MLBEDSW-3558: Put FC on CPU when OFM != 2D
This commit adds a constraint to FullyConnected
ops in supported_operators.py that puts any
such op on the CPU if tensor dimensions of the
output(s) are not 2D.
Signed-off-by: Dwight Lidman <dwight.lidman@arm.com>
Change-Id: I8c898a780b40fc4a1383c09213f0696ea6699b7d
diff --git a/ethosu/vela/test/testutil.py b/ethosu/vela/test/testutil.py
index ee407b6..4b2938b 100644
--- a/ethosu/vela/test/testutil.py
+++ b/ethosu/vela/test/testutil.py
@@ -20,6 +20,7 @@
from ethosu.vela import architecture_features
from ethosu.vela.data_type import DataType
from ethosu.vela.nn_graph import Subgraph
+from ethosu.vela.operation import Op
from ethosu.vela.operation import Operation
from ethosu.vela.tensor import create_const_tensor
from ethosu.vela.tensor import QuantizationParameters
@@ -90,7 +91,8 @@
else:
np_type = np.int32
qp = default_quant_params()
- qp.zero_point = np.zeros(weights_shape)
+ if op.type is not Op.FullyConnected:
+ qp.zero_point = np.zeros(weights_shape)
weights = create_const_tensor(
"weights", weights_shape, datatype, np.zeros(weights_shape), np_type, quantization=qp
)
@@ -98,7 +100,8 @@
# Optional bias tensor
if bias_shape is not None:
qp = default_quant_params()
- qp.zero_point = np.zeros(bias_shape)
+ if op.type is not Op.FullyConnected:
+ qp.zero_point = np.zeros(bias_shape)
bias = create_const_tensor("bias", bias_shape, DataType.int32, np.zeros(bias_shape), np.int32, quantization=qp)
op.add_input_tensor(bias)
return op