[][src]Struct onnx_pb::GraphProto

pub struct GraphProto {
    pub node: Vec<NodeProto>,
    pub name: String,
    pub initializer: Vec<TensorProto>,
    pub sparse_initializer: Vec<SparseTensorProto>,
    pub doc_string: String,
    pub input: Vec<ValueInfoProto>,
    pub output: Vec<ValueInfoProto>,
    pub value_info: Vec<ValueInfoProto>,
    pub quantization_annotation: Vec<TensorAnnotation>,
}

Graphs

A graph defines the computational logic of a model and is comprised of a parameterized list of nodes that form a directed acyclic graph based on their inputs and outputs. This is the equivalent of the "network" or "graph" in many deep learning frameworks.

Fields

node: Vec<NodeProto>

The nodes in the graph, sorted topologically.

name: String

The name of the graph.

namespace Graph

initializer: Vec<TensorProto>

A list of named tensor values, used to specify constant inputs of the graph. Each TensorProto entry must have a distinct name (within the list) that MAY also appear in the input list.

sparse_initializer: Vec<SparseTensorProto>

Initializers (see above) stored in sparse format.

doc_string: String

A human-readable documentation for this graph. Markdown is allowed.

input: Vec<ValueInfoProto>

The inputs and outputs of the graph.

output: Vec<ValueInfoProto>value_info: Vec<ValueInfoProto>

Information for the values in the graph. The ValueInfoProto.name's must be distinct. It is optional for a value to appear in value_info list.

quantization_annotation: Vec<TensorAnnotation>

This field carries information to indicate the mapping among a tensor and its quantization parameter tensors. For example: For tensor 'a', it may have {'SCALE_TENSOR', 'a_scale'} and {'ZERO_POINT_TENSOR', 'a_zero_point'} annotated, which means, tensor 'a_scale' and tensor 'a_zero_point' are scale and zero point of tensor 'a' in the model.

Trait Implementations

impl Clone for GraphProto[src]

impl Debug for GraphProto[src]

impl Default for GraphProto[src]

impl From<GraphProto> for Attribute[src]

impl Message for GraphProto[src]

impl PartialEq<GraphProto> for GraphProto[src]

impl StructuralPartialEq for GraphProto[src]

Auto Trait Implementations

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type Owned = T

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type Error = Infallible

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type Error = <U as TryFrom<T>>::Error

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