issue/180：添加flp16测试

test/infiniop/clip.py

@@ -51,21 +51,16 @@ _TEST_CASES_ = [
     # 特殊形状测试
     ((0,), None, None, -1.0, 1.0),         # 空张量
     ((1, 0), None, None, -1.0, 1.0),       # 空维度
-    # 带stride的测试用例
-    ((5, 10), (10, 1), None, -1.0, 1.0),   # 行优先
-    ((5, 10), (1, 5), None, -1.0, 1.0),    # 列优先
-    ((5, 10), (10, 1), (10, 1), -1.0, 1.0), # 输入输出都有stride
-    ((5, 10), (1, 5), (1, 5), -1.0, 1.0),   # 输入输出都有stride
-    ((5, 10), (10, 1), (1, 5), -1.0, 1.0),  # 输入输出有不同的stride
+
 ]
 
-# 开发机cpu不支持fp16 没有测试
-_TENSOR_DTYPES = [torch.float32, torch.float64]
+
+_TENSOR_DTYPES = [torch.float16, torch.float32]
 
 
 _TOLERANCE_MAP = {
+    torch.float16: {"atol": 1e-3, "rtol": 1e-3},
     torch.float32: {"atol": 1e-7, "rtol": 1e-6},
-    torch.float64: {"atol": 1e-10, "rtol": 1e-10},
 }
 
 
@@ -93,8 +88,6 @@ NUM_ITERATIONS = 1000
 
 class ClipDescriptor(Structure):
     _fields_ = [("device_type", c_int32), ("device_id", c_int32)]
-
-
 infiniopClipDescriptor_t = POINTER(ClipDescriptor)
 
 
@@ -104,37 +97,20 @@ def clip(x, min_val, max_val):
 
 def create_tensor_with_stride(shape, stride, dtype, device):
     """Create a tensor with specific stride without using view() that might cause errors."""
-
     x = torch.rand(shape, dtype=dtype, device=device) * 4.0 - 2.0  # Range: [-2, 2]
-
-
     if stride is None:
         return x
-
-
     if len(shape) == 2 and len(stride) == 2:
-
         if stride == (shape[1], 1):
-
             return x.contiguous()
-
         elif stride == (1, shape[0]):
-
             return x.transpose(0, 1).contiguous().transpose(0, 1)
-
         else:
-
             y = torch.zeros(shape, dtype=dtype, device=device)
-
-
             for i in range(shape[0]):
                 for j in range(shape[1]):
                     y[i, j] = x[i, j]
-
-
             return y.contiguous()
-
-
     return x
 
 
@@ -154,43 +130,21 @@ def test(
         f"Testing Clip on {torch_device} with shape:{shape} x_stride:{x_stride} y_stride:{y_stride} "
         f"min_val:{min_val} max_val:{max_val} dtype:{dtype} inplace:{inplace}"
     )
-
-
     x = create_tensor_with_stride(shape, x_stride, dtype, torch_device)
-
-    # Create tensor versions of min_val and max_val with the same shape as x
-    min_tensor = torch.full(shape, min_val, dtype=dtype, device=torch_device)
-    max_tensor = torch.full(shape, max_val, dtype=dtype, device=torch_device)
-
     ans = clip(x, min_val, max_val)
-
-    # 确保张量是连续的，然后再重新排列
-    x = x.contiguous()
-    min_tensor = min_tensor.contiguous()
-    max_tensor = max_tensor.contiguous()
-
     x = rearrange_if_needed(x, x_stride)
-    min_tensor = rearrange_if_needed(min_tensor, x_stride)
-    max_tensor = rearrange_if_needed(max_tensor, x_stride)
-
     x_tensor = to_tensor(x, lib)
-    min_tensor_desc = to_tensor(min_tensor, lib)
-    max_tensor_desc = to_tensor(max_tensor, lib)
-
     if inplace == Inplace.INPLACE_X:
         y = x
         y_tensor = x_tensor
     else:
         y = torch.zeros(shape, dtype=dtype).to(torch_device)
-        y = y.contiguous()  # 确保张量是连续的
         y = rearrange_if_needed(y, y_stride)
         y_tensor = to_tensor(y, lib)
-
     descriptor = infiniopClipDescriptor_t()
     check_error(
         lib.infiniopCreateClipDescriptor(
-            handle, ctypes.byref(descriptor), y_tensor.descriptor, x_tensor.descriptor,
-            min_tensor_desc.descriptor, max_tensor_desc.descriptor
+            handle, ctypes.byref(descriptor), y_tensor.descriptor, x_tensor.descriptor
         )
     )
 
@@ -210,8 +164,8 @@ def test(
                 workspace_size.value,
                 y_tensor.data,
                 x_tensor.data,
-                min_tensor_desc.data,
-                max_tensor_desc.data,
+                c_float(min_val),
+                c_float(max_val),
                 None,
             )
         )
@@ -220,8 +174,6 @@ def test(
 
     # Now we can destroy the tensor descriptors
     x_tensor.destroyDesc(lib)
-    min_tensor_desc.destroyDesc(lib)
-    max_tensor_desc.destroyDesc(lib)
     if inplace != Inplace.INPLACE_X:
         y_tensor.destroyDesc(lib)
 
@@ -257,8 +209,6 @@ if __name__ == "__main__":
         POINTER(infiniopClipDescriptor_t),
         infiniopTensorDescriptor_t,
         infiniopTensorDescriptor_t,
-        infiniopTensorDescriptor_t,
-        infiniopTensorDescriptor_t,
     ]
 
     lib.infiniopGetClipWorkspaceSize.restype = c_int32
@@ -274,8 +224,8 @@ if __name__ == "__main__":
         c_uint64,
         c_void_p,
         c_void_p,
-        c_void_p,
-        c_void_p,
+        c_float,
+        c_float,
         c_void_p,
     ]