| 44 | |
| 45 | |
| 46 | class CortexMQuantizer(ComposableQuantizer): |
| 47 | |
| 48 | def __init__(self) -> None: |
| 49 | conv_targets: set[OpOverload] = set() |
| 50 | for key in CONV_OP_PATTERNS.keys() | CONV_TRANSPOSE_OP_PATTERNS.keys(): |
| 51 | conv_targets.update(key) |
| 52 | |
| 53 | support_dict_name = ( |
| 54 | cortex_m_quantizer_support_module + ".CORTEX_M_QUANTIZER_SUPPORT_DICT" |
| 55 | ) |
| 56 | pattern_matcher = PatternMatcher( |
| 57 | cast( |
| 58 | dict[tuple[OpOverload, ...], Optional[type[PatternCheck]]], |
| 59 | CORTEX_M_QUANTIZER_SUPPORT_DICT, |
| 60 | ), |
| 61 | support_dict_name=support_dict_name, |
| 62 | ) |
| 63 | quantizers: List[Quantizer] = [ |
| 64 | PatternQuantizer( |
| 65 | INT8_PER_CHANNEL_CONFIG, |
| 66 | node_finder=NodeTargetNodeFinder(list(conv_targets)), |
| 67 | pattern_matcher=pattern_matcher, |
| 68 | ), |
| 69 | PatternQuantizer( |
| 70 | INT8_PER_TENSOR_CONFIG, |
| 71 | node_finder=GlobalNodeFinder(), |
| 72 | pattern_matcher=pattern_matcher, |
| 73 | ), |
| 74 | SharedQspecQuantizer(), |
| 75 | ] |
| 76 | super().__init__(quantizers) |
| 77 | |
| 78 | def annotate(self, model): |
| 79 | reporter = QuantizerReporter(self.quantizers) |
| 80 | model = super().annotate(model) |
| 81 | reporter.log_quantizer_report(model) |
| 82 | return model |
| 83 | |
| 84 | def validate(self, model: GraphModule) -> None: |
| 85 | return None |
| 86 | |
| 87 | def transform_for_annotation(self, model: GraphModule) -> GraphModule: |
| 88 | pass_manager = CortexMPassManager(None) |
| 89 | return pass_manager.transform_for_annotation(model) |
no outgoing calls