[Test] Modified graph shapes and node attributes

tests/finn-hls-onnx-model.onnx

-finn-hls-onnx-model:
-P
-inpout0"Mem2Stream_Batch*
-	DataWidth@
*
-numBytesh
*
-numReps

- 
-out0	memInStrm"
StreamingNode
-

+finn-hls-onnx-model:
+0
+inp	memInStrm	memInStrm"FIFO*
+depth

+

 	memInStrm
 weights0
-thresh0out1"StreamingFCLayer_Batch*
-L_MH
*
-L_MW
*
-L_PE 
*
-L_SIMD@
*
-numReps
*!
+thresh0out1"StreamingFCLayer_Batch*
+
+MH
*
+
+MW
*	
+PE 
*
+SIMD@
*!
 resDataType"Recast<XnorMul>
*
 resType"ap_resource_lut()

-
-out1inter0"
StreamingNode
-

+*
+out1inter0inter0"FIFO*
+depth

+

 inter0
 weights1
-thresh1out2"StreamingFCLayer_Batch*
-L_MH
*
-L_MW
*
-L_PE@
*
-L_SIMD 
*
-numReps
*!
+thresh1out2"StreamingFCLayer_Batch*
+
+MH
*
+
+MW
*	
+PE@
*
+SIMD 
*!
 resDataType"Recast<XnorMul>
*
 resType"ap_resource_lut()

-
-out2inter1"
StreamingNode
-

+*
+out2inter1inter1"FIFO*
+depth

+

 inter1
 weights2
-thresh2out3"StreamingFCLayer_Batch*
-L_MH
*
-L_MW
*
-L_PE 
*
-L_SIMD@
*
-numReps
*!
+thresh2out3"StreamingFCLayer_Batch*
+
+MH
*
+
+MW
*	
+PE 
*
+SIMD@
*!
 resDataType"Recast<XnorMul>
*
 resType"ap_resource_lut()

-
-out3inter2"
StreamingNode
-

+*
+out3inter2inter2"FIFO*
+depth

+

 inter2
 weights3
-thresh3out4"StreamingFCLayer_Batch*
-L_MH@
*
-L_MW
*
-L_PE
*
-L_SIMD
*
-numReps
*!
+thresh3out4"StreamingFCLayer_Batch*	
+MH@
*
+
+MW
*	
+PE
*
+SIMD
*!
 resDataType"Recast<XnorMul>
*
 resType"ap_resource_lut()

-!
-out4
-memOutStrm"
StreamingNode
-W
-
-memOutStrmoutp"Mem2Stream_Batch*
-	DataWidth@
*
-numBytes
*
-numReps
finn_hls_onnx_graphZ
-inp
-

-

-@b
-outp
-

-

-@j
-out0
+-
+out4outp
+memOutStrm"FIFO*
+depth
finn_hls_onnx_graphZ
+inp
 

 

- 
- j
+
+@b
+outp
+

+

+

+@j
 	memInStrm
 

 

- 
- j
+
+@j
 weights0
 

 @
@@ -98,13 +92,13 @@ memOutStrmoutp"Mem2Stream_Batch*
 out1
 

 

-
-@j
+ 
+ j
 inter0
 

 

-
-@j
+ 
+ j
 weights1
 

  
@@ -120,13 +114,13 @@ memOutStrmoutp"Mem2Stream_Batch*
 out2
 

 

- 
- j
+
+@j
 inter1
 

 

- 
- j
+
+@j
 weights2
 

 @
@@ -142,13 +136,13 @@ memOutStrmoutp"Mem2Stream_Batch*
 out3
 

 

-@
-j
+ 
+ j
 inter2
 

 

-@
-j
+ 
+ j
 weights3
 

 
@@ -160,13 +154,9 @@ memOutStrmoutp"Mem2Stream_Batch*
 
 

 
-
j
-out4
-

+
j
+out4
+

 

-@j
-
-memOutStrm
-

 

 @B
\ No newline at end of file

tests/test_finn_hls_onnx_graph.py

@@ -4,77 +4,65 @@ from onnx import TensorProto, helper
 
 def test_manually_construct_onnx_graph():
 
-    inp = helper.make_tensor_value_info("inp", TensorProto.FLOAT, [1, 64])
-    outp = helper.make_tensor_value_info("outp", TensorProto.FLOAT, [1, 64])
+    inp = helper.make_tensor_value_info("inp", TensorProto.FLOAT, [1, 13, 64])
+    outp = helper.make_tensor_value_info("outp", TensorProto.FLOAT, [1, 1, 64])
 
