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Commit 701d4f71 authored by Hendrik Borras's avatar Hendrik Borras
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Added QONNX_export test to TestEnd2End test.

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tests/end2end/test_end2end_bnn_pynq.py
+ 150
− 66
View file @ 701d4f71
...@@ -38,9 +38,11 @@ import os ...@@ -38,9 +38,11 @@ import os
import subprocess import subprocess
import torch import torch
import warnings import warnings
from brevitas.export.onnx.generic.manager import BrevitasONNXManager
from collections import OrderedDict from collections import OrderedDict
from dataset_loading import cifar, mnist from dataset_loading import cifar, mnist
from datetime import datetime from datetime import datetime
from qonnx.util.cleanup import cleanup as qonnx_cleanup
from scipy.stats import linregress from scipy.stats import linregress
import finn.transformation.fpgadataflow.convert_to_hls_layers as to_hls import finn.transformation.fpgadataflow.convert_to_hls_layers as to_hls
...@@ -82,6 +84,7 @@ from finn.transformation.insert_topk import InsertTopK ...@@ -82,6 +84,7 @@ from finn.transformation.insert_topk import InsertTopK
from finn.transformation.lower_convs_to_matmul import LowerConvsToMatMul from finn.transformation.lower_convs_to_matmul import LowerConvsToMatMul
from finn.transformation.merge_onnx_models import MergeONNXModels from finn.transformation.merge_onnx_models import MergeONNXModels
from finn.transformation.move_reshape import RemoveCNVtoFCFlatten from finn.transformation.move_reshape import RemoveCNVtoFCFlatten
from finn.transformation.qonnx.convert_qonnx_to_finn import ConvertQONNXtoFINN
from finn.transformation.streamline import Streamline from finn.transformation.streamline import Streamline
from finn.transformation.streamline.reorder import ( from finn.transformation.streamline.reorder import (
MakeMaxPoolNHWC, MakeMaxPoolNHWC,
...@@ -104,8 +107,14 @@ mem_mode = "decoupled" ...@@ -104,8 +107,14 @@ mem_mode = "decoupled"
rtlsim_trace = False rtlsim_trace = False
def get_checkpoint_name(topology, wbits, abits, step): def get_checkpoint_name(topology, wbits, abits, QONNX_export, step):
return build_dir + "/end2end_%s_w%da%d_%s.onnx" % (topology, wbits, abits, step) return build_dir + "/end2end_%s_w%da%d_QONNX-%d_%s.onnx" % (
topology,
wbits,
abits,
QONNX_export,
step,
)
def get_dashboard_data(topology, wbits, abits): def get_dashboard_data(topology, wbits, abits):
...@@ -303,15 +312,24 @@ def topology2dataset(topology): ...@@ -303,15 +312,24 @@ def topology2dataset(topology):
@pytest.mark.parametrize("wbits", [1, 2]) @pytest.mark.parametrize("wbits", [1, 2])
@pytest.mark.parametrize("abits", [1, 2]) @pytest.mark.parametrize("abits", [1, 2])
@pytest.mark.parametrize("topology", ["lfc", "tfc", "cnv"]) @pytest.mark.parametrize("topology", ["lfc", "tfc", "cnv"])
# @pytest.mark.parametrize("QONNX_export", [False, True])
@pytest.mark.parametrize("QONNX_export", [True])
class TestEnd2End: class TestEnd2End:
def test_export(self, topology, wbits, abits): def test_export(self, topology, wbits, abits, QONNX_export):
if wbits > abits: if wbits > abits:
pytest.skip("No wbits > abits end2end network configs for now") pytest.skip("No wbits > abits end2end network configs for now")
if topology == "lfc" and not (wbits == 1 and abits == 1): if topology == "lfc" and not (wbits == 1 and abits == 1):
pytest.skip("Skipping certain lfc configs") pytest.skip("Skipping certain lfc configs")
(model, ishape) = get_trained_network_and_ishape(topology, wbits, abits) (model, ishape) = get_trained_network_and_ishape(topology, wbits, abits)
chkpt_name = get_checkpoint_name(topology, wbits, abits, "export") chkpt_name = get_checkpoint_name(topology, wbits, abits, QONNX_export, "export")
