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ngraph
Commit c95c8b68 authored by Scott Cyphers's avatar Scott Cyphers Committed by Adam Procter
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Use compile-time tensor info for ops (#152) 

* Have abs use layout.

* Use layout to get vector info

* Add format selector for mapped arrays
Convert some ops
Drop runtime.cpp since we don't expose the functions any more.

* Add vector concat

* concat matrix

* Switch more ops to simpler eigen wrapping
parent eec7201d
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Showing with 284 additions and 420 deletions
src/ngraph/descriptor/layout/dense_tensor_view_layout.hpp
View file @ c95c8b68
...@@ -36,9 +36,11 @@ namespace ngraph ...@@ -36,9 +36,11 @@ namespace ngraph
DenseTensorViewLayout(const TensorView& tensor_view); DenseTensorViewLayout(const TensorView& tensor_view);
virtual size_t get_size() override { return m_size; } virtual size_t get_size() override { return m_size; }
size_t get_offset() const { return m_offset; } size_t get_offset() const { return m_offset; }
virtual size_t get_index_offset(const std::vector<size_t>& indices) override; virtual size_t get_index_offset(const std::vector<size_t>& indices) override;
const Strides& get_strides() const { return m_strides; }
protected: protected:
Strides m_strides; Strides m_strides;
size_t m_offset; size_t m_offset;
......
src/ngraph/descriptor/layout/tensor_view_layout.hpp
View file @ c95c8b68
...@@ -17,6 +17,7 @@ ...@@ -17,6 +17,7 @@
#include <tuple> #include <tuple>
#include <vector> #include <vector>
#include "ngraph/descriptor/tensor_view.hpp"
#include "ngraph/descriptor/buffer_pos.hpp" #include "ngraph/descriptor/buffer_pos.hpp"
namespace ngraph namespace ngraph
...@@ -51,6 +52,8 @@ namespace ngraph ...@@ -51,6 +52,8 @@ namespace ngraph
/// With non-linear buffers, this will need to be something other than size_t. /// With non-linear buffers, this will need to be something other than size_t.
virtual size_t get_index_offset(const std::vector<size_t>& indices) = 0; virtual size_t get_index_offset(const std::vector<size_t>& indices) = 0;
const Shape& get_shape() const { return m_tensor_view.get_tensor_view_type()->get_shape(); }
/// Where this view is located in the buffer. /// Where this view is located in the buffer.
const BufferPos& get_buffer_pos() const { return m_buffer_pos; } const BufferPos& get_buffer_pos() const { return m_buffer_pos; }
BufferPos& get_buffer_pos() { return m_buffer_pos; } BufferPos& get_buffer_pos() { return m_buffer_pos; }
......
src/ngraph/runtime/call_frame.hpp
View file @ c95c8b68
...@@ -18,7 +18,6 @@ ...@@ -18,7 +18,6 @@
#include <vector> #include <vector>
#include "ngraph/function.hpp" #include "ngraph/function.hpp"
#include "ngraph/runtime/instruction.hpp"
#include "ngraph/runtime/tensor_view.hpp" #include "ngraph/runtime/tensor_view.hpp"
namespace ngraph namespace ngraph
...@@ -26,6 +25,7 @@ namespace ngraph ...@@ -26,6 +25,7 @@ namespace ngraph
namespace runtime namespace runtime
{ {
class PrimaryTensorView; class PrimaryTensorView;
class Instruction;
// A VM for executing lightly-compiled graph functions. // A VM for executing lightly-compiled graph functions.
class CallFrame class CallFrame
...@@ -57,6 +57,14 @@ namespace ngraph ...@@ -57,6 +57,14 @@ namespace ngraph
return m_tensor_views[i]->get_parameterized_tensor_view<ET>(); return m_tensor_views[i]->get_parameterized_tensor_view<ET>();
} }
template<typename ET>
typename ET::type* get_tensor_view_data(size_t i)
{
return &get_parameterized_tensor_view<ET>(i)->get_vector()[0];
}
protected: protected:
size_t m_n_inputs; size_t m_n_inputs;
size_t m_n_outputs; size_t m_n_outputs;
......
src/ngraph/runtime/eigen/abs.hpp
View file @ c95c8b68
...@@ -18,6 +18,7 @@ ...@@ -18,6 +18,7 @@
#include "ngraph/runtime/eigen/utils.hpp" #include "ngraph/runtime/eigen/utils.hpp"
#include "ngraph/runtime/instruction.hpp" #include "ngraph/runtime/instruction.hpp"
#include "ngraph/runtime/tensor_view.hpp" #include "ngraph/runtime/tensor_view.hpp"
#include "ngraph/runtime/tensor_view_info.hpp"
namespace ngraph namespace ngraph
{ {
...@@ -25,17 +26,11 @@ namespace ngraph ...@@ -25,17 +26,11 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
template <typename T>
void abs(T arg, T out)
{
set_map_array(&*out, Eigen::abs(get_map_array(&*arg)));
}
template <typename ET> template <typename ET>
class AbsInstruction : public Instruction class AbsInstruction : public Instruction
{ {
public: public:
AbsInstruction(size_t arg, size_t out) AbsInstruction(const TensorViewInfo& arg, const TensorViewInfo& out)
: m_arg(arg) : m_arg(arg)
, m_out(out) , m_out(out)
{ {
...@@ -43,14 +38,12 @@ namespace ngraph ...@@ -43,14 +38,12 @@ namespace ngraph
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
runtime::eigen::abs( EigenArray1d<ET>(call_frame, m_out) = Eigen::abs(EigenArray1d<ET>(call_frame, m_arg));
call_frame.get_parameterized_tensor_view<ET>(m_arg),
call_frame.get_parameterized_tensor_view<ET>(m_out));
} }
protected: protected:
size_t m_arg; TensorViewInfo m_arg;
size_t m_out; TensorViewInfo m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/add.hpp
View file @ c95c8b68
...@@ -25,17 +25,13 @@ namespace ngraph ...@@ -25,17 +25,13 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
template <typename T>
void add(T arg0, T arg1, T out)
{
set_map_array(&*out, get_map_array(&*arg0) + get_map_array(&*arg1));
}
template <typename ET> template <typename ET>
class AddInstruction : public Instruction class AddInstruction : public Instruction
{ {
public: public:
AddInstruction(size_t arg0, size_t arg1, size_t out) AddInstruction(const TensorViewInfo& arg0,
const TensorViewInfo& arg1,
const TensorViewInfo& out)
: m_arg0(arg0) : m_arg0(arg0)
, m_arg1(arg1) , m_arg1(arg1)
, m_out(out) , m_out(out)
...@@ -44,16 +40,14 @@ namespace ngraph ...@@ -44,16 +40,14 @@ namespace ngraph
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
runtime::eigen::add( EigenArray1d<ET>(call_frame, m_out) =
call_frame.get_parameterized_tensor_view<ET>(m_arg0), EigenArray1d<ET>(call_frame, m_arg0) + EigenArray1d<ET>(call_frame, m_arg1);
call_frame.get_parameterized_tensor_view<ET>(m_arg1),
call_frame.get_parameterized_tensor_view<ET>(m_out));
} }
protected: protected:
size_t m_arg0; TensorViewInfo m_arg0;
size_t m_arg1; TensorViewInfo m_arg1;
size_t m_out; TensorViewInfo m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/call.hpp
View file @ c95c8b68
...@@ -29,7 +29,7 @@ namespace ngraph ...@@ -29,7 +29,7 @@ namespace ngraph
class CallInstruction : public Instruction class CallInstruction : public Instruction
{ {
public: public:
CallInstruction(std::shared_ptr<ExternalFunction> ef,std::vector<size_t> in, std::vector<size_t> out) CallInstruction(std::shared_ptr<ExternalFunction> ef,std::vector<TensorViewInfo> in, std::vector<TensorViewInfo> out)
: m_external_function(ef) : m_external_function(ef)
, m_in(in) , m_in(in)
, m_out(out) , m_out(out)
...@@ -45,19 +45,19 @@ namespace ngraph ...@@ -45,19 +45,19 @@ namespace ngraph
for (auto in : m_in) for (auto in : m_in)
{ {
inputs.push_back(call_frame.get_tensor_view(in)); inputs.push_back(call_frame.get_tensor_view(in.get_index()));
} }
for (auto out : m_out) for (auto out : m_out)
{ {
outputs.push_back(call_frame.get_tensor_view(out)); outputs.push_back(call_frame.get_tensor_view(out.get_index()));
} }
(*cf)(inputs,outputs); (*cf)(inputs,outputs);
} }
protected: protected:
std::shared_ptr<ExternalFunction> m_external_function; std::shared_ptr<ExternalFunction> m_external_function;
std::vector<size_t> m_in; std::vector<TensorViewInfo> m_in;
std::vector<size_t> m_out; std::vector<TensorViewInfo> m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/concat_matrix.hpp
View file @ c95c8b68
...@@ -18,6 +18,7 @@ ...@@ -18,6 +18,7 @@
#include "ngraph/runtime/eigen/utils.hpp" #include "ngraph/runtime/eigen/utils.hpp"
#include "ngraph/runtime/instruction.hpp" #include "ngraph/runtime/instruction.hpp"
#include "ngraph/runtime/tensor_view.hpp" #include "ngraph/runtime/tensor_view.hpp"
#include "ngraph/runtime/tensor_view_info.hpp"
namespace ngraph namespace ngraph
{ {
...@@ -25,69 +26,43 @@ namespace ngraph ...@@ -25,69 +26,43 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
// Intended substitutions for T are shared_ptr<ParameterizedTensorView<...>>
// and ParameterizedTensorView<...>*.