-    Mem2Stream0_node = helper.make_node(
-        "Mem2Stream_Batch", ["inp"], ["out0"], numReps=4, DataWidth=64, numBytes=104
+    memInStrm_node = helper.make_node(
+        "FIFO", ["inp"], ["memInStrm"], "memInStrm", depth=1024
     )
-    memInStrm_node = helper.make_node("StreamingNode", ["out0"], ["memInStrm"])
     FCLayer0_node = helper.make_node(
         "StreamingFCLayer_Batch",
         ["memInStrm", "weights0", "thresh0"],
         ["out1"],
-        numReps=4,
         resType="ap_resource_lut()",
-        L_MW=832,
-        L_MH=1024,
-        L_SIMD=64,
-        L_PE=32,
+        MW=832,
+        MH=1024,
+        SIMD=64,
+        PE=32,
         resDataType="Recast<XnorMul>",
     )
-    inter0_node = helper.make_node("StreamingNode", ["out1"], ["inter0"])
+    inter0_node = helper.make_node("FIFO", ["out1"], ["inter0"], "inter0", depth=16)
     FCLayer1_node = helper.make_node(
         "StreamingFCLayer_Batch",
         ["inter0", "weights1", "thresh1"],
         ["out2"],
-        numReps=4,
         resType="ap_resource_lut()",
-        L_MW=1024,
-        L_MH=1024,
-        L_SIMD=32,
-        L_PE=64,
+        MW=1024,
+        MH=1024,
+        SIMD=32,
+        PE=64,
         resDataType="Recast<XnorMul>",
     )
-    inter1_node = helper.make_node("StreamingNode", ["out2"], ["inter1"])
+    inter1_node = helper.make_node("FIFO", ["out2"], ["inter1"], "inter1", depth=16)
     FCLayer2_node = helper.make_node(
         "StreamingFCLayer_Batch",
         ["inter1", "weights2", "thresh2"],
         ["out3"],
-        numReps=4,
         resType="ap_resource_lut()",
-        L_MW=1024,
-        L_MH=1024,
-        L_SIMD=64,
-        L_PE=32,
+        MW=1024,
+        MH=1024,
+        SIMD=64,
+        PE=32,
         resDataType="Recast<XnorMul>",
     )
-    inter2_node = helper.make_node("StreamingNode", ["out3"], ["inter2"])
+    inter2_node = helper.make_node("FIFO", ["out3"], ["inter2"], "inter2", depth=8)
     FCLayer3_node = helper.make_node(
         "StreamingFCLayer_Batch",
         ["inter2", "weights3", "thresh3"],
         ["out4"],
-        numReps=4,
         resType="ap_resource_lut()",
-        L_MW=1024,
-        L_MH=64,
-        L_SIMD=8,
-        L_PE=16,
+        MW=1024,
+        MH=64,
+        SIMD=8,
+        PE=16,
         resDataType="Recast<XnorMul>",
     )
-    memOutStrm_node = helper.make_node("StreamingNode", ["out4"], ["memOutStrm"])
-    Mem2Stream1_node = helper.make_node(
-        "Mem2Stream_Batch",
-        ["memOutStrm"],
-        ["outp"],
-        numReps=4,
-        DataWidth=64,
-        numBytes=8,
+    memOutStrm_node = helper.make_node(
+        "FIFO", ["out4"], ["outp"], "memOutStrm", depth=1024
     )
 
     graph = helper.make_graph(
         nodes=[
-            Mem2Stream0_node,
             memInStrm_node,
             FCLayer0_node,
             inter0_node,
@@ -84,38 +72,35 @@ def test_manually_construct_onnx_graph():
             inter2_node,
             FCLayer3_node,
             memOutStrm_node,
-            Mem2Stream1_node,
         ],
         name="finn_hls_onnx_graph",
         inputs=[inp],
         outputs=[outp],
         value_info=[
-            helper.make_tensor_value_info("out0", TensorProto.FLOAT, [1, 32, 32]),
-            helper.make_tensor_value_info("memInStrm", TensorProto.FLOAT, [1, 32, 32]),
+            helper.make_tensor_value_info("memInStrm", TensorProto.FLOAT, [1, 13, 64]),
             helper.make_tensor_value_info("weights0", TensorProto.FLOAT, [64, 32, 416]),
             helper.make_tensor_value_info(
                 "thresh0", TensorProto.FLOAT, [32, 32, 1, 16, 1]
             ),
-            helper.make_tensor_value_info("out1", TensorProto.FLOAT, [1, 16, 64]),
-            helper.make_tensor_value_info("inter0", TensorProto.FLOAT, [1, 16, 64]),
+            helper.make_tensor_value_info("out1", TensorProto.FLOAT, [1, 32, 32]),
+            helper.make_tensor_value_info("inter0", TensorProto.FLOAT, [1, 32, 32]),
             helper.make_tensor_value_info("weights1", TensorProto.FLOAT, [32, 64, 512]),
             helper.make_tensor_value_info(
                 "thresh1", TensorProto.FLOAT, [16, 64, 1, 16, 1]
             ),
-            helper.make_tensor_value_info("out2", TensorProto.FLOAT, [1, 32, 32]),
-            helper.make_tensor_value_info("inter1", TensorProto.FLOAT, [1, 32, 32]),
+            helper.make_tensor_value_info("out2", TensorProto.FLOAT, [1, 16, 64]),
+            helper.make_tensor_value_info("inter1", TensorProto.FLOAT, [1, 16, 64]),
             helper.make_tensor_value_info("weights2", TensorProto.FLOAT, [64, 32, 512]),
             helper.make_tensor_value_info(
                 "thresh2", TensorProto.FLOAT, [32, 32, 1, 16, 1]
             ),
-            helper.make_tensor_value_info("out3", TensorProto.FLOAT, [1, 64, 16]),
-            helper.make_tensor_value_info("inter2", TensorProto.FLOAT, [1, 64, 16]),
+            helper.make_tensor_value_info("out3", TensorProto.FLOAT, [1, 32, 32]),
+            helper.make_tensor_value_info("inter2", TensorProto.FLOAT, [1, 32, 32]),
             helper.make_tensor_value_info("weights3", TensorProto.FLOAT, [8, 16, 512]),
             helper.make_tensor_value_info(
                 "thresh3", TensorProto.FLOAT, [4, 16, 1, 16, 1]
             ),
-            helper.make_tensor_value_info("out4", TensorProto.FLOAT, [1, 64]),
-            helper.make_tensor_value_info("memOutStrm", TensorProto.FLOAT, [1, 64]),
+            helper.make_tensor_value_info("out4", TensorProto.FLOAT, [1, 1, 64]),
         ],
     )
     model = helper.make_model(graph, producer_name="finn-hls-onnx-model")