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| author | Fredrik Svedberg <fredrik.svedberg@arm.com> | 2020-08-25 11:31:47 +0200 |
|---|---|---|
| committer | Fredrik Svedberg <fredrik.svedberg@arm.com> | 2020-08-27 16:39:29 +0200 |
| commit | 880e73543120648f08886365a45e8b2ce32d5ff1 (patch) | |
| tree | 420627fb8e7e5000f23f82c52ba6569f4a696813 /ethosu/vela/softmax.py | |
| parent | a41cd4de2af1e43b76a2a33d78eeb2d90a88b757 (diff) | |
| download | ethos-u-vela-880e73543120648f08886365a45e8b2ce32d5ff1.tar.gz | |
[MLBEDSW-2846] Do not use NHCWB16 for reduce_sum int32
Added checks for not using NHCWB16 for reduce_sum int32 which makes
int8/uint8 softmax work.
Also enabled softmax graph rewrite by default and fixed a saturation
problem.
Change-Id: Ic01bd9ece7e5c3edb2900b7915cc747efe9e5760
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Diffstat (limited to 'ethosu/vela/softmax.py')
| -rw-r--r-- | ethosu/vela/softmax.py | 24 |
1 files changed, 14 insertions, 10 deletions
diff --git a/ethosu/vela/softmax.py b/ethosu/vela/softmax.py index eb97c792..7c23f472 100644 --- a/ethosu/vela/softmax.py +++ b/ethosu/vela/softmax.py @@ -391,7 +391,9 @@ class SoftMax: F2_one = create_const_tensor( "F2_one_const", [1, 1, 1, 1], DataType.int32, [(1 << 29)], np.int32, quantization=no_scale_quant ) - two = create_const_tensor("two_const", [1, 1, 1, 1], DataType.int32, [2], np.int32, quantization=no_scale_quant) + four = create_const_tensor( + "four_const", [1, 1, 1, 1], DataType.int32, [4], np.int32, quantization=no_scale_quant + ) for i in range(3): # PASS 13, 18, 23 - MUL mul_op = Operation("MulAct", self.op.name + "_mul%d" % (13 + i * 5)) @@ -416,10 +418,10 @@ class SoftMax: to_rescale.quantization = one_scale_quant.clone() to_rescale.quantization.scale_f32 = 2.0 mul_op.set_output_tensor(to_rescale) - # PASS 16, 21, 26 - SHL - shl_op = Operation("SHL", self.op.name + "_shl%d" % (16 + i * 5)) + # PASS 16, 21, 26 - MUL + shl_op = Operation("MulAct", self.op.name + "_mul%d" % (16 + i * 5)) shl_op.add_input_tensor(to_rescale) - shl_op.add_input_tensor(two) + shl_op.add_input_tensor(four) to_add = Tensor(reduce_sum_shape, DataType.int32, shl_op.name + "_0") to_add.quantization = no_scale_quant shl_op.set_output_tensor(to_add) @@ -431,13 +433,15 @@ class SoftMax: nr_x.quantization = one_scale_quant add_op.set_output_tensor(nr_x) - # PASS 28 - SHL - shl28_op = Operation("SHL", self.op.name + "_shl28") - shl28_op.add_input_tensor(nr_x) - shl28_op.add_input_tensor(one) - scale_factor = Tensor(reduce_sum_shape, DataType.int32, shl28_op.name + "_0") + # PASS 28 - Multiply + mul28_op = Operation("MulAct", self.op.name + "_mul28") + mul28_op.add_input_tensor(nr_x) + mul28_op.add_input_tensor( + create_const_tensor("two_const", [1, 1, 1, 1], DataType.int32, [2], np.int32, quantization=no_scale_quant) + ) + scale_factor = Tensor(reduce_sum_shape, DataType.int32, mul28_op.name + "_0") scale_factor.quantization = one_scale_quant - shl28_op.set_output_tensor(scale_factor) + mul28_op.set_output_tensor(scale_factor) # PASS 29 - Multiply mul_op = Operation("MulAct", self.op.name + "_mul29") |