diff --git a/Cargo.toml b/Cargo.toml
index 5a4a796450..7995235c6c 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -27,7 +27,7 @@ members = [
     "examples/tensorflow-mobilenet-v2",
     "examples/tflite-mobilenet-v3",
     "examples/jupyter-keras-tract-tf1",
-    "examples/jupyter-keras-tract-tf2",
+    "examples/keras-tract-tf2",
     "examples/nnef-dump-mobilenet-v2",
     "examples/nnef-mobilenet-v2",
     "examples/onnx-mobilenet-v2",
diff --git a/examples/jupyter-keras-tract-tf2/README.md b/examples/jupyter-keras-tract-tf2/README.md
deleted file mode 100644
index 8b36e963b1..0000000000
--- a/examples/jupyter-keras-tract-tf2/README.md
+++ /dev/null
@@ -1,26 +0,0 @@
-A simple example of training a Tensorflow model with Python in a [Jupyter notebook](simple_model.ipynb), then [loading it into `tract`](src/main.rs) to make predictions.
-
-# To Use
-`conda env create -f environment.yml`
-
-Run the Jupyter notebook, which will create the model artifacts (1 onnx for `tract`, and one tensorflow artifact for benchmarking)
-
-Python
-
-```
-time python make_predictions.py
-real    0m1.667s
-user    0m2.575s
-sys     0m1.301s
-```
-
-tract, even in debug mode, is significantly faster:
-
-```
-time cargo run
-real    0m0.111s
-user    0m0.080s
-sys     0m0.040s
-```
-
-In a real-life server settings, the model would be loaded and optimized only once and used repeastedly to make predictions on different inputs. Compiled in release mode, the call to `run()` is clocked at 6 microseconds (0m0.000006s !) on one single core.
diff --git a/examples/jupyter-keras-tract-tf2/ci.sh b/examples/jupyter-keras-tract-tf2/ci.sh
deleted file mode 100755
index 64e948c97a..0000000000
--- a/examples/jupyter-keras-tract-tf2/ci.sh
+++ /dev/null
@@ -1,32 +0,0 @@
-#!/bin/sh
-
-set -e
-
-sudo apt-get update
-sudo apt-get install -y libgl1-mesa-glx libegl1-mesa libxrandr2 libxrandr2 libxss1 libxcursor1 libxcomposite1 libasound2 libxi6 libxtst6
-
-if [ ! -d $HOME/anaconda3 ]
-then
-    ANACONDA_SETUP=Anaconda3-2022.10-Linux-x86_64.sh
-    [ -e $ANACONDA_SETUP ] || wget -q https://repo.anaconda.com/archive/$ANACONDA_SETUP
-    bash $ANACONDA_SETUP -b
-fi
-
-. $HOME/anaconda3/bin/activate
-echo $CONDA_EXE
-if [ ! -d $HOME/anaconda3/envs/tf_37 ]
-then
-    conda env create -q -f environment.yml
-fi
-conda activate tf_37
-
-cd `dirname $0`
-jupyter nbconvert --to notebook --inplace --execute simple_model.ipynb
-cargo run
-cargo clean
-
-if [ -n "$CI" ]
-then
-    conda deactivate
-    conda env remove -n tf_37
-fi
diff --git a/examples/jupyter-keras-tract-tf2/environment.yml b/examples/jupyter-keras-tract-tf2/environment.yml
deleted file mode 100644
index cf5d384631..0000000000
--- a/examples/jupyter-keras-tract-tf2/environment.yml
+++ /dev/null
@@ -1,141 +0,0 @@
-name: tf_37
-channels:
-  - defaults
-dependencies:
-  - _libgcc_mutex=0.1=main
-  - _tflow_select=2.3.0=mkl
-  - absl-py=0.10.0=py37_0
-  - argon2-cffi=20.1.0=py37h7b6447c_1
-  - astunparse=1.6.3=py_0
-  - attrs=20.2.0=py_0
-  - backcall=0.2.0=py_0
-  - blas=1.0=mkl
-  - bleach=3.2.0=py_0
-  - blinker=1.4=py37_0
-  - brotlipy=0.7.0=py37h7b6447c_1000
-  - c-ares=1.15.0=h7b6447c_1001
-  - ca-certificates=2020.7.22=0
-  - cachetools=4.1.1=py_0
-  - certifi=2020.6.20=py37_0
