From fe8f8768cc9211bb0709b024ec517566b487ba45 Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <yamanu@xilinx.com>
Date: Wed, 13 Oct 2021 10:37:31 +0200
Subject: [PATCH] [Refactor] switch to CustomOp base-class impl for shape inf
---
src/finn/custom_op/fpgadataflow/addstreams_batch.py | 8 +-------
src/finn/custom_op/fpgadataflow/channelwise_op_batch.py | 8 +-------
.../custom_op/fpgadataflow/convolutioninputgenerator.py | 8 +-------
.../custom_op/fpgadataflow/convolutioninputgenerator1d.py | 8 +-------
src/finn/custom_op/fpgadataflow/downsampler.py | 8 +-------
src/finn/custom_op/fpgadataflow/fmpadding_batch.py | 8 +-------
src/finn/custom_op/fpgadataflow/globalaccpool_batch.py | 8 +-------
src/finn/custom_op/fpgadataflow/iodma.py | 8 +-------
src/finn/custom_op/fpgadataflow/labelselect_batch.py | 4 +++-
src/finn/custom_op/fpgadataflow/pool_batch.py | 8 +-------
.../fpgadataflow/streamingdatawidthconverter_batch.py | 8 +-------
src/finn/custom_op/fpgadataflow/streamingfclayer_batch.py | 8 +-------
src/finn/custom_op/fpgadataflow/streamingfifo.py | 8 +-------
src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py | 8 +-------
src/finn/custom_op/fpgadataflow/thresholding_batch.py | 8 +-------
src/finn/custom_op/fpgadataflow/upsampler.py | 8 +-------
.../fpgadataflow/vector_vector_activate_batch.py | 8 +-------
17 files changed, 19 insertions(+), 113 deletions(-)
diff --git a/src/finn/custom_op/fpgadataflow/addstreams_batch.py b/src/finn/custom_op/fpgadataflow/addstreams_batch.py
index aaf8687de..fa80e4748 100644
--- a/src/finn/custom_op/fpgadataflow/addstreams_batch.py
+++ b/src/finn/custom_op/fpgadataflow/addstreams_batch.py
@@ -29,7 +29,6 @@
import numpy as np
import os
import warnings
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -84,12 +83,7 @@ class AddStreams_Batch(HLSCustomOp):
assert ishape == exp_ishape, "Unexpected input1 shape."
ishape = tuple(model.get_tensor_shape(self.onnx_node.input[1]))
assert ishape == exp_ishape, "Unexpected input2 shape."
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/channelwise_op_batch.py b/src/finn/custom_op/fpgadataflow/channelwise_op_batch.py
index 083ee894f..4961f6148 100644
--- a/src/finn/custom_op/fpgadataflow/channelwise_op_batch.py
+++ b/src/finn/custom_op/fpgadataflow/channelwise_op_batch.py
@@ -30,7 +30,6 @@ import numpy as np
import os
import warnings
from math import ceil
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -125,12 +124,7 @@ class ChannelwiseOp_Batch(HLSCustomOp):
def make_shape_compatible_op(self, model):
oshape = self.get_normal_output_shape()
# implement tensor with correct shape
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/convolutioninputgenerator.py b/src/finn/custom_op/fpgadataflow/convolutioninputgenerator.py
index def0b20b0..a40188368 100644
--- a/src/finn/custom_op/fpgadataflow/convolutioninputgenerator.py
+++ b/src/finn/custom_op/fpgadataflow/convolutioninputgenerator.py
@@ -29,7 +29,6 @@
import math
import numpy as np
import os
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -148,12 +147,7 @@ class ConvolutionInputGenerator(HLSCustomOp):
ishape = tuple(model.get_tensor_shape(self.onnx_node.input[0]))
assert ishape == exp_ishape, "Unexpect input shape for ConvInpGen."
# implement tensor with correct shape
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/convolutioninputgenerator1d.py b/src/finn/custom_op/fpgadataflow/convolutioninputgenerator1d.py
index 6a81b9177..c4cf80412 100644
--- a/src/finn/custom_op/fpgadataflow/convolutioninputgenerator1d.py
+++ b/src/finn/custom_op/fpgadataflow/convolutioninputgenerator1d.py
@@ -29,7 +29,6 @@
import math
import numpy as np
import os
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -137,12 +136,7 @@ class ConvolutionInputGenerator1D(HLSCustomOp):
oshape = self.get_normal_output_shape()
ishape = tuple(model.get_tensor_shape(self.onnx_node.input[0]))
assert ishape == exp_ishape, "Unexpect input shape for ConvInpGen."