template <typename T>
void concat_matrix(std::vector<T>& args, T out, size_t axis)
{
auto mat_out = get_map_matrix_2d(&*out);
auto& out_shape = out->get_shape();
assert (out_shape.size() == 2);
assert (axis == 0 || axis == 1);
size_t concat_pos = 0;
for(T arg : args)
{
auto mat_arg = get_map_matrix_2d(&*arg);
auto& arg_shape = arg->get_shape();
assert (arg_shape.size() == 2);
if (axis == 0)
{
mat_out.block(concat_pos,0,arg_shape.at(0),arg_shape.at(1))
<< mat_arg;
concat_pos += arg_shape.at(0);
}
else
{
mat_out.block(0,concat_pos,arg_shape.at(0),arg_shape.at(1))
<< mat_arg;
concat_pos += arg_shape.at(1);
}
}
}
template <typename ET> template <typename ET>
class ConcatMatrixInstruction : public Instruction class ConcatMatrixInstruction : public Instruction
{ {
public: public:
ConcatMatrixInstruction(const std::vector<size_t>& args, size_t axis, size_t out) ConcatMatrixInstruction(const std::vector<TensorViewInfo>& args,
size_t axis,
const TensorViewInfo& out)
: m_args(args) : m_args(args)
, m_axis(axis) , m_axis(axis)
, m_out(out) , m_out(out)
{ {
size_t concat_pos[2]{0, 0};
for (auto arg : args)
{
auto& arg_shape = arg.get_tensor_view_layout()->get_shape();
m_blocks.push_back(
{concat_pos[0], concat_pos[1], arg_shape.at(0), arg_shape.at(1)});
concat_pos[axis] += arg_shape.at(axis);
}
} }
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
std::vector<ParameterizedTensorView<ET>*> ptvs; EigenMatrix<ET> out(call_frame, m_out);
for(size_t arg : m_args) for (size_t i = 0; i < m_args.size(); i++)
{ {
ptvs.push_back(call_frame.get_parameterized_tensor_view<ET>(arg)); auto& b = m_blocks[i];
out.block(b[0], b[1], b[2], b[3])
<< EigenMatrix<ET>(call_frame, m_args.at(i));
} }
runtime::eigen::concat_matrix(
ptvs,
call_frame.get_parameterized_tensor_view<ET>(m_out),
m_axis);
} }
protected: protected:
std::vector<size_t> m_args; std::vector<TensorViewInfo> m_args;
size_t m_axis; size_t m_axis;
size_t m_out; TensorViewInfo m_out;
std::vector<std::vector<size_t>> m_blocks;
}; };
} }
} }
......
src/ngraph/runtime/eigen/concat_vector.hpp
View file @ c95c8b68
...@@ -25,55 +25,37 @@ namespace ngraph ...@@ -25,55 +25,37 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
// Intended substitutions for T are shared_ptr<ParameterizedTensorView<...>> // Would be better to just generate a sequence of copy into slice of output instructions
// and ParameterizedTensorView<...>*.
template <typename T>
void concat_vector(std::vector<T>& args, T out)
{
auto vec_out = get_map_matrix(&*out);
auto& out_shape = out->get_shape();
assert (out_shape.size() == 1);
size_t concat_pos = 0;
for(T arg : args)
{
auto vec_arg = get_map_matrix(&*arg);
auto& arg_shape = arg->get_shape();
assert (arg_shape.size() == 1);
vec_out.segment(concat_pos,arg_shape.at(0)) << vec_arg;
concat_pos += arg_shape.at(0);
}
}
template <typename ET> template <typename ET>
class ConcatVectorInstruction : public Instruction class ConcatVectorInstruction : public Instruction
{ {
public: public:
ConcatVectorInstruction(const std::vector<size_t>& args, size_t out) ConcatVectorInstruction(const std::vector<TensorViewInfo>& args,
const TensorViewInfo& out)
: m_args(args) : m_args(args)
, m_out(out) , m_out(out)
{ {
for (auto arg : args)
{
auto& arg_shape = arg.get_tensor_view_layout()->get_shape();
m_sizes.push_back(arg_shape.at(0));
}
} }
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
std::vector<ParameterizedTensorView<ET>*> ptvs; EigenVector<ET> out(call_frame, m_out);
for(size_t arg : m_args) size_t concat_pos = 0;
{ for (size_t i = 0; i < m_args.size(); i++){
ptvs.push_back(call_frame.get_parameterized_tensor_view<ET>(arg)); out.segment(concat_pos, m_sizes[i]) << EigenVector<ET>(call_frame, m_args.at(i));
concat_pos += m_sizes[i];
} }
runtime::eigen::concat_vector(
ptvs,
call_frame.get_parameterized_tensor_view<ET>(m_out));
} }
protected: protected:
std::vector<size_t> m_args; std::vector<TensorViewInfo> m_args;
size_t m_out; TensorViewInfo m_out;
std::vector<size_t> m_sizes;
}; };
} }
} }
......
