[BUILD] Remove compilation warnings

python/src/triton.cc

@@ -127,10 +127,6 @@ void init_triton_runtime(py::module &&m) {
       .value("float", rt::FLOAT_T)
       .value("double", rt::DOUBLE_T)
       .value("buffer", rt::BUFFER_T);
-  // assembly mode
-  py::enum_<rt::asm_mode_t>(m, "asm_mode")
-      .value("ptx", rt::ASM_NV_PTX)
-      .value("sass", rt::ASM_NV_SASS);
   // compilation options
   py::class_<rt::options_t>(m, "options", py::dynamic_attr())
       .def(py::init<>())
@@ -142,7 +138,8 @@ void init_triton_runtime(py::module &&m) {
   //  kernel
   py::class_<rt::kernel>(m, "kernel")
       .def("__call__", &rt::kernel::operator())
-      .def_readonly("opt", &rt::kernel::opt);
+      .def_readonly("opt", &rt::kernel::opt)
+      .def("asm", &rt::kernel::get_asm);
   // tune conf
   py::class_<rt::config>(m, "config")
       .def(py::init<std::map<std::string, std::string>, int>(),

python/triton/kernel.py

@@ -6,14 +6,9 @@ import torch
 import triton._C.libtriton.triton as _triton
 
 codes = {
-    _triton.runtime.arg_type.int1: 'B',
-    _triton.runtime.arg_type.int8: 'B',
-    _triton.runtime.arg_type.int32: 'I',
-    _triton.runtime.arg_type.int64: 'Q',
-    _triton.runtime.arg_type.half: 'H',
-    _triton.runtime.arg_type.float: 'f',
-    _triton.runtime.arg_type.double: 'd',
-    _triton.runtime.arg_type.buffer: 'P'
+    _triton.runtime.arg_type.int1: 'B', _triton.runtime.arg_type.int8: 'B', _triton.runtime.arg_type.int32: 'I',
+    _triton.runtime.arg_type.int64: 'Q', _triton.runtime.arg_type.half: 'H', _triton.runtime.arg_type.float: 'f',
+    _triton.runtime.arg_type.double: 'd', _triton.runtime.arg_type.buffer: 'P'
 }
 
 

python/triton/testing.py

@@ -3,8 +3,10 @@ import os
 
 try:
     import triton._C.libtriton.cutlass as _cutlass
+    has_cutlass = True
 except ImportError:
     _cutlass = None
+    has_cutlass = False
 
 
 def sparsify_tensor(x, mask, block):
@@ -44,7 +46,7 @@ def mask_tensor(x, mask, block, value=0):
     return ret
 
 
-def allclose(x, y):
+def allclose(x, y, tol=1e-2):
     assert x.dtype == y.dtype
     diff = abs(x - y)
     x_max = torch.max(x)