Applied new pre-commit-config to all files, non-critical changes only

docs/finn/conf.py

@@ -12,14 +12,15 @@
 #
 import os
 import sys
-sys.path.insert(0, os.path.abspath('../../src/'))
+
+sys.path.insert(0, os.path.abspath("../../src/"))
 
 
 # -- Project information -----------------------------------------------------
 
-project = 'FINN'
-copyright = '2020, Xilinx'
-author = 'Y. Umuroglu and J. Petri-Koenig'
+project = "FINN"
+copyright = "2020, Xilinx"
+author = "Y. Umuroglu and J. Petri-Koenig"
 
 
 # -- General configuration ---------------------------------------------------
@@ -27,17 +28,16 @@ author = 'Y. Umuroglu and J. Petri-Koenig'
 # Add any Sphinx extension module names here, as strings. They can be
 # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
 # ones.
-extensions = [
-]
-extensions.append('sphinx.ext.autodoc')
+extensions = []
+extensions.append("sphinx.ext.autodoc")
 
 # Add any paths that contain templates here, relative to this directory.
-templates_path = ['_templates']
+templates_path = ["_templates"]
 
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.
 # This pattern also affects html_static_path and html_extra_path.
-exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
+exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"]
 
 
 # -- Options for HTML output -------------------------------------------------
@@ -45,11 +45,11 @@ exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
 # The theme to use for HTML and HTML Help pages.  See the documentation for
 # a list of builtin themes.
 #
-html_theme = 'sphinx_rtd_theme'
+html_theme = "sphinx_rtd_theme"
 
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
-html_static_path = ['_static']
+html_static_path = ["_static"]
 
-master_doc = 'index'
+master_doc = "index"

docs/finn/faq.rst

@@ -9,25 +9,25 @@ Frequently Asked Questions
 Can I install FINN out of the Docker container?
 ===============================================
 
-We do not support out of the Docker implementations at the moment. This is due 
+We do not support out of the Docker implementations at the moment. This is due
 to the high complexity of the FINN project dependencies.
 
 Since FINN uses ONNX, can I compile any model from the ONNX Model Zoo to an FPGA accelerator?
 =============================================================================================
 
-The short answer is no. FINN uses ONNX in a specific (non-standard) way, including custom layer 
+The short answer is no. FINN uses ONNX in a specific (non-standard) way, including custom layer
 types and quantization annotations. Networks must be first quantized using Brevitas and exported
 to FINN-ONNX to be converted to FPGA accelerators.
 
 
-Can I deploy custom NNs with arbitrary precisions and layers using FINN? 
+Can I deploy custom NNs with arbitrary precisions and layers using FINN?
 =========================================================================
 
 Yes, though the effort required and quality of results will vary.
-Although we do support arbitrary 
-precision, the way we create the hardware isn't typically practical for more than 
-4 bits, or very large networks for a single FPGA. 
-In terms of layers, only a subset of quantized layers covered by the various FINN examples 
+Although we do support arbitrary
+precision, the way we create the hardware isn't typically practical for more than
+4 bits, or very large networks for a single FPGA.
+In terms of layers, only a subset of quantized layers covered by the various FINN examples
 are currently supported.
 It is possible to add support for new layers, though we don't have tutorials for this in place
 just yet.
@@ -35,16 +35,16 @@ just yet.
 Does FINN only work with the example networks?
 ==============================================
 
-FINN isn't restricted to the example networks; 
-rather, it's restricted to certain patterns (e.g. certain layer types and their combinations). 
-The current best practice for custom networks is to take a working network and gradually modify it. 
+FINN isn't restricted to the example networks;
+rather, it's restricted to certain patterns (e.g. certain layer types and their combinations).
+The current best practice for custom networks is to take a working network and gradually modify it.
 
 What is the expected background for using FINN?
 ===============================================
 
 Some general knowledge of Python, Docker, machine learning with neural networks and Jupyter notebooks
 is expected.
-Our goal is to make the tool in a shape and form so that no hardware/FPGA background 
+Our goal is to make the tool in a shape and form so that no hardware/FPGA background
 should be necessary, although having some knowledge would give better results.
 
