WIP

.azure-pipelines/linux-conda-CI-tf-keras.yml

@@ -66,6 +66,7 @@ jobs:
       pip install -r requirements.txt
       pip install -r requirements-dev.txt
       $(INSTALL_ORT)
+      pip install git+https://github.com/onnx/tensorflow-onnx@tom/test_keras_tf1
     displayName: 'Install dependencies'
 
   - script: |
@@ -84,3 +85,129 @@ jobs:
       testResultsFiles: '**/test-results.xml'
       testRunTitle: 'Python $(python.version)'
     condition: succeededOrFailed()
+
+- job: 'NightlyTest'
+  timeoutInMinutes: 180
+  pool:
+    vmImage: 'Ubuntu-16.04'
+  strategy:
+    matrix:
+      Python36-onnx1.2:
+        python.version: '3.6'
+        ONNX_PATH: onnx==1.2.3
+        INSTALL_KERAS: pip install keras==2.1.6
+        UNINSTALL_KERAS:
+        INSTALL_TENSORFLOW: pip install tensorflow==1.15.0
+        INSTALL_ORT: pip install onnxruntime==1.1.1
+        INSTALL_KERAS_RESNET:
+        INSTALL_TRANSFORMERS:
+        NIGHTLY_BUILD_TEST: python run_all.py --exclude "test_keras_applications_v2.py"
+
+      Python36-onnx1.5:
+        python.version: '3.6'
+        ONNX_PATH: onnx==1.5.0
+        INSTALL_KERAS: pip install keras==2.2.4
+        UNINSTALL_KERAS:
+        INSTALL_TENSORFLOW: pip install tensorflow==1.15.0
+        INSTALL_ORT: pip install onnxruntime==1.1.1
+        INSTALL_KERAS_RESNET: pip install keras-resnet
+        INSTALL_TRANSFORMERS:
+        NIGHTLY_BUILD_TEST: python run_all.py --exclude "test_keras_applications_v2.py"
+
+      Python37:
+        python.version: '3.7.3'
+        ONNX_PATH: onnx==1.8.0
+        INSTALL_KERAS: pip install keras==2.3.1
+        UNINSTALL_KERAS:
+        INSTALL_TENSORFLOW: pip install tensorflow==1.15.0
+        INSTALL_ORT: pip install -i https://test.pypi.org/simple/ ort-nightly
+        INSTALL_KERAS_RESNET: pip install keras-resnet
+        INSTALL_TRANSFORMERS:
+        NIGHTLY_BUILD_TEST: python run_all.py --exclude "test_keras_applications_v2.py"
+
+      Python37-official-ort:
+        python.version: '3.7.3'
+        ONNX_PATH: onnx==1.6.0
+        INSTALL_KERAS: pip install keras==2.3.1
+        UNINSTALL_KERAS:
+        INSTALL_TENSORFLOW: pip install tensorflow==1.15.0
+        INSTALL_ORT: pip install onnxruntime==1.3.0
+        INSTALL_KERAS_RESNET: pip install keras-resnet
+        INSTALL_TRANSFORMERS:
+        NIGHTLY_BUILD_TEST: python run_all.py --exclude "test_keras_applications_v2.py"
+
+      Python38-tf2:
+        python.version: '3.8'
+        ONNX_PATH: onnx==1.8.0
+        INSTALL_KERAS:
+        UNINSTALL_KERAS: pip uninstall keras -y
+        INSTALL_TENSORFLOW: pip install tensorflow==2.2.0
+        INSTALL_ORT: pip install -i https://test.pypi.org/simple/ ort-nightly
+        INSTALL_KERAS_RESNET: pip install keras-resnet
+        INSTALL_TRANSFORMERS: pip install transformers==3.4.0
+        NIGHTLY_BUILD_TEST: python run_all_v2.py
+
+    maxParallel: 3
+
+  steps:
+  - script: sudo install -d -m 0777 /home/vsts/.conda/envs
+    displayName: Fix Conda permissions
+
+  - task: CondaEnvironment@1
+    inputs:
+      createCustomEnvironment: true
+      environmentName: 'py$(python.version)'
+      packageSpecs: 'python=$(python.version)'
+
+  - script: |
+      python -m pip install --upgrade pip
+      conda config --set always_yes yes --set changeps1 no
+      pip install $(ONNX_PATH)
+      pip install h5py==2.9.0
+      $(INSTALL_TENSORFLOW)
+      $(INSTALL_KERAS)
+      pip install git+https://github.com/microsoft/onnxconverter-common
+      pip install -r requirements.txt
+      pip install -r requirements-dev.txt
+      $(INSTALL_ORT)
+      pip install opencv-python
+      pip install tqdm
+      pip install keras-segmentation==0.2.0
+      git clone https://github.com/matterport/Mask_RCNN
+      cd Mask_RCNN
+      pip install -r requirements.txt
+      python setup.py install
+      cd ..
+      pip install matplotlib
+      git clone https://github.com/qqwweee/keras-yolo3
+      $(INSTALL_KERAS_RESNET)
+      pip install git+https://www.github.com/keras-team/keras-contrib.git
+      pip install keras-tcn==2.8.3
+      $(UNINSTALL_KERAS)
+      pip install git+https://github.com/qubvel/efficientnet
+      $(INSTALL_TRANSFORMERS)
+      pip install keras-self-attention
+      pip install git+https://github.com/onnx/tensorflow-onnx@tom/test_keras_tf1
+    displayName: 'Install dependencies'
+
+  - script: |
+      pip install -e .
+      python -c "import onnxruntime"
+      pytest tests --doctest-modules --junitxml=junit/test-results.xml
+      cd applications/nightly_build
+      $(NIGHTLY_BUILD_TEST)
+    displayName: 'pytest'
+
+  - script: |
+      pip install -e .
+      python -c "import onnxruntime"
+      coverage run --include=keras2onnx/* -m pytest tests/test_layers.py
+      coverage report -m
+      coverage html
+    displayName: 'coverage'
+
+  - task: PublishTestResults@2
+    inputs:
+      testResultsFiles: '**/test-results-*.xml'
+      testRunTitle: 'Python $(python.version)'
+    condition: succeededOrFailed()

