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-rw-r--r--ethosu/vela/operation.py5
1 files changed, 0 insertions, 5 deletions
diff --git a/ethosu/vela/operation.py b/ethosu/vela/operation.py
index f85cb4bb..19b00b31 100644
--- a/ethosu/vela/operation.py
+++ b/ethosu/vela/operation.py
@@ -487,7 +487,6 @@ class Operation:
"read_shapes",
"rounding_mode",
"explicit_scaling",
- "low_precision_scaling",
"write_offset",
"write_shape",
"ifm_resampling_mode",
@@ -525,9 +524,6 @@ class Operation:
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
# Write offset, for operations that only produce a part of the OFM
self.write_offset: Optional[Shape4D] = None
# The amount of OFM that is produced by the operation (only if write_offset is not None).
@@ -567,7 +563,6 @@ class Operation:
res.write_shape = Shape4D(*self.write_shape) if self.write_shape else None
res.rounding_mode = self.rounding_mode
res.explicit_scaling = self.explicit_scaling
- res.low_precision_scaling = self.low_precision_scaling
res.ifm_resampling_mode = self.ifm_resampling_mode
res.tile_base_offsets_ifm = [_ifm.copy() for _ifm in self.tile_base_offsets_ifm]
res.tile_base_offsets_ofm = self.tile_base_offsets_ofm.copy()