public Mapper(OnnxTransform parent, Schema inputSchema) :
base(Contracts.CheckRef(parent, nameof(parent)).Host.Register(nameof(Mapper)), inputSchema)
{
_parent = parent;
_inputColIndices = new int[_parent.Inputs.Length];
_isInputVector = new bool[_parent.Inputs.Length];
_inputTensorShapes = new OnnxShape[_parent.Inputs.Length];
_inputOnnxTypes = new DataType[_parent.Inputs.Length];
var model = _parent.Model;
for (int i = 0; i < _parent.Inputs.Length; i++)
{
var idx = model.InputNames.IndexOf(_parent.Inputs[i]);
if (idx < 0)
{
throw Host.Except($"Column {_parent.Inputs[i]} doesn't match input node names of model");
}
var inputNodeInfo = model.ModelInfo.InputsInfo[idx];
var shape = inputNodeInfo.Shape;
var inputType = OnnxUtils.OnnxToMlNetType(inputNodeInfo.Type);
var inputShape = inputNodeInfo.Shape;
_inputTensorShapes[i] = inputShape;
_inputOnnxTypes[i] = inputNodeInfo.Type;
if (!inputSchema.TryGetColumnIndex(_parent.Inputs[i], out _inputColIndices[i]))
{
throw Host.Except($"Column {_parent.Inputs[i]} doesn't exist");
}
var type = inputSchema.GetColumnType(_inputColIndices[i]);
_isInputVector[i] = type.IsVector;
if (type.IsVector && type.VectorSize == 0)
{
throw Host.Except($"Variable length input columns not supported");
}
if (type.ItemType != inputType)
{
throw Host.ExceptSchemaMismatch(nameof(inputSchema), "input", _parent.Inputs[i], inputType.ToString(), type.ToString());
}
// If the column is one dimension we make sure that the total size of the Onnx shape matches.
// Compute the total size of the known dimensions of the shape.
int valCount = inputShape.Select(x => (int)x).Where(x => x > 0).Aggregate((x, y) => x * y);
// The column length should be divisible by this, so that the other dimensions can be integral.
if (type.ValueCount % valCount != 0)
{
throw Contracts.Except($"Input shape mismatch: Input '{_parent.Inputs[i]}' has shape {String.Join(",", inputShape)}, but input data is of length {type.ValueCount}.");
}
//Host.Assert(_outputItemRawType == _outputColType.ItemType.RawType);
}
}
public Mapper(IHostEnvironment env, OnnxTransform parent, Schema inputSchema)
{
Contracts.CheckValue(env, nameof(env));
_host = env.Register(nameof(Mapper));
_host.CheckValue(inputSchema, nameof(inputSchema));
_host.CheckValue(parent, nameof(parent));
_parent = parent;
var model = _parent.Model;
_idvToTensorAdapter = new IdvToTensorAdapter(inputSchema, parent._args.InputColumn,
model.ModelInfo.InputsInfo[0]);
// TODO: Remove assumption below
// Assume first output dimension is 1
var outputNodeInfo = model.ModelInfo.OutputsInfo[0];
var inputNodeInfo = model.ModelInfo.InputsInfo[0];
int[] dims = outputNodeInfo.Shape.Skip(1).Select(x => (int)x).ToArray();
var outputItemType = OnnxUtils.OnnxToMlNetType(outputNodeInfo.Type);
var inputShape = inputNodeInfo.Shape;
_outputColType = new VectorType(outputItemType, dims);
_outputColName = _parent.Output;
_outputItemRawType = outputItemType.RawType;
int inColIndex;
if (!inputSchema.TryGetColumnIndex(_parent.Input, out inColIndex))
{
throw _host.Except($"Column {_parent.Input} doesn't exist");
}
var type = inputSchema.GetColumnType(inColIndex);
if (type.IsVector && type.VectorSize == 0)
{
throw _host.Except($"Variable length input columns not supported");
}
if (type.ItemType != outputItemType)
{
throw _host.ExceptSchemaMismatch(nameof(inputSchema), "input", _parent.Input, outputItemType.ToString(), type.ToString());
}
// If the column is one dimension we make sure that the total size of the TF shape matches.
// Compute the total size of the known dimensions of the shape.
int valCount = inputShape.Select(x => (int)x).Where(x => x > 0).Aggregate((x, y) => x * y);
// The column length should be divisible by this, so that the other dimensions can be integral.
if (type.ValueCount % valCount != 0)
{
throw Contracts.Except($"Input shape mismatch: Input '{_outputColName}' has shape {String.Join(",", inputShape)}, but input data is of length {type.ValueCount}.");
}
_host.Assert(_outputItemRawType == _outputColType.ItemType.RawType);
}