bo.export_finn_onnx(model, ishape, chkpt_name) if QONNX_export:
BrevitasONNXManager.export(model, ishape, chkpt_name)
qonnx_cleanup(chkpt_name, out_file=chkpt_name)
model = ModelWrapper(chkpt_name)
model = model.transform(ConvertQONNXtoFINN())
model.save(chkpt_name)
else:
bo.export_finn_onnx(model, ishape, chkpt_name)
nname = "%s_w%da%d" % (topology, wbits, abits) nname = "%s_w%da%d" % (topology, wbits, abits)
update_dashboard_data(topology, wbits, abits, "network", nname) update_dashboard_data(topology, wbits, abits, "network", nname)
dtstr = datetime.now().strftime("%Y-%m-%d %H:%M:%S") dtstr = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
...@@ -323,8 +341,10 @@ class TestEnd2End: ...@@ -323,8 +341,10 @@ class TestEnd2End:
update_dashboard_data(topology, wbits, abits, "finn-commit", finn_commit) update_dashboard_data(topology, wbits, abits, "finn-commit", finn_commit)
assert os.path.isfile(chkpt_name) assert os.path.isfile(chkpt_name)
def test_import_and_tidy(self, topology, wbits, abits): def test_import_and_tidy(self, topology, wbits, abits, QONNX_export):
prev_chkpt_name = get_checkpoint_name(topology, wbits, abits, "export") prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "export"
)
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
model = model.transform(InferShapes()) model = model.transform(InferShapes())
model = model.transform(FoldConstants()) model = model.transform(FoldConstants())
...@@ -332,17 +352,23 @@ class TestEnd2End: ...@@ -332,17 +352,23 @@ class TestEnd2End:
model = model.transform(GiveReadableTensorNames()) model = model.transform(GiveReadableTensorNames())
model = model.transform(InferDataTypes()) model = model.transform(InferDataTypes())
model = model.transform(RemoveStaticGraphInputs()) model = model.transform(RemoveStaticGraphInputs())
chkpt = get_checkpoint_name(topology, wbits, abits, "import_and_tidy") chkpt = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "import_and_tidy"
)
model.save(chkpt) model.save(chkpt)
def test_add_pre_and_postproc(self, topology, wbits, abits): def test_add_pre_and_postproc(self, topology, wbits, abits, QONNX_export):
prev_chkpt_name = get_checkpoint_name(topology, wbits, abits, "import_and_tidy") prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "import_and_tidy"
)
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
global_inp_name = model.graph.input[0].name global_inp_name = model.graph.input[0].name
ishape = model.get_tensor_shape(global_inp_name) ishape = model.get_tensor_shape(global_inp_name)
# preprocessing: torchvision's ToTensor divides uint8 inputs by 255 # preprocessing: torchvision's ToTensor divides uint8 inputs by 255
totensor_pyt = ToTensor() totensor_pyt = ToTensor()
chkpt_preproc_name = get_checkpoint_name(topology, wbits, abits, "preproc") chkpt_preproc_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "preproc"
)
bo.export_finn_onnx(totensor_pyt, ishape, chkpt_preproc_name) bo.export_finn_onnx(totensor_pyt, ishape, chkpt_preproc_name)
assert os.path.isfile(chkpt_preproc_name) assert os.path.isfile(chkpt_preproc_name)
# join preprocessing and core model # join preprocessing and core model
...@@ -355,7 +381,9 @@ class TestEnd2End: ...@@ -355,7 +381,9 @@ class TestEnd2End:
model.set_tensor_datatype(global_inp_name, DataType.UINT8) model.set_tensor_datatype(global_inp_name, DataType.UINT8)
# postprocessing: insert Top-1 node at the end # postprocessing: insert Top-1 node at the end
model = model.transform(InsertTopK(k=1)) model = model.transform(InsertTopK(k=1))
chkpt_name = get_checkpoint_name(topology, wbits, abits, "pre_post") chkpt_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "pre_post"
)
# tidy-up again # tidy-up again
model = model.transform(InferShapes()) model = model.transform(InferShapes())
