diff options
Diffstat (limited to 'ethosu/vela/tosa_supported_operators.py')
| -rw-r--r-- | ethosu/vela/tosa_supported_operators.py | 50 |
1 files changed, 46 insertions, 4 deletions
diff --git a/ethosu/vela/tosa_supported_operators.py b/ethosu/vela/tosa_supported_operators.py index d3686160..a4f822eb 100644 --- a/ethosu/vela/tosa_supported_operators.py +++ b/ethosu/vela/tosa_supported_operators.py @@ -39,16 +39,15 @@ class TosaSupportedOperators: mac_main_ops = convolution_like_ops | pooling_ops | fc_vector_products memory_only_ops = set((Op.Reshape, Op.Transpose, Op.Concat, Op.SplitSliceRead,)) - binary_elem_wise_add_mul_sub = set((Op.Add, Op.Mul, Op.RescaleMul, Op.Sub,)) - type_conversion_ops = set((Op.Rescale,)) relu_ops = set((Op.Clamp, Op.ReluN,)) activation_ops = relu_ops + pad_ops = set((Op.Pad,)) npu_post_ops = activation_ops supported_operators = ( - mac_main_ops | type_conversion_ops | npu_post_ops | memory_only_ops | binary_elem_wise_add_mul_sub + mac_main_ops | type_conversion_ops | npu_post_ops | memory_only_ops | binary_elem_wise_add_mul_sub | pad_ops ) # Supported data types @@ -60,12 +59,15 @@ class TosaSupportedOperators: # Setup the generic constraints. Note: the order matters self.generic_constraints = [] self.generic_constraints.append(TosaSupportedOperators.constraint_tens_dtype) - self.generic_constraints.append(TosaSupportedOperators.constraint_tens_dimension) + self.generic_constraints.append(TosaSupportedOperators.constraint_tens_dimension) # TODO as not supported yet + self.generic_constraints.append(TosaSupportedOperators.constraint_rank) # TODO as not supported yet + self.generic_constraints.append(TosaSupportedOperators.constraint_batch) # TODO as not supported yet # Setup specific constraints. Note: the order matters self.specific_constraints = defaultdict(list) self.specific_constraints[Op.Transpose].append(TosaSupportedOperators.constraint_ifm_producer) + self.specific_constraints[Op.Pad].append(TosaSupportedOperators.constraint_padding_producer) # Depthwise Conv specific checks: for op_type in TosaSupportedOperators.depthwise_convolution_ops: @@ -127,6 +129,38 @@ class TosaSupportedOperators: extra.append(f"Tensor '{tens.name}' has shape: {tens.shape}") return valid, ", ".join(extra) + # TODO This is for a HW limitation, that is to be resolved in SW later on + @staticmethod + def constraint_rank(op): + "Tensor rank must be <= 4" + valid = True + extra = [] + tensors = [tens for tens in op.get_ifm_ifm2_weights_ofm() if tens] + if not tensors: + tensors = [tens for tens in op.inputs if tens] + for tens in tensors: + rank = len(tens.shape) + if not rank <= 4: + valid = False + extra.append(f"Tensor '{tens.name}' has rank: {rank}") + return valid, ", ".join(extra) + + # TODO This is for a HW limitation, that is to be resolved in SW later on + @staticmethod + def constraint_batch(op): + "If Tensor rank is 4 batch of ifms/ofm must be 1" + valid = True + extra = [] + tensors = [tens for tens in op.get_ifm_ifm2_ofm() if tens] + if not tensors: + tensors = [tens for tens in op.inputs if tens] + for tens in tensors: + rank = len(tens.shape) + if rank == 4 and tens.shape[0] != 1: + valid = False + extra.append(f"Tensor '{tens.name}' has rank: 4 and N: {tens.shape[0]}") + return valid, ", ".join(extra) + @staticmethod def constraint_ifm_producer(cls, op): "Input must be constant data" @@ -143,6 +177,14 @@ class TosaSupportedOperators: return valid, "Avgpool with pad_top {top} and pad_left {left}" + # TODO limit padding to be const data for now. + # For TFLite it is assumed to be constant. + @staticmethod + def constraint_padding_producer(op): + "Input must be constant data" + valid = op.inputs[1].ops and op.inputs[1].ops[0].type == Op.Const + return valid, "PAD Op with non-constant data padding" + # TODO duplicates tflite_supported operators, but support for depth multiplier should be added at a later stage @staticmethod def constraint_depth_multiplier(op): |