hls4ml.model.optimizer.passes package
Submodules
hls4ml.model.optimizer.passes.bn_fuse module
- class hls4ml.model.optimizer.passes.bn_fuse.FuseBatchNormalization
Bases:
OptimizerPass
hls4ml.model.optimizer.passes.fuse_biasadd module
- class hls4ml.model.optimizer.passes.fuse_biasadd.FuseBiasAdd
Bases:
OptimizerPass
Fuses BiasAdd into Dense/Conv2D layer (common in TF models).
hls4ml.model.optimizer.passes.multi_dense module
- class hls4ml.model.optimizer.passes.multi_dense.ReplaceMultidimensionalDenseWithConv
Bases:
OptimizerPass
hls4ml.model.optimizer.passes.nop module
- class hls4ml.model.optimizer.passes.nop.EliminateLinearActivation
Bases:
OptimizerPass
hls4ml.model.optimizer.passes.precision_merge module
- class hls4ml.model.optimizer.passes.precision_merge.SetPrecisionConcat
Bases:
OptimizerPass
- match(node)
Predicate to match on a given node.
- Parameters:
node (Layer) – Node in the model graph to try matching the optimizer on.
- transform(model, node)
Set concat output precision
- hls4ml.model.optimizer.passes.precision_merge.get_concat_type(itype1, itype2)
hls4ml.model.optimizer.passes.qkeras module
hls4ml.model.optimizer.passes.stamp module
- class hls4ml.model.optimizer.passes.stamp.MakeStamp
Bases:
ModelOptimizerPass
hls4ml.model.optimizer.passes.transpose_opt module
- class hls4ml.model.optimizer.passes.transpose_opt.RemoveUselessTranspose
Bases:
OptimizerPass
- match(node)
Predicate to match on a given node.
- Parameters:
node (Layer) – Node in the model graph to try matching the optimizer on.
- transform(model, node)
Remove a transpose layer if it doesn’t do anything. i.e 1D input and perm = [0]