.azure-pipelines/linux-conda-CI.yml

@@ -73,6 +73,7 @@ jobs:
       pip install -r requirements.txt
       pip install -r requirements-dev.txt
       $(INSTALL_ORT)
+      pip install git+https://github.com/onnx/tensorflow-onnx@tom/test_keras_tf1
     displayName: 'Install dependencies'
 
   - script: |

.azure-pipelines/win32-conda-CI-tf-keras.yml

@@ -69,6 +69,7 @@ jobs:
       pip install -r requirements.txt
       pip install -r requirements-dev.txt
       %INSTALL_ORT%
+      pip install git+https://github.com/onnx/tensorflow-onnx@tom/test_keras_tf1
     displayName: 'Install dependencies'
 
   - script: |
@@ -84,3 +85,130 @@ jobs:
       testResultsFiles: '**/test-results.xml'
       testRunTitle: 'Python $(python.version)'
     condition: succeededOrFailed()
+
+- job: 'NightlyTest'
+  timeoutInMinutes: 180
+  pool:
+    vmImage: 'vs2017-win2016'
+  strategy:
+    matrix:
+      # No python 2.x since no available ONNX package for Windows
+      Python36-onnx1.2:
+        python.version: '3.6'
+        ONNX_PATH: onnx==1.2.3
+        INSTALL_KERAS: pip install keras==2.1.6
+        UNINSTALL_KERAS:
+        INSTALL_TENSORFLOW: pip install tensorflow==1.14.0
+        INSTALL_ORT: pip install onnxruntime==1.1.1
+        INSTALL_KERAS_RESNET:
+        INSTALL_TRANSFORMERS:
+        NIGHTLY_BUILD_TEST: python run_all.py --exclude "test_keras_applications_v2.py test_mask_rcnn.py"
+
+      Python36-onnx1.5:
+        python.version: '3.6'
+        ONNX_PATH: onnx==1.5.0
+        INSTALL_KERAS: pip install keras==2.2.4
+        UNINSTALL_KERAS:
+        INSTALL_TENSORFLOW: pip install tensorflow==1.14.0
+        INSTALL_ORT: pip install onnxruntime==1.1.1
+        INSTALL_KERAS_RESNET: pip install keras-resnet
+        INSTALL_TRANSFORMERS:
+        NIGHTLY_BUILD_TEST: python run_all.py --exclude "test_keras_applications_v2.py test_mask_rcnn.py"
+
+      Python37:
+        python.version: '3.7'
+        ONNX_PATH: onnx==1.8.0
+        INSTALL_KERAS: pip install keras==2.3.1
+        UNINSTALL_KERAS:
+        INSTALL_TENSORFLOW: pip install tensorflow==1.14.0
+        INSTALL_ORT: pip install -i https://test.pypi.org/simple/ ort-nightly
+        INSTALL_KERAS_RESNET: pip install keras-resnet
+        INSTALL_TRANSFORMERS:
+        NIGHTLY_BUILD_TEST: python run_all.py --exclude "test_keras_applications_v2.py test_mask_rcnn.py"
+
+      Python37-official-ort:
+        python.version: '3.7'
+        ONNX_PATH: onnx==1.6.0
+        INSTALL_KERAS: pip install keras==2.3.1
+        UNINSTALL_KERAS:
+        INSTALL_TENSORFLOW: pip install tensorflow==1.14.0
+        INSTALL_ORT: pip install onnxruntime==1.1.1
+        INSTALL_KERAS_RESNET: pip install keras-resnet
+        INSTALL_TRANSFORMERS:
+        NIGHTLY_BUILD_TEST: python run_all.py --exclude "test_keras_applications_v2.py test_mask_rcnn.py"
+
+      Python38-tf2:
+        python.version: '3.8'
+        ONNX_PATH: onnx==1.8.0
+        INSTALL_KERAS:
+        UNINSTALL_KERAS: pip uninstall keras -y
+        INSTALL_TENSORFLOW: pip install tensorflow==2.2.0
+        INSTALL_ORT: pip install onnxruntime==1.7.0
+        INSTALL_KERAS_RESNET: pip install keras-resnet
+        INSTALL_TRANSFORMERS: pip install transformers==3.4.0
+        NIGHTLY_BUILD_TEST: python run_all_v2.py
+
+    maxParallel: 3
+
+  steps:
+  - task: UsePythonVersion@0
+    inputs:
+      versionSpec: '$(python.version)'
+      architecture: 'x64'
+
+  - powershell: Write-Host "##vso[task.prependpath]$env:CONDA\Scripts"
+    displayName: Add conda to PATH
+
+  - script: conda create --yes --quiet --name py$(python.version) -c conda-forge python=$(python.version) numpy protobuf
+    displayName: Create Anaconda environment
+
+  - script: |
+      call activate py$(python.version)
+      python -m pip install --upgrade pip numpy
+      echo Test numpy installation... && python -c "import numpy"
+      pip install %ONNX_PATH%
+      pip install h5py==2.9.0
+      %INSTALL_TENSORFLOW%
+      %INSTALL_KERAS%
+      pip install git+https://github.com/microsoft/onnxconverter-common
+      pip install -r requirements.txt
+      pip install -r requirements-dev.txt
+      %INSTALL_ORT%
+      pip install opencv-python
+      pip install tqdm
+      pip install keras-segmentation==0.2.0
+      pip install matplotlib
+      git clone https://github.com/qqwweee/keras-yolo3
+      %INSTALL_KERAS_RESNET%
+      pip install git+https://www.github.com/keras-team/keras-contrib.git
+      pip install keras-tcn==2.8.3
+      %UNINSTALL_KERAS%
+      pip install git+https://github.com/qubvel/efficientnet
+      %INSTALL_TRANSFORMERS%
+      pip install keras-self-attention
+      pip install git+https://github.com/onnx/tensorflow-onnx@tom/test_keras_tf1
+    displayName: 'Install dependencies'
+
+  - script: |
+      call activate py$(python.version)
+      pip install -e .
+      echo Test onnxruntime installation... && python -c "import onnxruntime"
+      pytest tests --doctest-modules --junitxml=junit/test-results.xml
+      cd applications/nightly_build
+      %NIGHTLY_BUILD_TEST%
+    displayName: 'pytest'
+
+  - script: |
+      call activate py$(python.version)
+      pip install -e .
+      echo Test onnxruntime installation... && python -c "import onnxruntime"
+      coverage run --include=keras2onnx/* -m pytest tests/test_layers.py
+      coverage report -m
+      coverage html
+    displayName: 'coverage'
+
+  - task: PublishTestResults@2
+    inputs:
+      testResultsFiles: '**/test-results-*.xml'
+      testRunTitle: 'Python $(python.version)'
+    condition: succeededOrFailed()

.azure-pipelines/win32-conda-CI.yml

@@ -69,6 +69,7 @@ jobs:
       pip install -r requirements.txt
       pip install -r requirements-dev.txt
       %INSTALL_ORT%
+      pip install git+https://github.com/onnx/tensorflow-onnx@tom/test_keras_tf1
     displayName: 'Install dependencies'
 
