Update Docker environment to Ubuntu 22, Python 3.10

.pre-commit-config.yaml

@@ -29,11 +29,11 @@
 exclude: '^docs/conf.py'
 
 default_language_version:
-    python: python3.8
+    python: python3.10
 
 repos:
 - repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v4.2.0
+  rev: v4.4.0
   hooks:
   - id: trailing-whitespace
     exclude: '\.dat$'
@@ -56,13 +56,13 @@ repos:
   - id: isort
 
 - repo: https://github.com/psf/black
-  rev: 22.3.0
+  rev: 23.3.0
   hooks:
   - id: black
     language_version: python3
 
 - repo: https://github.com/PyCQA/flake8
-  rev: 3.9.2
+  rev: 6.0.0
   hooks:
   - id: flake8
     # black-compatible flake-8 config

docker/Dockerfile.finn

@@ -26,10 +26,10 @@
 # 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 pytorch/pytorch:1.7.1-cuda11.0-cudnn8-runtime
+FROM ubuntu:jammy-20230126
 LABEL maintainer="Yaman Umuroglu <yamanu@xilinx.com>"
 
-ARG XRT_DEB_VERSION="xrt_202210.2.13.466_18.04-amd64-xrt"
+ARG XRT_DEB_VERSION="xrt_202220.2.14.354_22.04-amd64-xrt"
 
 WORKDIR /workspace
 
@@ -57,12 +57,15 @@ RUN apt-get update && \
     unzip \
     zip \
     locales \
-    lsb-core
+    lsb-core \
+    python3 \
+    python-is-python3 \
+    python3-pip
 RUN echo "StrictHostKeyChecking no" >> /etc/ssh/ssh_config
 RUN locale-gen "en_US.UTF-8"
 
 # install Verilator from source to get the right version
-RUN apt-get install -y git perl python3 make autoconf g++ flex bison ccache libgoogle-perftools-dev numactl perl-doc libfl2 libfl-dev zlibc zlib1g zlib1g-dev
+RUN apt-get install -y git perl make autoconf g++ flex bison ccache libgoogle-perftools-dev numactl perl-doc libfl2 libfl-dev zlib1g zlib1g-dev
 RUN git clone https://github.com/verilator/verilator
 RUN cd verilator && \
     git checkout v4.224 && \
@@ -81,19 +84,23 @@ RUN rm /tmp/$XRT_DEB_VERSION.deb
 COPY requirements.txt .
 RUN pip install -r requirements.txt
 RUN rm requirements.txt
+
+# install PyTorch
+RUN pip install torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cu116
+
 # extra Python package dependencies (for testing and interaction)
-RUN pip install pygments==2.4.1
-RUN pip install ipykernel==5.5.5
+RUN pip install pygments==2.14.0
+RUN pip install ipykernel==6.21.2
 RUN pip install jupyter==1.0.0 --ignore-installed
 RUN pip install markupsafe==2.0.1
-RUN pip install matplotlib==3.3.1 --ignore-installed
+RUN pip install matplotlib==3.7.0  --ignore-installed
 RUN pip install pytest-dependency==0.5.1
-RUN pip install pytest-xdist[setproctitle]==2.4.0
-RUN pip install pytest-parallel==0.1.0
+RUN pip install pytest-xdist[setproctitle]==3.2.0
+RUN pip install pytest-parallel==0.1.1
 RUN pip install "netron>=5.0.0"
-RUN pip install pandas==1.1.5
-RUN pip install scikit-learn==0.24.1
-RUN pip install tqdm==4.31.1
+RUN pip install pandas==1.5.3
+RUN pip install scikit-learn==1.2.1
+RUN pip install tqdm==4.64.1
 RUN pip install -e git+https://github.com/fbcotter/dataset_loading.git@0.0.4#egg=dataset_loading
 
