From 8359a474e4f125382fd7b7d5431a612f6013f107 Mon Sep 17 00:00:00 2001 From: Dwight Lidman Date: Mon, 28 Sep 2020 15:53:40 +0200 Subject: MLBEDSW-3061: Update supported_operators.py This commit changes and amends some parts of the restriction functions in order to make sure operators are correctly placed. Signed-off-by: Dwight Lidman Change-Id: I336cf33a874c9078a5bbf81ce129ff917dbc5e9a --- ethosu/vela/test/testutil.py | 24 +++++++++++++++++++++--- 1 file changed, 21 insertions(+), 3 deletions(-) (limited to 'ethosu/vela/test/testutil.py') diff --git a/ethosu/vela/test/testutil.py b/ethosu/vela/test/testutil.py index adb874a0..c5ff0033 100644 --- a/ethosu/vela/test/testutil.py +++ b/ethosu/vela/test/testutil.py @@ -22,6 +22,7 @@ from ethosu.vela.data_type import DataType from ethosu.vela.nn_graph import Subgraph from ethosu.vela.operation import Operation from ethosu.vela.tensor import create_const_tensor +from ethosu.vela.tensor import QuantizationParameters from ethosu.vela.tensor import Tensor @@ -38,7 +39,17 @@ def create_arch(): ) -def create_elemwise_op(type, name, ifm_shape, ifm2_shape, ofm_shape, datatype=DataType.uint8): +def create_elemwise_op( + type, + name, + ifm_shape, + ifm2_shape, + ofm_shape, + datatype=DataType.uint8, + ifm_quant=QuantizationParameters(), + ifm2_quant=QuantizationParameters(), + ofm_quant=QuantizationParameters(), +): # Creates elementwise operation with constant IFM/IFM2 if datatype.size_in_bytes() == 1: np_type = np.uint8 @@ -47,9 +58,16 @@ def create_elemwise_op(type, name, ifm_shape, ifm2_shape, ofm_shape, datatype=Da else: np_type = np.int32 op = Operation(type, name) - op.add_input_tensor(create_const_tensor(name + "_ifm", ifm_shape, datatype, np.zeros(ifm_shape), np_type)) - op.add_input_tensor(create_const_tensor(name + "_ifm2", ifm2_shape, datatype, np.zeros(ifm2_shape), np_type)) + op.add_input_tensor( + create_const_tensor(name + "_ifm", ifm_shape, datatype, np.zeros(ifm_shape), np_type, quantization=ifm_quant) + ) + op.add_input_tensor( + create_const_tensor( + name + "_ifm2", ifm2_shape, datatype, np.zeros(ifm2_shape), np_type, quantization=ifm2_quant + ) + ) ofm = Tensor(ofm_shape, datatype, name + "_ofm") + ofm.quantization = ofm_quant op.set_output_tensor(ofm) return op -- cgit v1.2.1