   - script: |

keras2onnx/_tf_utils.py

@@ -85,8 +85,8 @@ def tf_attrs_to_onnx(node):
     return attrs
 
 
-def to_tf_tensor_spec(onnx_type, name=None):
-    shp = [1 if isinstance(n_, str) else n_ for n_ in onnx_type.shape]
+def to_tf_tensor_spec(onnx_type, name=None, unknown_dim=1):
+    shp = [unknown_dim if isinstance(n_, str) else n_ for n_ in onnx_type.shape]
     return tensorflow.TensorSpec(shp,
                                  mapping.TENSOR_TYPE_TO_NP_TYPE[onnx_type.to_onnx_type().tensor_type.elem_type],
                                  name=name)

keras2onnx/main.py

@@ -18,7 +18,7 @@
 from ._parser_tf import build_layer_output_from_model
 
 
-def _process_initial_types(initial_types):
+def _process_initial_types(initial_types, unknown_dim=1):
     if initial_types is None:
         return None
 
@@ -30,15 +30,33 @@ def _process_initial_types(initial_types):
         if isinstance(initial_types[c_], str):
             name = initial_types[c_]
             type_idx = c_ + 1
-        ts_spec = to_tf_tensor_spec(initial_types[type_idx], name)
+        ts_spec = to_tf_tensor_spec(initial_types[type_idx], name, unknown_dim)
         input_specs.append(ts_spec)
         c_ += 1 if name is None else 2
 
     return input_specs
 
 
-def convert_keras(model, name=None, doc_string='', target_opset=None, initial_types=None,
-                  channel_first_inputs=None, debug_mode=False, custom_op_conversions=None):
+def convert_keras_tf2onnx(model, name=None, doc_string='', target_opset=None, initial_types=None,
+                          channel_first_inputs=None, debug_mode=False, custom_op_conversions=None):
+    if target_opset is None:
+        target_opset = get_maximum_opset_supported()
+    input_signature = _process_initial_types(initial_types, unknown_dim=None)
+
+
+    import tf2onnx
+    model, external_tensor_storage = tf2onnx.convert.from_keras(model, input_signature, opset=target_opset,
+                                                                inputs_as_nchw=channel_first_inputs)
+
+    return model
+
+
+def convert_keras(*args, **kwargs):
+    return convert_keras_tf2onnx(*args, **kwargs)
+
+
+def convert_keras_old(model, name=None, doc_string='', target_opset=None, initial_types=None,
+                      channel_first_inputs=None, debug_mode=False, custom_op_conversions=None):
     # type: (keras.Model, str, str, int, [], [], bool, {}) -> onnx.ModelProto
     """
     :param model: keras model
@@ -51,6 +69,7 @@ def convert_keras(model, name=None, doc_string='', target_opset=None, initial_ty
     :param custom_op_conversions: the handler for custom operator conversion
     :return an ONNX ModelProto
     """
+    print("Hello! I'm a test")
     if isinstance(model, tf.keras.Model) and not is_tf_keras:
         raise Exception("This is a tensorflow keras model, but keras standalone converter is used." +
                         " Please set environment variable TF_KERAS = 1 before importing keras2onnx.")

tests/test_layers.py

@@ -1982,10 +1982,11 @@ def test_LSTM_with_initializer(runner):
                     reason="None seq_length LSTM is not supported before opset 5.")
 def test_LSTM_seqlen_none(runner):
     lstm_dim = 2
+    np.random.seed(42)
     data = np.random.rand(1, 5, 1).astype(np.float32)
     for return_sequences in [True, False]:
         inp = Input(batch_shape=(1, None, 1))
-        out = LSTM(lstm_dim, return_sequences=return_sequences, stateful=True)(inp)
+        out = LSTM(lstm_dim, return_sequences=return_sequences, stateful=False)(inp)
         keras_model = keras.Model(inputs=inp, outputs=out)
 
         onnx_model = keras2onnx.convert_keras(keras_model)

tests/test_subclassing.py

@@ -195,7 +195,7 @@ def _tf_where(input_0):
         return c
 
     swm = SimpleWrapperModel(_tf_where)
-    const_in = [np.array([2, 4, 6, 8, 10]).astype(np.int32)]
+    const_in = np.array([2, 4, 6, 8, 10]).astype(np.int32)
     expected = swm(const_in)
     swm._set_inputs(const_in)
     oxml = keras2onnx.convert_keras(swm)

tests/test_utils.py

@@ -211,6 +211,8 @@ def run_onnx_runtime(case_name, onnx_model, data, expected, model_files, rtol=1.
     elif not isinstance(expected, list):
         expected = [expected]
 
+    for n_ in range(len(expected)):
+        np.testing.assert_allclose(expected[n_], actual[n_], rtol=rtol, atol=atol)
     res = all(np.allclose(expected[n_], actual[n_], rtol=rtol, atol=atol) for n_ in range(len(expected)))
 
     if res and temp_model_file not in model_files:  # still keep the failed case files for the diagnosis.