aboutsummaryrefslogtreecommitdiff
path: root/ethosu/vela/supported_operators.py
diff options
context:
space:
mode:
Diffstat (limited to 'ethosu/vela/supported_operators.py')
-rw-r--r--ethosu/vela/supported_operators.py14
1 files changed, 14 insertions, 0 deletions
diff --git a/ethosu/vela/supported_operators.py b/ethosu/vela/supported_operators.py
index 505d4d16..8bb9c581 100644
--- a/ethosu/vela/supported_operators.py
+++ b/ethosu/vela/supported_operators.py
@@ -105,6 +105,7 @@ class SupportedOperators:
supported_operators = npu_pre_ops | mac_main_ops | elem_wise_main_ops | pad_ops | npu_post_ops | memory_only_ops
# Supported data types
supported_op_dtypes = set((DataType.uint8, DataType.int8, DataType.int16, DataType.int32))
+ supported_faf_dtypes = set((DataType.uint8, DataType.int8, DataType.int16))
supported_bias_dtypes = set((DataType.int32, DataType.int64))
supported_pad_dtypes = set((DataType.int32, DataType.int64))
# Defined ranges for allowed values:
@@ -135,6 +136,7 @@ class SupportedOperators:
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)
+ self.generic_constraints.append(SupportedOperators.constraint_faf_type)
self.generic_constraints.append(SupportedOperators.constraint_quant_scale_inf)
# Setup specific constraints. Note: the order matters
@@ -451,6 +453,18 @@ class SupportedOperators:
res = valid, f"Op has its fused activation function as: {faf}"
return res
+ @classmethod
+ @docstring_format_args([_list_formatter(supported_faf_dtypes)])
+ def constraint_faf_type(cls, op):
+ "If a fused activation function is present, the Output tensor must be one of type: {}"
+ if op.activation is None:
+ res = True, "Op has no fused activation function"
+ else:
+ valid = op.ofm.dtype in cls.supported_faf_dtypes
+ ext_type = optype_to_builtintype(op.activation.op_type)
+ res = valid, f"Op has fused activation function {ext_type}, and Output tensor data type: {op.ofm.dtype}"
+ return res
+
@staticmethod
def constraint_stride_type(op):
"Stride values for both width and height must be integer types"