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Commit 5b405c16 authored by Adam Procter's avatar Adam Procter
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Merge remote-tracking branch 'origin' into bob/pass_ptr

parents cc98a99c 96ae6fdb
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Showing with 353 additions and 105 deletions
src/ngraph/ops/constant.cpp
View file @ 5b405c16
......@@ -16,10 +16,35 @@
using namespace ngraph::op;
void ScalarConstantBase::propagate_types()
void ConstantBase::propagate_types()
{
}
void TensorConstantBase::propagate_types()
template <typename ET>
void check_value_strings(const std::vector<std::string>& value_strings)
{
auto result = ET::read(value_strings);
}
void Constant::propagate_types()
{
// No actual type propagation is done here; however, we check the number of value strings and
// also call check_value_strings just to make sure the result will be parseable at compile
// time. (It will throw an exception if not.)
auto tvt = std::dynamic_pointer_cast<const TensorViewType>(get_value_type());
if (nullptr == tvt)
{
throw ngraph_error("Constant does not have tensor view type");
}
auto shape = tvt->get_shape();
if (ngraph::shape_size(shape) != m_value_strings.size())
{
throw ngraph_error("Constant does not have the expected number of literals");
}
auto& et = tvt->get_element_type();
FUNCTION_ON_ELEMENT_TYPE(
et, "Constant has unhandled element type", check_value_strings, m_value_strings);
}
src/ngraph/ops/constant.hpp
View file @ 5b405c16
......@@ -24,11 +24,11 @@ namespace ngraph
{
namespace op
{
// Defines methods to all constant scalars
class ScalarConstantBase : public Node
// Defines methods to all constants
class ConstantBase : public Node
{
protected:
ScalarConstantBase(const std::shared_ptr<TensorViewType>& type)
ConstantBase(const std::shared_ptr<TensorViewType>& type)
: Node({}, type)
{
}
......@@ -36,10 +36,9 @@ namespace ngraph
virtual void propagate_types() override;
};
// Implement a constant scalar for each element type.
// The static make method takes a
// Implement a constant tensor for each element type.
template <typename T>
class ScalarConstant : public ScalarConstantBase
class ParameterizedConstant : public ConstantBase
{
public:
// The ngraph element type
......@@ -47,13 +46,15 @@ namespace ngraph
// The C++ type that holds the element type
using type = typename T::type;
ScalarConstant(typename T::type value)
: ScalarConstantBase(std::make_shared<TensorViewType>(T::element_type(), Shape{}))
ParameterizedConstant(
const Shape& shape,
typename std::shared_ptr<ngraph::runtime::ParameterizedTensorView<T>>& value)
: ConstantBase(std::make_shared<TensorViewType>(T::element_type(), shape))
, m_value(value)
{
}
virtual std::string description() const override { return "ScalarConstant"; }
virtual std::string description() const override { return "ParameterizedConstant"; }
virtual std::string get_node_id() const override
{
std::stringstream ss;
......@@ -61,48 +62,41 @@ namespace ngraph
return ss.str();
}
type get_value() const { return m_value; }
protected:
typename T::type m_value;
};
using Float32ScalarConstant = ScalarConstant<element::Float32>;
using Int8ScalarConstant = ScalarConstant<element::Int8>;
using Int32ScalarConstant = ScalarConstant<element::Int32>;
using Int64ScalarConstant = ScalarConstant<element::Int64>;
using UInt8ScalarConstant = ScalarConstant<element::UInt8>;
using UInt32ScalarConstant = ScalarConstant<element::UInt32>;
using UInt64ScalarConstant = ScalarConstant<element::UInt64>;
// Defines methods to all constant tensors
class TensorConstantBase : public Node
{
protected:
TensorConstantBase(const std::shared_ptr<TensorViewType>& type)
: Node({}, type)
typename std::shared_ptr<ngraph::runtime::ParameterizedTensorView<T>> get_value() const
{
return m_value;
}
virtual void propagate_types() override;
protected:
std::shared_ptr<ngraph::runtime::ParameterizedTensorView<T>> m_value;
};
// Implement a constant tensor for each element type.
