fix windows encoding bugs

python/jittor/__init__.py

@@ -9,7 +9,7 @@
 # file 'LICENSE.txt', which is part of this source code package.
 # ***************************************************************
 
-__version__ = '1.3.1.44'
+__version__ = '1.3.1.45'
 from jittor_utils import lock
 with lock.lock_scope():
     ori_int = int
@@ -410,9 +410,7 @@ def flatten(input, start_dim=0, end_dim=-1):
     return input.reshape(out_shape)
 Var.flatten = flatten
 
-def start_grad(x):
+Var.detach_inplace = Var.start_grad
-    return x._update(x)
-Var.detach_inplace = Var.start_grad = start_grad
 
 def detach(x):
     return x.detach()

python/jittor/compile_extern.py

@@ -190,6 +190,11 @@ def setup_cub():
 
 def setup_cuda_extern():
     if not has_cuda: return
+    check_ld_path = os.environ.get("LD_LIBRARY_PATH", "")
+    if "cuda" in check_ld_path.lower() and "lib" in check_ld_path.lower():
+        LOG.w(f"CUDA related path found in LD_LIBRARY_PATH({check_ld_path}), "
+            "This path may cause jittor found the wrong libs, "
+            "please unset LD_LIBRARY_PATH. ")
     LOG.vv("setup cuda extern...")
     cache_path_cuda = os.path.join(cache_path, "cuda")
     cuda_include = os.path.join(jittor_path, "extern", "cuda", "inc")

python/jittor/compiler.py

@@ -199,7 +199,7 @@ def gen_jit_tests():
     }} // jittor
     """
     LOG.vvvv(jit_src)
-    with open(os.path.join(cache_path, "gen", "jit_tests.h"), 'w') as f:
+    with open(os.path.join(cache_path, "gen", "jit_tests.h"), 'w', encoding='utf8') as f:
         f.write(jit_src)
 
 def gen_jit_flags():
@@ -257,7 +257,7 @@ def gen_jit_flags():
     }} // jittor
     """
     LOG.vvvv(jit_src)
-    with open(os.path.join(cache_path, "gen", "jit_flags.h"), 'w') as f:
+    with open(os.path.join(cache_path, "gen", "jit_flags.h"), 'w', encoding='utf8') as f:
         f.write(jit_src)
 
 def gen_jit_op_maker(op_headers, export=False, extra_flags=""):
@@ -639,9 +639,9 @@ def compile_custom_op(header, source, op_name, warp=True):
     make_cache_dir(cops_dir)
     hname = os.path.join(cops_dir, op_name+"_op.h")
     ccname = os.path.join(cops_dir, op_name+"_op.cc")
-    with open(hname, 'w') as f:
+    with open(hname, 'w', encoding='utf8') as f:
         f.write(header)
-    with open(ccname, 'w') as f:
+    with open(ccname, 'w', encoding='utf8') as f:
         f.write(source)
     m = compile_custom_ops([hname, ccname])
     return getattr(m, op_name)
@@ -679,7 +679,7 @@ def compile_custom_ops(
             dirname = os.path.dirname(name)
             if dirname.endswith("inc"):
                 includes.append(dirname)
-            with open(name, "r") as f:
+            with open(name, "r", encoding='utf8') as f:
                 if "@pyjt" in f.read():
                     pyjt_includes.append(name)
         bname = os.path.basename(name)
@@ -736,7 +736,7 @@ def compile_custom_ops(
             "init_module(PyModuleDef* mdef, PyObject* m) {",
             f"jittor::pyjt_def_{bname}(m);")
 
-    with open(gen_head_fname, "w") as f:
+    with open(gen_head_fname, "w", encoding='utf8') as f:
         f.write(gen_src)
 
     LOG.vvv(f"Build custum ops lib:{gen_lib}")
@@ -781,7 +781,7 @@ def compile_extern():
     files = os.listdir(jittor_path_llvm)
     # test_pass.cc is used for test link problem of llvm pass plugin
     test_pass_path = os.path.join(cache_path_llvm, "test_pass.cc")
-    with open(test_pass_path, 'w') as f:
+    with open(test_pass_path, 'w', encoding='utf8') as f:
         f.write("int main() {return 0;}")
     