src/ngraph/runtime/eigen/constant.hpp
View file @ c95c8b68
...@@ -18,6 +18,7 @@ ...@@ -18,6 +18,7 @@
#include "ngraph/runtime/eigen/utils.hpp" #include "ngraph/runtime/eigen/utils.hpp"
#include "ngraph/runtime/instruction.hpp" #include "ngraph/runtime/instruction.hpp"
#include "ngraph/runtime/tensor_view.hpp" #include "ngraph/runtime/tensor_view.hpp"
#include "ngraph/runtime/tensor_view_info.hpp"
namespace ngraph namespace ngraph
{ {
...@@ -25,17 +26,11 @@ namespace ngraph ...@@ -25,17 +26,11 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
template <typename ET,typename T>
void assign_constant(const std::vector<ET>& value, T out)
{
out->get_vector() = value;
}
template <typename ET> template <typename ET>
class ConstantInstruction : public Instruction class ConstantInstruction : public Instruction
{ {
public: public:
ConstantInstruction(const std::vector<typename ET::type> value, size_t out) ConstantInstruction(const std::vector<typename ET::type> value, const TensorViewInfo& out)
: m_value(value) : m_value(value)
, m_out(out) , m_out(out)
{ {
...@@ -43,14 +38,12 @@ namespace ngraph ...@@ -43,14 +38,12 @@ namespace ngraph
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
runtime::eigen::assign_constant( call_frame.get_parameterized_tensor_view<ET>(m_out.get_index())->get_vector() = m_value;
m_value,
call_frame.get_parameterized_tensor_view<ET>(m_out));
} }
protected: protected:
const std::vector<typename ET::type> m_value; const std::vector<typename ET::type> m_value;
size_t m_out; TensorViewInfo m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/divide.hpp
View file @ c95c8b68
...@@ -25,17 +25,13 @@ namespace ngraph ...@@ -25,17 +25,13 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
template <typename T>
void divide(T arg0, T arg1, T out)
{
set_map_array(&*out, get_map_array(&*arg0) / get_map_array(&*arg1));
}
template <typename ET> template <typename ET>
class DivideInstruction : public Instruction class DivideInstruction : public Instruction
{ {
public: public:
DivideInstruction(size_t arg0, size_t arg1, size_t out) DivideInstruction(const TensorViewInfo& arg0,
const TensorViewInfo& arg1,
const TensorViewInfo& out)
: m_arg0(arg0) : m_arg0(arg0)
, m_arg1(arg1) , m_arg1(arg1)
, m_out(out) , m_out(out)
...@@ -44,16 +40,14 @@ namespace ngraph ...@@ -44,16 +40,14 @@ namespace ngraph
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
runtime::eigen::divide( EigenArray1d<ET>(call_frame, m_out) =
call_frame.get_parameterized_tensor_view<ET>(m_arg0), EigenArray1d<ET>(call_frame, m_arg0) / EigenArray1d<ET>(call_frame, m_arg1);
call_frame.get_parameterized_tensor_view<ET>(m_arg1),
call_frame.get_parameterized_tensor_view<ET>(m_out));
} }
protected: protected:
size_t m_arg0; TensorViewInfo m_arg0;
size_t m_arg1; TensorViewInfo m_arg1;
size_t m_out; TensorViewInfo m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/equal.hpp
View file @ c95c8b68
...@@ -25,19 +25,11 @@ namespace ngraph ...@@ -25,19 +25,11 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
template <typename TI,typename TO>
void equal(TI arg0, TI arg1, TO out)
{
auto result_as_float = get_map_array(&*arg0) == get_map_array(&*arg1);
auto result_as_char = result_as_float.template cast<char>();
set_map_array(&*out, result_as_char);
}
template <typename ET> template <typename ET>
class EqualInstruction : public Instruction class EqualInstruction : public Instruction
{ {
public: public:
EqualInstruction(size_t arg0, size_t arg1, size_t out) EqualInstruction(TensorViewInfo arg0, TensorViewInfo arg1, TensorViewInfo out)
: m_arg0(arg0) : m_arg0(arg0)
, m_arg1(arg1) , m_arg1(arg1)
, m_out(out) , m_out(out)
...@@ -46,16 +38,16 @@ namespace ngraph ...@@ -46,16 +38,16 @@ namespace ngraph
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
runtime::eigen::equal( EigenArray1d<element::Bool>(call_frame, m_out) =
call_frame.get_parameterized_tensor_view<ET>(m_arg0), (EigenArray1d<ET>(call_frame, m_arg0) ==
call_frame.get_parameterized_tensor_view<ET>(m_arg1), EigenArray1d<ET>(call_frame, m_arg1))
call_frame.get_parameterized_tensor_view<element::Bool>(m_out)); .template cast<char>();
} }
protected: protected:
size_t m_arg0; TensorViewInfo m_arg0;
size_t m_arg1; TensorViewInfo m_arg1;
size_t m_out; TensorViewInfo m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/less_than.hpp
View file @ c95c8b68
...@@ -25,7 +25,7 @@ namespace ngraph ...@@ -25,7 +25,7 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
template <typename TI,typename TO> template <typename TI, typename TO>
void less_than(TI arg0, TI arg1, TO out) void less_than(TI arg0, TI arg1, TO out)
{ {
auto result_as_float = get_map_array(&*arg0) < get_map_array(&*arg1); auto result_as_float = get_map_array(&*arg0) < get_map_array(&*arg1);
...@@ -37,7 +37,7 @@ namespace ngraph ...@@ -37,7 +37,7 @@ namespace ngraph
class LessThanInstruction : public Instruction class LessThanInstruction : public Instruction
{ {
public: public:
LessThanInstruction(size_t arg0, size_t arg1, size_t out) LessThanInstruction(TensorViewInfo arg0, TensorViewInfo arg1, TensorViewInfo out)
: m_arg0(arg0) : m_arg0(arg0)
, m_arg1(arg1) , m_arg1(arg1)
, m_out(out) , m_out(out)
...@@ -46,16 +46,16 @@ namespace ngraph ...@@ -46,16 +46,16 @@ namespace ngraph
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
runtime::eigen::less_than( EigenArray1d<element::Bool>(call_frame, m_out) =
call_frame.get_parameterized_tensor_view<ET>(m_arg0), (EigenArray1d<ET>(call_frame, m_arg0) <
call_frame.get_parameterized_tensor_view<ET>(m_arg1), EigenArray1d<ET>(call_frame, m_arg1))
call_frame.get_parameterized_tensor_view<element::Bool>(m_out)); .template cast<char>();
} }
protected: protected:
size_t m_arg0; TensorViewInfo m_arg0;
size_t m_arg1; TensorViewInfo m_arg1;
size_t m_out; TensorViewInfo m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/log.hpp
View file @ c95c8b68
...@@ -25,17 +25,11 @@ namespace ngraph ...@@ -25,17 +25,11 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
template <typename T>
void log(T arg, T out)
{
set_map_array(&*out, Eigen::log(get_map_array(&*arg)));
}
template <typename ET> template <typename ET>
class LogInstruction : public Instruction class LogInstruction : public Instruction
{ {
public: public:
LogInstruction(size_t arg, size_t out) LogInstruction(TensorViewInfo arg, TensorViewInfo out)
: m_arg(arg) : m_arg(arg)
, m_out(out) , m_out(out)
{ {
...@@ -43,14 +37,12 @@ namespace ngraph ...@@ -43,14 +37,12 @@ namespace ngraph
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
runtime::eigen::log( EigenArray1d<ET, fmt::V>(call_frame, m_out) = Eigen::log(EigenArray1d<ET, fmt::V>(call_frame, m_arg));
call_frame.get_parameterized_tensor_view<ET>(m_arg),
call_frame.get_parameterized_tensor_view<ET>(m_out));
} }
protected: protected:
size_t m_arg; TensorViewInfo m_arg;
size_t m_out; TensorViewInfo m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/maximum.hpp
View file @ c95c8b68
...@@ -25,17 +25,11 @@ namespace ngraph ...@@ -25,17 +25,11 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
template <typename T>
void maximum(T arg0, T arg1, T out)
{
set_map_array(out, get_map_array(&*arg0).max(get_map_array(&*arg1)));
}
template <typename ET> template <typename ET>
class MaximumInstruction : public Instruction class MaximumInstruction : public Instruction
{ {
public: public:
MaximumInstruction(size_t arg0, size_t arg1, size_t out) MaximumInstruction(TensorViewInfo arg0, TensorViewInfo arg1, TensorViewInfo out)