template <typename T>
class TensorConstant : public TensorConstantBase
using Float32Constant = ParameterizedConstant<element::Float32>;
using Int8Constant = ParameterizedConstant<element::Int8>;
using Int32Constant = ParameterizedConstant<element::Int32>;
using Int64Constant = ParameterizedConstant<element::Int64>;
using UInt8Constant = ParameterizedConstant<element::UInt8>;
using UInt32Constant = ParameterizedConstant<element::UInt32>;
using UInt64Constant = ParameterizedConstant<element::UInt64>;
class Constant : public ConstantBase
{
public:
// The ngraph element type
using element_type = T;
// The C++ type that holds the element type
using type = typename T::type;
Constant(const element::Type& et,
const Shape& shape,
const std::vector<std::string>& value_strings)
: ConstantBase(std::make_shared<TensorViewType>(et, shape))
, m_value_strings(value_strings)
{
}
TensorConstant(const Shape& shape)
: TensorConstantBase(std::make_shared<TensorViewType>(T::element_type(), shape))
, m_value(ngraph::runtime::make_tensor<T>(shape))
Constant(const element::Type& et, const Shape& shape, const std::string& value_string)
: ConstantBase(std::make_shared<TensorViewType>(et, shape))
, m_value_strings(ngraph::shape_size(shape), value_string)
{
}
virtual std::string description() const override { return "TensorConstant"; }
virtual std::string description() const override { return "Constant"; }
virtual std::string get_node_id() const override
{
std::stringstream ss;
......@@ -110,21 +104,11 @@ namespace ngraph
return ss.str();
}
typename std::shared_ptr<ngraph::runtime::ParameterizedTensorView<T>> get_value() const
{
return m_value;
}
const std::vector<std::string>& get_value_strings() const { return m_value_strings; }
virtual void propagate_types() override;
protected:
std::shared_ptr<ngraph::runtime::ParameterizedTensorView<T>> m_value;
const std::vector<std::string> m_value_strings;
};
using Float32TensorConstant = TensorConstant<element::Float32>;
using Int8TensorConstant = TensorConstant<element::Int8>;
using Int32TensorConstant = TensorConstant<element::Int32>;
using Int64TensorConstant = TensorConstant<element::Int64>;
using UInt8TensorConstant = TensorConstant<element::UInt8>;
using UInt32TensorConstant = TensorConstant<element::UInt32>;
using UInt64TensorConstant = TensorConstant<element::UInt64>;
}
}
src/ngraph/runtime/ngvm/eigen/acos.hpp
View file @ 5b405c16
......@@ -51,4 +51,4 @@ namespace ngraph
}
}
}
}
\ No newline at end of file
}
src/ngraph/runtime/ngvm/eigen/asin.hpp
View file @ 5b405c16
......@@ -51,4 +51,4 @@ namespace ngraph
}
}
}
}
\ No newline at end of file
}
src/ngraph/runtime/ngvm/eigen/atan.hpp
View file @ 5b405c16
......@@ -51,4 +51,4 @@ namespace ngraph
}
}
}
}
\ No newline at end of file
}
src/ngraph/runtime/ngvm/eigen/cos.hpp
View file @ 5b405c16
......@@ -51,4 +51,4 @@ namespace ngraph
}
}
}
}
\ No newline at end of file
}
src/ngraph/runtime/ngvm/eigen/cosh.hpp
View file @ 5b405c16