 What operating systems are supported by FINN?
@@ -66,6 +66,6 @@ What board do you recommend to start working with FINN?
 Our preferred target platforms are those supported by  `PYNQ <http://www.pynq.io/board.html>`_.
 For those boards we can offer end-to-end (DNN-to-bitstream) deployment,
 see the `finn-examples <https://github.com/Xilinx/finn-examples>`_ repository for some examples.
-However, FINN also supports Vivado IP Integrator designs. The IPs connect using AXI stream (FIFO) 
+However, FINN also supports Vivado IP Integrator designs. The IPs connect using AXI stream (FIFO)
 in-and-out interfaces. This means that it can be integrated onto any Xilinx FPGA board,
 though you will have to do the system integration manually.

finn-rtllib/memstream/sim/gen_memblocks.sh

@@ -36,4 +36,4 @@ for (( i=0; i<$NBLOCKS; i++ ))
 do
     START=$(( 1 + $i * 1024 ))
     tail -n +$START $1 | head -n 1024 >> memblock_$i.dat
-done
\ No newline at end of file
+done

notebooks/end2end_example/cybersecurity/dataloader_quantized.py

@@ -26,12 +26,12 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-import torch
-import pandas as pd
+import math
 import numpy as np
+import pandas as pd
+import torch
 from sklearn import preprocessing
 from sklearn.preprocessing import OneHotEncoder
-import math
 
 # quantize the UNSW_NB15 dataset and convert it to binary vectors
 # reimplementation
@@ -112,7 +112,7 @@ class UNSW_NB15_quantized(torch.utils.data.Dataset):
 
     def round_like_matlab_number(self, n: np.float64) -> int:
         """Round the input "n" like matlab uint32(n) cast (which also rounds) e.g.
-        0.5->1;  1.5->2; 2.3->2;   2.45->2 """
+        0.5->1;  1.5->2; 2.3->2;   2.45->2"""
         if n - math.floor(n) < 0.5:
             return math.floor(n)
         return math.ceil(n)

notebooks/end2end_example/cybersecurity/validate-unsw-nb15.py

@@ -27,9 +27,9 @@
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
 import argparse
+import numpy as np
 from driver import io_shape_dict
 from driver_base import FINNExampleOverlay
-import numpy as np
 
 
 def make_unsw_nb15_test_batches(bsize, dataset_root):

setup.py

@@ -35,10 +35,11 @@
     PyScaffold helps you to put up the scaffold of your new Python project.
     Learn more under: https://pyscaffold.org/
 """
-import sys
 from pkg_resources import VersionConflict, require
 from setuptools import setup
 
+import sys
+
 try:
     require("setuptools>=38.3")
 except VersionConflict:

src/finn/analysis/fpgadataflow/floorplan_params.py

@@ -26,8 +26,8 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-from finn.util.fpgadataflow import is_fpgadataflow_node
 from finn.custom_op.registry import getCustomOp
+from finn.util.fpgadataflow import is_fpgadataflow_node
 
 
 def floorplan_params(model):

src/finn/analysis/fpgadataflow/hls_synth_res_estimation.py

@@ -25,8 +25,8 @@
 # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-import warnings
 import os
+import warnings
 import xml.etree.ElementTree as ET
 
 import finn.custom_op.registry as registry

src/finn/analysis/fpgadataflow/post_synth_res.py

@@ -29,9 +29,9 @@
 import os
 import xml.etree.ElementTree as ET
 
-from finn.transformation.move_reshape import _is_fpgadataflow_node
 from finn.core.modelwrapper import ModelWrapper
 from finn.custom_op.registry import getCustomOp
+from finn.transformation.move_reshape import _is_fpgadataflow_node
 
 
 def post_synth_res(model, override_synth_report_filename=None):

