diff --git a/src/finn/qnn-data/templates/driver/driver_base.py b/src/finn/qnn-data/templates/driver/driver_base.py
index ef16a537ce18c52ea42ce9178a7178e8f8b667dd..58ef94bfd7a03bb0d5fb8e5a7bf5695f6b961527 100644
--- a/src/finn/qnn-data/templates/driver/driver_base.py
+++ b/src/finn/qnn-data/templates/driver/driver_base.py
@@ -125,15 +125,16 @@ class FINNExampleOverlay(Overlay):
layer_w = np.fromiter(
[int(x, 16) for x in dat.strip().split()], dtype=np.uint32
)
- layer_ind = int(w_filename.split("_")[0])
- rt_weight_dict[layer_ind] = layer_w
- for layer_ind in rt_weight_dict.keys():
- cand_if_name = "StreamingDataflowPartition_1/s_axilite_%d" % layer_ind
+ sdp_ind = int(w_filename.split("_")[0])
+ layer_ind = int(w_filename.split("_")[1])
+ rt_weight_dict[(sdp_ind,layer_ind)] = layer_w
+ for sdp_ind,layer_ind in rt_weight_dict.keys():
+ cand_if_name = "StreamingDataflowPartition_%d/s_axilite_%d" % (sdp_ind,layer_ind)
if cand_if_name in self.ip_dict.keys():
layer_mmio = getattr(
- self.StreamingDataflowPartition_1, "s_axilite_%d" % layer_ind
+ getattr(self,"StreamingDataflowPartition_%d" % sdp_ind), "s_axilite_%d" % layer_ind
).mmio
- layer_w = rt_weight_dict[layer_ind]
+ layer_w = rt_weight_dict[(sdp_ind,layer_ind)]
layer_mmio.write_mm(0, layer_w.tobytes())
if verify:
new_w = np.copy(layer_mmio.array[: layer_w.shape[0]])
diff --git a/src/finn/transformation/fpgadataflow/make_pynq_driver.py b/src/finn/transformation/fpgadataflow/make_pynq_driver.py
index 84dc01e536e96298ecb57e133610d800fcd2eb5c..ac5cdb4f5389cd2f30f180773741f140b7145822 100644
--- a/src/finn/transformation/fpgadataflow/make_pynq_driver.py
+++ b/src/finn/transformation/fpgadataflow/make_pynq_driver.py
@@ -37,12 +37,12 @@ import os
import warnings
import pkg_resources as pk
from . import template_driver
-
+from finn.core.modelwrapper import ModelWrapper
class MakePYNQDriver(Transformation):
"""Create PYNQ Python code to correctly interface the generated
accelerator, including data packing/unpacking. Should be called
- after conversion to HLS layers and folding, but prior to the creation of
+ after conversion to HLS layers, folding and the creation of
dataflow partitions for correct operation.
platform: one of ["zynq-iodma", "alveo"]
@@ -149,24 +149,29 @@ class MakePYNQDriver(Transformation):
# generate weight files for runtime-writable layers
weights_dir = pynq_driver_dir + "/runtime_weights"
- rt_layer_ind = 0
+
os.makedirs(weights_dir)
- for node in model.graph.node:
- if node.op_type in ["StreamingFCLayer_Batch", "Thresholding_Batch"]:
- node_inst = getCustomOp(node)
- is_rt_weights = node_inst.get_nodeattr("runtime_writeable_weights")
- if is_rt_weights == 1:
- fcl_w = model.get_initializer(node.input[1])
- w_filename = weights_dir + "/%d_%s.dat" % (rt_layer_ind, node.name)
- node_inst.make_weight_file(fcl_w, "decoupled_runtime", w_filename)
- rt_layer_ind += 1
- elif node.op_type == "StreamingDataflowPartition":
- warnings.warn(
- """Please call MakePYNQDriver prior to
- CreateDataflowPartition. Can only extract runtime-writable
- weights from HLSCustomOp instances and not StreamingDataflowPartition.