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/downsampler.py b/src/finn/custom_op/fpgadataflow/downsampler.py
index 9dcbb5e14..6a0667f67 100644
--- a/src/finn/custom_op/fpgadataflow/downsampler.py
+++ b/src/finn/custom_op/fpgadataflow/downsampler.py
@@ -1,7 +1,6 @@
import numpy as np
import os
import warnings
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -83,12 +82,7 @@ class DownSampler(HLSCustomOp):
oshape = self.get_normal_output_shape()
ishape = tuple(model.get_tensor_shape(self.onnx_node.input[0]))
assert ishape == exp_ishape, "Unexpect input shape for DownSampler."
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/fmpadding_batch.py b/src/finn/custom_op/fpgadataflow/fmpadding_batch.py
index dd7619566..f29ea431f 100644
--- a/src/finn/custom_op/fpgadataflow/fmpadding_batch.py
+++ b/src/finn/custom_op/fpgadataflow/fmpadding_batch.py
@@ -1,7 +1,6 @@
import numpy as np
import os
import warnings
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -99,12 +98,7 @@ class FMPadding_Batch(HLSCustomOp):
oshape = self.get_normal_output_shape()
ishape = tuple(model.get_tensor_shape(self.onnx_node.input[0]))
assert ishape == exp_ishape, "Unexpect input shape for SameResize."
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/globalaccpool_batch.py b/src/finn/custom_op/fpgadataflow/globalaccpool_batch.py
index d6f860db1..6d4a55ee5 100644
--- a/src/finn/custom_op/fpgadataflow/globalaccpool_batch.py
+++ b/src/finn/custom_op/fpgadataflow/globalaccpool_batch.py
@@ -29,7 +29,6 @@
import numpy as np
import os
import warnings
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -95,12 +94,7 @@ class GlobalAccPool_Batch(HLSCustomOp):
oshape = self.get_normal_output_shape()
ishape = tuple(model.get_tensor_shape(self.onnx_node.input[0]))
assert ishape == exp_ishape, "Unexpected input shape."
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/iodma.py b/src/finn/custom_op/fpgadataflow/iodma.py
index 34842181c..802c7e785 100644
--- a/src/finn/custom_op/fpgadataflow/iodma.py
+++ b/src/finn/custom_op/fpgadataflow/iodma.py
@@ -29,7 +29,6 @@
import math
import numpy as np
import warnings
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -146,12 +145,7 @@ class IODMA(HLSCustomOp):
oshape = self.get_normal_output_shape()
ishape = tuple(model.get_tensor_shape(self.onnx_node.input[0]))
assert ishape == exp_ishape, "Unexpected input shape."
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/labelselect_batch.py b/src/finn/custom_op/fpgadataflow/labelselect_batch.py
index 4d34de8fc..1eb5962fd 100644
--- a/src/finn/custom_op/fpgadataflow/labelselect_batch.py
+++ b/src/finn/custom_op/fpgadataflow/labelselect_batch.py
@@ -106,8 +106,10 @@ class LabelSelect_Batch(HLSCustomOp):
"RandomNormal",
inputs=[],
outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
+ mean=0.0,
+ scale=1.0,
dtype=TensorProto.INT64,
+ shape=list(oshape),
)
def infer_node_datatype(self, model):
diff --git a/src/finn/custom_op/fpgadataflow/pool_batch.py b/src/finn/custom_op/fpgadataflow/pool_batch.py
index 332b400c0..ba8a446f2 100644
--- a/src/finn/custom_op/fpgadataflow/pool_batch.py
+++ b/src/finn/custom_op/fpgadataflow/pool_batch.py
@@ -28,7 +28,6 @@
import numpy as np
import os
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -163,12 +162,7 @@ class Pool_Batch(HLSCustomOp):
oshape = self.get_normal_output_shape()
ishape = tuple(model.get_tensor_shape(self.onnx_node.input[0]))
assert ishape == exp_ishape, "Unexpected input shape for Pool_Batch."
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/streamingdatawidthconverter_batch.py b/src/finn/custom_op/fpgadataflow/streamingdatawidthconverter_batch.py
index aaf796b15..1791706af 100644
--- a/src/finn/custom_op/fpgadataflow/streamingdatawidthconverter_batch.py
+++ b/src/finn/custom_op/fpgadataflow/streamingdatawidthconverter_batch.py
@@ -30,7 +30,6 @@ import math
import numpy as np
import os
import warnings
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -165,12 +164,7 @@ class StreamingDataWidthConverter_Batch(HLSCustomOp):
oshape = self.get_normal_output_shape()
ishape = tuple(model.get_tensor_shape(self.onnx_node.input[0]))
assert ishape == tuple(exp_ishape), "Unexpect input shape for StreamingDWC."