 # extra dependencies from other FINN deps

docker/finn_entrypoint.sh

@@ -54,8 +54,9 @@ recho () {
   echo -e "${RED}ERROR: $1${NC}"
 }
 
-# qonnx
-pip install --user -e ${FINN_ROOT}/deps/qonnx
+# qonnx (using workaround for https://github.com/pypa/pip/issues/7953)
+# to be fixed in future Ubuntu versions (https://bugs.launchpad.net/ubuntu/+source/setuptools/+bug/1994016)
+pip install --no-build-isolation --no-warn-script-location -e ${FINN_ROOT}/deps/qonnx
 # finn-experimental
 pip install --user -e ${FINN_ROOT}/deps/finn-experimental
 # brevitas

fetch-repos.sh

@@ -27,9 +27,9 @@
 # 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.
 
-QONNX_COMMIT="20a34289cf2297d2b2bbbe75d6ac152ece86e3b4"
+QONNX_COMMIT="0c980ef410c7c99b33c5b96486233f5a723ca1bc"
 FINN_EXP_COMMIT="0aa7e1c44b20cf085b6fe42cff360f0a832afd2c"
-BREVITAS_COMMIT="c65f9c13dc124971f14739349531bbcda5c2a4aa"
+BREVITAS_COMMIT="d30ba0d6b3db4a333072624fa3d10827a686488d"
 PYVERILATOR_COMMIT="766e457465f5c0dd315490d7b9cc5d74f9a76f4f"
 CNPY_COMMIT="4e8810b1a8637695171ed346ce68f6984e585ef4"
 HLSLIB_COMMIT="c17aa478ae574971d115afa9fa4d9c215857d1ac"
@@ -39,7 +39,7 @@ XIL_BDF_COMMIT="8cf4bb674a919ac34e3d99d8d71a9e60af93d14e"
 KV260_BDF_COMMIT="98e0d3efc901f0b974006bc4370c2a7ad8856c79"
 EXP_BOARD_FILES_MD5="30eecc497c31050bd46d10ea20eba232"
 
-QONNX_URL="https://github.com/fastmachinelearning/qonnx.git"
+QONNX_URL="https://github.com/iksnagreb/qonnx.git"
 FINN_EXP_URL="https://github.com/Xilinx/finn-experimental.git"
 BREVITAS_URL="https://github.com/Xilinx/brevitas.git"
 PYVERILATOR_URL="https://github.com/maltanar/pyverilator.git"

requirements.txt

@@ -3,19 +3,17 @@ clize==4.1.1
 dataclasses-json==0.5.7
 gspread==3.6.0
 ipython==8.12.2
-numpy==1.22.0
+numpy==1.24.1
 onnx==1.13.0
 onnxoptimizer
-onnxruntime==1.11.1
-pre-commit==2.9.2
+onnxruntime==1.15.0
+pre-commit==3.3.2
 protobuf==3.20.3
 psutil==5.9.4
-pyscaffold==3.2.1
-scipy==1.5.2
+pyscaffold==4.4
+scipy==1.10.1
 setupext-janitor>=1.1.2
 sigtools==2.0.3
-sphinx==5.0.2
-sphinx_rtd_theme==0.5.0
-toposort==1.5
+toposort==1.7.0
 vcdvcd==1.0.5
 wget==3.2