     # -fno-rtti fix link error
@@ -1082,7 +1082,7 @@ if os.name == 'nt':
         cc_flags = cc_flags.replace("-lstdc++", "")
         cc_flags = cc_flags.replace("-ldl", "")
         cc_flags += f" -L\"{py3_link_path}\" -lpython3{sys.version_info.minor} "
-        cc_flags += " -EHa -MD "
+        cc_flags += " -EHa -MD -utf-8 "
         import jittor_utils
         if jittor_utils.msvc_path:
             mp = jittor_utils.msvc_path
@@ -1217,7 +1217,7 @@ gen_jit_tests()
 op_headers = glob.glob(jittor_path+"/src/ops/**/*op.h", recursive=True)
 jit_src = gen_jit_op_maker(op_headers)
 LOG.vvvv(jit_src)
-with open(os.path.join(cache_path, "gen", "jit_op_maker.h"), 'w') as f:
+with open(os.path.join(cache_path, "gen", "jit_op_maker.h"), 'w', encoding='utf8') as f:
     f.write(jit_src)
 cc_flags += f' -I\"{cache_path}\" -L\"{cache_path}\" -L\"{jit_utils.cache_path}\" '
 # gen pyjt

python/jittor/notebook/60分钟快速入门Jittor/计图入门教程 2 --- 如何训练一个简单线性回归.ipynb

@@ -460,7 +460,7 @@
     "    train_loss_list.append(train_loss)\n",
     "    # 在验证集上进行验证，模型参数不做更新。\n",
     "    val_loss = val(model, x_val_var, y_val_var, loss_function)\n",
-    "    val_loss_list.append(val_loss)\n",
+    "    val_loss_list.append(val_loss.item())\n",
     "    \n",
     "# 打印训练结束后的模型参数\n",
     "print(\"After training: \\n\", model.state_dict())"
@@ -598,4 +598,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}

python/jittor/notebook/60分钟快速入门Jittor/计图入门教程 3 --- 尝试解决一个实际问题.ipynb

@@ -192,7 +192,7 @@
     "    \n",
     "    plt.imshow(inputs[num].numpy().transpose(1, 2, 0))      # 利用 matplotlib 根据第一个 input 绘制手写数字的图像\n",
     "    plt.show()                                              # 展示图像\n",
-    "    print(\"target:\", targets[num].data[0])                  # 打印第一个 input 数据的真实标签值，即手写数字图像所表达的真实数字\n",
+    "    print(\"target:\", targets[num].numpy()[0])                  # 打印第一个 input 数据的真实标签值，即手写数字图像所表达的真实数字\n",
     "    break"
    ]
   },
@@ -910,12 +910,12 @@
     "        outputs = model(inputs)                                        # 通过模型预测手写数字。outputs 中每个数据输出有 10 个分量，对应十个数字的相似度\n",
     "        loss = loss_function(outputs, targets)                         # 计算损失函数\n",
     "        optimizer.step(loss)                                           # 根据损失函数，对模型参数进行优化、更新\n",
-    "        train_losses.append(loss)                                      # 记录该批次的 Loss\n",
+    "        train_losses.append(loss.item())                                      # 记录该批次的 Loss\n",
     "        \n",
     "        if batch_idx % 10 == 0:                                        # 每十个批次，打印一次训练集上的 Loss \n",
     "            print('Train Epoch: {} [{}/{} ({:.0f}%)]\\tLoss: {:.6f}'.format(\n",
     "                    epoch, batch_idx, len(train_loader),\n",
-    "                    100. * batch_idx / len(train_loader), loss.data[0]))\n",
+    "                    100. * batch_idx / len(train_loader), loss.item()))\n",
     "    return train_losses                                                # 返回本纪元的 Loss\n",
     "\n",
     "\n",
@@ -926,8 +926,8 @@
     "    total_num = 0                                                      # 本纪元数据总数\n",
     "    for batch_idx, (inputs, targets) in enumerate(val_loader):         # 通过测试集加载器，按批次迭代数据\n",
     "        outputs = model(inputs)                                        # 通过模型预测手写数字。outputs 中每个数据输出有 10 个分量，对应十个数字的相似度\n",
-    "        pred = np.argmax(outputs.data, axis=1)                         # 根据 10 个分量，选择最大相似度的为预测的数字值\n",
+    "        pred = np.argmax(outputs.numpy(), axis=1)                      # 根据 10 个分量，选择最大相似度的为预测的数字值\n",
-    "        correct = np.sum(targets.data==pred)                           # 计算本批次中，正确预测的次数，即数据标签等于预测值的数目\n",
+    "        correct = np.sum(targets.numpy()==pred)                        # 计算本批次中，正确预测的次数，即数据标签等于预测值的数目\n",
     "        batch_size = inputs.shape[0]                                   # 计算本批次中，数据的总数目\n",
     "        acc = correct / batch_size                                     # 计算本批次的正确率\n",
     "        \n",
@@ -1075,10 +1075,10 @@
     "    plt.imshow(inputs[num].numpy().transpose(1, 2, 0))        # 绘制该数据的手写数字图像\n",
     "    plt.show()                                              \n",
     "    \n",
-    "    print(\"target:\", targets[num].data[0])                    # 打印该数据的真实标签值\n",
+    "    print(\"target:\", targets[num].numpy()[0])                    # 打印该数据的真实标签值\n",
     "    \n",
     "    outputs = model(inputs)                                   # 模型根据输入数据进行预测\n",
-    "    pred = np.argmax(outputs.data, axis=1)                    # 根据最大相似度得到预测值\n",
+    "    pred = np.argmax(outputs.numpy(), axis=1)                    # 根据最大相似度得到预测值\n",
     "    print(\"prediction:\", pred[num])                           # 打印该数据的预测值\n",
     "    break"
    ]
@@ -1158,4 +1158,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}

