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Commit 6abeca2b authored by Scott Cyphers's avatar Scott Cyphers
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Merge branch 's-barannikov/new_op_form/l-o_ops' into cyphers/s-barannikov

parents dfa5d4d1 3396681c
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Showing with 202 additions and 97 deletions
src/ngraph/op/less.cpp
View file @ 6abeca2b
......@@ -19,10 +19,10 @@
using namespace std;
using namespace ngraph;
op::Less::Less(const shared_ptr<Node>& arg0,
const shared_ptr<Node>& arg1,
const AutoBroadcastSpec& autob)
: BinaryElementwiseComparison("Less", arg0, arg1, autob)
const string op::Less::type_name{"Less"};
op::Less::Less(const Output<Node>& arg0, const Output<Node>& arg1, const AutoBroadcastSpec& autob)
: BinaryElementwiseComparison(arg0, arg1, autob)
{
constructor_validate_and_infer_types();
}
......
src/ngraph/op/less.hpp
View file @ 6abeca2b
......@@ -26,13 +26,18 @@ namespace ngraph
class Less : public util::BinaryElementwiseComparison
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a less-than operation.
Less() = default;
/// \brief Constructs a less-than operation.
///
/// \param arg0 Node that produces the first input tensor.
/// \param arg1 Node that produces the second input tensor.
/// \param autob Auto broadcast specification
Less(const std::shared_ptr<Node>& arg0,
const std::shared_ptr<Node>& arg1,
Less(const Output<Node>& arg0,
const Output<Node>& arg1,
const AutoBroadcastSpec& autob = AutoBroadcastSpec());
virtual std::shared_ptr<Node>
......
src/ngraph/op/less_eq.cpp
View file @ 6abeca2b
......@@ -19,10 +19,12 @@
using namespace std;
using namespace ngraph;
op::LessEq::LessEq(const shared_ptr<Node>& arg0,
const shared_ptr<Node>& arg1,
const string op::LessEq::type_name{"LessEq"};
op::LessEq::LessEq(const Output<Node>& arg0,
const Output<Node>& arg1,
const AutoBroadcastSpec& autob)
: BinaryElementwiseComparison("LessEq", arg0, arg1, autob)
: BinaryElementwiseComparison(arg0, arg1, autob)
{
constructor_validate_and_infer_types();
}
......
src/ngraph/op/less_eq.hpp
View file @ 6abeca2b
......@@ -26,13 +26,18 @@ namespace ngraph
class LessEq : public util::BinaryElementwiseComparison
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a less-than-or-equal operation.
LessEq() = default;
/// \brief Constructs a less-than-or-equal operation.
///
/// \param arg0 Node that produces the first input tensor.
/// \param arg1 Node that produces the second input tensor.
/// \param autob Auto broadcast specification
LessEq(const std::shared_ptr<Node>& arg0,
const std::shared_ptr<Node>& arg1,
LessEq(const Output<Node>& arg0,
const Output<Node>& arg1,
const AutoBroadcastSpec& autob = AutoBroadcastSpec());
virtual std::shared_ptr<Node>
......
src/ngraph/op/log.cpp
View file @ 6abeca2b
......@@ -20,8 +20,10 @@
using namespace std;
using namespace ngraph;
op::Log::Log(const shared_ptr<Node>& arg)
: UnaryElementwiseArithmetic("Log", arg)
const string op::Log::type_name{"Log"};
op::Log::Log(const Output<Node>& arg)
: UnaryElementwiseArithmetic(arg)
{
constructor_validate_and_infer_types();
}
......
src/ngraph/op/log.hpp
View file @ 6abeca2b
......@@ -26,10 +26,15 @@ namespace ngraph
class Log : public util::UnaryElementwiseArithmetic
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a natural log operation.
Log() = default;
/// \brief Constructs a natural log operation.
///
/// \param arg Node that produces the input tensor.
