| 222 | } |
| 223 | |
| 224 | Result<std::shared_ptr<Tensor>> VariableShapeTensorType::MakeTensor( |
| 225 | const std::shared_ptr<ExtensionScalar>& scalar) { |
| 226 | const auto& tensor_scalar = internal::checked_cast<const StructScalar&>(*scalar->value); |
| 227 | const auto& ext_type = |
| 228 | internal::checked_cast<const VariableShapeTensorType&>(*scalar->type); |
| 229 | |
| 230 | if (!tensor_scalar.is_valid) { |
| 231 | return Status::Invalid("Cannot convert null scalar to Tensor."); |
| 232 | } |
| 233 | ARROW_ASSIGN_OR_RAISE(const auto data_scalar, tensor_scalar.field(0)); |
| 234 | ARROW_ASSIGN_OR_RAISE(const auto shape_scalar, tensor_scalar.field(1)); |
| 235 | const auto data_array = |
| 236 | internal::checked_pointer_cast<BaseListScalar>(data_scalar)->value; |
| 237 | const auto shape_array = internal::checked_pointer_cast<Int32Array>( |
| 238 | internal::checked_pointer_cast<FixedSizeListScalar>(shape_scalar)->value); |
| 239 | |
| 240 | const auto& value_type = |
| 241 | internal::checked_cast<const FixedWidthType&>(*ext_type.value_type()); |
| 242 | |
| 243 | if (data_array->null_count() > 0) { |
| 244 | return Status::Invalid("Cannot convert data with nulls to Tensor."); |
| 245 | } |
| 246 | |
| 247 | auto permutation = ext_type.permutation(); |
| 248 | if (permutation.empty()) { |
| 249 | permutation.resize(ext_type.ndim()); |
| 250 | std::iota(permutation.begin(), permutation.end(), 0); |
| 251 | } |
| 252 | |
| 253 | if (shape_array->length() != ext_type.ndim()) { |
| 254 | return Status::Invalid("Expected shape array of length ", ext_type.ndim(), ", got ", |
| 255 | shape_array->length()); |
| 256 | } |
| 257 | std::vector<int64_t> shape; |
| 258 | shape.reserve(ext_type.ndim()); |
| 259 | for (int64_t j = 0; j < static_cast<int64_t>(ext_type.ndim()); ++j) { |
| 260 | const auto size_value = shape_array->Value(j); |
| 261 | if (size_value < 0) { |
| 262 | return Status::Invalid("shape must have non-negative values"); |
| 263 | } |
| 264 | shape.push_back(size_value); |
| 265 | } |
| 266 | |
| 267 | std::vector<std::string> dim_names = ext_type.dim_names(); |
| 268 | if (!dim_names.empty()) { |
| 269 | internal::Permute<std::string>(permutation, &dim_names); |
| 270 | } |
| 271 | |
| 272 | ARROW_ASSIGN_OR_RAISE( |
| 273 | auto strides, internal::ComputeStrides(ext_type.value_type(), shape, permutation)); |
| 274 | internal::Permute<int64_t>(permutation, &shape); |
| 275 | |
| 276 | ARROW_ASSIGN_OR_RAISE(const auto buffer, |
| 277 | internal::SliceTensorBuffer(*data_array, value_type, shape)); |
| 278 | |
| 279 | return Tensor::Make(ext_type.value_type(), buffer, shape, strides, dim_names); |
| 280 | } |
| 281 |
nothing calls this directly
no test coverage detected