diff options
Diffstat (limited to 'ethosu/vela/operation.py')
| -rw-r--r-- | ethosu/vela/operation.py | 32 |
1 files changed, 30 insertions, 2 deletions
diff --git a/ethosu/vela/operation.py b/ethosu/vela/operation.py index 6bd955d2..0558e527 100644 --- a/ethosu/vela/operation.py +++ b/ethosu/vela/operation.py @@ -238,6 +238,8 @@ class Op(Enum): Relu = OperatorInfo(indices=IFM_INDICES) Relu6 = OperatorInfo(indices=IFM_INDICES) ReluN1To1 = OperatorInfo(indices=IFM_INDICES) + ReluN = OperatorInfo(indices=IFM_INDICES) # TOSA specific + Rescale = OperatorInfo(indices=IFM_INDICES) # TOSA specific RescaleAdd = OperatorInfo(block_type=NpuBlockType.ElementWise, indices=IFM_IFM2_INDICES) Reshape = OperatorInfo(indices=IFM_INDICES) ResizeBilinear = OperatorInfo(block_type=NpuBlockType.Pooling, indices=IFM_INDICES) @@ -321,7 +323,7 @@ class Op(Enum): return self.info.block_type == NpuBlockType.ElementWise and not self.info.is_unary def is_relu_op(self): - return self in (Op.Relu, Op.Relu6, Op.ReluN1To1, Op.Clip) + return self in (Op.Relu, Op.Relu6, Op.ReluN1To1, Op.ReluN, Op.Clip) def is_activation_op(self): return self.is_relu_op() or self in (Op.Tanh, Op.Sigmoid, Op.Softmax, Op.LUT, Op.HardSwish) @@ -374,7 +376,20 @@ class ActivationFunction: return res -def create_activation_function(op_type: Op) -> ActivationFunction: +class ExplicitScaling: + """Explicit scaling parameters""" + + def __init__(self, per_channel, shift, multiplier): + self.per_channel = per_channel + self.shift = shift + self.multiplier = multiplier + + def clone(self): + res = copy.copy(self) + return res + + +def create_activation_function(op_type: Op, min=None, max=None) -> ActivationFunction: """Creates activation function with min/max depending on op_type""" act = ActivationFunction(op_type) if op_type == Op.Relu: @@ -393,6 +408,15 @@ def create_activation_function(op_type: Op) -> ActivationFunction: act.max = 1.0 elif op_type == Op.HardSwish: act.min = 0.0 + if op_type == Op.Clip: + assert min is not None and max is not None + act.min = min + act.max = max + elif op_type == Op.ReluN: + assert max is not None + act.min = 0.0 + act.max = max + return act @@ -436,6 +460,7 @@ class Operation: "read_offsets", "read_shapes", "rounding_mode", + "explicit_scaling", "low_precision_scaling", "write_offset", "write_shape", @@ -470,6 +495,8 @@ class Operation: self.read_offsets: List[Shape4D] = [None, None] # offset for [ifm, ifm2] self.read_shapes: List[Shape4D] = [None, None] # read shape for [ifm, ifm2] self.rounding_mode: Optional[NpuRoundingMode] = None + # Rescale op in TOSA supplies explicit multiplier and shift values + self.explicit_scaling: Optional[ExplicitScaling] = None # The Mean operator (implemented as a depthwise convolution) requires scaling # to be calculated differently in one case. In that case, this is set to True. self.low_precision_scaling = False @@ -498,6 +525,7 @@ class Operation: res.read_offsets = list(self.read_offsets) res.read_shapes = list(self.read_shapes) res.rounding_mode = self.rounding_mode + res.explicit_scaling = self.explicit_scaling res.low_precision_scaling = self.low_precision_scaling return res |