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Test calculation output shape for Broadcast op, relax restrictions fo…
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…r partially dynamic input data (#1247)
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Mateusz Bencer authored Aug 10, 2020
1 parent ffe8599 commit ae48d9d
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Showing 5 changed files with 638 additions and 45 deletions.
44 changes: 32 additions & 12 deletions ngraph/src/ngraph/op/broadcast.cpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -90,15 +90,21 @@ std::pair<bool, AxisSet> op::v3::Broadcast::get_broadcast_axes() const

namespace
{
PartialShape
get_result_shape_bidirectional(const Node* this_ptr, Shape& arg_shape, Shape& target_shape)
PartialShape get_result_shape_bidirectional(const Node* this_ptr,
const PartialShape& arg_shape,
Shape& target_shape)
{
if (arg_shape.rank().is_dynamic())
{
return PartialShape::dynamic();
}
auto arg_shape_vec = static_cast<std::vector<Dimension>>(arg_shape);
PartialShape result_shape;
// Add left padding to shorter target or argument shape
const auto target_padded_rank = std::max(arg_shape.size(), target_shape.size());
while (arg_shape.size() < target_padded_rank)
const auto target_padded_rank = std::max(arg_shape_vec.size(), target_shape.size());
while (arg_shape_vec.size() < target_padded_rank)
{
arg_shape.insert(arg_shape.begin(), 1);
arg_shape_vec.insert(arg_shape_vec.begin(), 1);
}
while (target_shape.size() < target_padded_rank)
{
Expand All @@ -108,15 +114,28 @@ namespace
result_shape = target_shape;
for (auto i = 0; i < target_shape.size(); ++i)
{
if (arg_shape_vec[i].is_dynamic())
{
if (target_shape[i] == 1)
{
result_shape[i] = Dimension::dynamic();
}
else
{
result_shape[i] = target_shape[i];
}
continue;
}
const size_t arg_shape_dim = arg_shape_vec[i].get_length();
NODE_VALIDATION_CHECK(this_ptr,
arg_shape[i] == 1 || target_shape[i] == 1 ||
arg_shape[i] == target_shape[i],
arg_shape_dim == 1 || target_shape[i] == 1 ||
arg_shape_dim == target_shape[i],
"Broadcast incorrect target shape. Expecting either 1 or ",
arg_shape[i],
arg_shape_dim,
". Got ",
target_shape[i]);

result_shape[i] = std::max(arg_shape[i], target_shape[i]);
result_shape[i] = std::max(arg_shape_dim, target_shape[i]);
}
return result_shape;
}
Expand All @@ -143,9 +162,9 @@ void op::v3::Broadcast::validate_and_infer_types()
auto result_shape = get_output_partial_shape(0);
if (m_mode.m_type == BroadcastType::BIDIRECTIONAL)
{
if (get_input_partial_shape(0).is_static() && get_input_partial_shape(1).is_static())
if (get_input_partial_shape(0).rank().is_static() && get_input_partial_shape(1).is_static())
{
auto arg_shape = get_input_shape(0);
auto arg_shape = get_input_partial_shape(0);

const auto shape_constant =
as_type_ptr<op::v0::Constant>(input_value(1).get_node_shared_ptr());
Expand Down Expand Up @@ -196,7 +215,8 @@ bool op::v3::Broadcast::evaluate(const HostTensorVector& outputs,
{
auto arg_shape = inputs[0]->get_shape();
Shape target_shape = op::util::BroadcastBase::get_target_shape(inputs[1]);
PartialShape result_shape = get_result_shape_bidirectional(this, arg_shape, target_shape);
PartialShape result_shape =
get_result_shape_bidirectional(this, PartialShape{arg_shape}, target_shape);
auto pair_broadcast_axes =
get_broadcast_axes_bidirectional(arg_shape, result_shape.to_shape());
return op::util::BroadcastBase::evaluate_broadcast(
Expand Down
122 changes: 96 additions & 26 deletions ngraph/src/ngraph/op/util/broadcast_base.cpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -47,35 +47,79 @@ op::util::BroadcastBase::BroadcastBase(const Output<Node>& arg,
{
}

PartialShape op::util::BroadcastBase::get_result_shape_numpy_pdpd(
const Shape& arg0_shape,
PartialShape op::util::BroadcastBase::get_result_shape_pdpd(
const PartialShape& arg0_shape,
const Shape& target_shape,
const op::BroadcastModeSpec& broadcast_spec) const
{
if (arg0_shape.rank().is_dynamic())
{
return PartialShape::dynamic(target_shape.size());
}
const auto arg_rank_length = arg0_shape.rank().get_length();
PartialShape result_shape = target_shape;
auto start_axis = (broadcast_spec.m_type == op::BroadcastType::PDPD)
? broadcast_spec.m_axis
: target_shape.size() - arg0_shape.size();
auto start_axis = broadcast_spec.m_axis;

NODE_VALIDATION_CHECK(this,
start_axis >= 0,
"Broadcast target_shape has smaller rank ",
target_shape.size(),
" than arg shape ",
arg0_shape.size());
arg_rank_length);
for (auto i = start_axis; i < target_shape.size(); i++)
{
if (arg0_shape[i - start_axis].is_dynamic())
{
result_shape[i] = Dimension::dynamic();
continue;
}
const size_t arg_dim = arg0_shape[i - start_axis].get_length();
NODE_VALIDATION_CHECK(this,
arg0_shape[i - start_axis] == 1 || target_shape[i] == 1 ||
arg0_shape[i - start_axis] == target_shape[i],
arg_dim == 1 || target_shape[i] == 1 || arg_dim == target_shape[i],
"Broadcast incorrect target shape. Expecting either 1 or ",
arg0_shape[i - start_axis],
arg_dim,
" . Got ",
target_shape[i]);
result_shape[i] = std::max(arg0_shape[i - start_axis], target_shape[i]);
result_shape[i] = std::max(arg_dim, target_shape[i]);
}
return result_shape;
}

void op::util::BroadcastBase::validate_target_shape_numpy(const PartialShape& arg_shape,
const Shape& target_shape) const
{
if (arg_shape.rank().is_dynamic())
{
return;
}
const auto arg_rank_length = arg_shape.rank().get_length();
auto start_axis = target_shape.size() - arg_rank_length;
NODE_VALIDATION_CHECK(this,
start_axis >= 0,
"Broadcast target_shape has smaller rank ",
target_shape.size(),
" than arg shape ",
arg_rank_length);
for (auto i = start_axis; i < target_shape.size(); i++)
{
if (arg_shape[i - start_axis].is_dynamic())
{
continue;
}
const size_t arg_dim = arg_shape[i - start_axis].get_length();
NODE_VALIDATION_CHECK(this,
arg_dim == 1 || arg_dim == target_shape[i],
"Input shape dimension equal ",
arg_dim,
" cannot be broadcasted (numpy mode) to ",
target_shape[i],
". Allowed input dimension value would be 1",
target_shape[i] != 1
? (std::string(" or ") + std::to_string(target_shape[i])).c_str()
: "");
}
}

void op::util::BroadcastBase::validate_target_shape_none(const Shape& arg_shape,
const AxisVector& axes_mapping_val,
const Shape& target_shape) const
Expand Down Expand Up @@ -142,13 +186,28 @@ void op::util::BroadcastBase::validate_and_infer_types()
}

PartialShape result_shape{PartialShape::dynamic()};
auto input_rank = input_value(0).get_partial_shape().rank();
auto output_rank = input_value(1).get_partial_shape();
if (input_rank.is_static() && output_rank.is_static() && output_rank[0].is_static())
const auto& input_shape = get_input_partial_shape(0);
const auto input_rank = input_shape.rank();
const auto& target_shape = input_value(1).get_partial_shape();
const bool is_target_shape_known =
target_shape.rank().is_static() && target_shape[0].is_static();

if (m_mode.m_type == BroadcastType::BIDIRECTIONAL)
{
result_shape =
PartialShape::dynamic(std::max(input_rank.get_length(), output_rank[0].get_length()));
if (input_rank.is_static() && is_target_shape_known)
{
result_shape = PartialShape::dynamic(
std::max(input_rank.get_length(), target_shape[0].get_length()));
}
}
else
{
if (is_target_shape_known)
{
result_shape = PartialShape::dynamic(target_shape[0].get_length());
}
}

const auto shape_constant = as_type_ptr<op::v0::Constant>(input_value(1).get_node_shared_ptr());

if (auto concat = as_type_ptr<op::v0::Concat>(input_value(1).get_node_shared_ptr()))
Expand Down Expand Up @@ -206,17 +265,21 @@ void op::util::BroadcastBase::validate_and_infer_types()
}
}
}
else if (m_mode.m_type == BroadcastType::NUMPY || m_mode.m_type == BroadcastType::PDPD)
else if (m_mode.m_type == BroadcastType::NUMPY)
{
if (get_input_partial_shape(0).is_static() && get_input_partial_shape(1).is_static())
if (shape_constant)
{
auto arg_shape = get_input_shape(0);

if (shape_constant)
{
const auto target_shape = shape_constant->get_shape_val();
result_shape = get_result_shape_numpy_pdpd(arg_shape, target_shape, m_mode);
}
const auto target_shape = shape_constant->get_shape_val();
result_shape = target_shape;
validate_target_shape_numpy(input_shape, target_shape);
}
}
else if (m_mode.m_type == BroadcastType::PDPD)
{
if (shape_constant)
{
const auto target_shape = shape_constant->get_shape_val();
result_shape = get_result_shape_pdpd(input_shape, target_shape, m_mode);
}
}
set_output_type(0, get_input_element_type(0), result_shape);
Expand Down Expand Up @@ -490,9 +553,16 @@ bool op::util::BroadcastBase::evaluate(const HostTensorVector& outputs,
validate_target_shape_none(inputs[0]->get_shape(), axes_mapping_val, target_shape);
result_shape = target_shape;
}
else if (m_mode.m_type == BroadcastType::NUMPY || m_mode.m_type == BroadcastType::PDPD)
else if (m_mode.m_type == BroadcastType::PDPD)
{
result_shape = get_result_shape_pdpd(arg_shape, target_shape, m_mode);
pair_broadcast_axes =
get_broadcast_axes_numpy_pdpd(arg_shape, result_shape.to_shape(), m_mode);
}
else if (m_mode.m_type == BroadcastType::NUMPY)
{
result_shape = get_result_shape_numpy_pdpd(arg_shape, target_shape, m_mode);
result_shape = target_shape;
validate_target_shape_numpy(arg_shape, target_shape);
pair_broadcast_axes =
get_broadcast_axes_numpy_pdpd(arg_shape, result_shape.to_shape(), m_mode);
}
Expand Down
10 changes: 7 additions & 3 deletions ngraph/src/ngraph/op/util/broadcast_base.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -77,9 +77,13 @@ namespace ngraph
const AxisSet& broadcast_axes) const;

PartialShape
get_result_shape_numpy_pdpd(const Shape& arg0_shape,
const Shape& target_shape,
const op::BroadcastModeSpec& broadcast_spec) const;
get_result_shape_pdpd(const PartialShape& arg0_shape,
const Shape& target_shape,
const op::BroadcastModeSpec& broadcast_spec) const;

void validate_target_shape_numpy(const PartialShape& arg_shape,
const Shape& target_shape) const;

static std::pair<bool, AxisSet>
get_broadcast_axes_numpy_pdpd(const Shape& arg_shape,
const Shape& result_shape,
Expand Down
22 changes: 21 additions & 1 deletion ngraph/test/eval.cpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -315,7 +315,7 @@ TEST(eval, evaluate_broadcast_v3_numpy_vs_bidi)
Shape in_shape{1, 4, 1};

auto A = make_shared<op::Parameter>(element::f32, in_shape);
auto target_shape = op::Constant::create<int64_t>(element::i64, Shape{3}, {1, 1, 4});
auto target_shape = op::Constant::create<int64_t>(element::i64, Shape{3}, {1, 4, 4});
auto bcast_v3_num = make_shared<op::v3::Broadcast>(A, target_shape, op::BroadcastType::NUMPY);
auto fun_num = make_shared<Function>(OutputVector{bcast_v3_num}, ParameterVector{A});

Expand Down Expand Up @@ -343,6 +343,26 @@ TEST(eval, evaluate_broadcast_v3_numpy_vs_bidi)
ASSERT_EQ(expec2, result_val2);
}

TEST(eval, evaluate_broadcast_v3_bidi_3d)
{
Shape in_shape{1, 4, 1};

auto A = make_shared<op::Parameter>(element::f32, in_shape);
auto target_shape = op::Constant::create<int64_t>(element::i64, Shape{3}, {1, 1, 3});
auto bcast_v3_num =
make_shared<op::v3::Broadcast>(A, target_shape, op::BroadcastType::BIDIRECTIONAL);
auto fun_num = make_shared<Function>(OutputVector{bcast_v3_num}, ParameterVector{A});

auto result = make_shared<HostTensor>();
ASSERT_TRUE(fun_num->evaluate(
{result}, {make_host_tensor<element::Type_t::f32>(in_shape, {1.0f, 2.0f, 3.0f, 4.0f})}));
EXPECT_EQ(result->get_element_type(), element::f32);
EXPECT_EQ(result->get_partial_shape(), (PartialShape{1, 4, 3}));
auto result_val = read_vector<float>(result);
vector<float> expec{1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f, 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f};
ASSERT_EQ(expec, result_val);
}

TEST(eval, evaluate_broadcast_v3_bidi_4d)
{
Shape in_shape{4, 1, 1};
Expand Down
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