if (!s.ok()) {
    device_name = "<error fetching device name>";
  }
  return absl::StrCat("TensorHandle(", value_string, ", shape=", shape_string,
                      ", dtype=", DataType_Name(DataType()), ", device=\"",
                      device_name, "\")");
}

absl::Status ImmediateExecutionTensorHandle::SummarizeValue(
    std::string& summary) const {
  absl::Status status;
  AbstractTensorPtr resolved(

  builder->Set(*iter, static_cast<tensorflow::DataType>(value));
}

void TF_AttrBuilderSetTypeList(TF_AttrBuilder* builder, const char* attr_name,
                               const TF_DataType* values, int num_values) {
  auto iter = builder->attr_names.insert(attr_name).first;
  builder->Set(*iter, tensorflow::gtl::ArraySlice<const tensorflow::DataType>(

						columnType)
				}
			case "name":
				dataType := DB.Dialector.DataTypeOf(stmt.Schema.LookUpField(columnType.Name()))
				if !strings.Contains(strings.ToUpper(dataType), strings.ToUpper(columnType.DatabaseTypeName())) {
					t.Fatalf("column name type should be correct, name: %v, length: %v, expects: %v, column: %#v",
						columnType.Name(), columnType.DatabaseTypeName(), dataType, columnType)
				}

			} else {
				schema.Fields = append(schema.Fields, field)
			}
		}
	}

	for _, field := range schema.Fields {
		if field.DBName == "" && field.DataType != "" {
			field.DBName = namer.ColumnName(schema.Table, field.Name)
		}

		bindName := field.BindName()
		if field.DBName != "" {
			// nonexistence or shortest path or first appear prioritized if has permission

  virtual AbstractTensorInterface* CreateBoolScalar(bool value) = 0;

  // Tensor creation functions
  virtual AbstractTensorInterface* CreateTensor(
      DataType dtype, absl::Span<const int64_t> dim_sizes) = 0;

  typedef void (*MemoryReleaser)(void* data, size_t len, void* arg);

  // Create a tensor instance from the given data buffer and description.

 protected:
  explicit TracingContext(AbstractContextKind kind) : AbstractContext(kind) {}

 public:
  // Add a function parameter and return the corresponding tensor.
  virtual absl::Status AddParameter(DataType dtype,
                                    const PartialTensorShape& shape,
                                    TracingTensorHandle**) = 0;

  // Finalize this context and make a function out of it. The context is in a

  if (h) {
    tensorflow::unwrap(h)->Unref();
  }
}

TF_DataType TFE_TensorHandleDataType(TFE_TensorHandle* h) {
  return static_cast<TF_DataType>(tensorflow::unwrap(h)->DataType());
}

int TFE_TensorHandleNumDims(TFE_TensorHandle* h, TF_Status* status) {
  if (h == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");
    return -1;
  }

    val jacksonDatabind = "com.fasterxml.jackson.core:jackson-databind"
    val jacksonDatatypeJdk8 = "com.fasterxml.jackson.datatype:jackson-datatype-jdk8"
    val jacksonDatatypeJsr310 = "com.fasterxml.jackson.datatype:jackson-datatype-jsr310"
    val jakartaActivation = "com.sun.activation:jakarta.activation"
    val jakartaXmlBind = "jakarta.xml.bind:jakarta.xml.bind-api"
    val jansi = "org.fusesource.jansi:jansi"

	for _, ref := range relation.References {
		f := joinSchema.LookUpField(ref.ForeignKey.DBName)
		if f == nil {
			return fmt.Errorf("missing field %s for join table", ref.ForeignKey.DBName)
		}

		f.DataType = ref.ForeignKey.DataType
		f.GORMDataType = ref.ForeignKey.GORMDataType
		if f.Size == 0 {
			f.Size = ref.ForeignKey.Size
		}
		ref.ForeignKey = f
	}

class TapeTensor {
 public:
  explicit TapeTensor(AbstractTensorHandle* handle);
  TapeTensor(const TapeTensor& other);
  ~TapeTensor();

  int64_t GetID() const;
  tensorflow::DataType GetDType() const;

  AbstractTensorHandle* ZerosLike() const;

  AbstractTensorHandle* GetHandle() const;

 private:
  AbstractTensorHandle* handle_;
};