run-docker.sh

@@ -86,7 +86,7 @@ SCRIPTPATH=$(dirname "$SCRIPT")
 : ${ALVEO_BOARD="U250"}
 : ${ALVEO_TARGET_DIR="/tmp"}
 : ${PLATFORM_REPO_PATHS="/opt/xilinx/platforms"}
-: ${XRT_DEB_VERSION="xrt_202210.2.13.466_18.04-amd64-xrt"}
+: ${XRT_DEB_VERSION="xrt_202220.2.14.354_22.04-amd64-xrt"}
 : ${FINN_HOST_BUILD_DIR="/tmp/$DOCKER_INST_NAME"}
 : ${FINN_DOCKER_TAG="xilinx/finn:$(git describe --always --tags --dirty).$XRT_DEB_VERSION"}
 : ${FINN_DOCKER_PREBUILT="0"}
@@ -201,6 +201,9 @@ DOCKER_EXEC+="-e PYNQ_PASSWORD=$PYNQ_PASSWORD "
 DOCKER_EXEC+="-e PYNQ_TARGET_DIR=$PYNQ_TARGET_DIR "
 DOCKER_EXEC+="-e OHMYXILINX=$OHMYXILINX "
 DOCKER_EXEC+="-e NUM_DEFAULT_WORKERS=$NUM_DEFAULT_WORKERS "
+# Workaround for FlexLM issue, see:
+# https://community.flexera.com/t5/InstallAnywhere-Forum/Issues-when-running-Xilinx-tools-or-Other-vendor-tools-in-docker/m-p/245820#M10647
+DOCKER_EXEC+="-e LD_PRELOAD=/lib/x86_64-linux-gnu/libudev.so.1 "
 if [ "$FINN_DOCKER_RUN_AS_ROOT" = "0" ];then
   DOCKER_EXEC+="-v /etc/group:/etc/group:ro "
   DOCKER_EXEC+="-v /etc/passwd:/etc/passwd:ro "

setup.cfg

@@ -34,12 +34,12 @@
 name = finn
 description = A Framework for Fast, Scalable Quantized Neural Network Inference
 author = Yaman Umuroglu
-author-email = yamanu@xilinx.com
+author_email = yamanu@xilinx.com
 license = new-bsd
-long-description = file: README.md
-long-description-content-type = text/markdown
+long_description = file: README.md
+long_description_content_type = text/markdown
 url = https://xilinx.github.io/finn/
-project-urls =
+project_urls =
     Documentation = https://finn.readthedocs.io/
 # Change if running only on Windows, Mac or Linux (comma-separated)
 platforms = any

src/finn/analysis/fpgadataflow/post_synth_res.py

@@ -85,7 +85,7 @@ def get_instance_stats(inst_name):
         row = root.findall(".//*[@contents='%s']/.." % inst_name)
         if row != []:
             node_dict = {}
-            row = row[0].getchildren()
+            row = list(row[0])
             for (restype, ind) in restype_to_ind.items():
                 node_dict[restype] = int(row[ind].attrib["contents"])
             return node_dict

src/finn/transformation/fpgadataflow/templates.py

@@ -135,7 +135,7 @@
 
 create_bd_design "top"
 if {$ZYNQ_TYPE == "zynq_us+"} {
-    create_bd_cell -type ip -vlnv xilinx.com:ip:zynq_ultra_ps_e:3.4 zynq_ps
+    create_bd_cell -type ip -vlnv xilinx.com:ip:zynq_ultra_ps_e:3.5 zynq_ps
     apply_bd_automation -rule xilinx.com:bd_rule:zynq_ultra_ps_e -config {apply_board_preset "1" }  [get_bd_cells zynq_ps]
     #activate one slave port, deactivate the second master port
     set_property -dict [list CONFIG.PSU__USE__S_AXI_GP2 {1}] [get_bd_cells zynq_ps]

tests/brevitas/test_brevitas_avg_pool_export.py

@@ -31,7 +31,7 @@
 import os
 import torch
 from brevitas.export import export_qonnx
-from brevitas.nn import QuantAvgPool2d, QuantIdentity, QuantReLU
+from brevitas.nn import TruncAvgPool2d, QuantIdentity, QuantReLU
 from qonnx.core.datatype import DataType
 from qonnx.core.modelwrapper import ModelWrapper
 from qonnx.transformation.infer_datatypes import InferDataTypes
@@ -73,7 +73,7 @@ def test_brevitas_avg_pool_export(
             bit_width=input_bit_width,
             return_quant_tensor=True,
         )
-    quant_avgpool = QuantAvgPool2d(
+    quant_avgpool = TruncAvgPool2d(
         kernel_size=kernel_size,
         stride=stride,
         bit_width=bit_width,