-  - cffi=1.14.2=py37he30daa8_0
-  - chardet=3.0.4=py37_1003
-  - click=7.1.2=py_0
-  - cryptography=3.1=py37h1ba5d50_0
-  - decorator=4.4.2=py_0
-  - defusedxml=0.6.0=py_0
-  - entrypoints=0.3=py37_0
-  - gast=0.3.3=py_0
-  - google-auth=1.21.2=py_0
-  - google-auth-oauthlib=0.4.1=py_2
-  - google-pasta=0.2.0=py_0
-  - grpcio=1.31.0=py37hf8bcb03_0
-  - h5py=2.10.0=py37hd6299e0_1
-  - hdf5=1.10.6=hb1b8bf9_0
-  - idna=2.10=py_0
-  - importlib-metadata=1.7.0=py37_0
-  - importlib_metadata=1.7.0=0
-  - intel-openmp=2020.2=254
-  - ipykernel=5.3.4=py37h5ca1d4c_0
-  - ipython=7.18.1=py37h5ca1d4c_0
-  - ipython_genutils=0.2.0=py37_0
-  - jedi=0.17.2=py37_0
-  - jinja2=2.11.2=py_0
-  - jsonschema=3.2.0=py37_1
-  - jupyter_client=6.1.6=py_0
-  - jupyter_core=4.6.3=py37_0
-  - keras-preprocessing=1.1.0=py_1
-  - ld_impl_linux-64=2.33.1=h53a641e_7
-  - libedit=3.1.20191231=h14c3975_1
-  - libffi=3.3=he6710b0_2
-  - libgcc-ng=9.1.0=hdf63c60_0
-  - libgfortran-ng=7.3.0=hdf63c60_0
-  - libprotobuf=3.13.0=hd408876_0
-  - libsodium=1.0.18=h7b6447c_0
-  - libstdcxx-ng=9.1.0=hdf63c60_0
-  - markdown=3.2.2=py37_0
-  - markupsafe=1.1.1=py37h14c3975_1
-  - mistune=0.8.4=py37h14c3975_1001
-  - mkl=2020.2=256
-  - mkl-service=2.3.0=py37he904b0f_0
-  - mkl_fft=1.1.0=py37h23d657b_0
-  - mkl_random=1.1.1=py37h0573a6f_0
-  - nb_conda=2.2.1=py37_0
-  - nb_conda_kernels=2.2.4=py37_0
-  - nbconvert=5.6.1=py37_1
-  - nbformat=5.0.7=py_0
-  - ncurses=6.2=he6710b0_1
-  - notebook=6.1.1=py37_0
-  - numpy=1.19.1=py37hbc911f0_0
-  - numpy-base=1.19.1=py37hfa32c7d_0
-  - oauthlib=3.1.0=py_0
-  - openssl=1.1.1g=h7b6447c_0
-  - opt_einsum=3.1.0=py_0
-  - packaging=20.4=py_0
-  - pandoc=2.10.1=0
-  - pandocfilters=1.4.2=py37_1
-  - parso=0.7.0=py_0
-  - pexpect=4.8.0=py37_1
-  - pickleshare=0.7.5=py37_1001
-  - pip=20.2.2=py37_0
-  - prometheus_client=0.8.0=py_0
-  - prompt-toolkit=3.0.7=py_0
-  - protobuf=3.13.0=py37hf484d3e_0
-  - ptyprocess=0.6.0=py37_0
-  - pyasn1=0.4.8=py_0
-  - pyasn1-modules=0.2.7=py_0
-  - pycparser=2.20=py_2
-  - pygments=2.7.0=py_0
-  - pyjwt=1.7.1=py37_0
-  - pyopenssl=19.1.0=py_1
-  - pyparsing=2.4.7=py_0
-  - pyrsistent=0.17.3=py37h7b6447c_0
-  - pysocks=1.7.1=py37_1
-  - python=3.7.9=h7579374_0
-  - python-dateutil=2.8.1=py_0
-  - pyzmq=19.0.1=py37he6710b0_1
-  - readline=8.0=h7b6447c_0
-  - requests=2.24.0=py_0
-  - requests-oauthlib=1.3.0=py_0
-  - rsa=4.6=py_0
-  - scipy=1.5.2=py37h0b6359f_0
-  - send2trash=1.5.0=py37_0
-  - setuptools=49.6.0=py37_0
-  - six=1.15.0=py_0
-  - sqlite=3.33.0=h62c20be_0
-  - tensorboard=2.2.1=pyh532a8cf_0
-  - tensorboard-plugin-wit=1.6.0=py_0
-  - tensorflow=2.2.0=mkl_py37h6e9ce2d_0
-  - tensorflow-base=2.2.0=mkl_py37hd506778_0
-  - tensorflow-estimator=2.2.0=pyh208ff02_0
-  - termcolor=1.1.0=py37_1
-  - terminado=0.8.3=py37_0
-  - testpath=0.4.4=py_0
-  - tk=8.6.10=hbc83047_0
-  - tornado=6.0.4=py37h7b6447c_1
-  - traitlets=4.3.3=py37_0
-  - urllib3=1.25.10=py_0
-  - wcwidth=0.2.5=py_0
-  - webencodings=0.5.1=py37_1
-  - werkzeug=1.0.1=py_0
-  - wheel=0.35.1=py_0
-  - wrapt=1.12.1=py37h7b6447c_1
-  - xz=5.2.5=h7b6447c_0
-  - zeromq=4.3.2=he6710b0_3
-  - zipp=3.1.0=py_0
-  - zlib=1.2.11=h7b6447c_3
-  - pip:
-    - fire==0.3.1
-    - joblib==0.16.0
-    - keras2onnx==1.7.0
