Ensure backward compatibility with Torch 2.2

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

ktransformers/ktransformers_ext/cuda/binding.cpp

@@ -20,38 +20,45 @@
 
 PYBIND11_MODULE(KTransformersOps, m) {
 
-    m.def("dequantize_q8_0", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, torch::Dtype target_dtype) {
-        return dequantize_q8_0((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, target_dtype);
+    m.def("dequantize_q8_0", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, py::object target_dtype) {
+        torch::Dtype dtype = torch::python::detail::py_object_to_dtype(target_dtype);
+        return dequantize_q8_0((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, dtype);
         }, "Function to dequantize q8_0 data.",
         py::arg("data"), py::arg("num_bytes"), py::arg("blk_size"), py::arg("ele_per_blk"), py::arg("device"), py::arg("target_dtype"));
 
-    m.def("dequantize_q6_k", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, torch::Dtype target_dtype) {
-        return dequantize_q6_k((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, target_dtype);
+    m.def("dequantize_q6_k", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, py::object target_dtype) {
+        torch::Dtype dtype = torch::python::detail::py_object_to_dtype(target_dtype);
+        return dequantize_q6_k((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, dtype);
         }, "Function to dequantize q6_k data.",
         py::arg("data"), py::arg("num_bytes"), py::arg("blk_size"), py::arg("ele_per_blk"), py::arg("device"), py::arg("target_dtype"));
 
-    m.def("dequantize_q5_k", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, torch::Dtype target_dtype) {
-        return dequantize_q5_k((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, target_dtype);
+    m.def("dequantize_q5_k", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, py::object target_dtype) {
+        torch::Dtype dtype = torch::python::detail::py_object_to_dtype(target_dtype);
+        return dequantize_q5_k((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, dtype);
         }, "Function to dequantize q5_k data.",
         py::arg("data"), py::arg("num_bytes"), py::arg("blk_size"), py::arg("ele_per_blk"), py::arg("device"), py::arg("target_dtype"));
 
-    m.def("dequantize_q4_k", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, torch::Dtype target_dtype) {
-        return dequantize_q4_k((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, target_dtype);
+    m.def("dequantize_q4_k", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, py::object target_dtype) {
+        torch::Dtype dtype = torch::python::detail::py_object_to_dtype(target_dtype);
+        return dequantize_q4_k((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, dtype);
         }, "Function to dequantize q4_k data.",
         py::arg("data"), py::arg("num_bytes"), py::arg("blk_size"), py::arg("ele_per_blk"), py::arg("device"), py::arg("target_dtype"));
 
-    m.def("dequantize_q3_k", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, torch::Dtype target_dtype) {
-        return dequantize_q3_k((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, target_dtype);
+    m.def("dequantize_q3_k", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, py::object target_dtype) {
+        torch::Dtype dtype = torch::python::detail::py_object_to_dtype(target_dtype);
+        return dequantize_q3_k((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, dtype);
         }, "Function to dequantize q3_k data.",
         py::arg("data"), py::arg("num_bytes"), py::arg("blk_size"), py::arg("ele_per_blk"), py::arg("device"), py::arg("target_dtype"));
 
-    m.def("dequantize_q2_k", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, torch::Dtype target_dtype) {
-        return dequantize_q2_k((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, target_dtype);
+    m.def("dequantize_q2_k", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, py::object target_dtype) {
+        torch::Dtype dtype = torch::python::detail::py_object_to_dtype(target_dtype);
+        return dequantize_q2_k((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, dtype);
         }, "Function to dequantize q2_k data.",
         py::arg("data"), py::arg("num_bytes"), py::arg("blk_size"), py::arg("ele_per_blk"), py::arg("device"), py::arg("target_dtype"));
 
-    m.def("dequantize_iq4_xs", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, torch::Dtype target_dtype) {
-        return dequantize_iq4_xs((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, target_dtype);
+    m.def("dequantize_iq4_xs", [](const intptr_t data, int num_bytes, int blk_size, const int ele_per_blk, torch::Device device, py::object target_dtype) {
+        torch::Dtype dtype = torch::python::detail::py_object_to_dtype(target_dtype);
+        return dequantize_iq4_xs((int8_t*)data, num_bytes, blk_size, ele_per_blk, device, dtype);
         }, "Function to dequantize iq4_xs data.",
         py::arg("data"), py::arg("num_bytes"), py::arg("blk_size"), py::arg("ele_per_blk"), py::arg("device"), py::arg("target_dtype"));
 

ktransformers/ktransformers_ext/cuda/custom_gguf/ops.h

@@ -13,10 +13,10 @@
 #include <torch/extension.h>
 #include <torch/torch.h>
 
-torch::Tensor dequantize_q8_0(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::ScalarType target_dtype);
-torch::Tensor dequantize_q6_k(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::ScalarType target_dtype);
-torch::Tensor dequantize_q5_k(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::ScalarType target_dtype);
-torch::Tensor dequantize_q4_k(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::ScalarType target_dtype);
-torch::Tensor dequantize_q3_k(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::ScalarType target_dtype);
-torch::Tensor dequantize_q2_k(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::ScalarType target_dtype);
-torch::Tensor dequantize_iq4_xs(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::ScalarType target_dtype);
+torch::Tensor dequantize_q8_0(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::Dtype target_dtype);
+torch::Tensor dequantize_q6_k(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::Dtype target_dtype);
+torch::Tensor dequantize_q5_k(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::Dtype target_dtype);
+torch::Tensor dequantize_q4_k(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::Dtype target_dtype);
+torch::Tensor dequantize_q3_k(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::Dtype target_dtype);
+torch::Tensor dequantize_q2_k(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::Dtype target_dtype);
+torch::Tensor dequantize_iq4_xs(const int8_t* data, const int num_bytes, const int blk_size, const int ele_per_blk, const torch::Device device, const torch::Dtype target_dtype);