This includes AttributeProto, GraphProto, NodeProto, TensorProto, TensorValueInfoProto, etc.
make_attribute(key, value, doc_string = NULL) make_graph(nodes, name, inputs, outputs, initializer = NULL, doc_string = NULL) make_node(op_type, inputs, outputs, name = NULL, doc_string = NULL) make_tensor(name, data_type, dims, vals, raw = FALSE) make_tensor_value_info(name, elem_type, shape, doc_string = "")
key | The key |
---|---|
value | The value |
doc_string | The doc_string |
nodes | The nodes |
name | The name |
inputs | The inputs |
outputs | The outputs |
initializer | The initializer |
op_type | The op type |
data_type | The data type |
dims | The dimensions |
vals | The values |
raw | If this is |
elem_type | The element type, e.g. |
shape | The shape |
if (FALSE) { library(onnx) # Define a node protobuf and check whether it's valid node_def <- make_node("Relu", list("X"), list("Y")) check(node_def) # Define an attribute protobuf and check whether it's valid attr_def <- make_attribute("this_is_an_int", 123L) check(attr_def) # Define a graph protobuf and check whether it's valid graph_def <- make_graph( nodes = list( make_node("FC", list("X", "W1", "B1"), list("H1")), make_node("Relu", list("H1"), list("R1")), make_node("FC", list("R1", "W2", "B2"), list("Y")) ), name = "MLP", inputs = list( make_tensor_value_info('X' , onnx$TensorProto$FLOAT, list(1L)), make_tensor_value_info('W1', onnx$TensorProto$FLOAT, list(1L)), make_tensor_value_info('B1', onnx$TensorProto$FLOAT, list(1L)), make_tensor_value_info('W2', onnx$TensorProto$FLOAT, list(1L)), make_tensor_value_info('B2', onnx$TensorProto$FLOAT, list(1L)) ), outputs = list( make_tensor_value_info('Y', onnx$TensorProto$FLOAT, list(1L)) ) ) check(graph_def) }