......@@ -51,4 +51,4 @@ namespace ngraph
}
}
}
}
\ No newline at end of file
}
src/ngraph/runtime/ngvm/eigen/sinh.hpp
View file @ 5b405c16
......@@ -51,4 +51,4 @@ namespace ngraph
}
}
}
}
\ No newline at end of file
}
src/ngraph/runtime/ngvm/eigen/tan.hpp
View file @ 5b405c16
......@@ -51,4 +51,4 @@ namespace ngraph
}
}
}
}
\ No newline at end of file
}
src/ngraph/runtime/ngvm/eigen/tanh.hpp
View file @ 5b405c16
......@@ -51,4 +51,4 @@ namespace ngraph
}
}
}
}
\ No newline at end of file
}
src/ngraph/runtime/ngvm/external_function.cpp
View file @ 5b405c16
......@@ -315,15 +315,10 @@ ExternalFunction::ExternalFunction(const std::shared_ptr<ngraph::Function>& func
#define REGISTER_CONSTANT_INSTRUCTIONS(T) \
{ \
REGISTER_INSTRUCTION( \
op::ScalarConstant<T>, \
eigen::ConstantInstruction<T>, \
std::vector<T::type>{dynamic_cast<const op::ScalarConstant<T>*>(n)->get_value()}, \
out[0]); \
REGISTER_INSTRUCTION( \
op::TensorConstant<T>, \
op::ParameterizedConstant<T>, \
eigen::ConstantInstruction<T>, \
std::vector<T::type>{ \
dynamic_cast<const op::TensorConstant<T>*>(n)->get_value()->get_vector()}, \
dynamic_cast<const op::ParameterizedConstant<T>*>(n)->get_value()->get_vector()}, \
out[0]); \
}
......@@ -371,6 +366,23 @@ ExternalFunction::OpMap& ExternalFunction::get_op_map()
REGISTER_NUMERIC_BINOP(op::Multiply, eigen::MultiplyInstruction);
REGISTER_NUMERIC_BINOP(op::Subtract, eigen::SubtractInstruction);
REGISTER_TO_OP_MAP(op::Constant)
{
auto c = static_cast<const op::Constant*>(n);
auto c_tensor_type = dynamic_pointer_cast<const TensorViewType>(c->get_value_type());
assert(nullptr != c_tensor_type);
auto& c_element_type = c_tensor_type->get_element_type();
auto c_value_strings = c->get_value_strings();
#define M_REGISTER_POLYMORPHIC_CONSTANT(ET) \
ef->get_instructions()->push_back( \
make_shared<eigen::ConstantInstruction<ET>>(ET::read(c_value_strings), out[0]));
DO_ON_ELEMENT_TYPE(c_element_type,
"Constant has unhandled element type",
M_REGISTER_POLYMORPHIC_CONSTANT);
};
REGISTER_POLYMORPHIC_BINOP(op::Equal, eigen::EqualInstruction);
REGISTER_POLYMORPHIC_BINOP(op::NotEqual, eigen::NotEqualInstruction);
......
src/ngraph/types/element_type.hpp
View file @ 5b405c16
......@@ -116,6 +116,35 @@ namespace ngraph
{
return std::make_shared<runtime::ParameterizedTensorView<TraitedType<T>>>(shape);
}
static T read(const std::string& s)
{
T result;
std::stringstream ss;
ss << s;
ss >> result;
// Check that (1) parsing succeeded and (2) the entire string was used.
if (ss.fail() || ss.rdbuf()->in_avail() != 0)
{
throw ngraph_error("Could not parse literal");
}
return result;
}
static std::vector<T> read(const std::vector<std::string>& ss)
{
std::vector<T> result;
for (auto s : ss)
{
result.push_back(read(s));
}
return result;
}
};
NGRAPH_DEFINE_TRAITED_TYPE_NAME(char)
......@@ -143,3 +172,23 @@ namespace ngraph
using UInt64 = TraitedType<uint64_t>;
}
}
//
// Utility macro for dispatching an element type-templated function at runtime.