model = model.transform(FoldConstants()) model = model.transform(FoldConstants())
...@@ -366,8 +394,10 @@ class TestEnd2End: ...@@ -366,8 +394,10 @@ class TestEnd2End:
model.save(chkpt_name) model.save(chkpt_name)
assert os.path.isfile(chkpt_name) assert os.path.isfile(chkpt_name)
def test_streamline(self, topology, wbits, abits): def test_streamline(self, topology, wbits, abits, QONNX_export):
prev_chkpt_name = get_checkpoint_name(topology, wbits, abits, "pre_post") prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "pre_post"
)
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
model = model.transform(absorb.AbsorbSignBiasIntoMultiThreshold()) model = model.transform(absorb.AbsorbSignBiasIntoMultiThreshold())
# move past any reshapes to be able to streamline input scaling # move past any reshapes to be able to streamline input scaling
...@@ -383,10 +413,14 @@ class TestEnd2End: ...@@ -383,10 +413,14 @@ class TestEnd2End:
model = model.transform(absorb.AbsorbScalarMulAddIntoTopK()) model = model.transform(absorb.AbsorbScalarMulAddIntoTopK())
model = model.transform(InferDataLayouts()) model = model.transform(InferDataLayouts())
model = model.transform(RemoveUnusedTensors()) model = model.transform(RemoveUnusedTensors())
model.save(get_checkpoint_name(topology, wbits, abits, "streamline")) model.save(
get_checkpoint_name(topology, wbits, abits, QONNX_export, "streamline")
)
def test_convert_to_hls_layers(self, topology, wbits, abits): def test_convert_to_hls_layers(self, topology, wbits, abits, QONNX_export):
prev_chkpt_name = get_checkpoint_name(topology, wbits, abits, "streamline") prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "streamline"
)
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
if topology == "tfc" and wbits == 1 and abits == 1: if topology == "tfc" and wbits == 1 and abits == 1:
# use standalone thresholds for tfc-w1a1 to also exercise that option # use standalone thresholds for tfc-w1a1 to also exercise that option
...@@ -408,16 +442,20 @@ class TestEnd2End: ...@@ -408,16 +442,20 @@ class TestEnd2End:
model = model.transform(absorb.AbsorbConsecutiveTransposes()) model = model.transform(absorb.AbsorbConsecutiveTransposes())
model = model.transform(GiveUniqueNodeNames()) model = model.transform(GiveUniqueNodeNames())
model = model.transform(InferDataLayouts()) model = model.transform(InferDataLayouts())
model.save(get_checkpoint_name(topology, wbits, abits, "convert_to_hls_layers")) model.save(
get_checkpoint_name(
topology, wbits, abits, QONNX_export, "convert_to_hls_layers"
)
)
def test_create_dataflow_partition(self, topology, wbits, abits): def test_create_dataflow_partition(self, topology, wbits, abits, QONNX_export):
prev_chkpt_name = get_checkpoint_name( prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, "convert_to_hls_layers" topology, wbits, abits, QONNX_export, "convert_to_hls_layers"
) )
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
parent_model = model.transform(CreateDataflowPartition()) parent_model = model.transform(CreateDataflowPartition())
parent_model_chkpt = get_checkpoint_name( parent_model_chkpt = get_checkpoint_name(
topology, wbits, abits, "dataflow_parent" topology, wbits, abits, QONNX_export, "dataflow_parent"
) )
parent_model.save(parent_model_chkpt) parent_model.save(parent_model_chkpt)
sdp_node = parent_model.get_nodes_by_op_type("StreamingDataflowPartition")[0] sdp_node = parent_model.get_nodes_by_op_type("StreamingDataflowPartition")[0]
...@@ -425,28 +463,36 @@ class TestEnd2End: ...@@ -425,28 +463,36 @@ class TestEnd2End:
dataflow_model_filename = sdp_node.get_nodeattr("model") dataflow_model_filename = sdp_node.get_nodeattr("model")
dataflow_model = load_test_checkpoint_or_skip(dataflow_model_filename) dataflow_model = load_test_checkpoint_or_skip(dataflow_model_filename)