- """
- )
- else:
- continue
- return (model, False)
+ for sdp_ind, sdp_node in enumerate(model.graph.node):
+ assert sdp_node.op_type == "StreamingDataflowPartition"
+ # get dataflow model
+ sdp_node = getCustomOp(sdp_node)
+ dataflow_model_filename = sdp_node.get_nodeattr("model")
+ dataflow_model = ModelWrapper(dataflow_model_filename)
+ rt_layer_ind = 0
+ for node in dataflow_model.graph.node:
+ if node.op_type in ["StreamingFCLayer_Batch", "Thresholding_Batch"]:
+ node_inst = getCustomOp(node)
+ is_rt_weights = node_inst.get_nodeattr("runtime_writeable_weights")
+ if is_rt_weights == 1:
+ fcl_w = dataflow_model.get_initializer(node.input[1])
+ w_filename = weights_dir + "/%d_%d_%s.dat" % (sdp_ind,rt_layer_ind, node.name)
+ node_inst.make_weight_file(fcl_w, "decoupled_runtime", w_filename)
+ rt_layer_ind += 1
+ elif node.op_type == "StreamingDataflowPartition":
+ warnings.warn(
+ """Nested StreamingDataflowPartition are not supported
+ """
+ )
+ else:
+ continue
+ return (model, False)
\ No newline at end of file
diff --git a/src/finn/transformation/fpgadataflow/make_zynq_proj.py b/src/finn/transformation/fpgadataflow/make_zynq_proj.py
index 1ac7ee178531e745bf68405d1ae9df35c0c216fb..3dab426ccf9bab73ddac83299bdc47f89ea46bdc 100644
--- a/src/finn/transformation/fpgadataflow/make_zynq_proj.py
+++ b/src/finn/transformation/fpgadataflow/make_zynq_proj.py
@@ -286,7 +286,10 @@ class MakeZYNQProject(Transformation):
class ZynqBuild(Transformation):
- """Best-effort attempt at building the accelerator for Zynq."""
+ """Best-effort attempt at building the accelerator for Zynq.
+ It assumes the model has only fpgadataflow nodes
+
+ """
def __init__(self, platform, period_ns, enable_debug=False):
super().__init__()
@@ -300,7 +303,6 @@ class ZynqBuild(Transformation):
model = model.transform(InferDataLayouts())
# prepare at global level, then break up into kernels
prep_transforms = [
- MakePYNQDriver(platform="zynq-iodma"),
InsertIODMA(64),
InsertDWC(),
Floorplan(),
@@ -335,6 +337,10 @@ class ZynqBuild(Transformation):
model = model.transform(
MakeZYNQProject(self.platform, enable_debug=self.enable_debug)
)
+
# set platform attribute for correct remote execution
model.set_metadata_prop("platform", "zynq-iodma")
+
+ # create driver
+ model = model.transform(MakePYNQDriver(platform="zynq-iodma"))
return (model, False)
diff --git a/src/finn/transformation/fpgadataflow/vitis_build.py b/src/finn/transformation/fpgadataflow/vitis_build.py
index 11cf46bb6e2233156c34b00f0d2126fc92255238..0fe4276096852c08d0798be8e1ee715cc5769286 100644
--- a/src/finn/transformation/fpgadataflow/vitis_build.py
+++ b/src/finn/transformation/fpgadataflow/vitis_build.py
@@ -330,6 +330,7 @@ class VitisLink(Transformation):
class VitisBuild(Transformation):
"""Best-effort attempt at building the accelerator with Vitis.
+ It assumes the model has only fpgadataflow nodes
fpga_part: string identifying the target FPGA
period_ns: target clock period
@@ -365,7 +366,6 @@ class VitisBuild(Transformation):
model = model.transform(InferDataLayouts())
# prepare at global level, then break up into kernels
prep_transforms = [
- MakePYNQDriver(platform="alveo"),
InsertIODMA(512),
InsertDWC(),
]
@@ -416,4 +416,6 @@ class VitisBuild(Transformation):
# set platform attribute for correct remote execution
model.set_metadata_prop("platform", "alveo")
+ #create driver
+ model = model.transform(MakePYNQDriver(platform="alveo"))
return (model, False)