Log(const std::shared_ptr<Node>& arg);
Log(const Output<Node>& arg);
virtual std::shared_ptr<Node>
copy_with_new_args(const NodeVector& new_args) const override;
......
src/ngraph/op/lrn.cpp
View file @ 6abeca2b
......@@ -20,12 +20,14 @@
using namespace std;
using namespace ngraph;
op::LRN::LRN(const std::shared_ptr<Node>& arg, double alpha, double beta, double bias, size_t nsize)
: UnaryElementwiseArithmetic("LRN", arg)
const string op::LRN::type_name{"LRN"};
op::LRN::LRN(const Output<Node>& arg, double alpha, double beta, double bias, size_t size)
: UnaryElementwiseArithmetic(arg)
, m_alpha(alpha)
, m_beta(beta)
, m_bias(bias)
, m_size(nsize)
, m_size(size)
{
constructor_validate_and_infer_types();
}
......
src/ngraph/op/lrn.hpp
View file @ 6abeca2b
......@@ -38,23 +38,29 @@ namespace ngraph
class LRN : public util::UnaryElementwiseArithmetic
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a LRN operation.
LRN() = default;
/// \brief Constructs a LRN operation.
///
/// \param arg Node that produces the input tensor.
LRN(const std::shared_ptr<Node>& arg,
double alpha,
double beta,
double bias,
size_t size);
LRN(const Output<Node>& arg, double alpha, double beta, double bias, size_t size);
virtual std::shared_ptr<Node>
copy_with_new_args(const NodeVector& new_args) const override;
void validate_and_infer_types() override;
double get_alpha() const { return m_alpha; }
void set_alpha(double alpha) { m_alpha = alpha; }
double get_beta() const { return m_beta; }
void set_beta(double beta) { m_beta = beta; }
double get_bias() const { return m_bias; }
void set_bias(double bias) { m_bias = bias; }
size_t get_nsize() const { return m_size; }
void set_nsize(size_t size) { m_size = size; }
protected:
virtual void generate_adjoints(autodiff::Adjoints& adjoints,
const NodeVector& deltas) override;
......
src/ngraph/op/max.cpp
View file @ 6abeca2b
......@@ -22,10 +22,6 @@ using namespace ngraph;
const string op::Max::type_name{"Max"};
op::Max::Max()
{
}
op::Max::Max(const Output<Node>& arg, const AxisSet& reduction_axes)
: ArithmeticReduction(arg, reduction_axes)
{
......
src/ngraph/op/max.hpp
View file @ 6abeca2b
......@@ -30,7 +30,7 @@ namespace ngraph
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a "max" reduction operation.
Max();
Max() = default;
/// \brief Constructs a max-reduction operation.
///
/// \param arg The tensor to be reduced.
......
src/ngraph/op/max_pool.cpp
View file @ 6abeca2b
......@@ -25,14 +25,16 @@
using namespace std;
using namespace ngraph;
op::MaxPool::MaxPool(const shared_ptr<Node>& arg,
const string op::MaxPool::type_name{"MaxPool"};
op::MaxPool::MaxPool(const Output<Node>& arg,
const Shape& window_shape,
const Strides& window_movement_strides,
const Shape& padding_below,
const Shape& padding_above,
const PadType& pad_type,
bool ceil_mode)
: Op("MaxPool", check_single_output_args({arg}))
: Op({arg})
, m_window_shape(window_shape)
, m_window_movement_strides(window_movement_strides)
, m_padding_below(padding_below)
......@@ -43,7 +45,7 @@ op::MaxPool::MaxPool(const shared_ptr<Node>& arg,
constructor_validate_and_infer_types();
}
op::MaxPool::MaxPool(const shared_ptr<Node>& arg,
op::MaxPool::MaxPool(const Output<Node>& arg,
const Shape& window_shape,
const Strides& window_movement_strides,
const Shape& padding_below,
......@@ -54,7 +56,7 @@ op::MaxPool::MaxPool(const shared_ptr<Node>& arg,
{
}
op::MaxPool::MaxPool(const shared_ptr<Node>& arg,
op::MaxPool::MaxPool(const Output<Node>& arg,
const Shape& window_shape,
const Strides& window_movement_strides,
const Shape& padding_below,
......@@ -121,14 +123,14 @@ void op::MaxPool::validate_and_infer_types()
