updata fa3 bwd hasco of A32_RTZ_CasualOrNon_Bf16OrFp16

include/ck_tile/host/host_tensor.hpp

@@ -11,7 +11,8 @@
 #include <thread>
 #include <utility>
 #include <vector>
-
+#include <functional>
+#include <fstream>
 #include "ck_tile/core.hpp"
 #include "ck_tile/host/ranges.hpp"
 
@@ -567,6 +568,84 @@ struct HostTensor
                                       size() * FromSize / ToSize};
     }
 
+    // read data from a file, as dtype
+    // the file could dumped from torch as (targeting tensor is t here)
+    // numpy.savetxt("f.txt", t.view(-1).numpy())
+    // numpy.savetxt("f.txt", t.cpu().view(-1).numpy()) # from cuda to cpu to save
+    // numpy.savetxt("f.txt", t.cpu().view(-1).numpy(), fmt="%d")   # save as int
+    // will output f.txt, each line is a value
+    // dtype=float or int, internally will cast to real type
+    void loadtxt(std::string file_name, std::string dtype = "float")
+    {
+        std::ifstream file(file_name);
+
+        if(file.is_open())
+        {
+            std::string line;
+
+            index_t cnt = 0;
+            while(std::getline(file, line))
+            {
+                if(cnt >= static_cast<index_t>(mData.size()))
+                {
+                    throw std::runtime_error(std::string("data read from file:") + file_name +
+                                             " is too big");
+                }
+
+                if(dtype == "float")
+                {
+                    mData[cnt] = type_convert<T>(std::stof(line));
+                }
+                else if(dtype == "int" || dtype == "int32")
+                {
+                    mData[cnt] = type_convert<T>(std::stoi(line));
+                }
+                cnt++;
+            }
+            file.close();
+            if(cnt < static_cast<index_t>(mData.size()))
+            {
+                std::cerr << "Warning! reading from file:" << file_name
+                          << ", does not match the size of this tensor" << std::endl;
+            }
+        }
+        else
+        {
+            // Print an error message to the standard error
+            // stream if the file cannot be opened.
+            throw std::runtime_error(std::string("unable to open file:") + file_name);
+        }
+    }
+
+    // can save to a txt file and read from torch as:
+    // torch.from_numpy(np.loadtxt('f.txt', dtype=np.int32/np.float32...)).view([...]).contiguous()
+    void savetxt(std::string file_name, std::string dtype = "float")
+    {
+        std::ofstream file(file_name);
+
+        if(file.is_open())
+        {
+            for(auto& itm : mData)
+            {
+                if(dtype == "float")
+                    file << type_convert<float>(itm) << std::endl;
+                else if(dtype == "int")
+                    file << type_convert<int>(itm) << std::endl;
+                else
+                    // TODO: we didn't implement operator<< for all custom
+                    // data types, here fall back to float in case compile error
+                    file << type_convert<float>(itm) << std::endl;
+            }
+            file.close();
+        }
+        else
+        {
+            // Print an error message to the standard error
+            // stream if the file cannot be opened.
+            throw std::runtime_error(std::string("unable to open file:") + file_name);
+        }
+    }
+
     Descriptor mDesc;
     Data mData;
 };