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/streamingfclayer_batch.py b/src/finn/custom_op/fpgadataflow/streamingfclayer_batch.py
index ccc9780ff..90abb66e6 100644
--- a/src/finn/custom_op/fpgadataflow/streamingfclayer_batch.py
+++ b/src/finn/custom_op/fpgadataflow/streamingfclayer_batch.py
@@ -31,7 +31,6 @@ import numpy as np
import os
import textwrap
import warnings
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -151,12 +150,7 @@ class StreamingFCLayer_Batch(HLSCustomOp):
def make_shape_compatible_op(self, model):
oshape = self.get_normal_output_shape()
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/streamingfifo.py b/src/finn/custom_op/fpgadataflow/streamingfifo.py
index 02d9a1915..91f6ed5b8 100644
--- a/src/finn/custom_op/fpgadataflow/streamingfifo.py
+++ b/src/finn/custom_op/fpgadataflow/streamingfifo.py
@@ -30,7 +30,6 @@ import numpy as np
import os
import subprocess
import warnings
-from onnx import helper
from shutil import copy
from finn.core.datatype import DataType
@@ -78,12 +77,7 @@ class StreamingFIFO(HLSCustomOp):
oshape = self.get_normal_output_shape()
ishape = tuple(model.get_tensor_shape(self.onnx_node.input[0]))
assert ishape == tuple(exp_ishape), "Unexpect input shape for StreamingFIFO."
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py b/src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py
index 5574d6706..1e66a5c20 100644
--- a/src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py
+++ b/src/finn/custom_op/fpgadataflow/streamingmaxpool_batch.py
@@ -29,7 +29,6 @@
import numpy as np
import os
import warnings
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -140,12 +139,7 @@ class StreamingMaxPool_Batch(HLSCustomOp):
oshape = self.get_normal_output_shape()
ishape = tuple(model.get_tensor_shape(self.onnx_node.input[0]))
assert ishape == exp_ishape, "Unexpect input shape for StreamingMaxPool."
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/thresholding_batch.py b/src/finn/custom_op/fpgadataflow/thresholding_batch.py
index d5fa86abd..610139f44 100644
--- a/src/finn/custom_op/fpgadataflow/thresholding_batch.py
+++ b/src/finn/custom_op/fpgadataflow/thresholding_batch.py
@@ -31,7 +31,6 @@ import os
import textwrap
import warnings
from math import ceil, log2
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -112,12 +111,7 @@ class Thresholding_Batch(HLSCustomOp):
def make_shape_compatible_op(self, model):
oshape = self.get_normal_output_shape()
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/upsampler.py b/src/finn/custom_op/fpgadataflow/upsampler.py
index 60052b46a..d5f809305 100644
--- a/src/finn/custom_op/fpgadataflow/upsampler.py
+++ b/src/finn/custom_op/fpgadataflow/upsampler.py
@@ -1,7 +1,6 @@
import numpy as np
import os
import warnings
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -69,12 +68,7 @@ class UpsampleNearestNeighbour_Batch(HLSCustomOp):
assert (
ishape == exp_ishape
), "Unexpect input shape for UpsampleNearestNeighbour_Batch."
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
diff --git a/src/finn/custom_op/fpgadataflow/vector_vector_activate_batch.py b/src/finn/custom_op/fpgadataflow/vector_vector_activate_batch.py
index 0ad03f37c..c67eb0f21 100644
--- a/src/finn/custom_op/fpgadataflow/vector_vector_activate_batch.py
+++ b/src/finn/custom_op/fpgadataflow/vector_vector_activate_batch.py
@@ -2,7 +2,6 @@ import math
import numpy as np
import os
import warnings
-from onnx import helper
from finn.core.datatype import DataType
from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
@@ -129,12 +128,7 @@ class Vector_Vector_Activate_Batch(HLSCustomOp):
def make_shape_compatible_op(self, model):
oshape = self.get_normal_output_shape()
- return helper.make_node(
- "RandomNormal",
- inputs=[],
- outputs=[self.onnx_node.output[0]],
- shape=list(oshape),
- )
+ return super().make_const_shape_op(oshape)
def infer_node_datatype(self, model):
node = self.onnx_node
--
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