From 1f30c3fbfbb0fcbbd6964d5c9b186ea26d2131ea Mon Sep 17 00:00:00 2001
From: auphelia <jakobapk@web.de>
Date: Thu, 9 Apr 2020 17:21:19 +0100
Subject: [PATCH] [StreamingFIFO] Remove functions that would overwrite
functions for npysim code generation
---
.../custom_op/fpgadataflow/streamingfifo.py | 16 +-
.../fpgadataflow/insert_fifo.py | 149 ++++++++++++++++++
2 files changed, 153 insertions(+), 12 deletions(-)
create mode 100644 src/finn/transformation/fpgadataflow/insert_fifo.py
diff --git a/src/finn/custom_op/fpgadataflow/streamingfifo.py b/src/finn/custom_op/fpgadataflow/streamingfifo.py
index 75f668c71..8fcb1fe43 100644
--- a/src/finn/custom_op/fpgadataflow/streamingfifo.py
+++ b/src/finn/custom_op/fpgadataflow/streamingfifo.py
@@ -95,7 +95,7 @@ class StreamingFIFO(HLSCustomOp):
# empty code gen dictionary for new entries
self.code_gen_dict.clear()
- self.code_gen_dict["$TOPNAME$"] = ["top_{}".format(self.onnx_node.name)]
+ self.code_gen_dict["$TOPNAME$"] = ["{}".format(self.onnx_node.name)]
self.code_gen_dict["$LAYER_NAME$"] = [
"{}_{}".format(self.onnx_node.name, self.onnx_node.name)
]
@@ -112,9 +112,7 @@ class StreamingFIFO(HLSCustomOp):
# transform list into long string separated by '\n'
code_gen_line = "\n".join(self.code_gen_dict[key])
template = template.replace(key, code_gen_line)
- f = open(
- os.path.join(code_gen_dir, "top_{}.v".format(self.onnx_node.name)), "w",
- )
+ f = open(os.path.join(code_gen_dir, "{}.v".format(self.onnx_node.name)), "w",)
f.write(template)
f.close()
self.code_gen_dict.clear()
@@ -124,7 +122,7 @@ class StreamingFIFO(HLSCustomOp):
# prepare the IP packaging tcl template
template = templates.ip_package_tcl
self.code_gen_dict.clear()
- self.code_gen_dict["$TOPNAME$"] = ["top_{}".format(self.onnx_node.name)]
+ self.code_gen_dict["$TOPNAME$"] = ["{}".format(self.onnx_node.name)]
self.code_gen_dict["$VERILOG_DIR$"] = [code_gen_dir]
for key in self.code_gen_dict:
# transform list into long string separated by '\n'
@@ -151,12 +149,6 @@ class StreamingFIFO(HLSCustomOp):
self.set_nodeattr("ip_vlnv", vlnv)
self.code_gen_dict.clear()
- def code_generation_npysim(self, model):
- pass
-
- def compile_singlenode_code(self):
- pass
-
def get_normal_input_shape(self):
depth = self.get_nodeattr("depth")
assert (
@@ -233,7 +225,7 @@ class StreamingFIFO(HLSCustomOp):
os.path.join(code_gen_dir, "input_0.npy"), reshaped_input,
)
verilog_file = os.path.join(
- code_gen_dir, "top_{}.v".format(self.onnx_node.name)
+ code_gen_dir, "{}.v".format(self.onnx_node.name)
)
if os.path.isfile(verilog_file):
nbits = self.get_instream_width(axi_strm_padding=True)
diff --git a/src/finn/transformation/fpgadataflow/insert_fifo.py b/src/finn/transformation/fpgadataflow/insert_fifo.py
new file mode 100644
index 000000000..c7efb95c8
--- /dev/null
+++ b/src/finn/transformation/fpgadataflow/insert_fifo.py
@@ -0,0 +1,149 @@
+from onnx import TensorProto
+from onnx import helper as oh
+
+from finn.custom_op.registry import getCustomOp
+from finn.transformation import Transformation
+from finn.util.fpgadataflow import is_fpgadataflow_node
+
+
+def _is_fifo_node(node):
+ if node.op_type == "StreamingFIFO":
+ return True
+ else:
+ return False
+
+
+def _suitable_node(node):
+ if node is not None:
+ if is_fpgadataflow_node(node) is True:
+ if _is_fifo_node(node) is False:
+ return True
+ else:
+ return False
+ else:
+ return False
+ else:
+ return False
+
+
+class InsertFIFO(Transformation):
+ """Ensure that the graph is terminated with a TLastMarker node, inserting
+ one if necessary."""
