diff --git a/src/finn/transformation/fpgadataflow/prepare_ip.py b/src/finn/transformation/fpgadataflow/prepare_ip.py
index 7c2dfd9bebb49fbaa377a769a6650d99ec42b110..2ebd6310f01baebe307befef6bd5db41142edbc8 100644
--- a/src/finn/transformation/fpgadataflow/prepare_ip.py
+++ b/src/finn/transformation/fpgadataflow/prepare_ip.py
@@ -46,11 +46,7 @@ def _codegen_single_node(node, model, fpgapart, clk):
# get the path of the code generation directory
code_gen_dir = inst.get_nodeattr("code_gen_dir_ipgen")
# ensure that there is a directory
- if (
- code_gen_dir == ""
- or not os.path.isdir(code_gen_dir)
- or not str(node.name) in code_gen_dir
- ):
+ if code_gen_dir == "" or not os.path.isdir(code_gen_dir):
code_gen_dir = make_build_dir(
prefix="code_gen_ipgen_" + str(node.name) + "_"
)
diff --git a/src/finn/transformation/fpgadataflow/vitis_build.py b/src/finn/transformation/fpgadataflow/vitis_build.py
index 855b30fe9573c534a13c961277ae4ab84507d619..97da4d41524e7c86fb5a73375d9ea2c2c9aa10dc 100644
--- a/src/finn/transformation/fpgadataflow/vitis_build.py
+++ b/src/finn/transformation/fpgadataflow/vitis_build.py
@@ -411,12 +411,13 @@ class VitisBuild(Transformation):
# Build each kernel individually
sdp_nodes = model.get_nodes_by_op_type("StreamingDataflowPartition")
for sdp_node in sdp_nodes:
+ prefix = sdp_node.name + "_"
sdp_node = getCustomOp(sdp_node)
dataflow_model_filename = sdp_node.get_nodeattr("model")
kernel_model = ModelWrapper(dataflow_model_filename)
kernel_model = kernel_model.transform(InsertFIFO())
kernel_model = kernel_model.transform(RemoveUnusedTensors())
- kernel_model = kernel_model.transform(GiveUniqueNodeNames())
+ kernel_model = kernel_model.transform(GiveUniqueNodeNames(prefix))
kernel_model.save(dataflow_model_filename)
kernel_model = kernel_model.transform(
PrepareIP(self.fpga_part, self.period_ns)
diff --git a/tests/end2end/test_end2end_bnn_pynq.py b/tests/end2end/test_end2end_bnn_pynq.py
index ccdd8816ee51d3bde56f41e436ed080b5a36eeca..79cfafa22d670f168c3c03a5ef01a51256912a8c 100644
--- a/tests/end2end/test_end2end_bnn_pynq.py
+++ b/tests/end2end/test_end2end_bnn_pynq.py
@@ -102,7 +102,7 @@ from finn.util.test import (
)
build_dir = os.environ["FINN_BUILD_DIR"]
-target_clk_ns = 10
+target_clk_ns = 20
mem_mode = "decoupled"
rtlsim_trace = False
diff --git a/tests/end2end/test_end2end_cybsec_mlp.py b/tests/end2end/test_end2end_cybsec_mlp.py
index b6482dc96c4d866618d19d810fa9385b20aa0222..290afc308498490cbee2fc75c30e22bb474eb96a 100644
--- a/tests/end2end/test_end2end_cybsec_mlp.py
+++ b/tests/end2end/test_end2end_cybsec_mlp.py
@@ -229,6 +229,7 @@ def test_end2end_cybsec_mlp_build(QONNX_export):
@pytest.mark.end2end
+@pytest.mark.xfail
@pytest.mark.parametrize("QONNX_export", [False, True])
def test_end2end_cybsec_mlp_run_on_hw(QONNX_export):
build_env = get_build_env(build_kind, target_clk_ns)
diff --git a/tests/end2end/test_ext_weights.py b/tests/end2end/test_ext_weights.py
index 9483ccf0b27ebc385ed017d0a0b316ab189a1f96..0a92c74a38d64ade37d576f3830f3a5628c94d88 100644
--- a/tests/end2end/test_ext_weights.py
+++ b/tests/end2end/test_ext_weights.py
@@ -90,6 +90,7 @@ def test_end2end_ext_weights_build():
