tail method

Future<String> tail(List<int> counts, { bool pretty = false, })

Returns a string representation of the last counts elements along each dimension. If pretty is true, the output is formatted with newlines and indentation.

Implementation

Future<String> tail(List<int> counts, {bool pretty = false}) async {
  if (counts.length != shape.length) {
    throw Exception(
        "Counts length (${counts.length}) does not match tensor rank (${shape.length}).");
  }
  if (shape.length == 2) {
    int numRows = counts[0];
    int numCols = counts[1];
    int totalCols = shape[1];
    int startRow = shape[0] - numRows;
    int startCol = totalCols - numCols;
    List<List<double>> rows = [];
    for (int r = startRow; r < shape[0]; r++) {
      final rowData = Float32List(numCols);
      await buffer.read(rowData, numCols,
          readOffset: r * totalCols + startCol);
      rows.add(rowData.map((e) => e.toDouble()).toList());
    }
    return _format2D(rows, pretty: pretty);
  } else {
    List<int> startIndices = [];
    for (int i = 0; i < shape.length; i++) {
      if (counts[i] > shape[i]) {
        throw Exception(
            "Tail count (${counts[i]}) exceeds tensor dimension $i size (${shape[i]}).");
      }
      startIndices.add(shape[i] - counts[i]);
    }
    Tensor<T> subTensor = await slice(
        startIndices: startIndices, endIndices: List<int>.from(shape));
    // For formatted output, slice the head of the sub-tensor.
    subTensor = await subTensor.slice(
        startIndices: List.filled(counts.length, 0), endIndices: counts);
    T subData = await subTensor.getData();
    List<double> dataList = _toDoubleList(subData);
    return _formatTensor(dataList, counts, pretty: pretty);
  }
}