dataflow_model_chkpt = get_checkpoint_name( dataflow_model_chkpt = get_checkpoint_name(
topology, wbits, abits, "dataflow_model" topology, wbits, abits, QONNX_export, "dataflow_model"
) )
dataflow_model.save(dataflow_model_chkpt) dataflow_model.save(dataflow_model_chkpt)
def test_fold(self, topology, wbits, abits): def test_fold(self, topology, wbits, abits, QONNX_export):
prev_chkpt_name = get_checkpoint_name(topology, wbits, abits, "dataflow_model") prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "dataflow_model"
)
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
folding_fxn = get_folding_function(topology, wbits, abits) folding_fxn = get_folding_function(topology, wbits, abits)
model = folding_fxn(model) model = folding_fxn(model)
model.save(get_checkpoint_name(topology, wbits, abits, "fold")) model.save(get_checkpoint_name(topology, wbits, abits, QONNX_export, "fold"))
@pytest.mark.slow @pytest.mark.slow
@pytest.mark.vivado @pytest.mark.vivado
def test_cppsim(self, topology, wbits, abits): def test_cppsim(self, topology, wbits, abits, QONNX_export):
prev_chkpt_name = get_checkpoint_name(topology, wbits, abits, "fold") prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "fold"
)
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
model = model.transform(PrepareCppSim()) model = model.transform(PrepareCppSim())
model = model.transform(CompileCppSim()) model = model.transform(CompileCppSim())
model = model.transform(SetExecMode("cppsim")) model = model.transform(SetExecMode("cppsim"))
cppsim_chkpt = get_checkpoint_name(topology, wbits, abits, "cppsim") cppsim_chkpt = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "cppsim"
)
model.save(cppsim_chkpt) model.save(cppsim_chkpt)
parent_chkpt = get_checkpoint_name(topology, wbits, abits, "dataflow_parent") parent_chkpt = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "dataflow_parent"
)
(input_tensor_npy, output_tensor_npy) = get_golden_io_pair( (input_tensor_npy, output_tensor_npy) = get_golden_io_pair(
topology, wbits, abits, return_topk=1 topology, wbits, abits, return_topk=1
) )
...@@ -456,22 +502,28 @@ class TestEnd2End: ...@@ -456,22 +502,28 @@ class TestEnd2End:
@pytest.mark.slow @pytest.mark.slow
@pytest.mark.vivado @pytest.mark.vivado
@pytest.mark.parametrize("kind", ["zynq", "alveo"]) @pytest.mark.parametrize("kind", ["zynq", "alveo"])
def test_ipgen(self, topology, wbits, abits, kind): def test_ipgen(self, topology, wbits, abits, QONNX_export, kind):
if kind == "alveo" and ("VITIS_PATH" not in os.environ): if kind == "alveo" and ("VITIS_PATH" not in os.environ):
pytest.skip("VITIS_PATH not set") pytest.skip("VITIS_PATH not set")
prev_chkpt_name = get_checkpoint_name(topology, wbits, abits, "fold") prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "fold"
)
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
test_fpga_part = get_build_env(kind, target_clk_ns)["part"] test_fpga_part = get_build_env(kind, target_clk_ns)["part"]
model = model.transform(GiveUniqueNodeNames()) model = model.transform(GiveUniqueNodeNames())
model = model.transform(PrepareIP(test_fpga_part, target_clk_ns)) model = model.transform(PrepareIP(test_fpga_part, target_clk_ns))
model = model.transform(HLSSynthIP()) model = model.transform(HLSSynthIP())
model.save(get_checkpoint_name(topology, wbits, abits, "ipgen_" + kind)) model.save(
get_checkpoint_name(topology, wbits, abits, QONNX_export, "ipgen_" + kind)
)
@pytest.mark.slow @pytest.mark.slow
@pytest.mark.vivado @pytest.mark.vivado
@pytest.mark.parametrize("kind", ["zynq", "alveo"]) @pytest.mark.parametrize("kind", ["zynq", "alveo"])
def test_set_fifo_depths(self, topology, wbits, abits, kind): def test_set_fifo_depths(self, topology, wbits, abits, QONNX_export, kind):