-    - onnx==1.7.0
-    - onnxconverter-common==1.7.0
-    - onnxmltools==1.7.0
-    - pyyaml==5.3.1
-    - scikit-learn==0.23.2
-    - skl2onnx==1.7.0
-    - tensorflow-addons==0.11.2
-    - threadpoolctl==2.1.0
-    - tract==0.20.18
-    - typeguard==2.9.1
-    - typing-extensions==3.7.4.3
-prefix: /home/kali/anaconda3/envs/tf_37
diff --git a/examples/jupyter-keras-tract-tf2/example.onnx b/examples/jupyter-keras-tract-tf2/example.onnx
deleted file mode 100644
index 71be7a4be1..0000000000
Binary files a/examples/jupyter-keras-tract-tf2/example.onnx and /dev/null differ
diff --git a/examples/jupyter-keras-tract-tf2/io.npz b/examples/jupyter-keras-tract-tf2/io.npz
deleted file mode 100644
index 1b5026dabc..0000000000
Binary files a/examples/jupyter-keras-tract-tf2/io.npz and /dev/null differ
diff --git a/examples/jupyter-keras-tract-tf2/make_predictions.py b/examples/jupyter-keras-tract-tf2/make_predictions.py
deleted file mode 100644
index cb747cf725..0000000000
--- a/examples/jupyter-keras-tract-tf2/make_predictions.py
+++ /dev/null
@@ -1,12 +0,0 @@
-import tensorflow as tf
-import numpy as np
-import warnings
-
-warnings.filterwarnings("ignore")
-X = np.random.random((10, 100))
-new_model = tf.keras.models.load_model('my_model')
-    
-    
-predictions = new_model.predict(X)
-
-print(f"result: {predictions}")
\ No newline at end of file
diff --git a/examples/jupyter-keras-tract-tf2/my_model/saved_model.pb b/examples/jupyter-keras-tract-tf2/my_model/saved_model.pb
deleted file mode 100644
index db3a71e687..0000000000
Binary files a/examples/jupyter-keras-tract-tf2/my_model/saved_model.pb and /dev/null differ
diff --git a/examples/jupyter-keras-tract-tf2/my_model/variables/variables.data-00000-of-00001 b/examples/jupyter-keras-tract-tf2/my_model/variables/variables.data-00000-of-00001
deleted file mode 100644
index 3645b84a0d..0000000000
Binary files a/examples/jupyter-keras-tract-tf2/my_model/variables/variables.data-00000-of-00001 and /dev/null differ
diff --git a/examples/jupyter-keras-tract-tf2/my_model/variables/variables.index b/examples/jupyter-keras-tract-tf2/my_model/variables/variables.index
deleted file mode 100644
index 2c97170ac0..0000000000
Binary files a/examples/jupyter-keras-tract-tf2/my_model/variables/variables.index and /dev/null differ
diff --git a/examples/jupyter-keras-tract-tf2/simple_model.ipynb b/examples/jupyter-keras-tract-tf2/simple_model.ipynb
deleted file mode 100644
index 1c200ba630..0000000000
--- a/examples/jupyter-keras-tract-tf2/simple_model.ipynb
+++ /dev/null
@@ -1,201 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import tensorflow as tf\n",
-    "from tensorflow.keras.models import Sequential\n",
-    "from tensorflow.keras.layers import Dense, Activation\n",
-    "import onnxmltools\n",
-    "import tract"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "model = Sequential([\n",
-    "    Dense(32, activation='relu', input_dim=100,  name='main_input'),\n",
-    "    Dense(1, activation='sigmoid', name=\"dense_1\"),\n",
-    "])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "model.compile(optimizer='rmsprop',\n",
-    "              loss='binary_crossentropy',\n",
-    "              metrics=['accuracy'])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Epoch 1/10\n",
