diff options
Diffstat (limited to 'ethosu/vela/test/testutil.py')
| -rw-r--r-- | ethosu/vela/test/testutil.py | 32 |
1 files changed, 20 insertions, 12 deletions
diff --git a/ethosu/vela/test/testutil.py b/ethosu/vela/test/testutil.py index 92bf53dc..b06008af 100644 --- a/ethosu/vela/test/testutil.py +++ b/ethosu/vela/test/testutil.py @@ -39,16 +39,23 @@ def create_arch(): ) +def default_quant_params(): + qp = QuantizationParameters() + qp.scale_f32 = np.float32(1) + qp.zero_point = 0 + return qp + + def create_elemwise_op( - type, + op_type, name, ifm_shape, ifm2_shape, ofm_shape, datatype=DataType.uint8, - ifm_quant=QuantizationParameters(), - ifm2_quant=QuantizationParameters(), - ofm_quant=QuantizationParameters(), + ifm_quant=default_quant_params(), + ifm2_quant=default_quant_params(), + ofm_quant=default_quant_params(), ): # Creates elementwise operation with constant IFM/IFM2 if datatype.size_in_bytes() == 1: @@ -57,15 +64,16 @@ def create_elemwise_op( np_type = np.int16 else: np_type = np.int32 - op = Operation(type, name) + op = Operation(op_type, name) 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 + if ifm2_shape is not None: + 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) @@ -73,11 +81,10 @@ def create_elemwise_op( def create_op_with_quant_tensors(op_type, ifm_shape, ofm_shape, weights_shape=None, datatype=DataType.uint8): - qp = QuantizationParameters() ifm = Tensor(ifm_shape, datatype, "in") - ifm.quantization = qp + ifm.quantization = default_quant_params() ofm = Tensor(ofm_shape, datatype, "out") - ofm.quantization = qp + ofm.quantization = default_quant_params() op = Operation(op_type, "op") op.add_input_tensor(ifm) op.set_output_tensor(ofm) @@ -89,6 +96,7 @@ def create_op_with_quant_tensors(op_type, ifm_shape, ofm_shape, weights_shape=No np_type = np.int16 else: np_type = np.int32 + qp = default_quant_params() qp.zero_point = np.zeros(weights_shape) weights = create_const_tensor( "weights", weights_shape, datatype, np.zeros(weights_shape), np_type, quantization=qp |