aimet - Robuta Search

https://quic.github.io/aimet-pages/AimetDocs/apiref/torch/generated/aimet_torch.nn.QuantizedConv3d.html QuantizedConv3d - AIMET https://quic.github.io/aimet-pages/releases/latest/_modules/aimet_torch/compress.html aimet_torch.compress - AIMET torch compress https://quic.github.io/aimet-pages/releases/latest/_modules/aimet_torch/_base/adaround/adaround_weight.html aimet_torch._base.adaround.adaround_weight - AIMET torch base weight https://quic.github.io/aimet-pages/releases/2.1.0/_modules/aimet_torch/_base/mixed_precision.html aimet_torch._base.mixed_precision - AIMET torch base mixed precision https://quic.github.io/aimet-pages/releases/latest/_modules/aimet_torch/_base/seq_mse.html aimet_torch._base.seq_mse - AIMET torch base seq mse https://quic.github.io/aimet-pages/AimetDocs/_modules/aimet_torch/_base/adaround/adaround_weight.html aimet_torch._base.adaround.adaround_weight - AIMET torch base weight https://quic.github.io/aimet-pages/releases/2.1.0/_modules/aimet_torch/v2/auto_quant.html aimet_torch.v2.auto_quant - AIMET torch auto quant https://aimet.tech/th/ Home - AIMET Apr 9, 2026 - Welcome To AIMET.tech Center of Excellence in Digital and AI for Mental Health Our mission is to create an ecosystem that cultivates mental health innovations... https://quic.github.io/aimet-pages/releases/latest/tutorials/notebooks/torch/quantization/bn_reestimation.html Quantization-Aware Training with BatchNorm Re-estimation - AIMET quantization aware training estimation https://quic.github.io/aimet-pages/releases/latest/apiref/onnx/amp.html aimet_onnx.mixed_precision - AIMET onnx mixed precision https://quic.github.io/aimet-pages/AimetDocs/overview/install/build_from_source.html Building from source - AIMET building from source https://quic.github.io/aimet-pages/releases/latest/_modules/aimet_torch/bn_reestimation.html aimet_torch.bn_reestimation - AIMET torch bn https://quic.github.io/aimet-pages/releases/latest/_modules/aimet_onnx/sequential_mse/seq_mse.html aimet_onnx.sequential_mse.seq_mse - AIMET onnx sequential mse https://quic.github.io/aimet-pages/AimetDocs/techniques/analysis_tools/index.html Analysis tools - AIMET analysis tools https://quic.github.io/aimet-pages/releases/latest/_modules/aimet_onnx/lite_mp.html aimet_onnx.lite_mp - AIMET onnx lite mp https://quic.github.io/aimet-pages/releases/2.1.0/_modules/aimet_torch/compress.html aimet_torch.compress - AIMET torch compress https://quic.github.io/aimet-pages/releases/latest/apiref/onnx/seq_mse.html aimet_onnx.apply_seq_mse - AIMET onnx apply seq mse https://quic.github.io/aimet-pages/releases/latest/tutorials/notebooks/onnx/quantization/AMP.html Automatic Mixed-Precision (AMP) - AIMET automatic mixed precision amp https://quic.github.io/aimet-pages/releases/latest/techniques/encoding_spec.html Encoding Format Specification - AIMET format specification encoding https://quic.github.io/aimet-pages/releases/2.3.0/examples/torch/quantization/qat_range_learning.html Quantization-aware training with range learning - AIMET quantization aware training range learning https://quic.github.io/aimet-pages/AimetDocs/_modules/aimet_torch/onnx.html aimet_torch.onnx - AIMET torch onnx https://quic.github.io/aimet-pages/AimetDocs/tutorials/notebooks/torch/quantization/qat_range_learning.html Quantization-aware training with range learning - AIMET quantization aware training range learning https://quic.github.io/aimet-pages/AimetDocs/apiref/torch/adascale.html aimet_torch.experimental.adascale - AIMET torch experimental https://www.qualcomm.com/news/onq/2021/09/neural-network-optimization-aimet Developers: Neural Network optimization with AIMET To run neural networks efficiently at the edge on mobile, IoT, and other embedded devices, developers strive to optimize their machine learning (ML) models'... neural network developers optimization https://quic.github.io/aimet-pages/releases/latest/glossary.html Glossary - AIMET glossary https://quic.github.io/aimet-pages/releases/latest/apiref/onnx/litemp.html aimet_onnx.lite_mp - AIMET onnx lite mp https://www.qualcomm.com/developer/software/ai-model-efficiency-toolkit AI Model Efficiency Toolkit (AIMET) | Qualcomm Developer AIMET provides advanced model quantization and compression techniques for trained neural network models, so that they run more efficiently. ai model efficiency toolkit qualcomm developer https://quic.github.io/aimet-pages/releases/latest/apiref/torch/model_validator.html aimet_torch.model_validator - AIMET torch model validator https://quic.github.io/aimet-pages/releases/latest/apiref/torch/bn.html aimet_torch.bn_reestimation - AIMET torch bn https://quic.github.io/aimet-pages/releases/latest/apiref/torch/adaround.html aimet_torch.adaround - AIMET torch https://quic.github.io/aimet-pages/releases/latest/apiref/torch/nn.html aimet_torch.nn - AIMET torch nn https://quic.github.io/aimet-pages/releases/latest/apiref/onnx/lpbq.html aimet_onnx.quantsim.set_lpbq_for_params - AIMET onnx set params https://quic.github.io/aimet-pages/releases/latest/tutorials/notebooks/onnx/quantization/cle.html Cross-Layer Equalization - AIMET cross layer equalization https://quic.github.io/aimet-pages/AimetDocs/ptq_techniques/bn.html Batch norm re-estimation - AIMET batch norm estimation https://quic.github.io/aimet-pages/releases/latest/apiref/torch/seq_mse.html aimet_torch.seq_mse - AIMET torch seq mse https://quic.github.io/aimet-pages/AimetDocs/techniques/blockwise.html Blockwise Quantization - AIMET blockwise quantization https://quic.github.io/aimet-pages/AimetDocs/apiref/torch/generated/aimet_torch.nn.QuantizedLocalResponseNorm.html QuantizedLocalResponseNorm - AIMET https://quic.github.io/aimet-pages/releases/latest/apiref/torch/quant_analyzer.html aimet_torch.quant_analyzer - AIMET torch quant analyzer https://quic.github.io/aimet-pages/AimetDocs/_modules/aimet_torch/defs.html aimet_torch.defs - AIMET torch defs https://quic.github.io/aimet-pages/releases/latest/tutorials/notebooks/torch/quantization/autoquant.html AutoQuant - AIMET https://quic.github.io/aimet-pages/releases/latest/tutorials/notebooks/torch/compression/channel_pruning.html Model compression using channel pruning - AIMET model compression using channel pruning https://quic.github.io/aimet-pages/releases/2.3.0/_modules/aimet_torch/_base/amp/mixed_precision_algo.html aimet_torch._base.amp.mixed_precision_algo - AIMET torch base amp mixed precision https://quic.github.io/aimet-pages/releases/latest/tutorials/notebooks/torch/quantization/quant_analyzer.html Quant Analyzer - AIMET quant analyzer https://quic.github.io/aimet-pages/releases/latest/ptq_techniques/quantized_LoRa/index.html Quantized LoRa - AIMET lora https://quic.github.io/aimet-pages/releases/latest/apiref/onnx/adaround.html aimet_onnx.apply_adaround - AIMET onnx apply https://quic.github.io/aimet-pages/AimetDocs/apiref/torch/generated/aimet_torch.quantization.affine.quantize_dequantize.html quantize_dequantize - AIMET quantize https://quic.github.io/aimet-pages/AimetDocs/techniques/compression/spatial_svd.html Spatial SVD - AIMET spatial svd https://quic.github.io/aimet-pages/releases/latest/_modules/aimet_torch/_base/amp/mixed_precision_algo.html aimet_torch._base.amp.mixed_precision_algo - AIMET torch base amp mixed precision https://quic.github.io/aimet-pages/releases/latest/apiref/torch/utils.html aimet_torch.utils - AIMET torch utils https://quic.github.io/aimet-pages/AimetDocs/apiref/torch/generated/aimet_torch.nn.QuantizedFold.html QuantizedFold - AIMET https://quic.github.io/aimet-pages/AimetDocs/apiref/torch/generated/aimet_torch.nn.QuantizedEmbeddingBag.html QuantizedEmbeddingBag - AIMET https://quic.github.io/aimet-pages/releases/latest/tutorials/notebooks/torch/compression/spatial_svd_channel_pruning.html Model compression using spatial SVD and channel pruning - AIMET model compression using spatial svd channel https://quic.github.io/aimet-pages/releases/2.1.0/_modules/aimet_torch/v2/quantsim/quantsim.html aimet_torch.v2.quantsim.quantsim - AIMET torch https://quic.github.io/aimet-pages/releases/latest/_modules/aimet_torch/cross_layer_equalization.html aimet_torch.cross_layer_equalization - AIMET torch cross layer equalization https://quic.github.io/aimet-pages/AimetDocs/tutorials/quantsim.html Quantization simulation guide - AIMET quantization simulation guide