//
// clang-format off
// Sorry, but you really don't want to see what clang-format does to this thing. :)
#define FUNCTION_ON_ELEMENT_TYPE(et, err_msg, f, ...) \
( \
((et) == element::Bool::element_type()) ? (f<element::Bool>(__VA_ARGS__)) : \
((et) == element::Float32::element_type()) ? (f<element::Float32>(__VA_ARGS__)) : \
((et) == element::Int8::element_type()) ? (f<element::Int8>(__VA_ARGS__)) : \
((et) == element::Int32::element_type()) ? (f<element::Int32>(__VA_ARGS__)) : \
((et) == element::Int64::element_type()) ? (f<element::Int64>(__VA_ARGS__)) : \
((et) == element::UInt8::element_type()) ? (f<element::UInt8>(__VA_ARGS__)) : \
((et) == element::UInt32::element_type()) ? (f<element::UInt32>(__VA_ARGS__)) : \
((et) == element::UInt64::element_type()) ? (f<element::UInt64>(__VA_ARGS__)) : \
(throw ngraph_error(err_msg)) \
)
// clang-format on
test/build_graph.cpp
View file @ 5b405c16
......@@ -80,23 +80,22 @@ TEST(build_graph, node_comparison)
TEST(build_graph, literal)
{
// float scalar from a float
//auto float0 = FloatScalarConstant::make(3.0);
auto float0 = make_shared<op::Float32ScalarConstant>(3.0);
//auto float0 = FloatConstant::make(3.0);
auto float_t = ngraph::runtime::make_tensor<element::Float32>(Shape{});
(*float_t) = std::vector<float>{3.0};
auto float0 = make_shared<op::Float32Constant>(Shape{}, float_t);
auto float_scalar_type = make_shared<TensorViewType>(element::Float32::element_type(), Shape{});
ASSERT_EQ(float0->get_value(), 3.0);
ASSERT_EQ(float0->get_value()->get_vector(), std::vector<float>{3.0});
ASSERT_EQ(*float0->get_value_type(), *float_scalar_type);
auto d = make_shared<op::Dot>(float0, float0);
ASSERT_EQ(d->get_arguments().at(0), float0);
ASSERT_EQ(d->get_arguments().at(1), float0);
// float scalar from an int
auto float1 = make_shared<op::Float32ScalarConstant>(3);
ASSERT_EQ(float1->get_value(), 3);
ASSERT_EQ(*float1->get_value_type(), *float_scalar_type);
auto int32_0 = make_shared<op::Int32ScalarConstant>(3.0);
auto int32_t = ngraph::runtime::make_tensor<element::Int32>(Shape{});
(*int32_t) = std::vector<int>{3};
auto int32_0 = make_shared<op::Int32Constant>(Shape{}, int32_t);
auto int32_scalar_type = make_shared<TensorViewType>(element::Int32::element_type(), Shape{});
ASSERT_EQ(int32_0->get_value(), 3);
ASSERT_EQ(int32_0->get_value()->get_vector(), std::vector<int>{3});
ASSERT_EQ(*int32_0->get_value_type(), *int32_scalar_type);
ASSERT_NE(*int32_0->get_value_type(), *float_scalar_type);
}
......@@ -104,8 +103,9 @@ TEST(build_graph, literal)
TEST(build_graph, tensor)
{
// float scalar from a float
//auto float0 = FloatScalarConstant::make(3.0);
auto float0 = make_shared<op::Float32TensorConstant>(Shape{2, 3});
//auto float0 = FloatConstant::make(3.0);
auto float_t = ngraph::runtime::make_tensor<element::Float32>(Shape{2, 3});
auto float0 = make_shared<op::Float32Constant>(Shape{2, 3}, float_t);
auto float_tensor_type =
make_shared<TensorViewType>(element::Float32::element_type(), Shape{2, 3});
ASSERT_EQ(*float0->get_value_type(), *float_tensor_type);
......@@ -113,7 +113,8 @@ TEST(build_graph, tensor)
ASSERT_EQ(d->get_arguments().at(0), float0);
ASSERT_EQ(d->get_arguments().at(1), float0);
auto int32_0 = make_shared<op::Int32TensorConstant>(Shape{3, 5});
auto int32_t = ngraph::runtime::make_tensor<element::Int32>(Shape{3, 5});
auto int32_0 = make_shared<op::Int32Constant>(Shape{3, 5}, int32_t);
auto int32_tensor_type =
make_shared<TensorViewType>(element::Int32::element_type(), Shape{3, 5});
ASSERT_EQ(*int32_0->get_value_type(), *int32_tensor_type);
......