python/jittor/notebook/md_to_ipynb.py

@@ -63,5 +63,5 @@ for mdname in all_md:
     ipynb_name = os.path.basename(mdname[:-2])+"ipynb"
     ipynb_name = os.path.join(notebook_dir, ipynb_name)
     print(mdname, len(src), len(blocks), len(cells), "--->", ipynb_name)
-    with open(ipynb_name, "w") as f:
+    with open(ipynb_name, "w", encoding='utf8') as f:
         f.write(json.dumps(ipynb))

python/jittor/pyjt_compiler.py

@@ -858,13 +858,13 @@ def compile_src(src, h, basename):
 def compile_single(head_file_name, src_file_name, src=None):
     basename = os.path.basename(head_file_name).split(".")[0]
     if src==None:
-        with open(head_file_name, 'r') as f:
+        with open(head_file_name, 'r', encoding='utf8') as f:
             src = f.read()
     code = compile_src(src, head_file_name, basename)
     if not code: return False
     LOG.vvv("write to", src_file_name)
     LOG.vvvv(code)
-    with open(src_file_name, 'w') as f:
+    with open(src_file_name, 'w', encoding='utf8') as f:
         f.write(code)
     return True
 
@@ -875,14 +875,14 @@ def compile(cache_path, jittor_path):
     basenames = []
     pyjt_names = []
     for h in headers:
-        with open(h, 'r') as f:
+        with open(h, 'r', encoding='utf8') as f:
             src = f.read()
 
         bh = os.path.basename(h)
         # jit_op_maker.h merge compile with var_holder.h
         if bh == "var_holder.h": continue
         if bh == "jit_op_maker.h":
-            with open(os.path.join(jittor_path, "src", "var_holder.h"), "r") as f:
+            with open(os.path.join(jittor_path, "src", "var_holder.h"), "r", encoding='utf8') as f:
                 src = f.read() + src
         basename = bh.split(".")[0]
         fname = "pyjt_"+basename+".cc"
@@ -913,7 +913,7 @@ def compile(cache_path, jittor_path):
     fname = os.path.join(cache_path, "gen", "pyjt_all.cc")
     LOG.vvv(("write to", fname))
     LOG.vvvv(code)
-    with open(fname, "w") as f:
+    with open(fname, "w", encoding='utf8') as f:
         f.write(code)
     pyjt_names.append(fname)
     return pyjt_names

python/jittor/script/make_doc.py

@@ -1,7 +1,7 @@
 import os
 
 def fix_config(in_name, out_name, src_path, out_path):
-    data = open(in_name, 'r').readlines()
+    data = open(in_name, 'r', encoding='utf8').readlines()
     out = []
     for d in data:
         if d.startswith('INPUT                  ='):
@@ -9,7 +9,7 @@ def fix_config(in_name, out_name, src_path, out_path):
         elif d.startswith('OUTPUT_DIRECTORY       ='):
             d = f'OUTPUT_DIRECTORY       ={out_path}\n'
         out.append(d)
-    f = open(out_name, 'w')
+    f = open(out_name, 'w', encoding='utf8')
     f.writelines(out)
 
 jt_path = os.getcwd()