: m_arg0(arg0) : m_arg0(arg0)
, m_arg1(arg1) , m_arg1(arg1)
, m_out(out) , m_out(out)
...@@ -44,16 +38,15 @@ namespace ngraph ...@@ -44,16 +38,15 @@ namespace ngraph
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
runtime::eigen::maximum( EigenArray1d<ET>(call_frame, m_out) =
call_frame.get_parameterized_tensor_view<ET>(m_arg0), EigenArray1d<ET>(call_frame, m_arg0)
call_frame.get_parameterized_tensor_view<ET>(m_arg1), .max(EigenArray1d<ET>(call_frame, m_arg1));
call_frame.get_parameterized_tensor_view<ET>(m_out));
} }
protected: protected:
size_t m_arg0; TensorViewInfo m_arg0;
size_t m_arg1; TensorViewInfo m_arg1;
size_t m_out; TensorViewInfo m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/multiply.hpp
View file @ c95c8b68
...@@ -24,17 +24,11 @@ namespace ngraph ...@@ -24,17 +24,11 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
template <typename T>
void multiply(T arg0, T arg1, T out)
{
set_map_array(&*out, get_map_array(&*arg0) * get_map_array(&*arg1));
}
template <typename ET> template <typename ET>
class MultiplyInstruction : public Instruction class MultiplyInstruction : public Instruction
{ {
public: public:
MultiplyInstruction(size_t arg0, size_t arg1, size_t out) MultiplyInstruction(TensorViewInfo arg0, TensorViewInfo arg1, TensorViewInfo out)
: m_arg0(arg0) : m_arg0(arg0)
, m_arg1(arg1) , m_arg1(arg1)
, m_out(out) , m_out(out)
...@@ -43,16 +37,14 @@ namespace ngraph ...@@ -43,16 +37,14 @@ namespace ngraph
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
runtime::eigen::multiply( EigenArray1d<ET>(call_frame, m_out) =
call_frame.get_parameterized_tensor_view<ET>(m_arg0), EigenArray1d<ET>(call_frame, m_arg0) * EigenArray1d<ET>(call_frame, m_arg1);
call_frame.get_parameterized_tensor_view<ET>(m_arg1),
call_frame.get_parameterized_tensor_view<ET>(m_out));
} }
protected: protected:
size_t m_arg0; TensorViewInfo m_arg0;
size_t m_arg1; TensorViewInfo m_arg1;
size_t m_out; TensorViewInfo m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/negate.hpp
View file @ c95c8b68
...@@ -25,17 +25,11 @@ namespace ngraph ...@@ -25,17 +25,11 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
template <typename T>
void negate(T arg, T out)
{
set_map_array(&*out, -(get_map_array(&*arg)));
}
template <typename ET> template <typename ET>
class NegateInstruction : public Instruction class NegateInstruction : public Instruction
{ {
public: public:
NegateInstruction(size_t arg, size_t out) NegateInstruction(TensorViewInfo arg, TensorViewInfo out)
: m_arg(arg) : m_arg(arg)
, m_out(out) , m_out(out)
{ {
...@@ -43,14 +37,12 @@ namespace ngraph ...@@ -43,14 +37,12 @@ namespace ngraph
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
runtime::eigen::negate( EigenArray1d<ET>(call_frame, m_out) = -EigenArray1d<ET>(call_frame, m_arg);
call_frame.get_parameterized_tensor_view<ET>(m_arg),
call_frame.get_parameterized_tensor_view<ET>(m_out));
} }
protected: protected:
size_t m_arg; TensorViewInfo m_arg;
size_t m_out; TensorViewInfo m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/not_equal.hpp
View file @ c95c8b68
...@@ -25,19 +25,11 @@ namespace ngraph ...@@ -25,19 +25,11 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
template <typename TI,typename TO>
void not_equal(TI arg0, TI arg1, TO out)
{
auto result_as_float = get_map_array(&*arg0) != get_map_array(&*arg1);
auto result_as_char = result_as_float.template cast<char>();
set_map_array(&*out, result_as_char);
}
template <typename ET> template <typename ET>
class NotEqualInstruction : public Instruction class NotEqualInstruction : public Instruction
{ {
public: public:
NotEqualInstruction(size_t arg0, size_t arg1, size_t out) NotEqualInstruction(TensorViewInfo arg0, TensorViewInfo arg1, TensorViewInfo out)
: m_arg0(arg0) : m_arg0(arg0)
, m_arg1(arg1) , m_arg1(arg1)
, m_out(out) , m_out(out)
...@@ -46,16 +38,16 @@ namespace ngraph ...@@ -46,16 +38,16 @@ namespace ngraph
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
runtime::eigen::not_equal( EigenArray1d<element::Bool>(call_frame, m_out) =
call_frame.get_parameterized_tensor_view<ET>(m_arg0), (EigenArray1d<ET>(call_frame, m_arg0) !=
call_frame.get_parameterized_tensor_view<ET>(m_arg1), EigenArray1d<ET>(call_frame, m_arg1))
call_frame.get_parameterized_tensor_view<element::Bool>(m_out)); .template cast<char>();
} }
protected: protected:
size_t m_arg0; TensorViewInfo m_arg0;
size_t m_arg1; TensorViewInfo m_arg1;
size_t m_out; TensorViewInfo m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/select.hpp
View file @ c95c8b68
...@@ -25,17 +25,14 @@ namespace ngraph ...@@ -25,17 +25,14 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
template <typename TA,typename TB>
void select(TA arg0, TB arg1, TB arg2, TB out)
{
set_map_array(&*out, get_map_array(&*arg0).select(get_map_array(&*arg1),get_map_array(&*arg2)));
}
template <typename ET> template <typename ET>
class SelectInstruction : public Instruction class SelectInstruction : public Instruction
{ {
public: public:
SelectInstruction(size_t arg0, size_t arg1, size_t arg2, size_t out) SelectInstruction(TensorViewInfo arg0,
TensorViewInfo arg1,
TensorViewInfo arg2,
TensorViewInfo out)
: m_arg0(arg0) : m_arg0(arg0)
, m_arg1(arg1) , m_arg1(arg1)
, m_arg2(arg2) , m_arg2(arg2)
...@@ -45,18 +42,17 @@ namespace ngraph ...@@ -45,18 +42,17 @@ namespace ngraph
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
runtime::eigen::select( EigenArray1d<ET>(call_frame, m_out) =
call_frame.get_parameterized_tensor_view<element::Bool>(m_arg0), EigenArray1d<element::Bool>(call_frame, m_arg0)
call_frame.get_parameterized_tensor_view<ET>(m_arg1), .select(EigenArray1d<ET>(call_frame, m_arg1),
call_frame.get_parameterized_tensor_view<ET>(m_arg2), EigenArray1d<ET>(call_frame, m_arg2));
call_frame.get_parameterized_tensor_view<ET>(m_out));
} }
protected: protected:
size_t m_arg0; TensorViewInfo m_arg0;
size_t m_arg1; TensorViewInfo m_arg1;
size_t m_arg2; TensorViewInfo m_arg2;
size_t m_out; TensorViewInfo m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/subtract.hpp
View file @ c95c8b68
...@@ -25,17 +25,11 @@ namespace ngraph ...@@ -25,17 +25,11 @@ namespace ngraph
{ {
namespace eigen namespace eigen
{ {
template <typename T>
void subtract(T arg0, T arg1, T out)
{
set_map_array(&*out, get_map_array(&*arg0) - get_map_array(&*arg1));
}
template <typename ET> template <typename ET>
class SubtractInstruction : public Instruction class SubtractInstruction : public Instruction
{ {
public: public:
SubtractInstruction(size_t arg0, size_t arg1, size_t out) SubtractInstruction(TensorViewInfo arg0, TensorViewInfo arg1, TensorViewInfo out)
: m_arg0(arg0) : m_arg0(arg0)
, m_arg1(arg1) , m_arg1(arg1)
, m_out(out) , m_out(out)
...@@ -44,16 +38,14 @@ namespace ngraph ...@@ -44,16 +38,14 @@ namespace ngraph
virtual void execute(CallFrame& call_frame) const override virtual void execute(CallFrame& call_frame) const override
{ {
runtime::eigen::subtract( EigenArray1d<ET>(call_frame, m_out) =
call_frame.get_parameterized_tensor_view<ET>(m_arg0), EigenArray1d<ET>(call_frame, m_arg0) - EigenArray1d<ET>(call_frame, m_arg1);
call_frame.get_parameterized_tensor_view<ET>(m_arg1),
call_frame.get_parameterized_tensor_view<ET>(m_out));
} }
protected: protected:
size_t m_arg0; TensorViewInfo m_arg0;
size_t m_arg1; TensorViewInfo m_arg1;
size_t m_out; TensorViewInfo m_out;
}; };
} }
} }
......