test/execute.cpp
View file @ 5b405c16
......@@ -997,7 +997,9 @@ TEST(execute, subtract)
TEST(execute, scalar_constant)
{
auto shape = Shape{};
auto A = make_shared<op::ScalarConstant<element::Float32>>(-3.0f);
auto t = ngraph::runtime::make_tensor<element::Float32>(shape);
(*t) = std::vector<float>{-3.0f};
auto A = make_shared<op::ParameterizedConstant<element::Float32>>(shape, t);
auto rt = make_shared<TensorViewType>(element::Float32::element_type(), shape);
auto f = make_shared<Function>(A, rt, op::Parameters{});
......@@ -1016,8 +1018,9 @@ TEST(execute, scalar_constant)
TEST(execute, tensor_constant)
{
auto shape = Shape{2, 2, 2};
auto A = make_shared<op::TensorConstant<element::Float32>>(shape);
A->get_value()->get_vector() = {1, 2, 3, 4, 5, 6, 7, 8};
auto t = ngraph::runtime::make_tensor<element::Float32>(shape);
(*t) = std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8};
auto A = make_shared<op::ParameterizedConstant<element::Float32>>(shape, t);
auto rt = make_shared<TensorViewType>(element::Float32::element_type(), shape);
auto f = make_shared<Function>(A, rt, op::Parameters{});
......@@ -1036,8 +1039,9 @@ TEST(execute, tensor_constant)
TEST(execute, tensor_constant_with_op)
{
auto shape = Shape{2, 2, 2};
auto A = make_shared<op::TensorConstant<element::Float32>>(shape);
A->get_value()->get_vector() = {-1, 2, 3, -4, 5, -6, -7, 8};
auto t = ngraph::runtime::make_tensor<element::Float32>(shape);
(*t) = std::vector<float>{-1, 2, 3, -4, 5, -6, -7, 8};
auto A = make_shared<op::ParameterizedConstant<element::Float32>>(shape, t);
auto rt = make_shared<TensorViewType>(element::Float32::element_type(), shape);
auto f = make_shared<Function>(make_shared<op::Abs>(A), rt, op::Parameters{});
......@@ -1882,7 +1886,7 @@ TEST(execute, sin)
auto result = backend->make_parameterized_tensor_view<element::Float32>(shape);
std::transform(
input.begin(), input.end(), input.begin(), [](float f) -> float { return sinf(f); });
input.begin(), input.end(), input.begin(), [](float x) -> float { return sinf(x); });
(*cf)({a}, {result});
ASSERT_EQ(input, result->get_vector());
......@@ -1908,7 +1912,7 @@ TEST(execute, cos)
auto result = backend->make_parameterized_tensor_view<element::Float32>(shape);
std::transform(
input.begin(), input.end(), input.begin(), [](float f) -> float { return cosf(f); });
input.begin(), input.end(), input.begin(), [](float x) -> float { return cosf(x); });
(*cf)({a}, {result});
ASSERT_EQ(input, result->get_vector());
......@@ -1934,7 +1938,7 @@ TEST(execute, tan)
auto result = backend->make_parameterized_tensor_view<element::Float32>(shape);
std::transform(
input.begin(), input.end(), input.begin(), [](float f) -> float { return tanf(f); });
input.begin(), input.end(), input.begin(), [](float x) -> float { return tanf(x); });
(*cf)({a}, {result});
ASSERT_EQ(input, result->get_vector());
......@@ -1959,7 +1963,7 @@ TEST(execute, asin)
auto result = backend->make_parameterized_tensor_view<element::Float32>(shape);
std::transform(
input.begin(), input.end(), input.begin(), [](float f) -> float { return asinf(f); });
input.begin(), input.end(), input.begin(), [](float x) -> float { return asinf(x); });
(*cf)({a}, {result});
ASSERT_EQ(input, result->get_vector());
......@@ -1984,7 +1988,7 @@ TEST(execute, acos)
auto result = backend->make_parameterized_tensor_view<element::Float32>(shape);
std::transform(
input.begin(), input.end(), input.begin(), [](float f) -> float { return acosf(f); });
input.begin(), input.end(), input.begin(), [](float x) -> float { return acosf(x); });
(*cf)({a}, {result});
ASSERT_EQ(input, result->get_vector());
......@@ -2009,7 +2013,7 @@ TEST(execute, atan)