prev_chkpt_name = get_checkpoint_name(topology, wbits, abits, "ipgen_" + kind) prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "ipgen_" + kind
)
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
test_fpga_part = get_build_env(kind, target_clk_ns)["part"] test_fpga_part = get_build_env(kind, target_clk_ns)["part"]
model = model.transform(InsertAndSetFIFODepths(test_fpga_part, target_clk_ns)) model = model.transform(InsertAndSetFIFODepths(test_fpga_part, target_clk_ns))
...@@ -483,14 +535,18 @@ class TestEnd2End: ...@@ -483,14 +535,18 @@ class TestEnd2End:
op_inst = getCustomOp(node) op_inst = getCustomOp(node)
assert op_inst.get_nodeattr("inFIFODepth") == 0 assert op_inst.get_nodeattr("inFIFODepth") == 0
assert op_inst.get_nodeattr("outFIFODepth") == 0 assert op_inst.get_nodeattr("outFIFODepth") == 0
model.save(get_checkpoint_name(topology, wbits, abits, "fifodepth_" + kind)) model.save(
get_checkpoint_name(
topology, wbits, abits, QONNX_export, "fifodepth_" + kind
)
)
@pytest.mark.slow @pytest.mark.slow
@pytest.mark.vivado @pytest.mark.vivado
@pytest.mark.parametrize("kind", ["zynq"]) @pytest.mark.parametrize("kind", ["zynq"])
def test_ipstitch_rtlsim(self, topology, wbits, abits, kind): def test_ipstitch_rtlsim(self, topology, wbits, abits, QONNX_export, kind):
prev_chkpt_name = get_checkpoint_name( prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, "fifodepth_" + kind topology, wbits, abits, QONNX_export, "fifodepth_" + kind
) )
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
test_fpga_part = get_build_env(kind, target_clk_ns)["part"] test_fpga_part = get_build_env(kind, target_clk_ns)["part"]
...@@ -514,10 +570,12 @@ class TestEnd2End: ...@@ -514,10 +570,12 @@ class TestEnd2End:
) )
os.environ["RTLSIM_TRACE_DEPTH"] = "3" os.environ["RTLSIM_TRACE_DEPTH"] = "3"
rtlsim_chkpt = get_checkpoint_name( rtlsim_chkpt = get_checkpoint_name(
topology, wbits, abits, "ipstitch_rtlsim_" + kind topology, wbits, abits, QONNX_export, "ipstitch_rtlsim_" + kind
) )
model.save(rtlsim_chkpt) model.save(rtlsim_chkpt)
parent_chkpt = get_checkpoint_name(topology, wbits, abits, "dataflow_parent") parent_chkpt = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "dataflow_parent"
)
(input_tensor_npy, output_tensor_npy) = get_golden_io_pair( (input_tensor_npy, output_tensor_npy) = get_golden_io_pair(
topology, wbits, abits, return_topk=1 topology, wbits, abits, return_topk=1
) )
...@@ -527,9 +585,9 @@ class TestEnd2End: ...@@ -527,9 +585,9 @@ class TestEnd2End:
@pytest.mark.slow @pytest.mark.slow
@pytest.mark.vivado @pytest.mark.vivado
@pytest.mark.parametrize("kind", ["zynq"]) @pytest.mark.parametrize("kind", ["zynq"])
def test_throughput_rtlsim(self, topology, wbits, abits, kind): def test_throughput_rtlsim(self, topology, wbits, abits, QONNX_export, kind):
prev_chkpt_name = get_checkpoint_name( prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, "ipstitch_rtlsim_" + kind topology, wbits, abits, QONNX_export, "ipstitch_rtlsim_" + kind
) )
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
n_nodes = len(model.graph.node) n_nodes = len(model.graph.node)
...@@ -550,15 +608,23 @@ class TestEnd2End: ...@@ -550,15 +608,23 @@ class TestEnd2End:
@pytest.mark.slow @pytest.mark.slow
@pytest.mark.vivado @pytest.mark.vivado
@pytest.mark.parametrize("kind", ["zynq"]) @pytest.mark.parametrize("kind", ["zynq"])
def test_validate_top1(self, topology, wbits, abits, kind): def test_validate_top1(self, topology, wbits, abits, QONNX_export, kind):
if "TEST_END2END_VALIDATE_TOP1" not in os.environ: if "TEST_END2END_VALIDATE_TOP1" not in os.environ:
pytest.skip("TEST_END2END_VALIDATE_TOP1 not set") pytest.skip("TEST_END2END_VALIDATE_TOP1 not set")
prepostproc_chkpt = get_checkpoint_name(topology, wbits, abits, "pre_post") prepostproc_chkpt = get_checkpoint_name(
