Add commit value to onnx file and clean up part of code (#1897)

* add commit value to onnx file, remove expired code and add License in generating version.py

Signed-off-by: Deyu Huang <[email protected]>
Co-authored-by: Guenther Schmuelling <[email protected]>

* change onnx repo master to main

Signed-off-by: Deyu Huang <[email protected]>

* fix comments

Signed-off-by: Deyu Huang <[email protected]>

Co-authored-by: Guenther Schmuelling <[email protected]>

Author: hwangdeyu

setup.py

@@ -37,8 +37,9 @@ def finalize_options(self):
         pass
 
     def run(self):
+        alv2_license = '# SPDX-License-Identifier: Apache-2.0\n\n'
         with open(os.path.join(SRC_DIR, 'version.py'), 'w') as f:
-            f.write(dedent('''
+            f.write(alv2_license + dedent('''
             version = '{version}'
             git_version = '{git_version}'
             '''.format(**dict(VersionInfo._asdict()))))

tests/keras2onnx_applications/model_source/densenet_1/densenet_1.py

@@ -8,9 +8,6 @@
 - [Densely Connected Convolutional Networks](https://arxiv.org/pdf/1608.06993.pdf)
 - [The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation](https://arxiv.org/pdf/1611.09326.pdf)
 '''
-from __future__ import print_function
-from __future__ import absolute_import
-from __future__ import division
 
 import warnings
 

tests/keras2onnx_applications/model_source/densenet_1/subpixel.py

@@ -3,8 +3,6 @@
 # From https://github.com/titu1994/DenseNet/blob/master/subpixel.py
 # Modifications Copyright (c) Microsoft.
 
-from __future__ import absolute_import
-
 from mock_keras2onnx.proto import keras
 from keras import backend as K
 from keras.engine import Layer

tests/test_onnx_shape_inference.py

@@ -22,7 +22,7 @@ class ONNXShapeInferenceTests(Tf2OnnxBackendTestBase):
     """
     Test shape inference, it's just a subset of all cases that can be inferred shape.
     For more information, please refer to onnx shape inference test:
-    https://github.com/onnx/onnx/blob/master/onnx/test/shape_inference_test.py
+    https://github.com/onnx/onnx/blob/main/onnx/test/shape_inference_test.py
     """
 
     def _run_test_case(self, graph, feed_dict):

tf2onnx/__init__.py

@@ -6,7 +6,6 @@
            "tfonnx", "shape_inference", "schemas", "tf_utils", "tf_loader", "convert"]
 
 import onnx
-from .version import version as __version__
+from .version import git_version, version as __version__
 from . import verbose_logging as logging
 from tf2onnx import tfonnx, utils, graph, graph_builder, graph_matcher, shape_inference, schemas, convert  # pylint: disable=wrong-import-order
-#from tf2onnx import tf_utils, tf_loader

tf2onnx/graph.py

@@ -12,7 +12,7 @@
 import numpy as np
 
 from onnx import helper, numpy_helper, shape_inference, AttributeProto, TensorProto
-from tf2onnx import utils, __version__
+from tf2onnx import utils, __version__, git_version
 from tf2onnx.utils import make_name, port_name, find_opset
 from tf2onnx import optimizer
 from tf2onnx.schemas import get_schema, infer_onnx_shape_dtype
@@ -1189,9 +1189,10 @@ def make_model(self, graph_doc, optimize=False, graph_name="tf2onnx", external_t
         graph = self.make_graph(graph_doc, graph_name, external_tensor_storage)
 
         if "producer_name" not in kwargs:
-            kwargs = {"producer_name": "tf2onnx",
-                      "producer_version": __version__}
-
+            kwargs = {
+                "producer_name": "tf2onnx",
+                "producer_version": __version__ + " " + git_version[:6]
+            }
         if "opset_imports" not in kwargs:
             opsets = [helper.make_opsetid(constants.ONNX_DOMAIN, self._opset)]
             opsets.append(constants.AI_ONNX_ML_OPSET)
@@ -1605,7 +1606,7 @@ def safe_remove_nodes(self, to_delete):
                 self.remove_node(n.name)
 
     def is_safe_to_remove_nodes(self, to_delete, outputs_to_ignore=None):
-        """Returns true if the outputs of all the nodes in to_delete have no third-party nodes consuming them"""
+        """Returns true if the outputs of all the nodes in to_delete have no third-party nodes consuming them."""
         delete_set = set(to_delete)
         outputs_to_ignore_set = set(outputs_to_ignore or [])
         for n in delete_set:
@@ -1660,7 +1661,7 @@ def optimize_model_proto(onnx_model_proto, catch_errors=True, return_graph=False
 
     @staticmethod
     def get_onnx_model_properties(onnx_model_proto):
-        """Get ModelProto properties"""
+        """Get ModelProto properties."""
         kwargs = {}
         if onnx_model_proto.HasField('ir_version'):
             kwargs["ir_version"] = onnx_model_proto.ir_version

tf2onnx/optimizer/const_fold_optimizer.py

@@ -150,7 +150,7 @@ def _fold_unsqueeze(node, graph):
         dims_out = len(shape_in) + len(axes)
         axes = [i if i >= 0 else i + dims_out for i in axes]
         # calculate the shape of output accroding to onnx Unsqueeze's spec
-        # https://github.com/onnx/onnx/blob/master/docs/Operators.md#Unsqueeze
+        # https://github.com/onnx/onnx/blob/main/docs/Operators.md#Unsqueeze
         shape_in = iter(shape_in)
         shape_out = [None] * dims_out
         for ind in axes:

tf2onnx/optimizer/loop_optimizer.py

@@ -16,7 +16,7 @@ class LoopOptimizer(GraphOptimizerBase):
     """Loop Optimizer."""
 
     # a lot of terms used here come from loop's onnx spec
-    # https://github.com/onnx/onnx/blob/master/docs/Operators.md#Loop
+    # https://github.com/onnx/onnx/blob/main/docs/Operators.md#Loop
     def __init__(self):  # pylint: disable=useless-super-delegation
         super(LoopOptimizer, self).__init__()
 

tf2onnx/version.py

@@ -1,4 +1,5 @@
 # SPDX-License-Identifier: Apache-2.0
 
+
 version = '1.10.0'
-git_version = '219e00c073f6e73fba7335630dcf1f96cc82c983'
+git_version = '0065af6273eac0e911a0e75eab1cdf6be1c9ac7b'

tools/aggregate-patterns.py

@@ -133,7 +133,7 @@ def get_args():
     parser.add_argument("--fold", action="store_true", help="fold smaller sub graphs")
     parser.add_argument("--max-nodes", type=int, default=6, help="number of max nodes in a pattern")
     parser.add_argument("--min-frequency", type=int, default=2, help="show patterns number seen at least this")
-    parser.add_argument("infile", nargs="*", help='event files')
+    parser.add_argument("--infile", nargs="*", help="event files")
     args = parser.parse_args()
     return args