python/jittor/src/jit_compiler.cc

@@ -153,7 +153,7 @@ jit_op_entry_t load_jit_lib(string name, string symbol_name="jit_entry") {
     const char* msg = "";
     LOGvv << "Opening jit lib:" << name;
     #ifdef _WIN32
-    void* handle = (void*)LoadLibraryExA(name.c_str(), nullptr,
+    void* handle = (void*)LoadLibraryExA(Utf8ToGbk(name.c_str()).c_str(), nullptr,
         LOAD_LIBRARY_SEARCH_DEFAULT_DIRS |
         LOAD_LIBRARY_SEARCH_USER_DIRS);
     #elif defined(__linux__)
@@ -206,13 +206,15 @@ jit_op_entry_t compile(const string& jit_key, const string& src, const bool is_c
     string jit_src_path = Op::get_filename_from_jit_key(jit_key, ".cc");
     #ifdef _WIN32
     string jit_lib_path = Op::get_filename_from_jit_key(jit_key, ".dll");
+    string jit_src_path2 = Utf8ToGbk(jit_src_path.c_str());
     #else
     string jit_lib_path = Op::get_filename_from_jit_key(jit_key, ".so");
+    string& jit_src_path2 = jit_src_path;
     #endif
     string other_src;
     LOGvvv << "Generate" << jit_src_path >> "\n" >> src;
-    if (rewrite_op || !file_exist(jit_src_path))
+    if (rewrite_op || !file_exist(jit_src_path2))
-        write(jit_src_path, src);
+        write(jit_src_path2, src);
     string cmd;
     
     auto symbol_name = get_symbol_name(jit_key);

python/jittor/src/pyjt/py_converter.h

@@ -45,13 +45,7 @@ DEF_IS(string, PyObject*) to_py_object(const string& a) {
 
 DEF_IS(string, string) from_py_object(PyObject* obj) {
     Py_ssize_t size;
-    #ifdef _WIN32
-    PyObjHolder a(PyUnicode_AsEncodedString(obj, win_encode.c_str(), "strict"));
-    char* s;
-    auto ret = PyBytes_AsStringAndSize(a.obj, &s, &size);
-    #else
     const char* s = PyUnicode_AsUTF8AndSize(obj, &size);
-    #endif
     CHECK(s);
     return string(s, size);
 }

python/jittor/src/utils/cache_compile.cc

@@ -234,7 +234,15 @@ static inline bool is_full_path(const string& name) {
 #endif
 }
 
-bool cache_compile(string cmd, const string& cache_path, const string& jittor_path) {
+bool cache_compile(string cmd, const string& cache_path_, const string& jittor_path_) {
+    #ifdef _WIN32
+    cmd = Utf8ToGbk(cmd.c_str());
+    string cache_path = Utf8ToGbk(cache_path_.c_str());
+    string jittor_path = Utf8ToGbk(jittor_path_.c_str());
+    #else
+    const string& cache_path = cache_path_;
+    const string& jittor_path = jittor_path_;
+    #endif
     vector<string> input_names;
     map<string,vector<string>> extra;
     string output_name;
@@ -255,6 +263,9 @@ bool cache_compile(string cmd, const string& cache_path, const string& jittor_pa
             continue;
         processed.insert(input_names[i]);
         auto src = read_all(input_names[i]);
+        #ifdef _WIN32
+        src = Utf8ToGbk(src.c_str());
+        #endif
         auto back = input_names[i].back();
         // *.lib
         if (back == 'b') continue;

python/jittor/src/utils/log.cc

@@ -316,19 +316,13 @@ int register_sigaction() {
     return 0;
 }
 
-#ifdef _WIN32
-string win_encode;
-#endif
-
 static int log_init() {
+    #ifdef _WIN32
+    SetConsoleCP(CP_UTF8);
+    SetConsoleOutputCP(CP_UTF8);
+    #endif
     register_sigaction();
     std::atexit(log_exiting);
-    #ifdef _WIN32
-    if (getenv("JITTOR_ENCODE"))
-        win_encode = getenv("JITTOR_ENCODE");
-    else
-        win_encode = "gbk";
-    #endif
     return 1;
 }
 
