Quantization

The Arm Ethos-U delegate only supports the execution of quantized models. To quantize a model so that is supported by this delegate, the EthosUQuantizer should be used.

Currently, the symmetric int8 config defined by executorch.backends.arm.quantizer.arm_quantizer.get_symmetric_quantization_config is the main config available to use with the Ethos-U quantizer.

Supported Quantization Schemes

The Arm Ethos-U delegate supports the following quantization schemes:

• 8-bit symmetric weights with 8-bit asymmetric activations (via the PT2E quantization flow).

• Limited support for 16-bit quantization with 16-bit activations and 8-bit weights (a.k.a 16x8 quantization). This is under development.

Quantization API

class EthosUQuantizer(compile_spec: 'EthosUCompileSpec') -> 'None'

Quantizer supported by the Arm Ethos-U backend.

Args:

• compile_spec: A EthosUCompileSpec instance.

def EthosUQuantizer.set_global(self, quantization_config: 'QuantizationConfig') -> 'TOSAQuantizer':

Set quantization_config for submodules that are not already annotated by name or type filters.

Args:

• quantization_config: The QuantizationConfig to set as global configuration.

def EthosUQuantizer.set_io(self, quantization_config: 'QuantizationConfig') -> 'TOSAQuantizer':

Set quantization_config for input and output nodes.

Args:

• quantization_config: The QuantizationConfig to set for input and output nodes.

def EthosUQuantizer.set_module_name(self, module_name: 'str', quantization_config: 'Optional[QuantizationConfig]') -> 'TOSAQuantizer':

Set quantization_config for a submodule with name: module_name, for example: quantizer.set_module_name(“blocks.sub”), it will quantize all supported operator/operator patterns in the submodule with this module name with the given quantization_config

Args:

• module_name: The name of the submodule to set the quantization config for.

• quantization_config: The QuantizationConfig to set for the submodule.

def EthosUQuantizer.set_module_type(self, module_type: 'Callable', quantization_config: 'QuantizationConfig') -> 'TOSAQuantizer':

Set quantization_config for a submodule with type: module_type, for example: quantizer.set_module_name(Sub) or quantizer.set_module_name(nn.Linear), it will quantize all supported operator/operator patterns in the submodule with this module type with the given quantization_config.

Args:

• module_type: The type of the submodule to set the quantization config for.

• quantization_config: The QuantizationConfig to set for the submodule.

def EthosUQuantizer.transform_for_annotation(self, model: 'GraphModule') -> 'GraphModule':

An initial pass for transforming the graph to prepare it for annotation. Currently transforms scalar values to tensor attributes.

Args:

• model: The model to transform. Returns: The transformed model.