auto result = backend->make_parameterized_tensor_view<element::Float32>(shape);
std::transform(
input.begin(), input.end(), input.begin(), [](float f) -> float { return atanf(f); });
input.begin(), input.end(), input.begin(), [](float x) -> float { return atanf(x); });
(*cf)({a}, {result});
ASSERT_EQ(input, result->get_vector());
......@@ -2034,7 +2038,7 @@ TEST(execute, sinh)
auto result = backend->make_parameterized_tensor_view<element::Float32>(shape);
std::transform(
input.begin(), input.end(), input.begin(), [](float f) -> float { return sinhf(f); });
input.begin(), input.end(), input.begin(), [](float x) -> float { return sinhf(x); });
(*cf)({a}, {result});
ASSERT_EQ(input, result->get_vector());
......@@ -2059,7 +2063,7 @@ TEST(execute, cosh)
auto result = backend->make_parameterized_tensor_view<element::Float32>(shape);
std::transform(
input.begin(), input.end(), input.begin(), [](float f) -> float { return coshf(f); });
input.begin(), input.end(), input.begin(), [](float x) -> float { return coshf(x); });
(*cf)({a}, {result});
ASSERT_EQ(input, result->get_vector());
......@@ -2084,7 +2088,7 @@ TEST(execute, tanh)
auto result = backend->make_parameterized_tensor_view<element::Float32>(shape);
std::transform(
input.begin(), input.end(), input.begin(), [](float f) -> float { return tanhf(f); });
input.begin(), input.end(), input.begin(), [](float x) -> float { return tanhf(x); });
(*cf)({a}, {result});
ASSERT_EQ(input, result->get_vector());
......@@ -2184,3 +2188,89 @@ TEST(execute, slice_vector)
(*cf)({a}, {result});
ASSERT_EQ((vector<float>{2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13}), result->get_vector());
}
TEST(execute, scalar_constant_float32)
{
auto rt = make_shared<TensorViewType>(element::Float32::element_type(), Shape{});
auto r = make_shared<op::Constant>(element::Float32::element_type(), Shape{}, "4.8");
auto f = make_shared<Function>(r, rt, op::Parameters{});
auto manager = runtime::Manager::get("NGVM");
auto external = manager->compile(f);
auto backend = manager->allocate_backend();
auto cf = backend->make_call_frame(external);
// Create some tensors for input/output
auto result = ngraph::runtime::make_tensor<element::Float32>(Shape{});
(*cf)({}, {result});
ASSERT_EQ(vector<float>{std::strtof("4.8", NULL)}, result->get_vector());
}
TEST(execute, scalar_constant_int64)
{
auto rt = make_shared<TensorViewType>(element::Int64::element_type(), Shape{});
auto r = make_shared<op::Constant>(element::Int64::element_type(), Shape{}, "2112");
auto f = make_shared<Function>(r, rt, op::Parameters{});
auto manager = runtime::Manager::get("NGVM");
auto external = manager->compile(f);
auto backend = manager->allocate_backend();
auto cf = backend->make_call_frame(external);
// Create some tensors for input/output
auto result = ngraph::runtime::make_tensor<element::Int64>(Shape{});
(*cf)({}, {result});
ASSERT_EQ(vector<element::Int64::type>{std::strtol("2112", NULL, 10)}, result->get_vector());
}
TEST(execute, tensor_constant_float32)
{
auto shape = Shape{2, 2};
auto rt = make_shared<TensorViewType>(element::Float32::element_type(), shape);
auto r = make_shared<op::Constant>(element::Float32::element_type(),
shape,
std::vector<std::string>{"4.8", "4.7", "-5.3", "0"});
auto f = make_shared<Function>(r, rt, op::Parameters{});
auto manager = runtime::Manager::get("NGVM");
auto external = manager->compile(f);
auto backend = manager->allocate_backend();
auto cf = backend->make_call_frame(external);
// Create some tensors for input/output
auto result = ngraph::runtime::make_tensor<element::Float32>(shape);
(*cf)({}, {result});
ASSERT_EQ((vector<float>{std::strtof("4.8", NULL),
std::strtof("4.7", NULL),
std::strtof("-5.3", NULL),
