dequantize
- fuse_conv_requantize
- fuse_matmul_redundant_dequantize
- fuse_matmul_requantize
- meta_op_optimizer
- post_hostconst_converter
- post_quantized_op_cse
- rnn_convert
- scale_propagation
- onnx
- onnx_graph
- onnx_node
- onnx_schema
- tf2onnx_utils
- qdq
- insert_qdq_pattern
- merge_duplicated_qdq
- graph_util
- quantize_graph
- qat
- fake_quantize
- quantize_config
- quantize_helper
- quantize_layers
- optimize_layer
- quantize_layer_add
- quantize_layer_base
- quantize_layer_bn
- quantize_wrapper
- qdq
- fuse_qdq_bn
- fuse_qdq_concatv2
- fuse_qdq_conv
- fuse_qdq_deconv
- fuse_qdq_in
- fuse_qdq_matmul
- fuse_qdq_pooling
- optimize_qdq
- quantize_graph_base
- quantize_graph_bn
- quantize_graph_concatv2
- quantize_graph_conv
- quantize_graph_for_intel_cpu
- quantize_graph_matmul
- quantize_graph_pooling
- quantize_graph_common
- smooth_quant_calibration
- smooth_quant_scaler
- tf2onnx_converter
- transform_graph
- bias_correction
- graph_transform_base
- insert_logging
- rerange_quantized_concat
- util
- torch_utils
- bf16_convert
- hawq_metric
- layer_wise_quant
- modified_pickle
- quantize
- torch_load
- utils
- model_wrapper
- pattern_detector
- symbolic_trace
- util
- algorithm
- algorithm
- fast_bias_correction
- smooth_quant
- weight_correction
- benchmark
- common
- base_config
- base_tuning
- benchmark
- tuning_param
- utils
- constants
- logger
- save_load
- utility
- version
- compression
- callbacks
- distillation
- criterions
- optimizers
- utility
- hpo
- sa_optimizer
- pruner
- criteria
- model_slim
- auto_slim
- pattern_analyzer
- weight_slim
- patterns
- base
- mha
- ninm
- nxm
- pruners
- base
- basic
- block_mask
- mha
- pattern_lock
- progressive
- retrain_free
- pruning
- regs
- schedulers
- tf_criteria
- utils
- wanda
- utils
- config
- contrib
- strategy
- sigopt
- tpe
- data
- dataloaders
- base_dataloader
- dataloader
- default_dataloader
- fetcher
- mxnet_dataloader
- onnxrt_dataloader
- pytorch_dataloader
- sampler
- tensorflow_dataloader
- datasets
- bert_dataset
- coco_dataset
- dataset
- dummy_dataset
- dummy_dataset_v2
- imagenet_dataset
- style_transfer_dataset
- filters
- coco_filter
- filter
- transforms
- imagenet_transform
- postprocess
- tokenization
- transform
- metric
- bleu
- bleu_util
- coco_label_map
- coco_tools
- evaluate_squad
- f1
- metric
- mix_precision
- model
- base_model
- keras_model
- model
- mxnet_model
- nets_factory
- onnx_model
- tensorflow_model
- torch_model
- objective
- profiling
- parser
- factory
- onnx_parser
- factory
- parser
- parser
- result
- tensorflow_parser
- factory
- parser
- profiler
- factory
- onnxrt_profiler
- factory
- profiler
- utils
- profiler
- tensorflow_profiler
- factory
- profiler
- utils
- quantization
- strategy
- auto
- auto_mixed_precision
- basic
- bayesian
- conservative
- exhaustive
- hawq_v2
- mse
- mse_v2
- random
- strategy
- utils
- constant
- tuning_sampler
- tuning_space
- tuning_structs
- utility
- template/api_doc_example
- tensorflow
- algorithms
- smoother
- calibration
- core
- scaler
- static_quant
- keras
- tensorflow
- keras
- layers
- conv2d
- dense
- depthwise_conv2d
- layer_initializer
- pool2d
- separable_conv2d
- quantization
- config
- quantization
- algorithm_entry
- autotune
- config
- quantize
- utils
- graph_converter
- graph_rewriter
- bf16
- bf16_convert
- dequantize_cast_optimizer
- generic
- convert_add_to_biasadd
- convert_layout
- convert_leakyrelu
- convert_nan_to_random
- convert_placeholder_to_const
- dilated_contraction
- dummy_biasadd
- expanddims_optimizer
- fetch_weight_from_reshape
- fold_batch_norm
- fold_constant
- fuse_biasadd_add
- fuse_column_wise_mul
- fuse_conv_with_math
- fuse_decomposed_bn
- fuse_decomposed_in
- fuse_gelu
- fuse_layer_norm
- fuse_pad_with_conv
- fuse_pad_with_fp32_conv
- fuse_reshape_transpose
- graph_cse_optimizer
- grappler_pass
- insert_print_node
- move_squeeze_after_relu
- pre_optimize
- remove_training_nodes
- rename_batch_norm
- strip_equivalent_nodes
- strip_unused_nodes
- switch_optimizer
- graph_base
- int8
- freeze_fake_quant
- freeze_value
- fuse_conv_redundant_dequantize
- fuse_conv_requantize
- fuse_matmul_redundant_dequantize
- fuse_matmul_requantize
- meta_op_optimizer
- post_hostconst_converter
- post_quantized_op_cse
- scale_propagation
- qdq
- insert_qdq_pattern
- merge_duplicated_qdq
- graph_util
- quantize_graph
- qdq
- fuse_qdq_bn
- fuse_qdq_concatv2
- fuse_qdq_conv
- fuse_qdq_deconv
- fuse_qdq_in
- fuse_qdq_matmul
- fuse_qdq_pooling
- optimize_qdq
- quantize_graph_base
- quantize_graph_bn
- quantize_graph_concatv2
- quantize_graph_conv
- quantize_graph_for_intel_cpu
- quantize_graph_matmul
- quantize_graph_pooling
- quantize_graph_common
- transform_graph
- bias_correction
- graph_transform_base
- insert_logging
- rerange_quantized_concat
- utility
- utils
- constants
- data
- model
- model_wrappers
- utility
- torch
- algorithms
- base_algorithm
- fp8_quant
- observer
- patched_module_base
- scaling_method_base
- utils/logger
- layer_wise
- load
- modified_pickle
- utils
- mixed_precision
- half_precision_convert
- module_wrappers
- mx_quant
- mx
- utils
- pt2e_quant
- core
- half_precision_rewriter
- save_load
- utility
- smooth_quant
- save_load
- smooth_quant
- utility
- static_quant
- save_load
- static_quant
- utility
- weight_only
- autoround
- awq
- gptq
- hqq
- bitpack
- config
- core
- optimizer
- qtensor
- quantizer
- modules
- rtn
- save_load
- teq
- utility
- export
- pt2e_export
- quantization
- algorithm_entry
- autotune
- config
- quantize
- save_load_entry
- utils
- auto_accelerator
- bit_packer
- block_wise
- constants
- environ
- utility
- training
- transformers
- quantization/utils
- utils
- quantization_config
- utils
- collect_layer_histogram
- constant
- create_obj_from_config
- export
- qlinear2qdq
- tf2onnx
- torch2onnx
- kl_divergence
- load_huggingface
- logger
- options
- pytorch
- utility
- weights_details
- version
- docs
- build_docs/source
- source
- 3x
- api-doc
- adaptor
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