src/ngraph/runtime/eigen/utils.hpp
View file @ c95c8b68
This diff is collapsed.
src/ngraph/runtime/external_function.cpp
View file @ c95c8b68
...@@ -19,6 +19,7 @@ ...@@ -19,6 +19,7 @@
#include <unordered_map> #include <unordered_map>
#include "ngraph/descriptor/input.hpp" #include "ngraph/descriptor/input.hpp"
#include "ngraph/descriptor/layout/dense_tensor_view_layout.hpp"
#include "ngraph/descriptor/output.hpp" #include "ngraph/descriptor/output.hpp"
#include "ngraph/function.hpp" #include "ngraph/function.hpp"
#include "ngraph/node.hpp" #include "ngraph/node.hpp"
...@@ -73,6 +74,8 @@ ...@@ -73,6 +74,8 @@
using namespace std; using namespace std;
using namespace ngraph::runtime; using namespace ngraph::runtime;
using ngraph::descriptor::layout::DenseTensorViewLayout;
ExternalFunction::ExternalFunction(const std::shared_ptr<ngraph::Function>& function, ExternalFunction::ExternalFunction(const std::shared_ptr<ngraph::Function>& function,
bool release_function) bool release_function)
: m_function(function) : m_function(function)
...@@ -86,25 +89,26 @@ ExternalFunction::ExternalFunction(const std::shared_ptr<ngraph::Function>& func ...@@ -86,25 +89,26 @@ ExternalFunction::ExternalFunction(const std::shared_ptr<ngraph::Function>& func
op_map[type_index(typeid(op_class))] = [](const Node* n, \ op_map[type_index(typeid(op_class))] = [](const Node* n, \
ExternalFunction* ef, \ ExternalFunction* ef, \
FunctionMap& function_map, \ FunctionMap& function_map, \
const std::vector<size_t>& in, \ const std::vector<TensorViewInfo>& in, \
const std::vector<size_t>& out) const std::vector<TensorViewInfo>& out)
#define REGISTER_INSTRUCTION(op_class, instr_class, ...) \ #define REGISTER_INSTRUCTION(op_class, instr_class, ...) \
REGISTER_TO_OP_MAP(op_class) { \ REGISTER_TO_OP_MAP(op_class) { \
ef->get_instructions()->push_back(make_shared<instr_class>(__VA_ARGS__)); \ ef->get_instructions()->push_back(make_shared<instr_class>(__VA_ARGS__)); \
} }
#define REGISTER_UNOP(op_class, instr_class) \ // Versions the include the descriptor
#define REGISTER_UNOP(op_class, instr_class) \
REGISTER_INSTRUCTION(op_class, instr_class, in[0], out[0]) REGISTER_INSTRUCTION(op_class, instr_class, in[0], out[0])
#define REGISTER_BINOP(op_class, instr_class) \ #define REGISTER_BINOP(op_class, instr_class) \
REGISTER_INSTRUCTION(op_class, instr_class, in[0], in[1], out[0]) REGISTER_INSTRUCTION(op_class, instr_class, in[0], in[1], out[0])
#define REGISTER_TERNOP(op_class, instr_class) \ #define REGISTER_TERNOP(op_class, instr_class) \
REGISTER_INSTRUCTION(op_class, instr_class, in[0], in[1], in[2], out[0]) REGISTER_INSTRUCTION(op_class, instr_class, in[0], in[1], in[2], out[0])
// Define code generators for handled ops. // Define code generators for handled ops.
ExternalFunction::OpMap& ExternalFunction::get_op_map() ExternalFunction::OpMap& ExternalFunction::get_op_map()
{ {
static bool initialized = false; static bool initialized = false;
static OpMap op_map; static OpMap op_map;
if (!initialized) if (!initialized)
{ {
...@@ -145,8 +149,8 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map() ...@@ -145,8 +149,8 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map()
if (result_shape.size() == 1) if (result_shape.size() == 1)
{ {
ef->get_instructions()->push_back( ef->get_instructions()->push_back(
make_shared<runtime::eigen::ConcatVectorInstruction<element::Float32>>(in, make_shared<runtime::eigen::ConcatVectorInstruction<element::Float32>>(
out[0])); in, out[0]));
} }
else if (result_shape.size() == 2) else if (result_shape.size() == 2)
{ {
...@@ -184,14 +188,14 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map() ...@@ -184,14 +188,14 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map()
{ {
ef->get_instructions()->push_back( ef->get_instructions()->push_back(
make_shared<runtime::eigen::ScalarTensorProductInstruction<element::Float32>>( make_shared<runtime::eigen::ScalarTensorProductInstruction<element::Float32>>(
in[0], in[1], out[0])); in[0].get_index(), in[1].get_index(), out[0].get_index()));
} }
else if (arg1_shape.size() == 0) else if (arg1_shape.size() == 0)
{ {
// If arg1 is the scalar, do the same thing but switch the order of operands. // If arg1 is the scalar, do the same thing but switch the order of operands.
ef->get_instructions()->push_back( ef->get_instructions()->push_back(
make_shared<runtime::eigen::ScalarTensorProductInstruction<element::Float32>>( make_shared<runtime::eigen::ScalarTensorProductInstruction<element::Float32>>(
in[1], in[0], out[0])); in[1].get_index(), in[0].get_index(), out[0].get_index()));
} }
// If arg0 and arg1 are both vectors, emit a dot product. // If arg0 and arg1 are both vectors, emit a dot product.
...@@ -199,7 +203,7 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map() ...@@ -199,7 +203,7 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map()
{ {
ef->get_instructions()->push_back( ef->get_instructions()->push_back(
make_shared<runtime::eigen::DotInstruction<element::Float32>>( make_shared<runtime::eigen::DotInstruction<element::Float32>>(
in[0], in[1], out[0])); in[0].get_index(), in[1].get_index(), out[0].get_index()));
} }
// If arg0 is a matrix and arg1 is a vector, emit a matrix-vector product. // If arg0 is a matrix and arg1 is a vector, emit a matrix-vector product.
