Merge branch 'main' into post-padded-lstm

q-ycong-p · web-flow · commit 232a536417b6 · 2022-10-12T09:00:28.000-07:00
diff --git a/.github/ISSUE_TEMPLATE/bug-performance-issue.md b/.github/ISSUE_TEMPLATE/bug-performance-issue.md
@@ -1,32 +1,38 @@
 ---
 name: Bug/Performance issue
 about: Use this template for reporting a bug or a performance issue.
-
+title: ''
+labels: 'bug'
+assignees: ''
 ---
 
+<!--
 **Dubugging advice**
-[delete this section if it doesn't solve your issue]
 - Add a `--opset` flag with the highest possible opset you can use. Some ops only convert in higher opsets.
 - Try installing the latest tf2onnx from main. Some bug fixes might not have been released to PyPI. Run `pip uninstall tf2onnx` and `pip install git+https://github.com/onnx/tensorflow-onnx`
 - If using a saved model, use the Tensorflow `saved_model_cli` to determine the correct `--tag` and `--signature_def` flags to use. If the signature you need is not listed, use the `--concrete_function` flag to index into the model's defined functions.
-- If your model was made in tf1.x, try running tf2onnx in a venv with tensorflow 1.x installed. tf2.x should be able to read tf1 models, but sometimes there are bugs.
+- If your model was made in tf1.x, try running tf2onnx in a venv with tensorflow 1.x installed. tf2.x should be able to read tf1.x models, but sometimes there are bugs.
+ -->
 
 **Describe the bug**
-A clear and concise description of what the bug is.
+<!-- Please describe a clear and concise description of what the bug is. -->
 
 **Urgency**
-If there are particular important use cases blocked by this or strict project-related timelines, please share more information and dates. If there are no hard deadlines, please specify none.
+<!-- If there are particular important use cases blocked by this or strict project-related timelines, please share more information and dates. If there are no hard deadlines, please specify none. -->
 
 **System information**
-- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
-- Tensorflow Version:
+- OS Platform and Distribution (e.g., Linux Ubuntu 18.04*):
+- TensorFlow Version:
 - Python version:
+- ONNX version (if applicable, e.g. 1.11*):
+- ONNXRuntime version (if applicable, e.g. 1.11*):
+
 
 **To Reproduce**
-Describe steps/code to reproduce the behavior. Please upload/link the model you are trying to convert if possible.
+<!-- Describe steps/code/command to reproduce the behavior. Please upload/link the model you are trying to convert if possible. -->
 
 **Screenshots**
-If applicable, add screenshots to help explain your problem.
+<!-- If applicable, add screenshots to help explain your problem. -->
 
 **Additional context**
-Add any other context about the problem here. If the issue is about a particular model, please share the model details as well to facilitate debugging.
+<!-- Add any other context about the problem here. If the issue is about a particular model, please share the model details as well to facilitate debugging. -->
diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md
@@ -0,0 +1,15 @@
+---
+name: Feature request
+about: Requests for new tf2onnx features
+title: ''
+labels: 'enhancement'
+assignees: ''
+
+---
+
+Before submitting your request, please review past submissions to ensure that it is not a duplicate of a known feature request.
+
+### Describe the feature request
+
+
+### Describe scenario use case
diff --git a/.github/ISSUE_TEMPLATE/operators.md b/.github/ISSUE_TEMPLATE/operators.md
@@ -0,0 +1,24 @@
+---
+name: Missing Operator
+about: Operator that does not currently support in tf2onnx.
+title: ''
+labels: 'unsupported ops'
+assignees: ''
+
+ 
+
+---
+# New Operator
+
+### Describe the operator
+<!-- Why is this operator necessary? What does it accomplish? -->
+
+### Do you know this operator be constructed using existing ONNX operators?
+<!-- If so, why not add it as a function? -->
+
+### Is this operator used by any model currently? Which one?
+
+### Are you willing to contribute it? (Y/N)
+
+### Notes
+<!-- Any additional information -->
diff --git a/.github/ISSUE_TEMPLATE/question.md b/.github/ISSUE_TEMPLATE/question.md
@@ -0,0 +1,23 @@
+---
+name: Question
+about: Ask a question about the tf2onnx.
+title: ''
+labels: 'question'
+assignees: ''
+
+ 
+
+---
+# Ask a Question
+
+### Question
+<!-- Explain your question here. -->
+
+### Further information
+- Is this issue related to a specific model?  
+**Model name**: <!-- *e.g. mnist* -->
+
+**Model opset**: <!-- *e.g. 17* -->
+
+### Notes
+<!-- Any additional information, code snippets. -->
diff --git a/ci_build/azure_pipelines/keras2onnx_unit_test.yml b/ci_build/azure_pipelines/keras2onnx_unit_test.yml
@@ -68,7 +68,7 @@ jobs:
         ONNX_PATH: -i onnx==1.12.0
         KERAS: keras==2.9.0
         TENSORFLOW_PATH: tensorflow==2.9.0
-        INSTALL_ORT: pip install onnxruntime==1.11.0
+        INSTALL_ORT: pip install onnxruntime==1.12.0
         INSTALL_NUMPY: pip install numpy==1.23.0
 