src/finn/builder/build_dataflow_config.py

@@ -26,14 +26,15 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-from typing import List, Optional, Any
-from finn.util.basic import pynq_part_map, alveo_part_map
-from finn.transformation.fpgadataflow.vitis_build import VitisOptStrategy
-from enum import Enum
+import numpy as np
+import os
 from dataclasses import dataclass
 from dataclasses_json import dataclass_json
-import os
-import numpy as np
+from enum import Enum
+from typing import Any, List, Optional
+
+from finn.transformation.fpgadataflow.vitis_build import VitisOptStrategy
+from finn.util.basic import alveo_part_map, pynq_part_map
 
 
 class ShellFlowType(str, Enum):

src/finn/builder/build_dataflow_steps.py

@@ -26,78 +26,78 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-from finn.core.modelwrapper import ModelWrapper
-import os
 import json
+import numpy as np
+import os
+from copy import deepcopy
+from shutil import copy, copytree
+
 import finn.transformation.fpgadataflow.convert_to_hls_layers as to_hls
 import finn.transformation.streamline.absorb as absorb
-from finn.transformation.bipolar_to_xnor import ConvertBipolarMatMulToXnorPopcount
-from finn.transformation.fold_constants import FoldConstants
-from finn.transformation.general import (
-    ApplyConfig,
-    GiveReadableTensorNames,
-    GiveUniqueNodeNames,
-    RemoveUnusedTensors,
-    RemoveStaticGraphInputs,
-)
-from finn.transformation.infer_datatypes import InferDataTypes
-from finn.transformation.infer_shapes import InferShapes
-from finn.transformation.streamline import Streamline
-from finn.transformation.infer_data_layouts import InferDataLayouts
-from finn.transformation.move_reshape import RemoveCNVtoFCFlatten
-from finn.transformation.lower_convs_to_matmul import LowerConvsToMatMul
-from finn.transformation.streamline.reorder import MakeMaxPoolNHWC
-
-from shutil import copy, copytree
-from finn.transformation.fpgadataflow.insert_dwc import InsertDWC
-from finn.transformation.fpgadataflow.insert_fifo import InsertFIFO
-from finn.transformation.fpgadataflow.prepare_ip import PrepareIP
-from finn.transformation.fpgadataflow.hlssynth_ip import HLSSynthIP
-from finn.transformation.fpgadataflow.create_stitched_ip import CreateStitchedIP
-from finn.transformation.fpgadataflow.set_fifo_depths import (
-    InsertAndSetFIFODepths,
-    RemoveShallowFIFOs,
-)
-from finn.transformation.fpgadataflow.make_zynq_proj import ZynqBuild
-from finn.transformation.fpgadataflow.vitis_build import VitisBuild
-from finn.transformation.fpgadataflow.make_pynq_driver import MakePYNQDriver
-from finn.transformation.fpgadataflow.set_folding import SetFolding
-from finn.transformation.fpgadataflow.create_dataflow_partition import (
-    CreateDataflowPartition,
-)
-from finn.transformation.fpgadataflow.replace_verilog_relpaths import (
-    ReplaceVerilogRelPaths,
-)
-from finn.custom_op.registry import getCustomOp
+from finn.analysis.fpgadataflow.dataflow_performance import dataflow_performance
 from finn.analysis.fpgadataflow.exp_cycles_per_layer import exp_cycles_per_layer
-from finn.analysis.fpgadataflow.res_estimation import (
-    res_estimation,
-    res_estimation_complete,
-)
+from finn.analysis.fpgadataflow.hls_synth_res_estimation import hls_synth_res_estimation
 from finn.analysis.fpgadataflow.op_and_param_counts import (
     aggregate_dict_keys,
     op_and_param_counts,
 )