-      "32/32 [==============================] - 0s 834us/step - loss: 0.7036 - accuracy: 0.4800\n",
-      "Epoch 2/10\n",
-      "32/32 [==============================] - 0s 802us/step - loss: 0.6949 - accuracy: 0.5210\n",
-      "Epoch 3/10\n",
-      "32/32 [==============================] - 0s 853us/step - loss: 0.6934 - accuracy: 0.5070\n",
-      "Epoch 4/10\n",
-      "32/32 [==============================] - 0s 910us/step - loss: 0.6885 - accuracy: 0.5380\n",
-      "Epoch 5/10\n",
-      "32/32 [==============================] - 0s 1ms/step - loss: 0.6819 - accuracy: 0.5600\n",
-      "Epoch 6/10\n",
-      "32/32 [==============================] - 0s 988us/step - loss: 0.6853 - accuracy: 0.5610\n",
-      "Epoch 7/10\n",
-      "32/32 [==============================] - 0s 820us/step - loss: 0.6797 - accuracy: 0.5800\n",
-      "Epoch 8/10\n",
-      "32/32 [==============================] - 0s 913us/step - loss: 0.6763 - accuracy: 0.5730\n",
-      "Epoch 9/10\n",
-      "32/32 [==============================] - 0s 904us/step - loss: 0.6713 - accuracy: 0.5980\n",
-      "Epoch 10/10\n",
-      "32/32 [==============================] - 0s 743us/step - loss: 0.6714 - accuracy: 0.5800\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<tensorflow.python.keras.callbacks.History at 0x7fcd24037110>"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "data = np.random.random((1000, 100))\n",
-    "labels = np.random.randint(2, size=(1000, 1))\n",
-    "\n",
-    "# Train the model, iterating on the data in batches of 32 samples\n",
-    "model.fit(data, labels, epochs=10, batch_size=32)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "WARNING:tensorflow:From /home/kali/anaconda3/envs/tf_37/lib/python3.7/site-packages/tensorflow/python/ops/resource_variable_ops.py:1817: calling BaseResourceVariable.__init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version.\n",
-      "Instructions for updating:\n",
-      "If using Keras pass *_constraint arguments to layers.\n",
-      "INFO:tensorflow:Assets written to: my_model/assets\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Save in tf's format, for benchmarking\n",
-    "model.save('my_model')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "tf executing eager_mode: True\n",
-      "tf.keras model eager_mode: False\n",
-      "The ONNX operator number change on the optimization: 10 -> 6\n",
-      "The maximum opset needed by this model is only 9.\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Save the model in ONNX format to pass to tract\n",
-    "onnx_model = onnxmltools.convert_keras(model)\n",
-    "onnxmltools.utils.save_model(onnx_model, 'example.onnx')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "input = np.random.random((1,100)).astype(np.float32)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "tf_output = model.predict(input)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Run the model in tract and check output against TensorFlow\n",
-    "tract_output = tract.onnx().model_for_path(\"example.onnx\").into_optimized().into_runnable().run([input])[0].to_numpy()\n",
-    "assert(np.allclose(tf_output, tract_output))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Save input and reference output for Rust demo\n",