   steps:
diff --git a/setup.py b/setup.py
@@ -82,7 +82,7 @@ def run(self):
     author='ONNX',
     author_email='onnx-technical-discuss@lists.lfaidata.foundation',
     url='https://github.com/onnx/tensorflow-onnx',
-    install_requires=['numpy>=1.14.1', 'onnx>=1.4.1', 'requests', 'six', 'flatbuffers~=1.12'],
+    install_requires=['numpy>=1.14.1', 'onnx>=1.4.1', 'requests', 'six', 'flatbuffers<3.0,>=1.12'],
     classifiers=[
         'Development Status :: 5 - Production/Stable',
         'Intended Audience :: Developers',
diff --git a/tests/keras2onnx_applications/nightly_build/test_acgan.py b/tests/keras2onnx_applications/nightly_build/test_acgan.py
@@ -10,7 +10,7 @@
 from os.path import dirname, abspath
 sys.path.insert(0, os.path.join(dirname(abspath(__file__)), '../../keras2onnx_tests/'))
 from test_utils import run_onnx_runtime
-from distutils.version import StrictVersion
+from packaging.version import Version
 
 Activation = keras.layers.Activation
 BatchNormalization = keras.layers.BatchNormalization
@@ -133,7 +133,7 @@ def tearDown(self):
         for fl in self.model_files:
             os.remove(fl)
 
-    @unittest.skipIf(StrictVersion(onnx.__version__) < StrictVersion("1.5.0"),
+    @unittest.skipIf(Version(onnx.__version__) < Version("1.5.0"),
                      "Not supported before onnx 1.5.0")
     def test_ACGAN(self):
         keras_model = ACGAN().combined
diff --git a/tests/keras2onnx_applications/nightly_build/test_mask_rcnn.py b/tests/keras2onnx_applications/nightly_build/test_mask_rcnn.py
@@ -21,7 +21,7 @@
 keras.backend.clear_session()
 sys.path.insert(0, os.path.join(dirname(abspath(__file__)), '../mask_rcnn/'))
 from mask_rcnn import model
-from distutils.version import StrictVersion
+from packaging.version import Version
 
 working_path = os.path.abspath(os.path.dirname(__file__))
 tmp_path = os.path.join(working_path, 'temp')
@@ -36,7 +36,7 @@ def tearDown(self):
         for fl in self.model_files:
             os.remove(fl)
 
-    @unittest.skipIf(StrictVersion(onnx.__version__.split('-')[0]) < StrictVersion("1.6.0"),
+    @unittest.skipIf(Version(onnx.__version__.split('-')[0]) < Version("1.6.0"),
                      "Mask-rcnn conversion needs contrib op for onnx < 1.6.0.")
     def test_mask_rcnn(self):
         set_converter('CropAndResize', convert_tf_crop_and_resize)
diff --git a/tests/keras2onnx_applications/nightly_build/test_unet.py b/tests/keras2onnx_applications/nightly_build/test_unet.py
@@ -8,7 +8,7 @@
 from os.path import dirname, abspath
 from mock_keras2onnx.proto import keras, is_keras_older_than
 from onnxconverter_common.onnx_ex import get_maximum_opset_supported
-from distutils.version import StrictVersion
+from packaging.version import Version
 
 sys.path.insert(0, os.path.join(dirname(abspath(__file__)), '../../keras2onnx_tests/'))
 from test_utils import run_image
@@ -126,7 +126,7 @@ def test_unet_2(self):
         res = run_image(model, self.model_files, img_path, color_mode="grayscale", target_size=(img_rows, img_cols))
         self.assertTrue(*res)
 
