From 49055cf229f1b959ba38916d5c25cd3a7036d35e Mon Sep 17 00:00:00 2001
From: icolbert <Ian.Colbert@amd.com>
Date: Tue, 21 Feb 2023 11:13:36 -0800
Subject: [PATCH] Remove MinimizeAccumulatorWidth from convert_to_hls layers
---
.../fpgadataflow/convert_to_hls_layers.py | 10 +---------
1 file changed, 1 insertion(+), 9 deletions(-)
diff --git a/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py b/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py
index 7b8a1bf6b..3029e09d4 100644
--- a/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py
+++ b/src/finn/transformation/fpgadataflow/convert_to_hls_layers.py
@@ -40,10 +40,6 @@ from qonnx.transformation.infer_shapes import InferShapes
from qonnx.util.basic import get_by_name
from qonnx.util.onnx import nchw_to_nhwc
-from finn.transformation.fpgadataflow.minimize_accumulator_width import (
- MinimizeAccumulatorWidth,
-)
-
class InferConvInpGen(Transformation):
"""Convert Im2Col layers to ConvolutionInputGenerator layers."""
@@ -761,7 +757,6 @@ class InferBinaryMatrixVectorActivation(Transformation):
graph.node.remove(n)
graph_modified = True
if graph_modified:
- model = model.transform(MinimizeAccumulatorWidth())
model = model.transform(InferShapes())
model = model.transform(InferDataTypes())
return (model, graph_modified)
@@ -904,7 +899,6 @@ class InferQuantizedMatrixVectorActivation(Transformation):
graph.node.remove(n)
graph_modified = True
if graph_modified:
- model = model.transform(MinimizeAccumulatorWidth())
model = model.transform(InferShapes())
model = model.transform(InferDataTypes())
return (model, graph_modified)
@@ -1057,7 +1051,6 @@ class InferVectorVectorActivation(Transformation):
graph.node.remove(n)
graph_modified = True
if graph_modified:
- model = model.transform(MinimizeAccumulatorWidth())
model = model.transform(InferShapes())
model = model.transform(InferDataTypes())
return (model, graph_modified)
@@ -1135,7 +1128,7 @@ class InferThresholdingLayer(Transformation):
PE=pe,
numSteps=thl_thres_shape[1],
inputDataType=idt.name,
- weightDataType=idt.name, # will be set by MinimizeAccumulatorWidth
+ weightDataType=idt.name, # can be tightened by MinimizeAccumulatorWidth
outputDataType=odt.name,
numInputVectors=list(thl_in_shape[:-1]),
ActVal=actval,
@@ -1148,7 +1141,6 @@ class InferThresholdingLayer(Transformation):
graph_modified = True
if graph_modified:
- model = model.transform(MinimizeAccumulatorWidth())
model = model.transform(InferShapes())
model = model.transform(InferDataTypes())
return (model, graph_modified)
--
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