Update ONNX graphsurgeon to v0.3.11

Signed-off-by: Rajeev Rao <rajeevrao@nvidia.com>

Author: rajeevsrao

tools/onnx-graphsurgeon/CHANGELOG.md

@@ -3,9 +3,17 @@
 Dates are in YYYY-MM-DD format.
 
 
+## v0.3.11 (2021-07-14)
+### Changed
+- Updated `fold_constants()` so that it no longer fails if a shape folding pass fails when `error_ok` is `True`.
+
+### Fixed
+- Fixed a bug where `fold_constants()` would fail if a model contained a `Slice` node without a `starts` or `ends` input.
+
+
 ## v0.3.10 (2021-05-20)
 ### Added
--  Added support for folding `Shape -> Slice` patterns even when the entire shape may not be known. 
+-  Added support for folding `Shape -> Slice` patterns even when the entire shape may not be known.
 
 
 ## v0.3.9 (2021-04-20)

tools/onnx-graphsurgeon/docs/conf.py

@@ -15,16 +15,17 @@
 #
 import sys
 import os
+
 ROOT_DIR = os.path.join(os.path.abspath(os.path.dirname(__file__)), os.path.pardir)
 sys.path.insert(0, ROOT_DIR)
 import onnx_graphsurgeon as gs
 
 extensions = [
-    'sphinx.ext.autodoc',
-    'sphinx.ext.intersphinx',
-    'sphinx.ext.autosummary',
-    'sphinx.ext.napoleon',
-    'sphinx.ext.mathjax',
+    "sphinx.ext.autodoc",
+    "sphinx.ext.intersphinx",
+    "sphinx.ext.autosummary",
+    "sphinx.ext.napoleon",
+    "sphinx.ext.mathjax",
 ]
 
 # Want to be able to generate docs with no dependencies installed
@@ -42,50 +43,48 @@
 
 autosummary_generate = True
 
-source_suffix = ['.rst']
+source_suffix = [".rst"]
 
 # The master toctree document.
-master_doc = 'index'
+master_doc = "index"
 
 # General information about the project.
-project = 'ONNX GraphSurgeon'
-copyright = '2020, NVIDIA'
-author = 'NVIDIA'
+project = "ONNX GraphSurgeon"
+copyright = "2020, NVIDIA"
+author = "NVIDIA"
 
 version = gs.__version__
 # The full version, including alpha/beta/rc tags.
 release = version
 
 # Style
-pygments_style = 'colorful'
+pygments_style = "colorful"
 
-html_theme = 'sphinx_rtd_theme'
+html_theme = "sphinx_rtd_theme"
 
 # Use the TRT theme and NVIDIA logo
-html_static_path = ['_static']
+html_static_path = ["_static"]
 
-html_logo = '_static/img/nvlogo_white.png'
+html_logo = "_static/img/nvlogo_white.png"
 
 # Hide source link
 html_show_sourcelink = False
 
 # Output file base name for HTML help builder.
-htmlhelp_basename = 'OnnxGraphSurgeonDoc'
+htmlhelp_basename = "OnnxGraphSurgeonDoc"
 
 # Template files to extend default Sphinx templates.
 # See https://www.sphinx-doc.org/en/master/templating.html for details.
 templates_path = ["_templates"]
 
 # For constructor arguments to show up in Sphinx generated doc
-autoclass_content = 'both'
+autoclass_content = "both"
 
 # Unlimited depth sidebar.
-html_theme_options = {
-    'navigation_depth': -1
-}
+html_theme_options = {"navigation_depth": -1}
 
-html_sidebars = { '**': ['globaltoc.html', 'relations.html', 'sourcelink.html', 'searchbox.html'] }
+html_sidebars = {"**": ["globaltoc.html", "relations.html", "sourcelink.html", "searchbox.html"]}
 
 # Allows us to override the default page width in the Sphinx theme.
 def setup(app):
-    app.add_css_file('style.css')
+    app.add_css_file("style.css")

tools/onnx-graphsurgeon/examples/07_creating_a_model_with_the_layer_api/generate.py

