diff options
Diffstat (limited to 'ethosu/vela/supported_operators.py')
| -rw-r--r-- | ethosu/vela/supported_operators.py | 21 |
1 files changed, 19 insertions, 2 deletions
diff --git a/ethosu/vela/supported_operators.py b/ethosu/vela/supported_operators.py index 91fcb5ad..6dcb27d0 100644 --- a/ethosu/vela/supported_operators.py +++ b/ethosu/vela/supported_operators.py @@ -43,8 +43,8 @@ def _optype_formatter(op_list): output = map(optype_to_builtintype, op_list) # Remove UNKNOWNs output = (x for x in output if x is not BUILTIN_OPERATOR_UNKNOWN) - # Order alphabetically - return sorted(output) + # Order alphabetically and join into a string representation + return ", ".join(str(op) for op in sorted(output)) class SupportedOperators: @@ -94,6 +94,7 @@ class SupportedOperators: concat_ops = set((Op.Concat, Op.ConcatTFLite, Op.PackReshaped, Op.Pack,)) memory_only_ops = set((Op.Squeeze, Op.Reshape, Op.QuantizedReshape,)) | concat_ops | split_ops shapeless_input_ops = binary_elem_wise_main_ops | set((Op.Split, Op.SplitV,)) + per_axis_quant_ops = convolution_like_ops # per-axis/channel quantization only currently supported for conv ops supported_fused_activations = relu_ops | set((Op.Tanh, Op.Sigmoid, Op.LUT,)) supported_operators = npu_pre_ops | mac_main_ops | elem_wise_main_ops | npu_post_ops | memory_only_ops # Supported data types @@ -113,6 +114,7 @@ class SupportedOperators: docstring_shapeless_input_ops = _optype_formatter(shapeless_input_ops) docstring_supported_int32_tensor_ops = _optype_formatter(supported_int32_tensor_ops) docstring_supported_fused_activations = _optype_formatter(supported_fused_activations) + docstring_per_axis_quant_ops = _optype_formatter(per_axis_quant_ops) def __init__(self): # Setup the generic constraints. Note: the order matters @@ -127,6 +129,7 @@ class SupportedOperators: self.generic_constraints.append(SupportedOperators.constraint_tens_dimension) self.generic_constraints.append(SupportedOperators.constraint_tens_quant_none_check) self.generic_constraints.append(SupportedOperators.constraint_tens_quant_scale) + self.generic_constraints.append(SupportedOperators.constraint_tens_quant_per_axis) self.generic_constraints.append(SupportedOperators.constraint_faf) # Setup specific constraints. Note: the order matters @@ -391,6 +394,20 @@ class SupportedOperators: return valid, ", ".join(extra) @classmethod + @docstring_format_args([docstring_per_axis_quant_ops]) + def constraint_tens_quant_per_axis(cls, op): + "Per-axis quantization is only supported for the following op types: {}" + valid = True + extra = [] + if op.type not in cls.per_axis_quant_ops: + tensors = [tens for tens in op.get_ifm_ifm2_weights_ofm() if tens] + for tens in tensors: + if tens.quantization.is_per_axis(): + valid = False + extra.append(tens.name) + return valid, "The following tensor(s) have per-axis quantization parameters: " + ", ".join(extra) + + @classmethod @docstring_format_args([docstring_supported_fused_activations]) def constraint_faf(cls, op): "The fused activation function (if present) must be one of type: {}" |