@@ -456,6 +450,39 @@ If you still have problems, please contact us:
 }
 
 #ifdef _WIN32
+
+string GbkToUtf8(const char *src_str)
+{
+	int len = MultiByteToWideChar(CP_ACP, 0, src_str, -1, NULL, 0);
+	wchar_t* wstr = new wchar_t[len + 1];
+	memset(wstr, 0, len + 1);
+	MultiByteToWideChar(CP_ACP, 0, src_str, -1, wstr, len);
+	len = WideCharToMultiByte(CP_UTF8, 0, wstr, -1, NULL, 0, NULL, NULL);
+	char* str = new char[len + 1];
+	memset(str, 0, len + 1);
+	WideCharToMultiByte(CP_UTF8, 0, wstr, -1, str, len, NULL, NULL);
+	string strTemp = str;
+	if (wstr) delete[] wstr;
+	if (str) delete[] str;
+	return strTemp;
+}
+
+string Utf8ToGbk(const char *src_str)
+{
+	int len = MultiByteToWideChar(CP_UTF8, 0, src_str, -1, NULL, 0);
+	wchar_t* wszGBK = new wchar_t[len + 1];
+	memset(wszGBK, 0, len * 2 + 2);
+	MultiByteToWideChar(CP_UTF8, 0, src_str, -1, wszGBK, len);
+	len = WideCharToMultiByte(CP_ACP, 0, wszGBK, -1, NULL, 0, NULL, NULL);
+	char* szGBK = new char[len + 1];
+	memset(szGBK, 0, len + 1);
+	WideCharToMultiByte(CP_ACP, 0, wszGBK, -1, szGBK, len, NULL, NULL);
+	string strTemp(szGBK);
+	if (wszGBK) delete[] wszGBK;
+	if (szGBK) delete[] szGBK;
+	return strTemp;
+}
+
 int system_popen(const char *cmd, const char* cwd) {
     HANDLE g_hChildStd_OUT_Rd = NULL;
     HANDLE g_hChildStd_OUT_Wr = NULL;

python/jittor/src/utils/log.h

@@ -16,6 +16,10 @@ namespace jittor {
 // define in tracer.cc
 void print_trace();
 void breakpoint();
+#ifdef _WIN32
+string GbkToUtf8(const char *src_str);
+string Utf8ToGbk(const char *src_str);
+#endif
     
 constexpr int32_t basename_index(const char * const path, const int32_t index = 0, const int32_t slash_index = -1) {
    return path[index]
@@ -277,8 +281,4 @@ bool check_vlog(const char* fileline, int verbose);
 
 void system_with_check(const char* cmd, const char* cwd=nullptr);
 
-#ifdef _WIN32
-extern string win_encode;
-#endif
-
 } // jittor

python/jittor/src/var_holder.h

@@ -181,12 +181,24 @@ struct VarHolder {
     inline void set_requires_grad(bool flag) {
         if (flag == get_requires_grad()) return;
         if (flag)
-            _update(this);
+            start_grad();
         else
             stop_grad(); 
         return;
     }
 
+    /** 
+     * enable the gradient calculation for the Var.
+     */
+    // @pyjt(start_grad)
+    // @attrs(return_self)
+    inline VarHolder* start_grad() {
+        if (!var->dtype().is_float())
+            LOGw << "cannot enable grad of a non-float value:" << var;
+        _update(this);
+        return this;
+    }
+
     // @pyjt(__get__uncertain_shape)
     inline NanoVector uncertain_shape() {
         return var->shape;

python/jittor/test/test_grad.py

@@ -142,6 +142,11 @@ class TestGrad(unittest.TestCase):
         expect_error(lambda: jt.grad(z, [y1]))
         dx, = jt.grad(z, [x])
         self.assertEqual(dx.data, 48)
+
+    def test_int_enable_grad(self):
+        a = jt.int([1,2,3])
+        a.requires_grad = True
+        a.start_grad()
         
     def test_nth_grad(self):
         x = jt.array(2.0)

python/jittor_utils/translator.py

@@ -23,7 +23,7 @@ def check_is_both(src):
 
 for mdname in all_src_md:
     print(mdname)
-    with open(mdname, "r") as f:
+    with open(mdname, "r", encoding='utf8') as f:
         src = f.read()
     src = src.split("```")
     en_src = []
@@ -47,8 +47,8 @@ for mdname in all_src_md:
             cn_src.append("\n".join(cn_s))
     en_src = "```".join(en_src)
     cn_src = "```".join(cn_src)
-    with open(mdname.replace(".src.md", ".md"), 'w') as f:
+    with open(mdname.replace(".src.md", ".md"), 'w', encoding='utf8') as f:
         f.write(en_src)
-    with open(mdname.replace(".src.md", ".cn.md"), 'w') as f:
+    with open(mdname.replace(".src.md", ".cn.md"), 'w', encoding='utf8') as f:
         f.write(cn_src)