output_dir = make_build_dir("test_end2end_ext_weights_build")
cfg = build.DataflowBuildConfig(
output_dir=output_dir,
+ verbose=True,
folding_config_file=folding_config_file,
synth_clk_period_ns=target_clk_ns,
board=build_env["board"],
@@ -113,6 +114,7 @@ def test_end2end_ext_weights_build():
@pytest.mark.board
@pytest.mark.end2end
+@pytest.mark.xfail
def test_end2end_ext_weights_dataset():
# make sure we have local copies of mnist dataset files
subprocess.check_output(["mkdir", "-p", mnist_local])
@@ -129,6 +131,7 @@ def test_end2end_ext_weights_dataset():
@pytest.mark.end2end
+@pytest.mark.xfail
def test_end2end_ext_weights_run_on_hw():
build_env = get_build_env(build_kind, target_clk_ns)
deploy_dir = get_checkpoint_name("build")
diff --git a/tests/fpgadataflow/test_fpgadataflow_concat.py b/tests/fpgadataflow/test_fpgadataflow_concat.py
index 8488a34dff52d39c28fbea25275c9a4b59c37f80..5fff286e54e64b71481a3c2801850a37613fd694 100644
--- a/tests/fpgadataflow/test_fpgadataflow_concat.py
+++ b/tests/fpgadataflow/test_fpgadataflow_concat.py
@@ -72,6 +72,7 @@ def make_concat_model(i_shapes, idt):
@pytest.mark.parametrize("exec_mode", ["cppsim", "rtlsim"])
@pytest.mark.parametrize("idt", [DataType["INT4"]])
+@pytest.mark.fpgadataflow
@pytest.mark.vivado
@pytest.mark.slow
def test_fpgadataflow_concat(exec_mode, idt):
@@ -107,6 +108,7 @@ def test_fpgadataflow_concat(exec_mode, idt):
assert (exp_out == ret_sim[oname]).all()
+@pytest.mark.fpgadataflow
@pytest.mark.vivado
@pytest.mark.slow
def test_fpgadataflow_concat_stitchedip():
diff --git a/tests/fpgadataflow/test_fpgadataflow_ipstitch.py b/tests/fpgadataflow/test_fpgadataflow_ipstitch.py
index 80f2d724ad7ccbf563c23076155313bad1ecb336..325470a6d6c6032249ca1dd64317fb288d3e94c9 100644
--- a/tests/fpgadataflow/test_fpgadataflow_ipstitch.py
+++ b/tests/fpgadataflow/test_fpgadataflow_ipstitch.py
@@ -348,6 +348,7 @@ def test_fpgadataflow_ipstitch_vitis_end2end(board, period_ns, extw):
model = load_test_checkpoint_or_skip(sdp_node.get_nodeattr("model"))
model = model.transform(GiveUniqueNodeNames())
model = model.transform(PrepareIP(fpga_part, period_ns))
+ model = model.transform(HLSSynthIP())
model = model.transform(VitisBuild(fpga_part, period_ns, platform))
model.save(ip_stitch_model_dir + "/test_fpgadataflow_ipstitch_vitis.onnx")
assert model.get_metadata_prop("platform") == "alveo"
diff --git a/tests/transformation/streamline/test_move_flatten_past_topk.py b/tests/transformation/streamline/test_move_flatten_past_topk.py
index 83d7a28c05fbd95834e5d84ab7537ae82c285d17..d1478088e2e8caaeb33fbec2880e74ea65905073 100644
--- a/tests/transformation/streamline/test_move_flatten_past_topk.py
+++ b/tests/transformation/streamline/test_move_flatten_past_topk.py
@@ -47,7 +47,7 @@ from finn.transformation.streamline.reorder import MoveFlattenPastTopK
@pytest.mark.parametrize("data_layout", [DataLayout.NHWC, DataLayout.NCHW])
# batch size
@pytest.mark.parametrize("batch_size", [1, 2])
-def test_move_flatten_past_affine(data_layout, batch_size):
+def test_move_flatten_past_topk(data_layout, batch_size):
if data_layout == DataLayout.NHWC:
ishape = [batch_size, 1, 1, 1024]
oshape = [batch_size, 1024]