[Py] Added GRN operator to Python API. (#3365)

* [Py] Added grn operator to Python API.

* [Py] Changed order of included files.

* [Py] Changed docstring.

* style

doc/sphinx/source/python_api/_autosummary/ngraph.ops.rst

@@ -42,6 +42,7 @@ ngraph.ops
       get_output_element
       greater
       greater_eq
+      grn
       less
       less_eq
       log

python/ngraph/__init__.py

@@ -55,6 +55,7 @@ from ngraph.ops import gemm
 from ngraph.ops import get_output_element
 from ngraph.ops import greater
 from ngraph.ops import greater_eq
+from ngraph.ops import grn
 from ngraph.ops import less
 from ngraph.ops import less_eq
 from ngraph.ops import log

python/ngraph/impl/op/__init__.py

@@ -79,6 +79,7 @@ from _pyngraph.op import Gemm
 from _pyngraph.op import GetOutputElement
 from _pyngraph.op import Greater
 from _pyngraph.op import GreaterEq
+from _pyngraph.op import GRN
 from _pyngraph.op import Less
 from _pyngraph.op import LessEq
 from _pyngraph.op import Log

python/ngraph/ops.py

@@ -23,7 +23,7 @@ from ngraph.impl import AxisSet, AxisVector, Coordinate, CoordinateDiff, Functio
 from ngraph.impl.op import Abs, Acos, Add, And, Asin, ArgMax, ArgMin, Atan, AvgPool, \
     BatchNormTraining, BatchNormInference, Broadcast, Ceiling, Clamp, Concat, Constant, Convert, \
     Convolution, ConvolutionBackpropData, Cos, Cosh, Divide, Dot, Elu, Equal, Exp, Floor, \
-    Gelu, Gemm, GetOutputElement, Greater, GreaterEq, Less, LessEq, Log, LRN, Max, Maximum, \
+    Gelu, Gemm, GetOutputElement, Greater, GreaterEq, GRN, Less, LessEq, Log, LRN, Max, Maximum, \
     MaxPool, Min, Minimum, Multiply, Negative, Not, NotEqual, OneHot, Or, Pad, Parameter, Product, \
     Power, Relu, ReplaceSlice, Reshape, Reverse, Select, Sign, Sin, Sinh, Slice, Softmax, \
     Sqrt, Subtract, Sum, Tan, Tanh, TopK
@@ -78,6 +78,22 @@ def elu(data, alpha, name=None):  # type: (NodeInput, NodeInput, str) -> Node
     return Elu(as_node(data), as_node(alpha))
 
 
+@nameable_op
+def grn(data, bias, name=None):  # type: (Node, float, str) -> Node
+    r"""Perform Global Response Normalization with L2 norm (across channels only).
+
+    Computes GRN operation on channels for input tensor:
+
+    .. math:: output_i = \dfrac{input_i}{\sqrt{\sum_{i}^{C} input_i}}
+
+    :param data: The node with data tensor.
+    :param bias: The bias added to the variance. Scalar value.
+    :param name: Optional output node name.
+    :return: The new node performing a GRN operation on tensor's channels.
+    """
+    return GRN(data, bias)
+
+
 # Unary ops
 @unary_op
 def absolute(node, name=None):  # type: (NodeInput, str) -> Node

python/pyngraph/ops/fused/grn.cpp

+//*****************************************************************************
+// 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.
+//*****************************************************************************
+
+#include <pybind11/pybind11.h>
+#include <pybind11/stl.h>
+
+#include "ngraph/op/fused/grn.hpp"
+#include "pyngraph/ops/fused/grn.hpp"
+
+namespace py = pybind11;
+
+void regclass_pyngraph_op_GRN(py::module m)
+{
+    py::class_<ngraph::op::GRN, std::shared_ptr<ngraph::op::GRN>, ngraph::op::Op> grn(m, "GRN");
+    grn.doc() = "ngraph.impl.op.GRN wraps ngraph::op::GRN";
+    grn.def(py::init<const std::shared_ptr<ngraph::Node>&, float&>());
+}

python/pyngraph/ops/fused/grn.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 <pybind11/pybind11.h>
+
+namespace py = pybind11;
+
+void regclass_pyngraph_op_GRN(py::module m);

python/pyngraph/ops/regmodule_pyngraph_op.cpp

@@ -59,6 +59,7 @@ void regmodule_pyngraph_op(py::module m_op)
     regclass_pyngraph_op_GetOutputElement(m_op);
     regclass_pyngraph_op_Greater(m_op);
     regclass_pyngraph_op_GreaterEq(m_op);
+    regclass_pyngraph_op_GRN(m_op);
     regclass_pyngraph_op_Less(m_op);
     regclass_pyngraph_op_LessEq(m_op);
     regclass_pyngraph_op_Log(m_op);

python/pyngraph/ops/regmodule_pyngraph_op.hpp

@@ -46,6 +46,7 @@
 #include "pyngraph/ops/fused/elu.hpp"
 #include "pyngraph/ops/fused/gelu.hpp"
 #include "pyngraph/ops/fused/gemm.hpp"
+#include "pyngraph/ops/fused/grn.hpp"
 #include "pyngraph/ops/get_output_element.hpp"
 #include "pyngraph/ops/greater.hpp"
 #include "pyngraph/ops/greater_eq.hpp"

python/setup.py

@@ -188,6 +188,7 @@ sources = [
     'pyngraph/ops/fused/gemm.cpp',
     'pyngraph/ops/greater.cpp',
     'pyngraph/ops/greater_eq.cpp',
+    'pyngraph/ops/fused/grn.cpp',
     'pyngraph/ops/less.cpp',
     'pyngraph/ops/less_eq.cpp',
     'pyngraph/ops/log.cpp',

python/test/ngraph/test_ops_fused.py

@@ -170,3 +170,26 @@ def test_clamp_operator_with_array():
     expected = np.clip(data_value, min_value, max_value)
 
     assert np.allclose(result, expected)
+
+
+def test_grn_operator():
+    runtime = get_runtime()
+
+    data_value = np.arange(start=1.0, stop=25.0, dtype=np.float32).reshape(1, 2, 3, 4)
+    bias = np.float32(1e-6)
+
+    data_shape = [1, 2, 3, 4]
+
+    parameter_data = ng.parameter(data_shape, name='Data', dtype=np.float32)
+
+    model = ng.grn(parameter_data, bias)
+    computation = runtime.computation(model, parameter_data)
+
+    result = computation(data_value)
+    expected = np.array([[[[0.0766965, 0.14142136, 0.19611613, 0.24253564],
+                           [0.28216633, 0.31622776, 0.34570536, 0.37139067],
+                           [0.39391932, 0.41380295, 0.4314555, 0.4472136]],
+                          [[0.9970545, 0.98994946, 0.9805807, 0.97014254],
+                           [0.9593655, 0.9486833, 0.9383431, 0.9284767],
+                           [0.91914505, 0.9103665, 0.9021342, 0.8944272]]]], dtype=np.float32)
+    assert np.allclose(result, expected)