tests/end2end/test_end2end_bnn_pynq.py

@@ -328,13 +328,13 @@ def test_export(self, topology, wbits, abits, QONNX_export):
         (model, ishape) = get_trained_network_and_ishape(topology, wbits, abits)
         chkpt_name = get_checkpoint_name(topology, wbits, abits, QONNX_export, "export")
         if QONNX_export:
-            export_qonnx(model, torch.randn(ishape), chkpt_name)
+            export_qonnx(model, torch.randn(ishape), chkpt_name, opset_version=13)
             qonnx_cleanup(chkpt_name, out_file=chkpt_name)
             model = ModelWrapper(chkpt_name)
             model = model.transform(ConvertQONNXtoFINN())
             model.save(chkpt_name)
         else:
-            export_finn_onnx(model, torch.randn(ishape), chkpt_name)
+            export_finn_onnx(model, torch.randn(ishape), chkpt_name, opset_version=13)
         nname = "%s_w%da%d" % (topology, wbits, abits)
         update_dashboard_data(topology, wbits, abits, "network", nname)
         dtstr = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
@@ -374,7 +374,7 @@ def test_add_pre_and_postproc(self, topology, wbits, abits, QONNX_export):
         chkpt_preproc_name = get_checkpoint_name(
             topology, wbits, abits, QONNX_export, "preproc"
         )
-        export_finn_onnx(totensor_pyt, torch.randn(ishape), chkpt_preproc_name)
+        export_finn_onnx(totensor_pyt, torch.randn(ishape), chkpt_preproc_name, opset_version=13)
         assert os.path.isfile(chkpt_preproc_name)
         # join preprocessing and core model
         pre_model = ModelWrapper(chkpt_preproc_name)

tests/end2end/test_end2end_cybsec_mlp.py

@@ -146,7 +146,7 @@ def test_end2end_cybsec_mlp_export(QONNX_export):
         model.save(export_onnx_path)
     else:
         export_finn_onnx(
-            model_for_export, export_path=export_onnx_path, input_t=input_qt
+            model_for_export, export_path=export_onnx_path, input_t=input_qt, input_names=["onnx::Mul_0"]
         )
     assert os.path.isfile(export_onnx_path)
     # fix input datatype

tests/fpgadataflow/test_convert_to_hls_layers_cnv.py

@@ -38,7 +38,7 @@
 from qonnx.custom_op.registry import getCustomOp
 from qonnx.transformation.bipolar_to_xnor import ConvertBipolarMatMulToXnorPopcount
 from qonnx.transformation.fold_constants import FoldConstants
-from qonnx.transformation.general import GiveReadableTensorNames, GiveUniqueNodeNames
+from qonnx.transformation.general import GiveReadableTensorNames, GiveUniqueNodeNames, GiveUniqueParameterTensors
 from qonnx.transformation.infer_data_layouts import InferDataLayouts
 from qonnx.transformation.infer_shapes import InferShapes
 from qonnx.transformation.lower_convs_to_matmul import LowerConvsToMatMul
@@ -67,6 +67,7 @@ def test_convert_to_hls_layers_cnv_w1a1(fused_activation):
     model = model.transform(InferShapes())
     model = model.transform(FoldConstants())
     model = model.transform(GiveUniqueNodeNames())
+    model = model.transform(GiveUniqueParameterTensors())
     model = model.transform(GiveReadableTensorNames())
     model = model.transform(Streamline())
     model = model.transform(LowerConvsToMatMul())

tests/fpgadataflow/test_convert_to_hls_layers_fc.py

@@ -39,7 +39,7 @@
 from qonnx.custom_op.registry import getCustomOp
 from qonnx.transformation.bipolar_to_xnor import ConvertBipolarMatMulToXnorPopcount
 from qonnx.transformation.fold_constants import FoldConstants
-from qonnx.transformation.general import GiveReadableTensorNames, GiveUniqueNodeNames
+from qonnx.transformation.general import GiveReadableTensorNames, GiveUniqueNodeNames, GiveUniqueParameterTensors
 from qonnx.transformation.infer_shapes import InferShapes
 