m_ceil_mode));
}
op::MaxPool::MaxPool(const shared_ptr<Node>& arg,
op::MaxPool::MaxPool(const Output<Node>& arg,
const Shape& window_shape,
const Strides& window_movement_strides)
: MaxPool(arg, window_shape, window_movement_strides, Shape(), Shape())
{
}
op::MaxPool::MaxPool(const shared_ptr<Node>& arg, const Shape& window_shape)
op::MaxPool::MaxPool(const Output<Node>& arg, const Shape& window_shape)
: MaxPool(arg, window_shape, Strides(), Shape(), Shape())
{
}
......@@ -145,13 +147,15 @@ shared_ptr<Node> op::MaxPool::copy_with_new_args(const NodeVector& new_args) con
m_ceil_mode);
}
op::MaxPoolBackprop::MaxPoolBackprop(const shared_ptr<Node>& arg_forward,
const shared_ptr<Node>& delta,
const string op::MaxPoolBackprop::type_name{"MaxPoolBackprop"};
op::MaxPoolBackprop::MaxPoolBackprop(const Output<Node>& arg_forward,
const Output<Node>& delta,
const Shape& window_shape,
const Strides& window_movement_strides,
const Shape& padding_below,
const Shape& padding_above)
: Op("MaxPoolBackprop", check_single_output_args({arg_forward, delta}))
: Op({arg_forward, delta})
, m_window_shape(window_shape)
, m_window_movement_strides(window_movement_strides)
, m_padding_below(padding_below)
......@@ -160,14 +164,14 @@ op::MaxPoolBackprop::MaxPoolBackprop(const shared_ptr<Node>& arg_forward,
constructor_validate_and_infer_types();
}
op::MaxPoolBackprop::MaxPoolBackprop(const shared_ptr<Node>& arg_forward,
const shared_ptr<Node>& delta,
const shared_ptr<Node>& result_forward,
op::MaxPoolBackprop::MaxPoolBackprop(const Output<Node>& arg_forward,
const Output<Node>& delta,
const Output<Node>& result_forward,
const Shape& window_shape,
const Strides& window_movement_strides,
const Shape& padding_below,
const Shape& padding_above)
: Op("MaxPoolBackprop", check_single_output_args({arg_forward, delta, result_forward}))
: Op({arg_forward, delta, result_forward})
, m_window_shape(window_shape)
, m_window_movement_strides(window_movement_strides)
, m_padding_below(padding_below)
......
src/ngraph/op/max_pool.hpp
View file @ 6abeca2b
......@@ -28,6 +28,13 @@ namespace ngraph
class MaxPool : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a batched max pooling operation.
MaxPool() = default;
/// \brief Constructs a batched max pooling operation.
///
/// \param arg The node producing the input data batch tensor.
......@@ -37,7 +44,7 @@ namespace ngraph
/// \param padding_above The above-padding shape.
/// \param pad_type The pad type for automatically computing padding sizes
/// \param ceil_mode Whether to use ceiling while computing output shape.
MaxPool(const std::shared_ptr<Node>& arg,
MaxPool(const Output<Node>& arg,
const Shape& window_shape,
const Strides& window_movement_strides,
const Shape& padding_below,
......@@ -53,7 +60,7 @@ namespace ngraph
/// \param padding_below The below-padding shape.
/// \param padding_above The above-padding shape.
/// \param pad_type The pad type for automatically computing padding sizes
MaxPool(const std::shared_ptr<Node>& arg,
MaxPool(const Output<Node>& arg,
const Shape& window_shape,
const Strides& window_movement_strides,
const Shape& padding_below,
......@@ -67,7 +74,7 @@ namespace ngraph
/// \param window_movement_strides The window movement strides.
/// \param padding_below The below-padding shape.
/// \param padding_above The above-padding shape.
MaxPool(const std::shared_ptr<Node>& arg,
MaxPool(const Output<Node>& arg,
const Shape& window_shape,
const Strides& window_movement_strides,
const Shape& padding_below,
......@@ -80,7 +87,7 @@ namespace ngraph
/// \param arg The node producing the input data batch tensor.