@@ -50,7 +50,9 @@ def mul(self, a, b):
 @gs.Graph.register()
 def gemm(self, a, b, trans_a=False, trans_b=False):
     attrs = {"transA": int(trans_a), "transB": int(trans_b)}
-    return propagate_dtype(self.layer(op="Gemm", inputs=[a, b], outputs=["gemm_out_gs"], attrs=attrs), a.dtype or b.dtype)
+    return propagate_dtype(
+        self.layer(op="Gemm", inputs=[a, b], outputs=["gemm_out_gs"], attrs=attrs), a.dtype or b.dtype
+    )
 
 
 # You can also specify a set of opsets when regsitering a function.

tools/onnx-graphsurgeon/examples/08_replacing_a_subgraph/generate.py

@@ -23,10 +23,12 @@
 def min(self, *args):
     return self.layer(op="Min", inputs=args, outputs=["min_out"])[0]
 
+
 @gs.Graph.register()
 def max(self, *args):
     return self.layer(op="Max", inputs=args, outputs=["max_out"])[0]
 
+
 @gs.Graph.register()
 def identity(self, inp):
     return self.layer(op="Identity", inputs=[inp], outputs=["identity_out"])[0]
@@ -44,7 +46,9 @@ def identity(self, inp):
 # Add identity nodes to make the graph structure a bit more interesting
 inp = graph.identity(graph.inputs[0])
 max_out = graph.max(graph.min(inp, MAX_VAL), MIN_VAL)
-graph.outputs = [graph.identity(max_out), ]
+graph.outputs = [
+    graph.identity(max_out),
+]
 
 # Graph outputs must include dtype information
 graph.outputs[0].to_variable(dtype=np.float32, shape=(4, 4))

tools/onnx-graphsurgeon/examples/09_shape_operations_with_the_layer_api/generate.py

@@ -29,7 +29,9 @@ def shape(self, a):
 
 @gs.Graph.register()
 def reduce_prod(self, a, axes, keepdims=True):
-    return self.layer(op="ReduceProd", inputs=[a], attrs={"axes": axes, "keepdims": int(keepdims)}, outputs=["reduce_prod_out_gs"])[0]
+    return self.layer(
+        op="ReduceProd", inputs=[a], attrs={"axes": axes, "keepdims": int(keepdims)}, outputs=["reduce_prod_out_gs"]
+    )[0]
 
 
 @gs.Graph.register()
@@ -69,8 +71,8 @@ def concat(self, inputs, axis=0):
 partially_flattened = graph.reshape(graph.inputs[0], new_shape)
 
 # Finally, set up the outputs and export.
-flattened.name = "flattened" # Rename output tensor to make it easy to find.
-flattened.dtype = np.float32 # NOTE: We must include dtype information for graph outputs
+flattened.name = "flattened"  # Rename output tensor to make it easy to find.
+flattened.dtype = np.float32  # NOTE: We must include dtype information for graph outputs
 partially_flattened.name = "partially_flattened"
 partially_flattened.dtype = np.float32
 

tools/onnx-graphsurgeon/onnx_graphsurgeon/__init__.py

@@ -5,4 +5,4 @@
 from onnx_graphsurgeon.ir.tensor import Constant, Tensor, Variable
 from onnx_graphsurgeon.util.exception import OnnxGraphSurgeonException
 
-__version__ = "0.3.10"
+__version__ = "0.3.11"

tools/onnx-graphsurgeon/onnx_graphsurgeon/exporters/base_exporter.py

@@ -16,6 +16,7 @@
 
 from onnx_graphsurgeon.ir.graph import Graph
 
+
 class BaseExporter(object):
     @staticmethod
     def export_graph(graph: Graph):

tools/onnx-graphsurgeon/onnx_graphsurgeon/exporters/onnx_exporter.py

@@ -42,23 +42,27 @@ def export_tensor_proto(tensor: Constant) -> onnx.TensorProto:
         onnx_tensor.name = tensor.name
         return onnx_tensor
 