 import finn.core.onnx_exec as oxe
@@ -64,6 +64,7 @@ def test_convert_to_hls_layers_tfc_w1a1():
     model = model.transform(InferShapes())
     model = model.transform(FoldConstants())
     model = model.transform(GiveUniqueNodeNames())
+    model = model.transform(GiveUniqueParameterTensors())
     model = model.transform(GiveReadableTensorNames())
     model = model.transform(Streamline())
     model = model.transform(ConvertBipolarMatMulToXnorPopcount())
@@ -135,6 +136,7 @@ def test_convert_to_hls_layers_tfc_w1a2():
     model = model.transform(InferShapes())
     model = model.transform(FoldConstants())
     model = model.transform(GiveUniqueNodeNames())
+    model = model.transform(GiveUniqueParameterTensors())
     model = model.transform(GiveReadableTensorNames())
     model = model.transform(Streamline())
     from finn.transformation.fpgadataflow.convert_to_hls_layers import (

tests/transformation/streamline/test_streamline_cnv.py

@@ -38,6 +38,7 @@
 from qonnx.transformation.general import (
     GiveReadableTensorNames,
     GiveUniqueNodeNames,
+    GiveUniqueParameterTensors,
     RemoveStaticGraphInputs,
     RemoveUnusedTensors,
 )
@@ -69,6 +70,7 @@ def test_streamline_cnv(size, wbits, abits):
     model = model.transform(InferShapes())
     model = model.transform(FoldConstants())
     model = model.transform(GiveUniqueNodeNames())
+    model = model.transform(GiveUniqueParameterTensors())
     model = model.transform(GiveReadableTensorNames())
     model = model.transform(RemoveStaticGraphInputs())
     # load one of the test vectors

tests/transformation/streamline/test_streamline_fc.py

@@ -39,6 +39,7 @@
 from qonnx.transformation.general import (
     GiveReadableTensorNames,
     GiveUniqueNodeNames,
+    GiveUniqueParameterTensors,
     RemoveStaticGraphInputs,
     RemoveUnusedTensors,
 )
@@ -72,6 +73,7 @@ def test_streamline_fc(size, wbits, abits):
     model = model.transform(InferShapes())
     model = model.transform(FoldConstants())
     model = model.transform(GiveUniqueNodeNames())
+    model = model.transform(GiveUniqueParameterTensors())
     model = model.transform(GiveReadableTensorNames())
     model = model.transform(RemoveStaticGraphInputs())
     # load one of the test vectors

tests/transformation/test_infer_data_layouts_cnv.py

@@ -35,7 +35,7 @@
 from qonnx.core.modelwrapper import ModelWrapper
 from qonnx.transformation.bipolar_to_xnor import ConvertBipolarMatMulToXnorPopcount
 from qonnx.transformation.fold_constants import FoldConstants
-from qonnx.transformation.general import GiveReadableTensorNames, GiveUniqueNodeNames
+from qonnx.transformation.general import GiveReadableTensorNames, GiveUniqueNodeNames, GiveUniqueParameterTensors
 from qonnx.transformation.infer_data_layouts import InferDataLayouts
 from qonnx.transformation.infer_shapes import InferShapes
 from qonnx.transformation.lower_convs_to_matmul import LowerConvsToMatMul
@@ -57,6 +57,7 @@ def test_infer_data_layouts_cnv():
     model = model.transform(InferShapes())
     model = model.transform(FoldConstants())
     model = model.transform(GiveUniqueNodeNames())
+    model = model.transform(GiveUniqueParameterTensors())
     model = model.transform(GiveReadableTensorNames())
     model = model.transform(Streamline())
     model = model.transform(InferDataLayouts())