...@@ -207,7 +211,7 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map() ...@@ -207,7 +211,7 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map()
{ {
ef->get_instructions()->push_back( ef->get_instructions()->push_back(
make_shared<runtime::eigen::MatrixVectorProductInstruction<element::Float32>>( make_shared<runtime::eigen::MatrixVectorProductInstruction<element::Float32>>(
in[0], in[1], out[0])); in[0].get_index(), in[1].get_index(), out[0].get_index()));
} }
// If arg0 and arg1 are both matrices, emit a matrix product. // If arg0 and arg1 are both matrices, emit a matrix product.
...@@ -215,7 +219,7 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map() ...@@ -215,7 +219,7 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map()
{ {
ef->get_instructions()->push_back( ef->get_instructions()->push_back(
make_shared<runtime::eigen::MatrixMultInstruction<element::Float32>>( make_shared<runtime::eigen::MatrixMultInstruction<element::Float32>>(
in[0], in[1], out[0])); in[0].get_index(), in[1].get_index(), out[0].get_index()));
} }
else else
...@@ -234,7 +238,7 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map() ...@@ -234,7 +238,7 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map()
ef->get_instructions()->push_back( ef->get_instructions()->push_back(
make_shared<runtime::eigen::CopyInstruction<element::Float32>>( make_shared<runtime::eigen::CopyInstruction<element::Float32>>(
in.at(get_tuple_element->get_n()), out.at(0))); in.at(get_tuple_element->get_n()).get_index(), out.at(0).get_index()));
}; };
// Tuple will be spliced out, with the users of out connected to the corresponding in's source, but, for now, we need to copy. // Tuple will be spliced out, with the users of out connected to the corresponding in's source, but, for now, we need to copy.
...@@ -243,8 +247,8 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map() ...@@ -243,8 +247,8 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map()
for (size_t i = 0; i < in.size(); ++i) for (size_t i = 0; i < in.size(); ++i)
{ {
ef->get_instructions()->push_back( ef->get_instructions()->push_back(
make_shared<runtime::eigen::CopyInstruction<element::Float32>>(in.at(i), make_shared<runtime::eigen::CopyInstruction<element::Float32>>(
out.at(i))); in.at(i).get_index(), out.at(i).get_index()));
} }
}; };
...@@ -295,6 +299,22 @@ void ExternalFunction::compile(FunctionMap& function_map) ...@@ -295,6 +299,22 @@ void ExternalFunction::compile(FunctionMap& function_map)
pass_manager.register_pass<pass::AssignTensors>(); pass_manager.register_pass<pass::AssignTensors>();
pass_manager.run_passes(m_function); pass_manager.run_passes(m_function);
// Turn this into a pass
// Assign layouts
// For now, just make everyone row-major.
for (const Node* node : pass_manager.get_call_graph())
{
for (const descriptor::Output& output : node->get_outputs())
{
auto tv = output.get_tensor_view();
if (nullptr == tv->get_tensor_view_layout())
{
auto layout = std::make_shared<DenseTensorViewLayout>(*tv);
tv->set_tensor_view_layout(layout);
}
}
}
// Determine tensor requirements for the call frame // Determine tensor requirements for the call frame
unordered_map<shared_ptr<ngraph::descriptor::TensorView>, size_t> tensor_index; unordered_map<shared_ptr<ngraph::descriptor::TensorView>, size_t> tensor_index;
// First come the function inputs // First come the function inputs
...@@ -342,18 +362,18 @@ void ExternalFunction::compile(FunctionMap& function_map) ...@@ -342,18 +362,18 @@ void ExternalFunction::compile(FunctionMap& function_map)
{ {
throw ngraph_error("Unhandled op during code generation"); throw ngraph_error("Unhandled op during code generation");
} }
std::vector<size_t> in; std::vector<TensorViewInfo> in;
for (const descriptor::Input& input : node->get_inputs()) for (const descriptor::Input& input : node->get_inputs())
{ {
const descriptor::Output& output = input.get_output(); const descriptor::Output& output = input.get_output();
auto tv = output.get_tensor_view(); auto tv = output.get_tensor_view();
in.push_back(tensor_index.at(tv)); in.push_back({tensor_index.at(tv), tv});
} }
std::vector<size_t> out; std::vector<TensorViewInfo> out;
for (const descriptor::Output& output : node->get_outputs()) for (const descriptor::Output& output : node->get_outputs())
{ {
auto tv = output.get_tensor_view(); auto tv = output.get_tensor_view();
out.push_back(tensor_index.at(tv)); out.push_back({tensor_index.at(tv), tv});
} }
handler_it->second(node, this, function_map, in, out); handler_it->second(node, this, function_map, in, out);
} }
......
src/ngraph/runtime/external_function.hpp
View file @ c95c8b68
...@@ -20,6 +20,7 @@ ...@@ -20,6 +20,7 @@
#include <unordered_map> #include <unordered_map>
#include "ngraph/function.hpp" #include "ngraph/function.hpp"
#include "ngraph/runtime/tensor_view_info.hpp"
namespace ngraph namespace ngraph
{ {
...@@ -32,8 +33,8 @@ namespace ngraph ...@@ -32,8 +33,8 @@ namespace ngraph
using OpFunction = std::function<void(const ngraph::Node*, using OpFunction = std::function<void(const ngraph::Node*,
ExternalFunction*, ExternalFunction*,
FunctionMap&, FunctionMap&,
const std::vector<size_t>& inputs, const std::vector<TensorViewInfo>& inputs,
const std::vector<size_t>& outputs)>; const std::vector<TensorViewInfo>& outputs)>;
using OpMap = std::unordered_map<std::type_index, OpFunction>; using OpMap = std::unordered_map<std::type_index, OpFunction>;
public: public:
......
src/ngraph/runtime/instruction.hpp
View file @ c95c8b68
...@@ -14,17 +14,25 @@ ...@@ -14,17 +14,25 @@
#pragma once #pragma once
#include <memory>
#include "ngraph/runtime/call_frame.hpp"
namespace ngraph namespace ngraph
{ {
namespace runtime namespace runtime
{ {
class CallFrame; class CallFrame;
// An interpreter for an Op /// @brief An interpreter for an Op
///
/// The call_frame has a vector of instructions and calls execute on each instruction, passing it the call_frame.
/// Instructions get argument, result, and intermediate tensor views from the call frame. Instructions may also
/// set a flag in the call_frame to end execution, or adjust execution by modifying the position in the instruction vector.
class Instruction class Instruction
{ {
public: public:
virtual ~Instruction(){} virtual ~Instruction() {}
virtual void execute(CallFrame& call_frame) const = 0; virtual void execute(CallFrame& call_frame) const = 0;
}; };
} }
......
src/ngraph/runtime/tensor_view_info.hpp 0 → 100644
View file @ c95c8b68
// ----------------------------------------------------------------------------
// Copyright 2017 Nervana Systems Inc.
// 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
// ----------------------------------------------------------------------------
#pragma once
#include <memory>
namespace ngraph
{
namespace runtime
{
/// @brief Compile-time information about a tensor view.
