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| author | Tim Hall <tim.hall@arm.com> | 2023-05-16 22:39:14 +0100 |
|---|---|---|
| committer | tim.hall <tim.hall@arm.com> | 2023-05-17 11:05:57 +0000 |
| commit | 5ff4cd12898f44228288a7969b52dff97be30cb2 (patch) | |
| tree | 1c8068c02254d5479706e41379bbd1f8c7b33205 /ethosu/vela/softmax.py | |
| parent | 0426fe9de82e0f6b339edbd2bec78a5d322fb05f (diff) | |
| download | ethos-u-vela-5ff4cd12898f44228288a7969b52dff97be30cb2.tar.gz | |
MLBEDSW-7223: Fusing Pad and AvgPool causes diff
- Fixed an issue with the fusing of PAD and AVERAGE_POOL_2D whereby
the rounding away from zero didn't work because it requires the zero
point to be at zero but the input padding required it to be set to the
desired zero point. This affected both int8 and int16. The solution
was to remove it by using the bias prior to the scaling
- Refactored the rounding away from zero mode
Change-Id: I8f2df69df06d2a9722315c346646e5a901cb2c3b
Signed-off-by: Tim Hall <tim.hall@arm.com>
Diffstat (limited to 'ethosu/vela/softmax.py')
| -rw-r--r-- | ethosu/vela/softmax.py | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/ethosu/vela/softmax.py b/ethosu/vela/softmax.py index 5a06c1bd..8f30fa14 100644 --- a/ethosu/vela/softmax.py +++ b/ethosu/vela/softmax.py @@ -24,13 +24,13 @@ import numpy as np from . import fp_math from . import scaling -from .api import NpuRoundingMode from .data_type import DataType from .debug_database import DebugDatabase from .operation import ActivationFunction from .operation import ExplicitScaling from .operation import Op from .operation import Operation +from .operation import RoundingMode from .operation_util import create_add from .operation_util import create_clz from .operation_util import create_depthwise_maxpool @@ -281,7 +281,7 @@ class SoftMax: name = f"{self.op.name}_shr{pass_number}" shift = create_const_tensor(f"{name}_const", [1, 1, 1, 1], DataType.int32, [12], quantization=no_scale_quant) shr_op = create_shr(name, ifm_exp, shift, no_scale_quant, activation) - shr_op.rounding_mode = NpuRoundingMode.NATURAL + shr_op.rounding_mode = RoundingMode.HalfUp rescaled_exp = add_op_get_ofm(shr_op) # PASS 3 - Reduce sum @@ -443,7 +443,7 @@ class SoftMax: # PASS 30 - SHR shr30_op = Operation(Op.SHR, f"{self.op.name}_shr{pass_number}") - shr30_op.rounding_mode = NpuRoundingMode.NATURAL + shr30_op.rounding_mode = RoundingMode.HalfUp shr30_op.add_input_tensor(scaled_exp) shr30_op.add_input_tensor(right_shift) shr30_op.set_output_tensor(ofm) |