/// \param window_shape The window shape.
/// \param window_movement_strides The window movement strides.
MaxPool(const std::shared_ptr<Node>& arg,
MaxPool(const Output<Node>& arg,
const Shape& window_shape,
const Strides& window_movement_strides);
......@@ -88,23 +95,32 @@ namespace ngraph
///
/// \param arg The node producing the input data batch tensor.
/// \param window_shape The window shape.
MaxPool(const std::shared_ptr<Node>& arg, const Shape& window_shape);
MaxPool(const Output<Node>& arg, const Shape& window_shape);
virtual std::shared_ptr<Node>
copy_with_new_args(const NodeVector& new_args) const override;
/// \return The window shape.
const Shape& get_window_shape() const { return m_window_shape; }
void set_window_shape(const Shape& window_shape) { m_window_shape = window_shape; }
/// \return The window movement strides.
const Strides& get_window_movement_strides() const { return m_window_movement_strides; }
void set_window_movement_strides(const Strides& window_movement_strides)
{
m_window_movement_strides = window_movement_strides;
}
/// \return The below-padding shape.
const Shape& get_padding_below() const { return m_padding_below; }
void set_padding_below(const Shape& padding_below) { m_padding_below = padding_below; }
/// \return The above-padding shape.
const Shape& get_padding_above() const { return m_padding_above; }
void set_adding_above(const Shape& padding_above) { m_padding_above = padding_above; }
/// \return The pad type for pooling.
const PadType& get_pad_type() const { return m_pad_type; }
void set_pad_type(const PadType& pad_type) { m_pad_type = pad_type; }
/// \return The ceiling mode being used for output shape computations
bool get_ceil_mode() const { return m_ceil_mode; }
void set_ceil_mode(bool ceil_mode) { m_ceil_mode = ceil_mode; }
/// \return The default value for MaxPool.
virtual std::shared_ptr<Node> get_default_value() const override
{
......@@ -126,16 +142,22 @@ namespace ngraph
class MaxPoolBackprop : public Op
{
public:
MaxPoolBackprop(const std::shared_ptr<Node>& arg_forward,
const std::shared_ptr<Node>& delta,
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
MaxPoolBackprop() = default;
MaxPoolBackprop(const Output<Node>& arg_forward,
const Output<Node>& delta,
const Shape& window_shape,
const Strides& window_movement_strides,
const Shape& padding_below,
const Shape& padding_above);
MaxPoolBackprop(const std::shared_ptr<Node>& arg_forward,
const std::shared_ptr<Node>& delta,
const std::shared_ptr<Node>& result_forward,
MaxPoolBackprop(const Output<Node>& arg_forward,
const Output<Node>& delta,
const Output<Node>& result_forward,
const Shape& window_shape,
const Strides& window_movement_strides,
const Shape& padding_below,
......@@ -147,9 +169,17 @@ namespace ngraph
void validate_and_infer_types() override;
const Shape& get_window_shape() const { return m_window_shape; }
void set_window_shape(const Shape& window_shape) { m_window_shape = window_shape; }
const Strides& get_window_movement_strides() const { return m_window_movement_strides; }
void set_window_movement_strides(const Strides& window_movement_strides)
{
m_window_movement_strides = window_movement_strides;
}
const Shape& get_padding_below() const { return m_padding_below; }
void set_padding_below(const Shape& padding_below) { m_padding_below = padding_below; }
const Shape& get_padding_above() const { return m_padding_above; }
void set_padding_above(const Shape& padding_above) { m_padding_above = padding_above; }
protected:
Shape m_window_shape;
Strides m_window_movement_strides;
......
src/ngraph/op/maximum.cpp
View file @ 6abeca2b
......@@ -25,10 +25,12 @@
using namespace std;
using namespace ngraph;
op::Maximum::Maximum(const shared_ptr<Node>& arg0,
const shared_ptr<Node>& arg1,
const string op::Maximum::type_name{"Maximum"};
op::Maximum::Maximum(const Output<Node>& arg0,
const Output<Node>& arg1,
const AutoBroadcastSpec& autob)
: BinaryElementwiseArithmetic("Maximum", arg0, arg1, autob)
: BinaryElementwiseArithmetic(arg0, arg1, autob)
{
constructor_validate_and_infer_types();
}
......
src/ngraph/op/maximum.hpp
View file @ 6abeca2b
......@@ -26,13 +26,18 @@ namespace ngraph
class Maximum : public util::BinaryElementwiseArithmetic
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a maximum operation.
