diff options
| author | Johan Alfven <johan.alfven@arm.com> | 2023-10-03 14:46:22 +0200 |
|---|---|---|
| committer | Johan Alfven <johan.alfven@arm.com> | 2023-10-03 14:46:22 +0200 |
| commit | 7972ee80215e1fd40f0cea39c688680be945d302 (patch) | |
| tree | f1db9e0162d42486f0da1f3186a1959eeb58313f | |
| parent | a5da0ab0aa83e05ca3b5952d75a4907223c54ac4 (diff) | |
| download | ethos-u-vela-7972ee80215e1fd40f0cea39c688680be945d302.tar.gz | |
MLBEDSW-8102: Fix regression on Argmax int64
- Fixed a regression where DepthWiseConv used in argmax int64
had the wrong shape.
- The error was introduced when adding support for a new operator
that changed the weight shape for the cast utility function. That
change only worked because reorder_depthwise_weights was called
later. Since argmax is converted after reorder_depthwise_weights
the cast operator in argmax got the wrong shape.
- The fix is to set the correct weight shape in the cast operator
and then mark that the weights already have been transposed correctly.
Change-Id: I61f5694f078cfcaf0d46d43faead6eb7e0a23ade
Signed-off-by: Johan Alfven <johan.alfven@arm.com>
| -rw-r--r-- | ethosu/vela/operation_util.py | 7 |
1 files changed, 5 insertions, 2 deletions
diff --git a/ethosu/vela/operation_util.py b/ethosu/vela/operation_util.py index 44a80b2..e2cdc20 100644 --- a/ethosu/vela/operation_util.py +++ b/ethosu/vela/operation_util.py @@ -98,8 +98,8 @@ def create_cast_op( c = ifm.shape[-1] - # Weigth shape is in format [h, w, c, b] - shape = [1, 1, c, 1] + # Weigth shape is in format [h, w, b, c] for DepthwiseConv2D + shape = [1, 1, 1, c] kernel = np.dstack([1] * c) identity_quant = QuantizationParameters(scale_f32=1.0, zero_point=0) op.add_input_tensor( @@ -111,6 +111,9 @@ def create_cast_op( quantization=identity_quant, ), ) + # Set flag to indicate that weights are already in correct order + # and prevent that they are transposed in reorder_depthwise_weights + op.inputs[1].weight_transpose_depthwise = True bias_values = [0] * c dtype = DataType.int64 if op.ifm.dtype == DataType.int16 else DataType.int32 op.add_input_tensor(create_const_tensor(op.name + "_bias", [c], dtype, bias_values)) |