///
/// Contains the offset of the tensor view in the call frame and the tensor descriptor.
class TensorViewInfo
{
public:
TensorViewInfo(size_t index,
const std::shared_ptr<ngraph::descriptor::TensorView>& descriptor)
: m_index(index)
, m_layout(descriptor->get_tensor_view_layout())
{
}
size_t get_index() const { return m_index; }
std::shared_ptr<ngraph::descriptor::layout::TensorViewLayout>
get_tensor_view_layout() const
{
return m_layout;
}
template <typename LT>
std::shared_ptr<LT> get_layout() const
{
return std::static_pointer_cast<LT>(m_layout);
}
protected:
size_t m_index;
std::shared_ptr<ngraph::descriptor::layout::TensorViewLayout> m_layout;
};
}
}
src/ngraph/runtime/utils.hpp
View file @ c95c8b68
...@@ -17,7 +17,6 @@ ...@@ -17,7 +17,6 @@
#include <memory> #include <memory>
#include <vector> #include <vector>
#include "ngraph/runtime/call_frame.hpp"
#include "ngraph/runtime/parameterized_tensor_view.hpp" #include "ngraph/runtime/parameterized_tensor_view.hpp"
#include "ngraph/runtime/tuple.hpp" #include "ngraph/runtime/tuple.hpp"
#include "ngraph/runtime/value.hpp" #include "ngraph/runtime/value.hpp"
......
test/CMakeLists.txt
View file @ c95c8b68
...@@ -32,7 +32,6 @@ set (SRC ...@@ -32,7 +32,6 @@ set (SRC
pass_liveness.cpp pass_liveness.cpp
pass_manager.cpp pass_manager.cpp
pass_memory_layout.cpp pass_memory_layout.cpp
runtime.cpp
shape.cpp shape.cpp
tensor.cpp tensor.cpp
test_tools.cpp test_tools.cpp
......
test/execute.cpp
View file @ c95c8b68
...@@ -165,19 +165,16 @@ TEST(execute, test_concat_matrix_colwise) ...@@ -165,19 +165,16 @@ TEST(execute, test_concat_matrix_colwise)
// Create some tensors for input/output // Create some tensors for input/output
auto a = ngraph::runtime::make_tensor<element::Float32>(shape_a); auto a = ngraph::runtime::make_tensor<element::Float32>(shape_a);
*a = vector<float>{2, 4, *a = vector<float>{2, 4, 8, 16};
8, 16};
auto b = ngraph::runtime::make_tensor<element::Float32>(shape_b); auto b = ngraph::runtime::make_tensor<element::Float32>(shape_b);
*b = vector<float>{ 1, 2, 4, *b = vector<float>{1, 2, 4, 8, 16, 32};
8,16,32};
auto c = ngraph::runtime::make_tensor<element::Float32>(shape_c); auto c = ngraph::runtime::make_tensor<element::Float32>(shape_c);
*c = vector<float>{ 2, 3, 5, *c = vector<float>{2, 3, 5, 7, 11, 13};
7,11,13};
auto result = ngraph::runtime::make_tensor<element::Float32>(shape_r); auto result = ngraph::runtime::make_tensor<element::Float32>(shape_r);
(*cf)({a,b,c}, {result}); (*cf)({a, b, c}, {result});
ASSERT_EQ((vector<float>{ 2, 4, 1, 2, 4, 2, 3, 5, ASSERT_EQ((vector<float>{2, 4, 1, 2, 4, 2, 3, 5, 8, 16, 8, 16, 32, 7, 11, 13}),
8, 16, 8, 16,32, 7, 11, 13}), result->get_vector()); result->get_vector());
} }
TEST(execute, test_concat_matrix_rowwise) TEST(execute, test_concat_matrix_rowwise)
...@@ -197,27 +194,16 @@ TEST(execute, test_concat_matrix_rowwise) ...@@ -197,27 +194,16 @@ TEST(execute, test_concat_matrix_rowwise)
// Create some tensors for input/output // Create some tensors for input/output
auto a = ngraph::runtime::make_tensor<element::Float32>(shape_a); auto a = ngraph::runtime::make_tensor<element::Float32>(shape_a);
*a = vector<float>{2, 4, *a = vector<float>{2, 4, 8, 16};
8, 16};
auto b = ngraph::runtime::make_tensor<element::Float32>(shape_b); auto b = ngraph::runtime::make_tensor<element::Float32>(shape_b);
*b = vector<float>{ 1, 2, *b = vector<float>{1, 2, 4, 8, 16, 32};
4, 8,
16,32};
auto c = ngraph::runtime::make_tensor<element::Float32>(shape_c); auto c = ngraph::runtime::make_tensor<element::Float32>(shape_c);
*c = vector<float>{ 2, 3, *c = vector<float>{2, 3, 5, 7, 11, 13};
5, 7,
11,13};
auto result = ngraph::runtime::make_tensor<element::Float32>(shape_r); auto result = ngraph::runtime::make_tensor<element::Float32>(shape_r);
(*cf)({a,b,c}, {result}); (*cf)({a, b, c}, {result});
ASSERT_EQ((vector<float>{ 2, 4, ASSERT_EQ((vector<float>{2, 4, 8, 16, 1, 2, 4, 8, 16, 32, 2, 3, 5, 7, 11, 13}),
8, 16, result->get_vector());
1, 2,
4, 8,
16, 32,
2, 3,
5, 7,
11, 13}), result->get_vector());
} }
TEST(execute, test_concat_vector) TEST(execute, test_concat_vector)
...@@ -237,15 +223,15 @@ TEST(execute, test_concat_vector) ...@@ -237,15 +223,15 @@ TEST(execute, test_concat_vector)
// Create some tensors for input/output // Create some tensors for input/output
auto a = ngraph::runtime::make_tensor<element::Float32>(shape_a); auto a = ngraph::runtime::make_tensor<element::Float32>(shape_a);
*a = vector<float>{2,4,8,16}; *a = vector<float>{2, 4, 8, 16};
auto b = ngraph::runtime::make_tensor<element::Float32>(shape_b); auto b = ngraph::runtime::make_tensor<element::Float32>(shape_b);
*b = vector<float>{1,2,4,8,16,32}; *b = vector<float>{1, 2, 4, 8, 16, 32};
auto c = ngraph::runtime::make_tensor<element::Float32>(shape_c); auto c = ngraph::runtime::make_tensor<element::Float32>(shape_c);
*c = vector<float>{18,19}; *c = vector<float>{18, 19};
auto result = ngraph::runtime::make_tensor<element::Float32>(shape_r); auto result = ngraph::runtime::make_tensor<element::Float32>(shape_r);
(*cf)({a,b,c}, {result}); (*cf)({a, b, c}, {result});
ASSERT_EQ((vector<float>{2,4,8,16,1,2,4,8,16,32,18,19}), result->get_vector()); ASSERT_EQ((vector<float>{2, 4, 8, 16, 1, 2, 4, 8, 16, 32, 18, 19}), result->get_vector());
} }
TEST(execute, test_divide) TEST(execute, test_divide)
...@@ -311,13 +297,13 @@ TEST(execute, test_dot1d) ...@@ -311,13 +297,13 @@ TEST(execute, test_dot1d)
*b = vector<float>{1, 2, 4, 8}; *b = vector<float>{1, 2, 4, 8};
auto result = ngraph::runtime::make_tensor<element::Float32>(shape_r); auto result = ngraph::runtime::make_tensor<element::Float32>(shape_r);
(*cf)({a,b}, {result}); (*cf)({a, b}, {result});
ASSERT_EQ((vector<float>{170}), result->get_vector()); ASSERT_EQ((vector<float>{170}), result->get_vector());
} }
TEST(execute, test_dot2d) TEST(execute, test_dot2d)
{ {
auto shape = Shape{2,2}; auto shape = Shape{2, 2};
auto A = make_shared<op::Parameter>(element::Float32::element_type(), shape); auto A = make_shared<op::Parameter>(element::Float32::element_type(), shape);