streamline_chkpt = get_checkpoint_name(topology, wbits, abits, "streamline") topology, wbits, abits, QONNX_export, "pre_post"
parent_chkpt = get_checkpoint_name(topology, wbits, abits, "dataflow_parent") )
cppsim_chkpt = get_checkpoint_name(topology, wbits, abits, "cppsim") streamline_chkpt = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "streamline"
)
parent_chkpt = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "dataflow_parent"
)
cppsim_chkpt = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "cppsim"
)
rtlsim_chkpt = get_checkpoint_name( rtlsim_chkpt = get_checkpoint_name(
topology, wbits, abits, "ipstitch_rtlsim_" + kind topology, wbits, abits, QONNX_export, "ipstitch_rtlsim_" + kind
) )
dataset = topology2dataset(topology) dataset = topology2dataset(topology)
assert measure_top1_accuracy(prepostproc_chkpt, dataset) > 80 assert measure_top1_accuracy(prepostproc_chkpt, dataset) > 80
...@@ -570,11 +636,11 @@ class TestEnd2End: ...@@ -570,11 +636,11 @@ class TestEnd2End:
@pytest.mark.vivado @pytest.mark.vivado
@pytest.mark.vitis @pytest.mark.vitis
@pytest.mark.parametrize("kind", ["zynq", "alveo"]) @pytest.mark.parametrize("kind", ["zynq", "alveo"])
def test_build(self, topology, wbits, abits, kind): def test_build(self, topology, wbits, abits, QONNX_export, kind):
if kind == "alveo" and ("VITIS_PATH" not in os.environ): if kind == "alveo" and ("VITIS_PATH" not in os.environ):
pytest.skip("VITIS_PATH not set") pytest.skip("VITIS_PATH not set")
prev_chkpt_name = get_checkpoint_name( prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, "fifodepth_" + kind topology, wbits, abits, QONNX_export, "fifodepth_" + kind
) )
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
cfg = get_build_env(kind, target_clk_ns) cfg = get_build_env(kind, target_clk_ns)
...@@ -584,24 +650,32 @@ class TestEnd2End: ...@@ -584,24 +650,32 @@ class TestEnd2End:
for (k, v) in synth_dct.items(): for (k, v) in synth_dct.items():
update_dashboard_data(topology, wbits, abits, k, v) update_dashboard_data(topology, wbits, abits, k, v)
update_dashboard_data(topology, wbits, abits, "board", cfg["board"]) update_dashboard_data(topology, wbits, abits, "board", cfg["board"])
model.save(get_checkpoint_name(topology, wbits, abits, "build_" + kind)) model.save(
get_checkpoint_name(topology, wbits, abits, QONNX_export, "build_" + kind)
)
@pytest.mark.slow @pytest.mark.slow
@pytest.mark.vivado @pytest.mark.vivado
@pytest.mark.vitis @pytest.mark.vitis
@pytest.mark.parametrize("kind", ["zynq", "alveo"]) @pytest.mark.parametrize("kind", ["zynq", "alveo"])
def test_make_pynq_driver(self, topology, wbits, abits, kind): def test_make_pynq_driver(self, topology, wbits, abits, QONNX_export, kind):
if kind == "alveo" and ("VITIS_PATH" not in os.environ): if kind == "alveo" and ("VITIS_PATH" not in os.environ):
pytest.skip("VITIS_PATH not set") pytest.skip("VITIS_PATH not set")
prev_chkpt_name = get_checkpoint_name(topology, wbits, abits, "build_" + kind) prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "build_" + kind
)
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
kind_to_driver_platform = {"zynq": "zynq-iodma", "alveo": "alveo"} kind_to_driver_platform = {"zynq": "zynq-iodma", "alveo": "alveo"}
model = model.transform(MakePYNQDriver(kind_to_driver_platform[kind])) model = model.transform(MakePYNQDriver(kind_to_driver_platform[kind]))
model.save(get_checkpoint_name(topology, wbits, abits, "driver_" + kind)) model.save(
get_checkpoint_name(topology, wbits, abits, QONNX_export, "driver_" + kind)
)
@pytest.mark.parametrize("kind", ["zynq", "alveo"]) @pytest.mark.parametrize("kind", ["zynq", "alveo"])
def test_deploy(self, topology, wbits, abits, kind): def test_deploy(self, topology, wbits, abits, QONNX_export, kind):
