From 4672031c90861297a93556a40c71a8c32db4d4e1 Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <maltanar@gmail.com>
Date: Tue, 11 Feb 2020 18:50:40 +0100
Subject: [PATCH] [CustomOp] add StreamingDataflowPartition CustomOp
---
src/finn/custom_op/registry.py | 2 +
.../custom_op/streamingdataflowpartition.py | 65 +++++++++++++++++++
2 files changed, 67 insertions(+)
create mode 100644 src/finn/custom_op/streamingdataflowpartition.py
diff --git a/src/finn/custom_op/registry.py b/src/finn/custom_op/registry.py
index bd1605c96..c38a28dae 100644
--- a/src/finn/custom_op/registry.py
+++ b/src/finn/custom_op/registry.py
@@ -7,6 +7,7 @@ from finn.custom_op.fpgadataflow.streamingfclayer_batch import StreamingFCLayer_
from finn.custom_op.fpgadataflow.streamingmaxpool_batch import StreamingMaxPool_Batch
from finn.custom_op.fpgadataflow.tlastmarker import TLastMarker
from finn.custom_op.multithreshold import MultiThreshold
+from finn.custom_op.streamingdataflowpartition import StreamingDataflowPartition
from finn.custom_op.xnorpopcount import XnorPopcountMatMul
# create a mapping of all known CustomOp names and classes
@@ -18,6 +19,7 @@ custom_op["StreamingMaxPool_Batch"] = StreamingMaxPool_Batch
custom_op["StreamingFCLayer_Batch"] = StreamingFCLayer_Batch
custom_op["ConvolutionInputGenerator"] = ConvolutionInputGenerator
custom_op["TLastMarker"] = TLastMarker
+custom_op["StreamingDataflowPartition"] = StreamingDataflowPartition
def getCustomOp(node):
diff --git a/src/finn/custom_op/streamingdataflowpartition.py b/src/finn/custom_op/streamingdataflowpartition.py
new file mode 100644
index 000000000..856ba6d56
--- /dev/null
+++ b/src/finn/custom_op/streamingdataflowpartition.py
@@ -0,0 +1,65 @@
+from finn.custom_op import CustomOp
+
+# note that the StreamingDataflowPartition node is only a meta/container node,
+# it does not produce any HLS or bitfile by itself. it's a placeholder for
+# a group of fpgadataflow nodes that have been separated out into a FINN-ONNX
+# model of its own.
+
+
+class StreamingDataflowPartition(CustomOp):
+ def get_nodeattr_types(self):
+ return {
+ "model": ("s", True, ""),
+ }
+
+ def make_shape_compatible_op(self):
+ pass
+
+ def infer_node_datatype(self, model):
+ pass
+
+ def execute_node(self, context, graph):
+ # TODO add RPC execution with synthesized bitfile?
+ # whole-design rtlsim with PyVerilator may also be an alternative
+ pass
+
+ def verify_node(self):
+ info_messages = []
+
+ # verify number of attributes
+ num_of_attr = 1
+ if len(self.onnx_node.attribute) == num_of_attr:
+ info_messages.append("The number of attributes is correct")
+ else:
+ info_messages.append(
+ """The number of attributes is incorrect,
+ {} should have {} attributes""".format(
+ self.onnx_node.op_type, num_of_attr
+ )
+ )
+
+ # verify that "domain" is set to "finn"
+ domain_value = self.onnx_node.domain
+ if domain_value == "finn":
+ info_messages.append("Attribute domain is set correctly")
+ else:
+ info_messages.append('Attribute domain should be set to "finn"')
+
+ # verify that all necessary attributes exist
+ try:
+ self.get_nodeattr("model")
+ info_messages.append("All necessary attributes exist")
+ except Exception:
+ info_messages.append(
+ """The necessary attributes do not exist.
+ StreamingDataflowPartition needs the following attribute(s):
+ model"""
+ )
+
+ # verify the number of inputs
+ if len(self.onnx_node.input) == 1:
+ info_messages.append("The number of inputs is correct")
+ else:
+ info_messages.append("StreamingDataflowPartition needs 1 data input")
+
+ return info_messages
--
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