Maximum() = default;
/// \brief Constructs a maximum operation.
///
/// \param arg0 Node that produces the first input tensor.
/// \param arg1 Node that produces the second input tensor.
/// \param autob Auto broadcast specification
Maximum(const std::shared_ptr<Node>& arg0,
const std::shared_ptr<Node>& arg1,
Maximum(const Output<Node>& arg0,
const Output<Node>& arg1,
const AutoBroadcastSpec& autob = AutoBroadcastSpec());
virtual std::shared_ptr<Node>
......
src/ngraph/op/min.cpp
View file @ 6abeca2b
......@@ -22,10 +22,6 @@ using namespace ngraph;
const string op::Min::type_name{"Min"};
op::Min::Min()
{
}
op::Min::Min(const Output<Node>& arg, const AxisSet& reduction_axes)
: ArithmeticReduction(arg, reduction_axes)
{
......
src/ngraph/op/min.hpp
View file @ 6abeca2b
......@@ -30,7 +30,7 @@ namespace ngraph
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a "min" reduction operation.
Min();
Min() = default;
/// \brief Constructs a min-reduction operation.
///
/// \param arg The tensor to be reduced.
......
src/ngraph/op/minimum.cpp
View file @ 6abeca2b
......@@ -25,10 +25,12 @@
using namespace std;
using namespace ngraph;
op::Minimum::Minimum(const shared_ptr<Node>& arg0,
const shared_ptr<Node>& arg1,
const string op::Minimum::type_name{"Minimum"};
op::Minimum::Minimum(const Output<Node>& arg0,
const Output<Node>& arg1,
const AutoBroadcastSpec& autob)
: BinaryElementwiseArithmetic("Minimum", arg0, arg1, autob)
: BinaryElementwiseArithmetic(arg0, arg1, autob)
{
constructor_validate_and_infer_types();
}
......
src/ngraph/op/minimum.hpp
View file @ 6abeca2b
......@@ -26,13 +26,18 @@ namespace ngraph
class Minimum : public util::BinaryElementwiseArithmetic
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a minimum operation.
Minimum() = default;
/// \brief Constructs a minimum operation.
///
/// \param arg0 Node that produces the first input tensor.
/// \param arg1 Node that produces the second input tensor.
/// \param autob Auto broadcast specification
Minimum(const std::shared_ptr<Node>& arg0,
const std::shared_ptr<Node>& arg1,
Minimum(const Output<Node>& arg0,
const Output<Node>& arg1,
const AutoBroadcastSpec& autob = AutoBroadcastSpec());
virtual std::shared_ptr<Node>
......
src/ngraph/op/multiply.cpp
View file @ 6abeca2b
......@@ -19,10 +19,12 @@
using namespace std;
using namespace ngraph;
op::Multiply::Multiply(const shared_ptr<Node>& arg0,
const shared_ptr<Node>& arg1,
const string op::Multiply::type_name{"Multiply"};
op::Multiply::Multiply(const Output<Node>& arg0,
const Output<Node>& arg1,
const AutoBroadcastSpec& autob)
: BinaryElementwiseArithmetic("Multiply", arg0, arg1, autob)
: BinaryElementwiseArithmetic(arg0, arg1, autob)
{
constructor_validate_and_infer_types();
}
......@@ -49,7 +51,7 @@ void op::Multiply::generate_adjoints(autodiff::Adjoints& adjoints, const NodeVec
adjoints.add_delta(y, x * delta);
}
shared_ptr<Node> ngraph::operator*(const shared_ptr<Node> arg0, const shared_ptr<Node> arg1)
shared_ptr<Node> ngraph::operator*(const Output<Node>& arg0, const Output<Node>& arg1)
{
return make_shared<op::Multiply>(arg0, arg1);
}
src/ngraph/op/multiply.hpp
View file @ 6abeca2b
......@@ -26,13 +26,18 @@ namespace ngraph
class Multiply : public util::BinaryElementwiseArithmetic
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a multiplication operation.