-    @unittest.skipIf(StrictVersion(onnxruntime.__version__.split('-')[0]) < StrictVersion('1.7.0'),
+    @unittest.skipIf(Version(onnxruntime.__version__.split('-')[0]) < Version('1.7.0'),
                      "ConvTranspose stride > 1 is fixed in onnxruntime 1.7.0.")
     def test_unet_3(self):
         # From https://github.com/yu4u/noise2noise/blob/master/model.py
diff --git a/tests/keras2onnx_applications/nightly_build/test_unet_plus_plus.py b/tests/keras2onnx_applications/nightly_build/test_unet_plus_plus.py
@@ -9,7 +9,7 @@
 from mock_keras2onnx.proto import keras, is_keras_older_than
 from keras.applications.vgg16 import VGG16
 from onnxconverter_common.onnx_ex import get_maximum_opset_supported
-from distutils.version import StrictVersion
+from packaging.version import Version
 
 sys.path.insert(0, os.path.join(dirname(abspath(__file__)), '../../keras2onnx_tests/'))
 from test_utils import run_image
@@ -102,7 +102,7 @@ def tearDown(self):
         for fl in self.model_files:
             os.remove(fl)
 
-    @unittest.skipIf(StrictVersion(onnxruntime.__version__.split('-')[0]) < StrictVersion('1.7.0'),
+    @unittest.skipIf(Version(onnxruntime.__version__.split('-')[0]) < Version('1.7.0'),
                      "ConvTranspose stride > 1 is fixed in onnxruntime 1.7.0.")
     def test_unet_plus_plus(self):
         backbone_name = 'vgg16'
diff --git a/tests/keras2onnx_applications/nightly_build/test_yolov3.py b/tests/keras2onnx_applications/nightly_build/test_yolov3.py
@@ -13,7 +13,7 @@
 import urllib.request
 from yolov3 import YOLO, convert_model
 
-from distutils.version import StrictVersion
+from packaging.version import Version
 import mock_keras2onnx
 from test_utils import is_bloburl_access
 
@@ -45,7 +45,7 @@ def post_compute(self, all_boxes, all_scores, indices):
             out_boxes.append(all_boxes[idx_1])
         return [out_boxes, out_scores, out_classes]
 
-    @unittest.skipIf(StrictVersion(onnx.__version__.split('-')[0]) < StrictVersion("1.5.0"),
+    @unittest.skipIf(Version(onnx.__version__.split('-')[0]) < Version("1.5.0"),
                      "NonMaxSuppression op is not supported for onnx < 1.5.0.")
     @unittest.skipIf(not is_bloburl_access(YOLOV3_WEIGHTS_PATH) or not is_bloburl_access(YOLOV3_TINY_WEIGHTS_PATH),
                      "Model blob url can't access.")
diff --git a/tests/keras2onnx_unit_tests/mock_keras2onnx/proto/tfcompat.py b/tests/keras2onnx_unit_tests/mock_keras2onnx/proto/tfcompat.py
@@ -3,9 +3,9 @@
 import os
 import tensorflow as _tf
 
-from distutils.version import StrictVersion
+from packaging.version import Version
 
-is_tf2 = StrictVersion(_tf.__version__.split('-')[0]) >= StrictVersion('2.0.0')
+is_tf2 = Version(_tf.__version__.split('-')[0]) >= Version("2.0.0")
 
 
 def normalize_tensor_shape(tensor_shape):
diff --git a/tests/keras2onnx_unit_tests/test_cgan.py b/tests/keras2onnx_unit_tests/test_cgan.py
@@ -6,7 +6,7 @@
 import numpy as np
 from mock_keras2onnx.proto import keras, is_tf_keras, is_tensorflow_older_than
 from tf2onnx.keras2onnx_api import convert_keras
-from distutils.version import StrictVersion
+from packaging.version import Version
 