-from finn.analysis.fpgadataflow.dataflow_performance import dataflow_performance
-from finn.analysis.fpgadataflow.hls_synth_res_estimation import hls_synth_res_estimation
-from finn.util.config import extract_model_config_to_json
-from finn.transformation.fpgadataflow.synth_ooc import SynthOutOfContext
+from finn.analysis.fpgadataflow.res_estimation import (
+    res_estimation,
+    res_estimation_complete,
+)
 from finn.builder.build_dataflow_config import (
     DataflowBuildConfig,
     DataflowOutputType,
     ShellFlowType,
     VerificationStepType,
 )
-from finn.transformation.fpgadataflow.annotate_cycles import AnnotateCycles
+from finn.core.modelwrapper import ModelWrapper
 from finn.core.onnx_exec import execute_onnx
-import numpy as np
-from finn.util.test import execute_parent
-from finn.transformation.fpgadataflow.prepare_cppsim import PrepareCppSim
+from finn.core.throughput_test import throughput_test_rtlsim
+from finn.custom_op.registry import getCustomOp
+from finn.transformation.bipolar_to_xnor import ConvertBipolarMatMulToXnorPopcount
+from finn.transformation.fold_constants import FoldConstants
+from finn.transformation.fpgadataflow.annotate_cycles import AnnotateCycles
 from finn.transformation.fpgadataflow.compile_cppsim import CompileCppSim
-from finn.transformation.fpgadataflow.set_exec_mode import SetExecMode
+from finn.transformation.fpgadataflow.create_dataflow_partition import (
+    CreateDataflowPartition,
+)
+from finn.transformation.fpgadataflow.create_stitched_ip import CreateStitchedIP
+from finn.transformation.fpgadataflow.hlssynth_ip import HLSSynthIP
+from finn.transformation.fpgadataflow.insert_dwc import InsertDWC
+from finn.transformation.fpgadataflow.insert_fifo import InsertFIFO
+from finn.transformation.fpgadataflow.make_pynq_driver import MakePYNQDriver
+from finn.transformation.fpgadataflow.make_zynq_proj import ZynqBuild
+from finn.transformation.fpgadataflow.prepare_cppsim import PrepareCppSim
+from finn.transformation.fpgadataflow.prepare_ip import PrepareIP
 from finn.transformation.fpgadataflow.prepare_rtlsim import PrepareRTLSim
-from finn.core.throughput_test import throughput_test_rtlsim
-from copy import deepcopy
+from finn.transformation.fpgadataflow.replace_verilog_relpaths import (
+    ReplaceVerilogRelPaths,
+)
+from finn.transformation.fpgadataflow.set_exec_mode import SetExecMode
+from finn.transformation.fpgadataflow.set_fifo_depths import (
+    InsertAndSetFIFODepths,
+    RemoveShallowFIFOs,
+)
+from finn.transformation.fpgadataflow.set_folding import SetFolding
+from finn.transformation.fpgadataflow.synth_ooc import SynthOutOfContext
+from finn.transformation.fpgadataflow.vitis_build import VitisBuild
+from finn.transformation.general import (
+    ApplyConfig,
+    GiveReadableTensorNames,
+    GiveUniqueNodeNames,
+    RemoveStaticGraphInputs,
+    RemoveUnusedTensors,
+)
+from finn.transformation.infer_data_layouts import InferDataLayouts
+from finn.transformation.infer_datatypes import InferDataTypes
+from finn.transformation.infer_shapes import InferShapes
+from finn.transformation.lower_convs_to_matmul import LowerConvsToMatMul
+from finn.transformation.move_reshape import RemoveCNVtoFCFlatten
+from finn.transformation.streamline import Streamline
+from finn.transformation.streamline.reorder import MakeMaxPoolNHWC
+from finn.util.config import extract_model_config_to_json
+from finn.util.test import execute_parent
 
