class ov::op::v8::RandomUniform

Overview

Tensor RandomUniform operation. More…

#include <random_uniform.hpp>

class RandomUniform: public ov::op::Op
{
public:
    // construction

    RandomUniform();

    RandomUniform(
        const Output<Node>& out_shape,
        const Output<Node>& min_val,
        const Output<Node>& max_val,
        const ov::element::Type& out_type,
        uint64_t global_seed = 0,
        uint64_t op_seed = 0
        );

    // methods

    OPENVINO_OP("RandomUniform", "opset8");
    virtual void validate_and_infer_types();
    virtual bool visit_attributes(AttributeVisitor& visitor);
    virtual std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const;

    virtual bool constant_fold(
        OutputVector& output_values,
        const OutputVector& inputs_values
        );

    const ov::element::Type& get_out_type() const;
    void set_out_type(const ov::element::Type& output_type);
    uint64_t get_global_seed() const;
    void set_global_seed(uint64_t seed);
    uint64_t get_op_seed() const;
    void set_op_seed(uint64_t seed2);
    std::pair<uint64_t, uint64_t> get_state() const;

    virtual OPENVINO_SUPPRESS_DEPRECATED_START bool evaluate(
        const HostTensorVector& output_values,
        const HostTensorVector& input_values
        ) const;

    virtual OPENVINO_SUPPRESS_DEPRECATED_END bool has_evaluate() 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_lower(const ov::HostTensorVector& output_values) const;
    virtual bool evaluate_upper(const ov::HostTensorVector& output_values) 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(std::shared_ptr<Node> source_node);
    void add_node_control_dependents(std::shared_ptr<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;
    virtual size_t get_version() const;
    virtual std::shared_ptr<Node> get_default_value() 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;
    OPENVINO_SUPPRESS_DEPRECATED_START void set_op_annotations(std::shared_ptr<ngraph::op::util::OpAnnotations> op_annotations);
    std::shared_ptr<ngraph::op::util::OpAnnotations> get_op_annotations() const;

    virtual OPENVINO_SUPPRESS_DEPRECATED_END 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

Tensor RandomUniform operation.

Construction

RandomUniform(
    const Output<Node>& out_shape,
    const Output<Node>& min_val,
    const Output<Node>& max_val,
    const ov::element::Type& out_type,
    uint64_t global_seed = 0,
    uint64_t op_seed = 0
    )

Constructs a RandomUniform operation.

Parameters:

out_shape

Node producing the tensor with output shape.

min_val

Node producing the tensor with minimum value.

max_val

Node producing the tensor with maximum value.

out_type

Output type of the tensor.

global_seed

Global seed value.

op_seed

Operational seed value.

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.

virtual bool constant_fold(
    OutputVector& output_values,
    const OutputVector& inputs_values
    )

Returns:

Turns off constant folding for RandomUniform operation.

const ov::element::Type& get_out_type() const

Returns:

The output tensor type.

uint64_t get_global_seed() const

Returns:

The global seed value.

uint64_t get_op_seed() const

Returns:

The operational seed value.

std::pair<uint64_t, uint64_t> get_state() const

Returns:

The state value.

virtual OPENVINO_SUPPRESS_DEPRECATED_START bool evaluate(
    const HostTensorVector& output_values,
    const HostTensorVector& input_values
    ) const

Evaluates the op on input_values putting results in output_values.

Deprecated Use evaluate with ov::Tensor instead

Parameters:

output_values

Tensors for the outputs to compute. One for each result

input_values

Tensors for the inputs. One for each inputs.

Returns:

true if successful

virtual OPENVINO_SUPPRESS_DEPRECATED_END bool has_evaluate() const

Allows to get information about availability of evaluate method for the current operation.