Multiply() = default;
/// \brief Constructs a multiplication operation.
///
/// \param arg0 Node that produces the first input tensor.
/// \param arg1 Node that produces the second input tensor.
/// \param autob Auto broadcast specification
Multiply(const std::shared_ptr<Node>& arg0,
const std::shared_ptr<Node>& arg1,
Multiply(const Output<Node>& arg0,
const Output<Node>& arg1,
const AutoBroadcastSpec& autob = AutoBroadcastSpec());
virtual std::shared_ptr<Node>
......@@ -45,6 +50,5 @@ namespace ngraph
};
};
std::shared_ptr<ngraph::Node> operator*(const std::shared_ptr<ngraph::Node> arg0,
const std::shared_ptr<ngraph::Node> arg1);
std::shared_ptr<Node> operator*(const Output<Node>& arg0, const Output<Node>& arg1);
}
src/ngraph/op/negative.cpp
View file @ 6abeca2b
......@@ -19,8 +19,10 @@
using namespace std;
using namespace ngraph;
op::Negative::Negative(const shared_ptr<Node>& arg)
: UnaryElementwiseArithmetic("Negative", arg)
const string op::Negative::type_name{"Negative"};
op::Negative::Negative(const Output<Node>& arg)
: UnaryElementwiseArithmetic(arg)
{
constructor_validate_and_infer_types();
}
......@@ -40,7 +42,7 @@ void op::Negative::generate_adjoints(autodiff::Adjoints& adjoints, const NodeVec
adjoints.add_delta(x, -delta);
}
shared_ptr<Node> ngraph::operator-(const shared_ptr<Node> arg0)
shared_ptr<Node> ngraph::operator-(const Output<Node>& arg0)
{
return make_shared<op::Negative>(arg0);
}
src/ngraph/op/negative.hpp
View file @ 6abeca2b
......@@ -26,17 +26,23 @@ namespace ngraph
class Negative : public util::UnaryElementwiseArithmetic
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a negative operation.
Negative() = default;
/// \brief Constructs a negative operation.
///
/// \param arg Node that produces the input tensor.
Negative(const std::shared_ptr<Node>& arg);
Negative(const Output<Node>& arg);
virtual std::shared_ptr<Node>
copy_with_new_args(const NodeVector& new_args) const override;
protected:
virtual void generate_adjoints(autodiff::Adjoints& adjoints,
const NodeVector& deltas) override;
};
}
std::shared_ptr<ngraph::Node> operator-(const std::shared_ptr<ngraph::Node> arg0);
std::shared_ptr<Node> operator-(const Output<Node>& arg0);
}
src/ngraph/op/not.cpp
View file @ 6abeca2b
......@@ -20,8 +20,10 @@
using namespace ngraph;
using namespace std;
op::Not::Not(const shared_ptr<Node>& arg)
: Op("Not", check_single_output_args({arg}))
const string op::Not::type_name{"Not"};
op::Not::Not(const Output<Node>& arg)
: Op({arg})
{
constructor_validate_and_infer_types();
}
......
src/ngraph/op/not.hpp
View file @ 6abeca2b
......@@ -26,10 +26,15 @@ namespace ngraph
class Not : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a logical negation operation.
Not() = default;
/// \brief Constructs a logical negation operation.
///
/// \param arg Node that produces the input tensor.
Not(const std::shared_ptr<Node>& arg);
Not(const Output<Node>& arg);
void validate_and_infer_types() override;
......
src/ngraph/op/not_equal.cpp
View file @ 6abeca2b
......@@ -19,10 +19,12 @@
using namespace std;
using namespace ngraph;
op::NotEqual::NotEqual(const shared_ptr<Node>& arg0,
const shared_ptr<Node>& arg1,
const string op::NotEqual::type_name{"NotEqual"};
op::NotEqual::NotEqual(const Output<Node> &arg0,
const Output<Node> &arg1,
const AutoBroadcastSpec& autob)
: BinaryElementwiseComparison("NotEqual", arg0, arg1, autob)
: BinaryElementwiseComparison(arg0, arg1, autob)
{
constructor_validate_and_infer_types();
}
......
src/ngraph/op/not_equal.hpp
View file @ 6abeca2b
......@@ -26,13 +26,18 @@ namespace ngraph
class NotEqual : public util::BinaryElementwiseComparison
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a not-equal operation.
