diff --git a/src/finn/custom_op/fpgadataflow/fmpadding_rtl.py b/src/finn/custom_op/fpgadataflow/fmpadding_rtl.py index ecfbe92b4b83e2bbc9143b92bee903c2f02b378b..5650d218857a7c7ff86c15ac057c4ebbc18df5ca 100644 --- a/src/finn/custom_op/fpgadataflow/fmpadding_rtl.py +++ b/src/finn/custom_op/fpgadataflow/fmpadding_rtl.py @@ -68,10 +68,6 @@ class FMPadding_rtl(HLSCustomOp): "SIMD": ("i", False, 1), # FINN input datatype "inputDataType": ("s", True, ""), - # controls distribution of padded pixels - # in case of uneven padding -- see FMPadding fxn - # in hlslib - "PaddingStyle": ("i", False, 2, {2, 1}), # shape describing input vecs per execution "numInputVectors": ("i", False, 1), # Enable reprogrammable implementation to change FM dimensions, @@ -136,7 +132,7 @@ class FMPadding_rtl(HLSCustomOp): exp_ishape = self.get_normal_input_shape() oshape = self.get_normal_output_shape() ishape = tuple(model.get_tensor_shape(self.onnx_node.input[0])) - assert ishape == exp_ishape, "Unexpect input shape for SameResize." + assert ishape == exp_ishape, "Unexpected input shape for FMPadding_rtl." return super().make_const_shape_op(oshape) def infer_node_datatype(self, model): @@ -160,7 +156,7 @@ class FMPadding_rtl(HLSCustomOp): ret = DataType[self.get_nodeattr("inputDataType")] # the hlslib op always pads with zeros, so ensure that the DataType # is able to represent zeros - assert ret.allowed(0), "FMPadding_Batch DataType must support zero" + assert ret.allowed(0), "FMPadding_rtl DataType must support zero" return ret def get_output_datatype(self, ind=0): diff --git a/tests/fpgadataflow/test_fpgadataflow_fmpadding.py b/tests/fpgadataflow/test_fpgadataflow_fmpadding.py index 090a0d1e65205f766c7169c1ada8d02c41f0240e..8ab8a7aa4df2554422f9e43319e7e3acc7aaa666 100644 --- a/tests/fpgadataflow/test_fpgadataflow_fmpadding.py +++ b/tests/fpgadataflow/test_fpgadataflow_fmpadding.py @@ -125,12 +125,6 @@ def test_fpgadataflow_fmpadding(idim, pad, num_ch, simd, idt, mode, impl_style): pad_h = pad[0] + pad[2] pad_w = pad[1] + pad[3] - if idim_h == idim_w and pad_h != pad_w and impl_style != "rtl": - pytest.skip( - """Only equal padding along the dimensions for square images - is supported for HLS, skipping""" - ) - # generate input data x = gen_finn_dt_tensor(idt, [1, idim_h, idim_w, num_ch]) input_dict = {"inp": x} @@ -150,8 +144,6 @@ def test_fpgadataflow_fmpadding(idim, pad, num_ch, simd, idt, mode, impl_style): model = model.transform(PrepareIP(test_fpga_part, target_clk_ns)) model = model.transform(HLSSynthIP()) model = model.transform(PrepareRTLSim()) - node = model.get_nodes_by_op_type(optype)[0] - inst = getCustomOp(node) y_produced = oxe.execute_onnx(model, input_dict)["outp"] expected_oshape = (1, odim_h, odim_w, num_ch)