std::strtof("0", NULL)}),
result->get_vector());
}
TEST(execute, tensor_constant_int64)
{
auto shape = Shape{2, 2};
auto rt = make_shared<TensorViewType>(element::Int64::element_type(), shape);
auto r = make_shared<op::Constant>(element::Int64::element_type(),
shape,
std::vector<std::string>{"2112", "1848", "1776", "1964"});
auto f = make_shared<Function>(r, rt, op::Parameters{});
auto manager = runtime::Manager::get("NGVM");
auto external = manager->compile(f);
auto backend = manager->allocate_backend();
auto cf = backend->make_call_frame(external);
// Create some tensors for input/output
auto result = ngraph::runtime::make_tensor<element::Int64>(shape);
(*cf)({}, {result});
ASSERT_EQ((vector<element::Int64::type>{std::strtol("2112", NULL, 10),
std::strtol("1848", NULL, 10),
std::strtol("1776", NULL, 10),
std::strtol("1964", NULL, 10)}),
result->get_vector());
}
test/type_prop.cpp
View file @ 5b405c16
......@@ -1517,3 +1517,98 @@ TEST(type_prop, slice_deduce_matrix_upper_extra)
FAIL() << "Deduced type check failed for unexpected reason";
}
}
TEST(type_prop, scalar_constant_deduce_float32)
{
auto c = make_shared<op::Constant>(element::Float32::element_type(), Shape{}, "208");
c->propagate_types();
ASSERT_EQ(*(c->get_value_type()), TensorViewType(element::Float32::element_type(), Shape{}));
}
TEST(type_prop, scalar_constant_deduce_bool)
{
auto c = make_shared<op::Constant>(element::Bool::element_type(), Shape{}, "1");
c->propagate_types();
ASSERT_EQ(*(c->get_value_type()), TensorViewType(element::Bool::element_type(), Shape{}));
}
TEST(type_prop, tensor_constant_deduce_float32)
{
auto c = make_shared<op::Constant>(element::Float32::element_type(),
Shape{2, 2},
std::vector<std::string>{"208", "208", "208", "208"});
c->propagate_types();
ASSERT_EQ(*(c->get_value_type()),
TensorViewType(element::Float32::element_type(), Shape{2, 2}));
}
TEST(type_prop, tensor_constant_deduce_bool)
{
auto c = make_shared<op::Constant>(
element::Bool::element_type(), Shape{2, 2}, std::vector<std::string>{"1", "1", "1", "1"});
c->propagate_types();
ASSERT_EQ(*(c->get_value_type()), TensorViewType(element::Bool::element_type(), Shape{2, 2}));
}
TEST(type_prop, tensor_constant_bad_parse)
{
auto c = make_shared<op::Constant>(element::Bool::element_type(),
Shape{2, 2},
std::vector<std::string>{"1", "grunk", "1", "1"});
try
{
c->propagate_types();
// Should have thrown, so fail if it didn't
FAIL() << "Bad literal parse not detected";
}
catch (const ngraph_error& error)
{
EXPECT_EQ(error.what(), std::string("Could not parse literal"));
}
catch (...)
{
FAIL() << "Deduced type check failed for unexpected reason";
}
}
TEST(type_prop, tensor_constant_bad_parse_float_for_int)
{
auto c = make_shared<op::Constant>(element::Int32::element_type(),
Shape{2, 2},
std::vector<std::string>{"1", "2.7", "1", "1"});
try
{
c->propagate_types();
// Should have thrown, so fail if it didn't
FAIL() << "Bad literal parse not detected";
}
catch (const ngraph_error& error)
{
EXPECT_EQ(error.what(), std::string("Could not parse literal"));
}
catch (...)
{
FAIL() << "Deduced type check failed for unexpected reason";
}
}
TEST(type_prop, tensor_constant_bad_count)
{
auto c = make_shared<op::Constant>(
element::Bool::element_type(), Shape{2, 2}, std::vector<std::string>{"1", "1", "1"});
try
{
c->propagate_types();
// Should have thrown, so fail if it didn't
FAIL() << "Incorrect number of literals not detected";
}
catch (const ngraph_error& error)
{
EXPECT_EQ(error.what(),
std::string("Constant does not have the expected number of literals"));
}
catch (...)
{
FAIL() << "Deduced type check failed for unexpected reason";
}
}
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