public Mapper(IHostEnvironment env, TensorFlowTransform parent, ISchema inputSchema)
{
Contracts.CheckValue(env, nameof(env));
_host = env.Register(nameof(Mapper));
_host.CheckValue(inputSchema, nameof(inputSchema));
_host.CheckValue(parent, nameof(parent));
_parent = parent;
_schema = inputSchema;
_inputColIndices = new int[_parent.Inputs.Length];
_isInputVector = new bool[_parent.Inputs.Length];
for (int i = 0; i < _parent.Inputs.Length; i++)
{
if (!inputSchema.TryGetColumnIndex(_parent.Inputs[i], out _inputColIndices[i]))
{
throw _host.Except($"Column {_parent.Inputs[i]} doesn't exist");
}
var type = inputSchema.GetColumnType(_inputColIndices[i]);
var expectedType = TensorFlowUtils.Tf2MlNetType(_parent.TFInputTypes[i]);
if (type.ItemType != expectedType)
{
throw _host.ExceptSchemaMismatch(nameof(inputSchema), "input", _parent.Inputs[i], expectedType.ToString(), type.ToString());
}
var originalShape = _parent.Graph.GetTensorShape(new TFOutput(_parent.Graph[_parent.Inputs[i]]));
var shape = originalShape.ToIntArray().Skip(originalShape[0] == -1 ? BatchSize : 0);
_isInputVector[i] = type.IsVector;
if (type.AsVector.DimCount == 1)
{
int valCount = shape.Aggregate((x, y) => x * y);
if (type.ValueCount != valCount)
{
throw _host.Except($"Input shape mismatch: Input '{_parent.Inputs[i]}' has shape {shape.ToString()}, but input data is of length {valCount}.");
}
}
else if (shape.Select((dim, j) => dim != type.AsVector.GetDim(j)).Any(b => b))
{
throw _host.Except($"Input shape mismatch: Input '{_parent.Inputs[i]}' has shape {shape.ToString()}, but input data is {type.AsVector.ToString()}.");
}
}
}
public Mapper(IHostEnvironment env, TensorFlowTransform parent, ISchema inputSchema)
{
Contracts.CheckValue(env, nameof(env));
_host = env.Register(nameof(Mapper));
_host.CheckValue(inputSchema, nameof(inputSchema));
_host.CheckValue(parent, nameof(parent));
_parent = parent;
_schema = inputSchema;
_inputColIndices = new int[_parent.Inputs.Length];
_isInputVector = new bool[_parent.Inputs.Length];
_fullySpecifiedShapes = new TFShape[_parent.Inputs.Length];
for (int i = 0; i < _parent.Inputs.Length; i++)
{
if (!inputSchema.TryGetColumnIndex(_parent.Inputs[i], out _inputColIndices[i]))
{
throw _host.Except($"Column {_parent.Inputs[i]} doesn't exist");
}
var type = inputSchema.GetColumnType(_inputColIndices[i]);
_isInputVector[i] = type.IsVector;
var expectedType = TensorFlowUtils.Tf2MlNetType(_parent.TFInputTypes[i]);
if (type.ItemType != expectedType)
{
throw _host.ExceptSchemaMismatch(nameof(inputSchema), "input", _parent.Inputs[i], expectedType.ToString(), type.ToString());
}
var originalShape = _parent.TFInputShapes[i];
var shape = originalShape.ToIntArray();
var colTypeDims = Enumerable.Range(0, type.AsVector.DimCount + 1).Select(d => d == 0 ? 1 : (long)type.AsVector.GetDim(d - 1)).ToArray();
if (shape == null)
{
_fullySpecifiedShapes[i] = new TFShape(colTypeDims);
}
else if (type.AsVector.DimCount == 1)
{
// 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 = shape.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($"Input shape mismatch: Input '{_parent.Inputs[i]}' has shape {originalShape.ToString()}, but input data is of length {type.ValueCount}.");
}
// If the shape is multi-dimensional, we should be able to create the length of the vector by plugging
// in a single value for the unknown shapes. E.g., if the shape is [?,?,3], then there should exist a value
// d such that d*d*3 is equal to the length of the input column.
var d = originalShape.NumDimensions > 2 ? Math.Pow(type.ValueCount / valCount, 1.0 / (originalShape.NumDimensions - 2)) : 1;
if (originalShape.NumDimensions > 2 && d - (int)d != 0)
{
throw Contracts.Except($"Input shape mismatch: Input '{_parent.Inputs[i]}' has shape {originalShape.ToString()}, but input data is of length {type.ValueCount}.");
}
// Fill in the unknown dimensions.
var l = new long[originalShape.NumDimensions];
for (int ishape = 0; ishape < originalShape.NumDimensions; ishape++)
{
l[ishape] = originalShape[ishape] == -1 ? (int)d : originalShape[ishape];
}
_fullySpecifiedShapes[i] = new TFShape(l);
}
else
{
if (shape.Select((dim, j) => dim != -1 && dim != colTypeDims[j]).Any(b => b))
{
throw Contracts.Except($"Input shape mismatch: Input '{_parent.Inputs[i]}' has shape {originalShape.ToString()}, but input data is {type.AsVector.ToString()}.");
}
// Fill in the unknown dimensions.
var l = new long[originalShape.NumDimensions];
for (int ishape = 0; ishape < originalShape.NumDimensions; ishape++)
{
l[ishape] = originalShape[ishape] == -1 ? colTypeDims[ishape] : originalShape[ishape];
}
_fullySpecifiedShapes[i] = new TFShape(l);
}
}
}