auto B = make_shared<op::Parameter>(element::Float32::element_type(), shape); auto B = make_shared<op::Parameter>(element::Float32::element_type(), shape);
auto shape_r = Shape{2,2}; auto shape_r = Shape{2,2};
...@@ -329,16 +315,13 @@ TEST(execute, test_dot2d) ...@@ -329,16 +315,13 @@ TEST(execute, test_dot2d)
// Create some tensors for input/output // Create some tensors for input/output
auto a = ngraph::runtime::make_tensor<element::Float32>(shape); auto a = ngraph::runtime::make_tensor<element::Float32>(shape);
*a = vector<float>{1, 2, *a = vector<float>{1, 2, 3, 4};
3, 4};
auto b = ngraph::runtime::make_tensor<element::Float32>(shape); auto b = ngraph::runtime::make_tensor<element::Float32>(shape);
*b = vector<float>{5, 6, *b = vector<float>{5, 6, 7, 8};
7, 8};
auto result = ngraph::runtime::make_tensor<element::Float32>(shape_r); auto result = ngraph::runtime::make_tensor<element::Float32>(shape_r);
(*cf)({a,b}, {result}); (*cf)({a, b}, {result});
ASSERT_EQ((vector<float>{19,22, ASSERT_EQ((vector<float>{19, 22, 43, 50}), result->get_vector());
43,50}), result->get_vector());
} }
TEST(execute, test_dot_scalar_tensor_arg0) TEST(execute, test_dot_scalar_tensor_arg0)
...@@ -471,10 +454,14 @@ TEST(execute, test_log) ...@@ -471,10 +454,14 @@ TEST(execute, test_log)
// Create some tensors for input/output // Create some tensors for input/output
auto a = ngraph::runtime::make_tensor<element::Float32>(shape); auto a = ngraph::runtime::make_tensor<element::Float32>(shape);
*a = vector<float>{expf(1), expf(2), expf(3), expf(4), expf(5), expf(6), expf(7), expf(8)}; *a = vector<float>{expf(1), expf(2), expf(3), expf(4), expf(5), expf(6), expf(7), expf(8)};
vector<float> loga;
for (auto elt : a->get_vector()){
loga.push_back(logf(elt));
}
auto result = ngraph::runtime::make_tensor<element::Float32>(shape); auto result = ngraph::runtime::make_tensor<element::Float32>(shape);
(*cf)({a}, {result}); (*cf)({a}, {result});
ASSERT_EQ((vector<float>{1, 2, 3, 4, 5, 6, 7, 8}), result->get_vector()); ASSERT_EQ(loga, result->get_vector());
} }
TEST(execute, test_maximum) TEST(execute, test_maximum)
...@@ -619,7 +606,7 @@ TEST(execute, test_tensor_constant) ...@@ -619,7 +606,7 @@ TEST(execute, test_tensor_constant)
auto result = ngraph::runtime::make_tensor<element::Float32>(shape); auto result = ngraph::runtime::make_tensor<element::Float32>(shape);
(*cf)({}, {result}); (*cf)({}, {result});
ASSERT_EQ((vector<float>{1,2,3,4,5,6,7,8}), result->get_vector()); ASSERT_EQ((vector<float>{1, 2, 3, 4, 5, 6, 7, 8}), result->get_vector());
} }
TEST(execute, test_tensor_constant_with_op) TEST(execute, test_tensor_constant_with_op)
...@@ -637,7 +624,7 @@ TEST(execute, test_tensor_constant_with_op) ...@@ -637,7 +624,7 @@ TEST(execute, test_tensor_constant_with_op)
auto result = ngraph::runtime::make_tensor<element::Float32>(shape); auto result = ngraph::runtime::make_tensor<element::Float32>(shape);
(*cf)({}, {result}); (*cf)({}, {result});
ASSERT_EQ((vector<float>{1,2,3,4,5,6,7,8}), result->get_vector()); ASSERT_EQ((vector<float>{1, 2, 3, 4, 5, 6, 7, 8}), result->get_vector());
} }
TEST(execute, test_function_call) TEST(execute, test_function_call)
......
test/runtime.cpp deleted 100644 → 0
View file @ eec7201d
// ----------------------------------------------------------------------------
// Copyright 2017 Nervana Systems Inc.
// 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
// ----------------------------------------------------------------------------
#include <memory>
#include <vector>
#include "gtest/gtest.h"
#include "ngraph/ngraph.hpp"
#include "ngraph/runtime/eigen/add.hpp"
#include "ngraph/runtime/eigen/multiply.hpp"
#include "ngraph/runtime/eigen/return.hpp"
using namespace std;
using namespace ngraph;
using namespace ngraph::runtime;
namespace ngeigen = ngraph::runtime::eigen;
TEST(runtime, test_add)
{
auto x = ngraph::runtime::make_tensor<element::Float32>(Shape{2, 2});
x->get_vector() = {1, 2, 3, 4};
auto y = ngraph::runtime::make_tensor<element::Float32>(Shape{2, 2});
y->get_vector() = {5, 6, 7, 8};
auto z = ngraph::runtime::make_tensor<element::Float32>(Shape{2, 2});
ngraph::runtime::eigen::add(x, y, z);
ASSERT_EQ((vector<float>{6, 8, 10, 12}), z->get_vector());
}
TEST(runtime, test_multiply)
{
auto x = ngraph::runtime::make_tensor<element::Float32>(Shape{2, 2});
x->get_vector() = {1, 2, 3, 4};
auto y = ngraph::runtime::make_tensor<element::Float32>(Shape{2, 2});
y->get_vector() = {5, 6, 7, 8};
auto z = ngraph::runtime::make_tensor<element::Float32>(Shape{2, 2});
ngraph::runtime::eigen::multiply(x, y, z);
ASSERT_EQ((vector<float>{5, 12, 21, 32}), z->get_vector());
}
TEST(runtime, test_add_multiply)
{
// Inputs:
// 0 : a
// 1 : b
// 2 : c
// Outputs:
// 3 : result
// Temporaries
// 4: t0
auto instructions = make_shared<std::vector<std::shared_ptr<ngraph::runtime::Instruction>>>();
// a + b -> t0
instructions->push_back(make_shared<ngeigen::AddInstruction<element::Float32>>(0, 1, 4));
// t0 * c -> result
instructions->push_back(make_shared<ngeigen::MultiplyInstruction<element::Float32>>(4, 2, 3));
instructions->push_back(make_shared<ngeigen::ReturnInstruction>());
runtime::CallFrame cf{
3, 1, {ngraph::runtime::make_tensor<element::Float32>(Shape{2, 2})}, 0, instructions};
// Create some tensors for input/output
auto a = ngraph::runtime::make_tensor<element::Float32>(Shape{2, 2});
a->get_vector() = {1, 2, 3, 4};
auto b = ngraph::runtime::make_tensor<element::Float32>(Shape{2, 2});
b->get_vector() = {5, 6, 7, 8};
auto c = ngraph::runtime::make_tensor<element::Float32>(Shape{2, 2});
c->get_vector() = {9, 10, 11, 12};
auto result = ngraph::runtime::make_tensor<element::Float32>(Shape{2, 2});
cf({a, b, c}, {result});
ASSERT_EQ((vector<float>{54, 80, 110, 144}), result->get_vector());
cf({b, a, c}, {result});
ASSERT_EQ((vector<float>{54, 80, 110, 144}), result->get_vector());
cf({a, c, b}, {result});
ASSERT_EQ((vector<float>{50, 72, 98, 128}), result->get_vector());
}
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