 
 def verify_step(

src/finn/custom_op/fpgadataflow/__init__.py

@@ -26,6 +26,8 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
+from finn.custom_op.fpgadataflow.addstreams_batch import AddStreams_Batch
+from finn.custom_op.fpgadataflow.channelwise_op_batch import ChannelwiseOp_Batch
 from finn.custom_op.fpgadataflow.convolutioninputgenerator import (
     ConvolutionInputGenerator,
 )
@@ -33,28 +35,26 @@ from finn.custom_op.fpgadataflow.convolutioninputgenerator1d import (
     ConvolutionInputGenerator1D,
 )
 from finn.custom_op.fpgadataflow.downsampler import DownSampler
-from finn.custom_op.fpgadataflow.streamingfclayer_batch import StreamingFCLayer_Batch
-from finn.custom_op.fpgadataflow.streamingmaxpool_batch import StreamingMaxPool_Batch
-from finn.custom_op.fpgadataflow.streamingfifo import StreamingFIFO
-from finn.custom_op.fpgadataflow.tlastmarker import TLastMarker
+from finn.custom_op.fpgadataflow.duplicatestreams_batch import DuplicateStreams_Batch
+from finn.custom_op.fpgadataflow.fmpadding_batch import FMPadding_Batch
+from finn.custom_op.fpgadataflow.globalaccpool_batch import GlobalAccPool_Batch
+from finn.custom_op.fpgadataflow.iodma import IODMA
+from finn.custom_op.fpgadataflow.labelselect_batch import LabelSelect_Batch
+from finn.custom_op.fpgadataflow.pool_batch import Pool_Batch
+from finn.custom_op.fpgadataflow.streamingdataflowpartition import (
+    StreamingDataflowPartition,
+)
 from finn.custom_op.fpgadataflow.streamingdatawidthconverter_batch import (
     StreamingDataWidthConverter_Batch,
 )
-from finn.custom_op.fpgadataflow.globalaccpool_batch import GlobalAccPool_Batch
-from finn.custom_op.fpgadataflow.pool_batch import Pool_Batch
-from finn.custom_op.fpgadataflow.fmpadding_batch import FMPadding_Batch
+from finn.custom_op.fpgadataflow.streamingfclayer_batch import StreamingFCLayer_Batch
+from finn.custom_op.fpgadataflow.streamingfifo import StreamingFIFO
+from finn.custom_op.fpgadataflow.streamingmaxpool_batch import StreamingMaxPool_Batch
 from finn.custom_op.fpgadataflow.thresholding_batch import Thresholding_Batch
-from finn.custom_op.fpgadataflow.addstreams_batch import AddStreams_Batch
-from finn.custom_op.fpgadataflow.labelselect_batch import LabelSelect_Batch
-from finn.custom_op.fpgadataflow.duplicatestreams_batch import DuplicateStreams_Batch
+from finn.custom_op.fpgadataflow.tlastmarker import TLastMarker
 from finn.custom_op.fpgadataflow.vector_vector_activate_batch import (
     Vector_Vector_Activate_Batch,
 )
-from finn.custom_op.fpgadataflow.channelwise_op_batch import ChannelwiseOp_Batch
-from finn.custom_op.fpgadataflow.iodma import IODMA
-from finn.custom_op.fpgadataflow.streamingdataflowpartition import (
-    StreamingDataflowPartition,
-)
 
 custom_op = dict()
 

src/finn/custom_op/fpgadataflow/addstreams_batch.py

@@ -26,13 +26,13 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-import os
-
 import numpy as np
+import os
 import warnings
+from onnx import TensorProto, helper
+
 from finn.core.datatype import DataType
 from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
-from onnx import TensorProto, helper
 from finn.util.data_packing import npy_to_rtlsim_input, rtlsim_output_to_npy
 
 

src/finn/custom_op/fpgadataflow/channelwise_op_batch.py

@@ -26,12 +26,12 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-from math import ceil
-import os
-
 import numpy as np
-
+import os
+import warnings
+from math import ceil
 from onnx import TensorProto, helper
+
 from finn.core.datatype import DataType
 from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
 from finn.util.data_packing import (
@@ -39,9 +39,8 @@ from finn.util.data_packing import (
     numpy_to_hls_code,
     rtlsim_output_to_npy,
 )
-from . import templates
 