-    "np.savez(\"io.npz\", input=input, output=tf_output)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.9"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/examples/jupyter-keras-tract-tf2/.gitignore b/examples/keras-tract-tf2/.gitignore
similarity index 100%
rename from examples/jupyter-keras-tract-tf2/.gitignore
rename to examples/keras-tract-tf2/.gitignore
diff --git a/examples/jupyter-keras-tract-tf2/Cargo.toml b/examples/keras-tract-tf2/Cargo.toml
similarity index 92%
rename from examples/jupyter-keras-tract-tf2/Cargo.toml
rename to examples/keras-tract-tf2/Cargo.toml
index 39d9a866b5..d06e2c1b4c 100644
--- a/examples/jupyter-keras-tract-tf2/Cargo.toml
+++ b/examples/keras-tract-tf2/Cargo.toml
@@ -1,5 +1,5 @@
 [package]
-name = "jupyter-keras-tract-tf2"
+name = "keras-tract-tf2"
 version = "0.20.7-pre"
 authors = ["Matthew Alhonte <mattalhonte@gmail.com>"]
 license = "MIT OR Apache-2.0"
diff --git a/examples/keras-tract-tf2/README.md b/examples/keras-tract-tf2/README.md
new file mode 100644
index 0000000000..386aa7ceea
--- /dev/null
+++ b/examples/keras-tract-tf2/README.md
@@ -0,0 +1,21 @@
+A simple example of training a Tensorflow model with Python, check the model with tract python API, then [loading it into `tract`](src/main.rs) and compare predictions.
+
+# Python side training
+
+```
+pip install -r requirements.txt
+```
+
+Train a model, export it to ONNX along with a input and output example.
+
+```
+python example.py
+```
+
+(Outputs are commited to git, you don't need to run the python step at all.)
+
+# Rust side inference
+
+```
+cargo run
+```
diff --git a/examples/keras-tract-tf2/ci.sh b/examples/keras-tract-tf2/ci.sh
new file mode 100755
index 0000000000..02b4dbb172
--- /dev/null
+++ b/examples/keras-tract-tf2/ci.sh
@@ -0,0 +1,13 @@
+#!/bin/sh
+
+set -e
+
+sudo apt-get update
+sudo apt-get install -y libgl1-mesa-glx libegl1-mesa libxrandr2 libxrandr2 libxss1 libxcursor1 libxcomposite1 libasound2 libxi6 libxtst6 
+
+virtualenv venv
+. venv/bin/activate
+
+pip install -r requirements.txt
+python example.py
+cargo run
diff --git a/examples/keras-tract-tf2/example.onnx b/examples/keras-tract-tf2/example.onnx
new file mode 100644
index 0000000000..ff3f019160
Binary files /dev/null and b/examples/keras-tract-tf2/example.onnx differ
diff --git a/examples/keras-tract-tf2/io.npz b/examples/keras-tract-tf2/io.npz
new file mode 100644
index 0000000000..9ead17dfc9
Binary files /dev/null and b/examples/keras-tract-tf2/io.npz differ
diff --git a/examples/jupyter-keras-tract-tf2/src/main.rs b/examples/keras-tract-tf2/src/main.rs
similarity index 91%
rename from examples/jupyter-keras-tract-tf2/src/main.rs
rename to examples/keras-tract-tf2/src/main.rs
index 057bca97e5..81945a2db0 100644
--- a/examples/jupyter-keras-tract-tf2/src/main.rs
+++ b/examples/keras-tract-tf2/src/main.rs
@@ -6,6 +6,8 @@ fn main() -> TractResult<()> {
     let model = tract_onnx::onnx()
     // load the model
     .model_for_path("example.onnx")?
+    // kill over-spcified output fact in ONNX
+    .with_output_fact(0, Default::default())?
     // optimize graph
     .into_optimized()?
     // make the model runnable and fix its inputs and outputs