 Activation = keras.layers.Activation
 BatchNormalization = keras.layers.BatchNormalization
@@ -116,7 +116,7 @@ def build_discriminator(self):
 
 
 @pytest.mark.skipif(mock_keras2onnx.proto.tfcompat.is_tf2 and is_tf_keras, reason="Tensorflow 1.x only tests.")
-@pytest.mark.skipif(is_tf_keras and StrictVersion(tf.__version__.split('-')[0]) < StrictVersion("1.14.0"),
+@pytest.mark.skipif(is_tf_keras and Version(tf.__version__.split('-')[0]) < Version("1.14.0"),
                     reason="Not supported before tensorflow 1.14.0 for tf_keras")
 @pytest.mark.skipif(mock_keras2onnx.proto.tfcompat.is_tf2 and is_tensorflow_older_than('2.2'),
                     reason="Variable freezing fails to replace ResourceGather op")
diff --git a/tests/keras2onnx_unit_tests/test_layers.py b/tests/keras2onnx_unit_tests/test_layers.py
@@ -2,12 +2,11 @@
 
 import pytest
 import numpy as np
-from tf2onnx.keras2onnx_api import get_maximum_opset_supported
 from mock_keras2onnx.proto.tfcompat import is_tf2, tensorflow as tf
 from mock_keras2onnx.proto import (keras, is_tf_keras,
                                    is_tensorflow_older_than, is_tensorflow_later_than,
                                    is_keras_older_than, is_keras_later_than, python_keras_is_deprecated)
-from test_utils import no_loops_in_tf2, all_recurrents_should_bidirectional
+from test_utils import no_loops_in_tf2, all_recurrents_should_bidirectional, convert_keras_for_test as convert_keras, get_max_opset_supported_for_test as get_maximum_opset_supported
 
 K = keras.backend
 Activation = keras.layers.Activation
@@ -88,9 +87,6 @@
 def _asarray(*a):
     return np.array([a], dtype='f')
 
-########################
-from tf2onnx.keras2onnx_api import convert_keras
-##########################
 
 def test_keras_lambda(runner):
     model = Sequential()
@@ -1143,8 +1139,8 @@ def test_conv1d_padding(conv1_runner):
     test_causal = False
     if is_tf_keras:
         import tensorflow
-        from distutils.version import StrictVersion
-        if StrictVersion(tensorflow.__version__.split('-')[0]) >= StrictVersion('1.12.0'):
+        from packaging.version import Version
+        if Version(tensorflow.__version__.split('-')[0]) >= Version('1.12.0'):
             test_causal = True
     else:
         test_causal = True
diff --git a/tests/keras2onnx_unit_tests/test_subclassing.py b/tests/keras2onnx_unit_tests/test_subclassing.py
@@ -4,7 +4,7 @@
 import mock_keras2onnx
 import numpy as np
 import tensorflow as tf
-from tf2onnx.keras2onnx_api import convert_keras
+from test_utils import convert_keras_for_test as convert_keras
 from mock_keras2onnx.proto import is_tensorflow_older_than
 
 if (not mock_keras2onnx.proto.is_tf_keras) or (not mock_keras2onnx.proto.tfcompat.is_tf2):
diff --git a/tests/keras2onnx_unit_tests/test_utils.py b/tests/keras2onnx_unit_tests/test_utils.py
@@ -8,10 +8,18 @@
 import mock_keras2onnx
 from mock_keras2onnx.proto import keras, is_keras_older_than
 from mock_keras2onnx.proto.tfcompat import is_tf2
+from packaging.version import Version
+from tf2onnx.keras2onnx_api import convert_keras, get_maximum_opset_supported
 import time
 import json
 import urllib
 