-
     @staticmethod
     def export_value_info_proto(tensor: Variable, do_type_check: bool) -> onnx.ValueInfoProto:
         if do_type_check and tensor.dtype is None:
-            G_LOGGER.critical("Graph input and output tensors must include dtype information. Please set the dtype attribute for: {:}".format(tensor))
+            G_LOGGER.critical(
+                "Graph input and output tensors must include dtype information. Please set the dtype attribute for: {:}".format(
+                    tensor
+                )
+            )
 
         if tensor.dtype is not None:
             onnx_tensor = onnx.helper.make_tensor_value_info(tensor.name, dtype_to_onnx(tensor.dtype), tensor.shape)
         else:
             onnx_tensor = onnx.helper.make_empty_tensor_value_info(tensor.name)
         return onnx_tensor
 
-
     @staticmethod
     def export_node(node: Node, do_type_check: bool) -> onnx.NodeProto:
         # Cannot pass in attrs directly as make_node will change the order
-        onnx_node = onnx.helper.make_node(node.op, inputs=[t.name for t in node.inputs], outputs=[t.name for t in node.outputs], name=node.name)
+        onnx_node = onnx.helper.make_node(
+            node.op, inputs=[t.name for t in node.inputs], outputs=[t.name for t in node.outputs], name=node.name
+        )
         # Convert Tensors and Graphs to TensorProtos and GraphProtos respectively
         for key, val in node.attrs.items():
             if isinstance(val, Tensor):
@@ -68,7 +72,6 @@ def export_node(node: Node, do_type_check: bool) -> onnx.NodeProto:
             onnx_node.attribute.extend([onnx.helper.make_attribute(key, val)])
         return onnx_node
 
-
     @staticmethod
     def export_graph(graph: Graph, do_type_check=True) -> onnx.GraphProto:
         """
@@ -83,7 +86,9 @@ def export_graph(graph: Graph, do_type_check=True) -> onnx.GraphProto:
         inputs = [OnnxExporter.export_value_info_proto(inp, do_type_check) for inp in graph.inputs]
         outputs = [OnnxExporter.export_value_info_proto(out, do_type_check) for out in graph.outputs]
         tensor_map = graph.tensors()
-        initializer = [OnnxExporter.export_tensor_proto(tensor) for tensor in tensor_map.values() if isinstance(tensor, Constant)]
+        initializer = [
+            OnnxExporter.export_tensor_proto(tensor) for tensor in tensor_map.values() if isinstance(tensor, Constant)
+        ]
 
         # Remove inputs and outputs to export ValueInfoProtos
         for tensor in graph.inputs + graph.outputs:
@@ -93,9 +98,22 @@ def export_graph(graph: Graph, do_type_check=True) -> onnx.GraphProto:
         # Omit tensors from value_info if we don't know their shape/dtype
         def has_value_info(tensor):
             return isinstance(tensor, Variable) and (tensor.dtype is not None or tensor.shape is not None)
-        value_info = [OnnxExporter.export_value_info_proto(tensor, do_type_check) for tensor in tensor_map.values() if has_value_info(tensor)]
 
-        return onnx.helper.make_graph(nodes=nodes, name=graph.name, inputs=inputs, outputs=outputs, initializer=initializer, doc_string=graph.doc_string, value_info=value_info)
+        value_info = [
+            OnnxExporter.export_value_info_proto(tensor, do_type_check)
+            for tensor in tensor_map.values()
+            if has_value_info(tensor)
+        ]
+
+        return onnx.helper.make_graph(
+            nodes=nodes,
+            name=graph.name,
+            inputs=inputs,
+            outputs=outputs,
+            initializer=initializer,
+            doc_string=graph.doc_string,
+            value_info=value_info,
+        )
 
 
 def export_onnx(graph: Graph, do_type_check=True, **kwargs) -> "onnx.ModelProto":

tools/onnx-graphsurgeon/onnx_graphsurgeon/importers/base_importer.py

@@ -16,6 +16,7 @@
 
 from onnx_graphsurgeon.ir.graph import Graph
 
+
 class BaseImporter(object):
     @staticmethod
     def import_graph(graph) -> Graph: