class ov::op::v1::DeformablePSROIPooling¶
Overview¶
DeformablePSROIPooling operation. More…
#include <deformable_psroi_pooling.hpp>
class DeformablePSROIPooling: public ov::op::Op
{
public:
// construction
DeformablePSROIPooling();
DeformablePSROIPooling(
const Output<Node>& input,
const Output<Node>& coords,
const Output<Node>& offsets,
const int64_t output_dim,
const float spatial_scale,
const int64_t group_size = 1,
const std::string mode = "bilinear_deformable",
int64_t spatial_bins_x = 1,
int64_t spatial_bins_y = 1,
float trans_std = 1,
int64_t part_size = 1
);
DeformablePSROIPooling(
const Output<Node>& input,
const Output<Node>& coords,
const int64_t output_dim,
const float spatial_scale,
const int64_t group_size = 1,
const std::string mode = "bilinear_deformable",
int64_t spatial_bins_x = 1,
int64_t spatial_bins_y = 1,
float trans_std = 1,
int64_t part_size = 1
);
// methods
OPENVINO_OP("DeformablePSROIPooling", "opset1", op::Op);
virtual bool visit_attributes(AttributeVisitor& visitor);
virtual void validate_and_infer_types();
virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const;
void set_output_dim(int64_t output_dim);
int64_t get_output_dim() const;
void set_group_size(int64_t group_size);
int64_t get_group_size() const;
float get_spatial_scale() const;
const std::string& get_mode() const;
int64_t get_spatial_bins_x() const;
int64_t get_spatial_bins_y() const;
float get_trans_std() const;
int64_t get_part_size() const;
};Inherited Members¶
public:
// typedefs
typedef DiscreteTypeInfo type_info_t;
typedef std::map<std::string, Any> RTMap;
// methods
virtual void validate_and_infer_types();
void constructor_validate_and_infer_types();
virtual bool visit_attributes(AttributeVisitor&);
virtual const ov::op::AutoBroadcastSpec& get_autob() const;
virtual bool has_evaluate() const;
virtual bool evaluate(
const ov::HostTensorVector& output_values,
const ov::HostTensorVector& input_values
) const;
virtual bool evaluate(
const ov::HostTensorVector& output_values,
const ov::HostTensorVector& input_values,
const EvaluationContext& evaluationContext
) const;
virtual bool evaluate(
ov::TensorVector& output_values,
const ov::TensorVector& input_values
) const;
virtual bool evaluate(
ov::TensorVector& output_values,
const ov::TensorVector& input_values,
const ov::EvaluationContext& evaluationContext
) const;
virtual bool evaluate_lower(ov::TensorVector& output_values) const;
virtual bool evaluate_upper(ov::TensorVector& output_values) const;
virtual bool evaluate_label(TensorLabelVector& output_labels) const;
virtual bool constant_fold(
OutputVector& output_values,
const OutputVector& inputs_values
);
virtual OutputVector decompose_op() const;
virtual const type_info_t& get_type_info() const = 0;
const char \* get_type_name() const;
void set_arguments(const NodeVector& arguments);
void set_arguments(const OutputVector& arguments);
void set_argument(size_t position, const Output<Node>& argument);
void set_output_type(
size_t i,
const element::Type& element_type,
const PartialShape& pshape
);
void set_output_size(size_t output_size);
void invalidate_values();
virtual void revalidate_and_infer_types();
virtual std::string description() const;
const std::string& get_name() const;
void set_friendly_name(const std::string& name);
const std::string& get_friendly_name() const;
virtual bool is_dynamic() const;
size_t get_instance_id() const;
virtual std::ostream& write_description(std::ostream& os, uint32_t depth = 0) const;
const std::vector<std::shared_ptr<Node>>& get_control_dependencies() const;
const std::vector<Node \*>& get_control_dependents() const;
void add_control_dependency(std::shared_ptr<Node> node);
void remove_control_dependency(std::shared_ptr<Node> node);
void clear_control_dependencies();
void clear_control_dependents();
void add_node_control_dependencies(const std::shared_ptr<const Node>& source_node);
void add_node_control_dependents(const std::shared_ptr<const Node>& source_node);
void transfer_control_dependents(std::shared_ptr<Node> replacement);
size_t get_output_size() const;
const element::Type& get_output_element_type(size_t i) const;
const element::Type& get_element_type() const;
const Shape& get_output_shape(size_t i) const;
const PartialShape& get_output_partial_shape(size_t i) const;
Output<const Node> get_default_output() const;
Output<Node> get_default_output();
virtual size_t get_default_output_index() const;
size_t no_default_index() const;
const Shape& get_shape() const;
descriptor::Tensor& get_output_tensor(size_t i) const;
descriptor::Tensor& get_input_tensor(size_t i) const;
std::set<Input<Node>> get_output_target_inputs(size_t i) const;
size_t get_input_size() const;
const element::Type& get_input_element_type(size_t i) const;
const Shape& get_input_shape(size_t i) const;
const PartialShape& get_input_partial_shape(size_t i) const;
Node \* get_input_node_ptr(size_t index) const;
std::shared_ptr<Node> get_input_node_shared_ptr(size_t index) const;
Output<Node> get_input_source_output(size_t i) const;
virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& inputs) const = 0;
std::shared_ptr<Node> copy_with_new_inputs(const OutputVector& new_args) const;
std::shared_ptr<Node> copy_with_new_inputs(
const OutputVector& inputs,
const std::vector<std::shared_ptr<Node>>& control_dependencies
) const;
bool has_same_type(std::shared_ptr<const Node> node) const;
RTMap& get_rt_info();
const RTMap& get_rt_info() const;
NodeVector get_users(bool check_is_used = false) const;
bool operator < (const Node& other) const;
std::vector<Input<Node>> inputs();
std::vector<Input<const Node>> inputs() const;
std::vector<Output<Node>> input_values() const;
std::vector<Output<Node>> outputs();
std::vector<Output<const Node>> outputs() const;
Input<Node> input(size_t input_index);
Input<const Node> input(size_t input_index) const;
Output<Node> input_value(size_t input_index) const;
Output<Node> output(size_t output_index);
Output<const Node> output(size_t output_index) const;
virtual bool match_value(
ov::pass::pattern::Matcher \* matcher,
const Output<Node>& pattern_value,
const Output<Node>& graph_value
);
virtual bool match_node(
ov::pass::pattern::Matcher \* matcher,
const Output<Node>& graph_value
);
static _OPENVINO_HIDDEN_METHODconst ::ov::Node::type_info_t& get_type_info_static();
virtual const ::ov::Node::type_info_t& get_type_info() const;Detailed Documentation¶
DeformablePSROIPooling operation.
Construction¶
DeformablePSROIPooling(
const Output<Node>& input,
const Output<Node>& coords,
const Output<Node>& offsets,
const int64_t output_dim,
const float spatial_scale,
const int64_t group_size = 1,
const std::string mode = "bilinear_deformable",
int64_t spatial_bins_x = 1,
int64_t spatial_bins_y = 1,
float trans_std = 1,
int64_t part_size = 1
)Constructs a DeformablePSROIPooling operation.
Parameters:
input |
Input tensor with position sensitive score maps |
coords |
Input tensor with list of five element tuples describing ROI coordinates |
offsets |
Input tensor with transformation values |
output_dim |
Pooled output channel number |
group_size |
Number of horizontal bins per row to divide ROI area, it defines output width and height |
spatial_scale |
Multiplicative spatial scale factor to translate ROI coordinates from their input scale to the scale used when pooling |
mode |
Specifies mode for pooling. |
spatial_bins_x |
Specifies numbers of bins to divide ROI single bin over width |
spatial_bins_y |
Specifies numbers of bins to divide ROI single bin over height |
no_trans |
The flag that specifies whenever third input exists and contains transformation (offset) values |
trans_std |
The value that all transformation (offset) values are multiplied with |
part_size |
The number of parts the output tensor spatial dimensions are divided into. Basically it is the height and width of the third input |
Methods¶
virtual void validate_and_infer_types()Verifies that attributes and inputs are consistent and computes output shapes and element types. Must be implemented by concrete child classes so that it can be run any number of times.
Throws if the node is invalid.