+
+# Mapping opset to ONNXRuntime version.
+ORT_OPSET_VERSION = {
+    "1.6.0": 13, "1.7.0": 13, "1.8.0": 14, "1.9.0": 15, "1.10.0": 15, "1.11.0": 16, "1.12.0": 17
+}
+
 working_path = os.path.abspath(os.path.dirname(__file__))
 tmp_path = os.path.join(working_path, 'temp')
 test_level_0 = True
@@ -299,3 +307,30 @@ def is_bloburl_access(url):
         return response.getcode() == 200
     except urllib.error.URLError:
         return False
+
+
+def get_max_opset_supported_by_ort():
+    try:
+        import onnxruntime as ort
+        ort_ver = Version(ort.__version__)
+        ort_ver = Version("{}.{}.0".format(ort_ver.major, ort_ver.minor)).base_version
+
+        if ort_ver in ORT_OPSET_VERSION.keys():
+            return ORT_OPSET_VERSION[ort_ver]
+        else:
+            print("Given onnxruntime version doesn't exist in ORT_OPSET_VERSION: {}".format(ort_ver))
+            return None
+    except ImportError:
+        return None
+
+
+def get_max_opset_supported_for_test():
+    return min(get_max_opset_supported_by_ort(), get_maximum_opset_supported())
+
+
+def convert_keras_for_test(model, name=None, target_opset=None, **kwargs):
+    if target_opset is None:
+        target_opset = get_max_opset_supported_by_ort()
+
+    print("Trying to run test with opset version: {}".format(target_opset))
+    return convert_keras(model=model, name=name, target_opset=target_opset, **kwargs)
diff --git a/tests/test_backend.py b/tests/test_backend.py
@@ -3488,6 +3488,17 @@ def func(x):
             return tf.identity(picks, name=_TFOUTPUT)
         self._run_test_case(func, [_OUTPUT], {_INPUT: x_val})
 
+    @check_opset_min_version(9, "IsNaN")
+    def test_where_ismulinf(self):
+        x_val1 = np.array([np.inf], dtype=np.float32)
+        x_val2 = np.array([0], dtype=np.float32)
+        true_result = np.array([np.inf], dtype=np.float32)
+        def func(x1, x2):
+            mul = tf.multiply(x1, x2)
+            picks = tf.where(x1 < mul, true_result, x2)
+            return tf.identity(picks, name=_TFOUTPUT)
+        self._run_test_case(func, [_OUTPUT], {_INPUT: x_val1, _INPUT1: x_val2})
+
     @check_opset_min_version(9, "Where for strings needs opset 9")
     @skip_tfjs("Technically tf where doesn't support strings and tfjs doesn't like it")
     def test_where_string(self):
@@ -5542,7 +5553,7 @@ def func(x):
         self._run_test_case(func, [_OUTPUT], {_INPUT: x_val0}, rtol=1e-6, atol=1e-4)
         self._run_test_case(func, [_OUTPUT], {_INPUT: x_val}, rtol=1e-6, atol=1e-4)
 
-        x_val = np.random.random(size=[4, 3]).astype(np.float32) * 2048. - 1024
+        x_val = np.random.random(size=[4, 3]).astype(np.float32) * 2048. - 1024.
         x_val[0, 0] = -1024
         x_val[0, 1] = -1023
         x_val[0, 2] = 1024
@@ -5579,7 +5590,7 @@ def func(x):
         self._run_test_case(func, [_OUTPUT], {_INPUT: x_val0}, rtol=1e-6, atol=1e-4)
         self._run_test_case(func, [_OUTPUT], {_INPUT: x_val}, rtol=1e-6, atol=1e-4)
 
-        x_val = np.random.random(size=[4, 3]).astype(np.float32) * 2048. - 1024
+        x_val = np.random.random(size=[4, 3]).astype(np.float32) * 2048. - 1024.
         x_val[0, 0] = -1024
         x_val[0, 1] = -1023
         x_val[0, 2] = 1024
diff --git a/tf2onnx/onnx_opset/controlflow.py b/tf2onnx/onnx_opset/controlflow.py
diff --git a/tf2onnx/tf_loader.py b/tf2onnx/tf_loader.py