+
+ def __init__(self):
+ super().__init__()
+
+ def apply(self, model):
+ # default depth for FIFOs
+ default_depth = 2
+ graph = model.graph
+ node_ind = -1
+ graph_modified = False
+ for n in graph.node:
+ node_ind += 1
+ if _suitable_node(n):
+ n_output = n.output[0]
+ consumer = model.find_consumer(n_output)
+ if _suitable_node(consumer) is True:
+ graph_modified = True
+ n0 = getCustomOp(n)
+ # determine fifo node attributes
+ fld_shape = n0.get_folded_output_shape()
+ dtype = n0.get_output_datatype()
+
+ # create fifo node
+ fifo_output_tensor = oh.make_tensor_value_info(
+ model.make_new_valueinfo_name(),
+ TensorProto.FLOAT,
+ n0.get_normal_output_shape(),
+ )
+ graph.value_info.append(fifo_output_tensor)
+
+ fifo_node = oh.make_node(
+ "StreamingFIFO",
+ [n_output],
+ [fifo_output_tensor.name],
+ domain="finn",
+ backend="fpgadataflow",
+ depth=default_depth,
+ folded_shape=fld_shape,
+ dataType=str(dtype.name),
+ )
+ # insert fifo
+ graph.node.insert(node_ind + 1, fifo_node)
+
+ # set fifo output tensor as new input tensor of second node
+ consumer.input[0] = fifo_output_tensor.name
+
+ if graph_modified is False:
+ # insert FIFO as first node
+ if graph.node[0].op_type != "StreamingFIFO":
+ n = graph.node[0]
+ n_input = n.input[0]
+ n0 = getCustomOp(n)
+ # determine fifo node attributes
+ fld_shape = n0.get_folded_input_shape()
+ dtype = n0.get_input_datatype()
+
+ # create fifo node
+ fifo_output_tensor = oh.make_tensor_value_info(
+ model.make_new_valueinfo_name(),
+ TensorProto.FLOAT,
+ n0.get_normal_input_shape(),
+ )
+ graph.value_info.append(fifo_output_tensor)
+
+ fifo_node = oh.make_node(
+ "StreamingFIFO",
+ [n_input],
+ [fifo_output_tensor.name],
+ domain="finn",
+ backend="fpgadataflow",
+ depth=default_depth,
+ folded_shape=fld_shape,
+ dataType=str(dtype.name),
+ )
+ # insert fifo
+ graph.node.insert(0, fifo_node)
+
+ # set fifo output tensor as new input tensor of second node
+ n.input[0] = fifo_output_tensor.name
+
+ # insert FIFO as first node
+ if graph.node[-1].op_type != "StreamingFIFO":
+ n = graph.node[-1]
+ assert (
+ n.op_type != "TLastMarker"
+ ), """Insert tlast marker should be done
+ after inserting the FIFOs"""
+ graph_out_name = graph.output[0].name
+ n0 = getCustomOp(n)
+ # determine fifo node attributes
+ fld_shape = n0.get_folded_output_shape()
+ dtype = n0.get_output_datatype()
+
+ # create fifo node
+ fifo_input_tensor = oh.make_tensor_value_info(
+ model.make_new_valueinfo_name(),
+ TensorProto.FLOAT,
+ n0.get_normal_output_shape(),
+ )
+ graph.value_info.append(fifo_input_tensor)
+
+ fifo_node = oh.make_node(
+ "StreamingFIFO",
+ [fifo_input_tensor.name],
+ [graph_out_name],
+ domain="finn",
+ backend="fpgadataflow",
+ depth=default_depth,
+ folded_shape=fld_shape,
+ dataType=str(dtype.name),
+ )
+ # insert fifo
+ graph.node.append(fifo_node)
+
+ # set fifo output tensor as new input tensor of second node
+ n.output[0] = fifo_input_tensor.name
+
+ return (model, graph_modified)
--
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