Fix linter errors

Co-Authored-By: Emilio Castillo <ecastillo@nvidia.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: 3 people

cuda_core/cuda/core/_tensor_bridge.pyx

@@ -134,26 +134,26 @@ cdef inline int check_aoti(AOTITorchError err, const char* name) except? -1:
 
 cdef dict _build_dtype_map():
     try:
-        from ml_dtypes import bfloat16 as _bf16
+        from ml_dtypes import bfloat16 as _bf16  # noqa: F811
         has_bfloat16 = True
     except ImportError:
         has_bfloat16 = False
 
     cdef dict m = {
-        aoti_torch_dtype_float16():    numpy.dtype(numpy.float16),
-        aoti_torch_dtype_float32():    numpy.dtype(numpy.float32),
-        aoti_torch_dtype_float64():    numpy.dtype(numpy.float64),
-        aoti_torch_dtype_uint8():      numpy.dtype(numpy.uint8),
-        aoti_torch_dtype_int8():       numpy.dtype(numpy.int8),
-        aoti_torch_dtype_int16():      numpy.dtype(numpy.int16),
-        aoti_torch_dtype_int32():      numpy.dtype(numpy.int32),
-        aoti_torch_dtype_int64():      numpy.dtype(numpy.int64),
-        aoti_torch_dtype_bool():       numpy.dtype(numpy.bool_),
-        aoti_torch_dtype_complex64():  numpy.dtype(numpy.complex64),
+        aoti_torch_dtype_float16(): numpy.dtype(numpy.float16),
+        aoti_torch_dtype_float32(): numpy.dtype(numpy.float32),
+        aoti_torch_dtype_float64(): numpy.dtype(numpy.float64),
+        aoti_torch_dtype_uint8(): numpy.dtype(numpy.uint8),
+        aoti_torch_dtype_int8(): numpy.dtype(numpy.int8),
+        aoti_torch_dtype_int16(): numpy.dtype(numpy.int16),
+        aoti_torch_dtype_int32(): numpy.dtype(numpy.int32),
+        aoti_torch_dtype_int64(): numpy.dtype(numpy.int64),
+        aoti_torch_dtype_bool(): numpy.dtype(numpy.bool_),
+        aoti_torch_dtype_complex64(): numpy.dtype(numpy.complex64),
         aoti_torch_dtype_complex128(): numpy.dtype(numpy.complex128),
     }
     if has_bfloat16:
-        m[aoti_torch_dtype_bfloat16()] = numpy.dtype("bfloat16")
+        m[aoti_torch_dtype_bfloat16()] = numpy.dtype(_bf16)
     return m
 
 

cuda_core/tests/test_utils.py

@@ -845,6 +845,7 @@ def test_torch_tensor_bridge_cpu(init_cuda):
 @_torch_skip
 def test_torch_tensor_bridge_decorator(init_cuda):
     """Verify tensor bridge works through the args_viewable_as_strided_memory decorator."""
+
     @args_viewable_as_strided_memory((0,))
     def fn(tensor, stream):
         return tensor.view(stream.handle)