prev_chkpt_name = get_checkpoint_name(topology, wbits, abits, "driver_" + kind) prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "driver_" + kind
)
model = load_test_checkpoint_or_skip(prev_chkpt_name) model = load_test_checkpoint_or_skip(prev_chkpt_name)
cfg = get_build_env(kind, target_clk_ns) cfg = get_build_env(kind, target_clk_ns)
if cfg["ip"] == "": if cfg["ip"] == "":
...@@ -616,11 +690,15 @@ class TestEnd2End: ...@@ -616,11 +690,15 @@ class TestEnd2End:
) )
) )
# save the model to be able to link it to the parent # save the model to be able to link it to the parent
model.save(get_checkpoint_name(topology, wbits, abits, "deploy_" + kind)) model.save(
get_checkpoint_name(topology, wbits, abits, QONNX_export, "deploy_" + kind)
)
@pytest.mark.parametrize("kind", ["zynq", "alveo"]) @pytest.mark.parametrize("kind", ["zynq", "alveo"])
def test_run_on_hw(self, topology, wbits, abits, kind): def test_run_on_hw(self, topology, wbits, abits, QONNX_export, kind):
prev_chkpt_name = get_checkpoint_name(topology, wbits, abits, "deploy_" + kind) prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "deploy_" + kind
)
model = load_test_checkpoint_or_skip(prev_chkpt_name) # NOQA model = load_test_checkpoint_or_skip(prev_chkpt_name) # NOQA
cfg = get_build_env(kind, target_clk_ns) cfg = get_build_env(kind, target_clk_ns)
if cfg["ip"] == "": if cfg["ip"] == "":
...@@ -629,7 +707,7 @@ class TestEnd2End: ...@@ -629,7 +707,7 @@ class TestEnd2End:
topology, wbits, abits, return_topk=1 topology, wbits, abits, return_topk=1
) )
parent_model = load_test_checkpoint_or_skip( parent_model = load_test_checkpoint_or_skip(
get_checkpoint_name(topology, wbits, abits, "dataflow_parent") get_checkpoint_name(topology, wbits, abits, QONNX_export, "dataflow_parent")
) )
iname = parent_model.graph.input[0].name iname = parent_model.graph.input[0].name
oname = parent_model.graph.output[0].name oname = parent_model.graph.output[0].name
...@@ -641,8 +719,10 @@ class TestEnd2End: ...@@ -641,8 +719,10 @@ class TestEnd2End:
assert np.isclose(y, output_tensor_npy).all() assert np.isclose(y, output_tensor_npy).all()
@pytest.mark.parametrize("kind", ["zynq", "alveo"]) @pytest.mark.parametrize("kind", ["zynq", "alveo"])
def test_throughput_hw(self, topology, wbits, abits, kind): def test_throughput_hw(self, topology, wbits, abits, QONNX_export, kind):
prev_chkpt_name = get_checkpoint_name(topology, wbits, abits, "deploy_" + kind) prev_chkpt_name = get_checkpoint_name(
topology, wbits, abits, QONNX_export, "deploy_" + kind
)
end2end_example = "%s_w%da%d_%s" % (topology, wbits, abits, kind) end2end_example = "%s_w%da%d_%s" % (topology, wbits, abits, kind)
model = load_test_checkpoint_or_skip(prev_chkpt_name) # NOQA model = load_test_checkpoint_or_skip(prev_chkpt_name) # NOQA
cfg = get_build_env(kind, target_clk_ns) cfg = get_build_env(kind, target_clk_ns)
...@@ -698,9 +778,13 @@ class TestEnd2End: ...@@ -698,9 +778,13 @@ class TestEnd2End:
ret[largest_bsize]["throughput[images/s]"], ret[largest_bsize]["throughput[images/s]"],
) )
def test_upload_results_to_dashboard(self, topology, wbits, abits): def test_upload_results_to_dashboard(self, topology, wbits, abits, QONNX_export):
dashboard_data = get_dashboard_data(topology, wbits, abits) # ToDo: Extend the dashboard to also upload QONNX exported models?
if len(dashboard_data.keys()) > 0: if QONNX_export:
upload_to_end2end_dashboard(dashboard_data) pytest.skip("Dashboard data upload is disabled for QONNX exported models.")
else: else:
pytest.skip("No data to upload to dashboard") dashboard_data = get_dashboard_data(topology, wbits, abits)
if len(dashboard_data.keys()) > 0:
upload_to_end2end_dashboard(dashboard_data)
else:
pytest.skip("No data to upload to dashboard")
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