All modules for which code is available
- akida.core
- akida.layers.add
- akida.layers.attention
- akida.layers.batch_normalization
- akida.layers.concatenate
- akida.layers.conv2d
- akida.layers.conv2d_transpose
- akida.layers.convolutional
- akida.layers.dense1d
- akida.layers.dense2d
- akida.layers.depthwise_conv2d
- akida.layers.depthwise_conv2d_transpose
- akida.layers.dequantizer
- akida.layers.extract_token
- akida.layers.fully_connected
- akida.layers.input_conv2d
- akida.layers.input_convolutional
- akida.layers.input_data
- akida.layers.madnorm
- akida.layers.separable_convolutional
- akida.layers.shiftmax
- akida.layers.stem
- akida.sparsity
- akida.virtual_devices
- akida_models.centernet.centernet_batch_generator
- akida_models.centernet.centernet_loss
- akida_models.centernet.centernet_processing
- akida_models.centernet.model_centernet
- akida_models.detection.batch_generator
- akida_models.detection.box_utils
- akida_models.detection.generate_anchors
- akida_models.detection.map_evaluation
- akida_models.detection.model_yolo
- akida_models.detection.processing
- akida_models.distiller
- akida_models.extract
- akida_models.gamma_constraint
- akida_models.imagenet.model_akidanet
- akida_models.imagenet.model_akidanet18
- akida_models.imagenet.model_akidanet_edge
- akida_models.imagenet.model_mobilenet
- akida_models.imagenet.preprocessing
- akida_models.kws.model_ds_cnn
- akida_models.kws.preprocessing
- akida_models.layer_blocks
- akida_models.macs
- akida_models.mnist.model_gxnor
- akida_models.model_io
- akida_models.modelnet40.model_pointnet_plus
- akida_models.modelnet40.preprocessing
- akida_models.portrait128.model_akida_unet
- akida_models.transformers.model_deit
- akida_models.transformers.model_vit
- akida_models.unfuse_sepconv_layers
- akida_models.utils
- akida_models.utk_face.model_vgg
- akida_models.utk_face.preprocessing
- cnn2snn.akida_versions
- cnn2snn.calibration.adaround
- cnn2snn.calibration.bias_correction
- cnn2snn.calibration.calibration
- cnn2snn.converter
- cnn2snn.min_value_constraint
- cnn2snn.quantization
- cnn2snn.quantization_layers
- cnn2snn.quantization_ops
- cnn2snn.quantizeml.compatibility_checks
- cnn2snn.transforms.batch_normalization
- cnn2snn.transforms.equalization
- cnn2snn.transforms.reshape
- cnn2snn.transforms.sequential
- cnn2snn.utils
- quantizeml.layers.activations
- quantizeml.layers.attention
- quantizeml.layers.batch_normalization
- quantizeml.layers.convolution
- quantizeml.layers.dense
- quantizeml.layers.depthwise_convolution
- quantizeml.layers.dropout
- quantizeml.layers.multi_inbounds
- quantizeml.layers.normalization
- quantizeml.layers.output_observer
- quantizeml.layers.pooling
- quantizeml.layers.quantization_params
- quantizeml.layers.quantizers.aligned_weight_quantizer
- quantizeml.layers.quantizers.output_quantizer
- quantizeml.layers.quantizers.quantizers
- quantizeml.layers.quantizers.weight_quantizer
- quantizeml.layers.recorders
- quantizeml.layers.rescaling
- quantizeml.layers.reshaping.flatten
- quantizeml.layers.reshaping.permute
- quantizeml.layers.reshaping.reshape
- quantizeml.layers.separable_convolution
- quantizeml.layers.shiftmax
- quantizeml.layers.vit
- quantizeml.models.calibrate
- quantizeml.models.check_quantization
- quantizeml.models.quantize
- quantizeml.models.record
- quantizeml.models.transforms.align_rescaling
- quantizeml.models.transforms.fold_batchnorms
- quantizeml.models.transforms.insert_layer
- quantizeml.models.transforms.invert_batchnorm_pooling
- quantizeml.models.transforms.relu_maxpool
- quantizeml.models.transforms.remove_zeropadding2d
- quantizeml.models.transforms.replace_lambda
- quantizeml.models.transforms.sanitize
- quantizeml.models.utils
- quantizeml.tensors.fixed_point
- quantizeml.tensors.qfloat
- quantizeml.tensors.qtensor