-import warnings
+from . import templates
 
 # ONNX i/o tensor shape assumptions for channelwise ops:
 # input 0 is the input tensor, shape (..., NumChannels)
@@ -217,7 +216,7 @@ class ChannelwiseOp_Batch(HLSCustomOp):
             return 0
 
     def lut_estimation(self):
-        """Calculates LUT cost, taking memory resource type into account """
+        """Calculates LUT cost, taking memory resource type into account"""
         # TODO add in/out FIFO contributions
         style = self.get_nodeattr("ram_style")
         P = self.get_nodeattr("PE")
@@ -490,7 +489,9 @@ class ChannelwiseOp_Batch(HLSCustomOp):
         numReps = numInputVectors[0]
         self.code_gen_dict["$DEFINES$"] = [
             """#define NumChannels1 {}\n#define PE1 {}\n#define numReps {}""".format(
-                self.get_nodeattr("NumChannels"), self.get_nodeattr("PE"), numReps,
+                self.get_nodeattr("NumChannels"),
+                self.get_nodeattr("PE"),
+                numReps,
             )
         ]
 
@@ -533,7 +534,9 @@ class ChannelwiseOp_Batch(HLSCustomOp):
         self.code_gen_dict["$DOCOMPUTE$"] = [
             """Thresholding_Batch<{}, NumChannels1, PE1, {}, {}>
             (in0, out, threshs, numReps);""".format(
-                imgdim, tmpl_args["TSrcI"], tmpl_args["TDstI"],
+                imgdim,
+                tmpl_args["TSrcI"],
+                tmpl_args["TDstI"],
             )
         ]
 

src/finn/custom_op/fpgadataflow/convolutioninputgenerator.py

@@ -26,15 +26,14 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-import os
-
 import math
 import numpy as np
+import os
+from onnx import TensorProto, helper
 
 from finn.core.datatype import DataType
 from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
 from finn.custom_op.general.im2col import compute_conv_output_dim
-from onnx import TensorProto, helper
 from finn.util.data_packing import npy_to_rtlsim_input, rtlsim_output_to_npy
 
 # ONNX i/o tensor shape assumptions for ConvolutionInputGenerator:

src/finn/custom_op/fpgadataflow/convolutioninputgenerator1d.py

@@ -26,15 +26,14 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-import os
-
 import math
 import numpy as np
+import os
+from onnx import TensorProto, helper
 
 from finn.core.datatype import DataType
 from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
 from finn.custom_op.general.im2col import compute_conv_output_dim
-from onnx import TensorProto, helper
 from finn.util.data_packing import npy_to_rtlsim_input, rtlsim_output_to_npy
 
 # This operation should only be used for 1D convolutions. Either the

src/finn/custom_op/fpgadataflow/downsampler.py

-import os
 import numpy as np
+import os
+import warnings
 from onnx import TensorProto, helper
+
 from finn.core.datatype import DataType
 from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
 from finn.util.data_packing import npy_to_rtlsim_input, rtlsim_output_to_npy
-import warnings
 
 
 class DownSampler(HLSCustomOp):

src/finn/custom_op/fpgadataflow/duplicatestreams_batch.py

@@ -26,13 +26,13 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-import os
-
 import numpy as np
+import os
 import warnings
+from onnx import TensorProto, helper
+
 from finn.core.datatype import DataType
 from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
-from onnx import helper, TensorProto
 from finn.util.data_packing import npy_to_rtlsim_input, rtlsim_output_to_npy
 
 

src/finn/custom_op/fpgadataflow/fmpadding_batch.py

-import os
 import numpy as np
+import os
+import warnings
 from onnx import TensorProto, helper
+
 from finn.core.datatype import DataType
 from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
 from finn.util.data_packing import npy_to_rtlsim_input, rtlsim_output_to_npy
-import warnings
 
 
 class FMPadding_Batch(HLSCustomOp):

src/finn/custom_op/fpgadataflow/globalaccpool_batch.py

@@ -26,13 +26,13 @@
 # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-import os
-
 import numpy as np
+import os
 import warnings
+from onnx import TensorProto, helper
+
 from finn.core.datatype import DataType
 from finn.custom_op.fpgadataflow.hlscustomop import HLSCustomOp
-from onnx import TensorProto, helper
 from finn.util.data_packing import npy_to_rtlsim_input, rtlsim_output_to_npy