NotEqual() = default;
/// \brief Constructs a not-equal operation.
///
/// \param arg0 Node that produces the first input tensor.
/// \param arg1 Node that produces the second input tensor.
/// \param autob Auto broadcast specification
NotEqual(const std::shared_ptr<Node>& arg0,
const std::shared_ptr<Node>& arg1,
NotEqual(const Output<Node>& arg0,
const Output<Node>& arg1,
const AutoBroadcastSpec& autob = AutoBroadcastSpec());
virtual std::shared_ptr<Node>
......
src/ngraph/op/one_hot.cpp
View file @ 6abeca2b
......@@ -20,8 +20,10 @@
using namespace std;
using namespace ngraph;
op::OneHot::OneHot(const shared_ptr<Node>& arg, const PartialShape& shape, size_t one_hot_axis)
: Op("OneHot", check_single_output_args({arg}))
const string op::OneHot::type_name{"OneHot"};
op::OneHot::OneHot(const Output<Node>& arg, const PartialShape& shape, size_t one_hot_axis)
: Op({arg})
, m_shape(shape)
, m_one_hot_axis(one_hot_axis)
{
......
src/ngraph/op/one_hot.hpp
View file @ 6abeca2b
......@@ -45,14 +45,17 @@ namespace ngraph
class OneHot : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a one-hot operation.
OneHot() = default;
/// \brief Constructs a one-hot operation.
///
/// \param arg Node that produces the input tensor to be one-hot encoded.
/// \param shape The shape of the output tensor, including the new one-hot axis.
/// \param one_hot_axis The index within the output shape of the new one-hot axis.
OneHot(const std::shared_ptr<Node>& arg,
const PartialShape& shape,
size_t one_hot_axis);
OneHot(const Output<Node>& arg, const PartialShape& shape, size_t one_hot_axis);
virtual std::shared_ptr<Node>
copy_with_new_args(const NodeVector& new_args) const override;
......@@ -60,6 +63,8 @@ namespace ngraph
/// \return The index of the one-hot axis.
size_t get_one_hot_axis() const { return m_one_hot_axis; }
void set_one_hot_axis(size_t one_hot_axis) { m_one_hot_axis = one_hot_axis; }
protected:
PartialShape m_shape;
size_t m_one_hot_axis;
......
src/ngraph/op/or.cpp
View file @ 6abeca2b
......@@ -19,10 +19,10 @@
using namespace std;
using namespace ngraph;
op::Or::Or(const shared_ptr<Node>& arg0,
const shared_ptr<Node>& arg1,
const AutoBroadcastSpec& autob)
: BinaryElementwiseLogical("Or", arg0, arg1, autob)
const string op::Or::type_name{"Or"};
op::Or::Or(const Output<Node>& arg0, const Output<Node>& arg1, const AutoBroadcastSpec& autob)
: BinaryElementwiseLogical(arg0, arg1, autob)
{
constructor_validate_and_infer_types();
}
......
src/ngraph/op/or.hpp
View file @ 6abeca2b
......@@ -29,6 +29,9 @@ namespace ngraph
class Or : public util::BinaryElementwiseLogical
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a logical-or operation.
///
/// \param arg0 Node that produces the first input tensor.<br>
......@@ -39,8 +42,8 @@ namespace ngraph
///
/// Output `[d0, ...]`
///
Or(const std::shared_ptr<Node>& arg0,
const std::shared_ptr<Node>& arg1,
Or(const Output<Node>& arg0,
const Output<Node>& arg1,
const AutoBroadcastSpec& autob = AutoBroadcastSpec());
virtual std::shared_ptr<Node>
......
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