[ONNX] Erf op support (#2763)

* [ONNX] Erf op support

* [ONNX] Missing CMakeLists entry for the Erf op

* [ONNX] model_erf unit test excluded from GPU

* Update quoting style to fix errors raised by updated version of flake8.

python/ngraph/runtime.py

@@ -43,7 +43,7 @@ class Runtime:
         self.backend = Backend.create(backend_name)
 
     def __repr__(self):  # type: () -> str
-        return '<Runtime: Backend=\'{}\'>'.format(self.backend_name)
+        return "<Runtime: Backend='{}'>".format(self.backend_name)
 
     def computation(self, node_or_function, *inputs):
         # type: (Union[Node, Function], *Node) -> 'Computation'
@@ -120,7 +120,7 @@ class Computation(object):
         # type: (np.ndarray, Tensor) -> None
         tensor_view_dtype = get_dtype(tensor_view.element_type)
         if list(tensor_view.shape) != list(value.shape) and len(value.shape) > 0:
-            raise UserInputError('Provided tensor\'s shape: %s does not match the expected: %s.',
+            raise UserInputError("Provided tensor's shape: %s does not match the expected: %s.",
                                  list(value.shape), list(tensor_view.shape))
         if value.dtype != tensor_view_dtype:
             log.warning(

python/setup.py

@@ -381,7 +381,7 @@ with open(os.path.join(PYNGRAPH_ROOT_DIR, 'requirements.txt')) as req:
 
 setup(
     name='ngraph-core',
-    description='nGraph - Intel\'s graph compiler and runtime for Neural Networks',
+    description="nGraph - Intel's graph compiler and runtime for Neural Networks",
     version=__version__,
     author='Intel Corporation',
     author_email='intelnervana@intel.com',

src/ngraph/frontend/onnx_import/CMakeLists.txt

@@ -81,6 +81,7 @@ add_library(onnx_import STATIC
         op/elu.cpp
         op/elu.hpp
         op/equal.hpp
+        op/erf.hpp
         op/exp.hpp
         op/flatten.cpp
         op/flatten.hpp

src/ngraph/frontend/onnx_import/op/erf.hpp

+//*****************************************************************************
+// Copyright 2017-2019 Intel Corporation
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//*****************************************************************************
+
+#pragma once
+
+#include <memory>
+
+#include "core/node.hpp"
+#include "ngraph/node_vector.hpp"
+#include "ngraph/op/erf.hpp"
+
+namespace ngraph
+{
+    namespace onnx_import
+    {
+        namespace op
+        {
+            namespace set_1
+            {
+                inline NodeVector erf(const Node& node)
+                {
+                    return {std::make_shared<ngraph::op::Erf>(node.get_ng_inputs().at(0))};
+                }
+            } // namespace set_1
+
+        } //namespace op
+
+    } // namespace onnx_import
+
+} // namespace ngraph

src/ngraph/frontend/onnx_import/ops_bridge.cpp

@@ -50,6 +50,7 @@
 #include "op/dropout.hpp"
 #include "op/elu.hpp"
 #include "op/equal.hpp"
+#include "op/erf.hpp"
 #include "op/exp.hpp"
 #include "op/flatten.hpp"
 #include "op/floor.hpp"
@@ -250,6 +251,7 @@ namespace ngraph
             REGISTER_OPERATOR("Dropout", 1, dropout);
             REGISTER_OPERATOR("Elu", 1, elu);
             REGISTER_OPERATOR("Equal", 1, equal);
+            REGISTER_OPERATOR("Erf", 1, erf);
             REGISTER_OPERATOR("Exp", 1, exp);
             REGISTER_OPERATOR("Flatten", 1, flatten);
             REGISTER_OPERATOR("Floor", 1, floor);

src/ngraph/runtime/gpu/unit_test.manifest

@@ -136,3 +136,4 @@ create_tensor_2_output
 # Not implemented
 erf
 zero_sized_erf
+model_erf

test/models/onnx/erf.prototxt

+ir_version: 3
+producer_name: "nGraph ONNX Importer"
+graph {
+  node {
+    input: "x"
+    output: "y"
+    op_type: "Erf"
+  }
+  name: "erf_graph"
+  input {
+    name: "x"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+          dim {
+            dim_value: 2
+          }
+        }
+      }
+    }
+  }
+  output {
+    name: "y"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+          dim {
+            dim_value: 2
+          }
+        }
+      }
+    }
+  }
+}
+opset_import {
+  version: 9
+}

test/onnx_import.in.cpp

@@ -2827,4 +2827,25 @@ NGRAPH_TEST(onnx_${BACKEND_NAME}, model_quant_conv_linear_3d)
         read_binary_file<uint8_t>(file_util::path_join(TEST_FILES, "onnx/qlinearconv3d/y.bin")));
 
     EXPECT_EQ(expected_output.front(), outputs.front());
-}
\ No newline at end of file
+}
+
+NGRAPH_TEST(onnx_${BACKEND_NAME}, model_erf)
+{
+    const auto function =
+        onnx_import::import_onnx_model(file_util::path_join(SERIALIZED_ZOO, "onnx/erf.prototxt"));
+
+    Inputs inputs;
+    inputs.emplace_back(test::NDArray<float, 2>{
+        {-std::numeric_limits<float>::infinity(), std::numeric_limits<float>::infinity()},
+        {-3.141592f, 0.0f},
+        {0.5f, 1.0f}}.get_vector());
+
+    const std::vector<float> expected_outputs = test::NDArray<float, 2>{
+        {-1.0f, 1.0f},
+        {-0.99999112f, 0.0f},
+        {0.52049988f, 0.84270079f}}.get_vector();
+
+    const Outputs outputs{execute(function, inputs, "${BACKEND_NAME}")};
+
+    EXPECT_TRUE(test::all_close_f(expected_outputs, outputs.front()));
+}