issue/180：添加clip算子

include/infiniop.h

@@ -6,6 +6,7 @@
 #include "infiniop/ops/attention.h"
 #include "infiniop/ops/avg_pool.h"
 #include "infiniop/ops/causal_softmax.h"
+#include "infiniop/ops/clip.h"
 #include "infiniop/ops/conv.h"
 #include "infiniop/ops/expand.h"
 #include "infiniop/ops/gemm.h"

include/infiniop/ops/clip.h

+#ifndef __INFINIOP_CLIP_API_H__
+#define __INFINIOP_CLIP_API_H__
+
+#include "../operator_descriptor.h"
+
+typedef struct InfiniopDescriptor *infiniopClipDescriptor_t;
+
+__C __export infiniStatus_t infiniopCreateClipDescriptor(infiniopHandle_t handle,
+                                                         infiniopClipDescriptor_t *desc_ptr,
+                                                         infiniopTensorDescriptor_t y,
+                                                         infiniopTensorDescriptor_t x,
+                                                         infiniopTensorDescriptor_t min_val,
+                                                         infiniopTensorDescriptor_t max_val);
+
+__C __export infiniStatus_t infiniopGetClipWorkspaceSize(infiniopClipDescriptor_t desc, size_t *size);
+
+__C __export infiniStatus_t infiniopClip(infiniopClipDescriptor_t desc,
+                                         void *workspace,
+                                         size_t workspace_size,
+                                         void *y,
+                                         const void *x,
+                                         const void *min_val,
+                                         const void *max_val,
+                                         void *stream);
+
+__C __export infiniStatus_t infiniopDestroyClipDescriptor(infiniopClipDescriptor_t desc);
+
+#endif

src/infiniop/ops/clip/clip.h

+#ifndef __CLIP_H__
+#define __CLIP_H__
+
+#include "../../elementwise/elementwise.h"
+#include "../../operator.h"
+
+/**
+ * @brief Define the Clip descriptor for the ternary operator
+ *
+ * This macro defines a Descriptor class for the Clip operator that inherits from InfiniopDescriptor.
+ * It uses the standard elementwise operation fields and methods for a ternary operator
+ * where min_val and max_val are tensors.
+ *
+ * @param OP The operator name (clip)
+ * @param NAMESPACE The namespace (cpu or cuda)
+ */
+#define CLIP_DESCRIPTOR(OP, NAMESPACE)                                        \
+                                                                              \
+    namespace op::OP::NAMESPACE {                                             \
+    class Descriptor final : public InfiniopDescriptor {                      \
+        infiniDtype_t _dtype;                                                 \
+        op::elementwise::ElementwiseInfo _info;                               \
+        std::unique_ptr<op::elementwise::NAMESPACE::DeviceImpl> _device_info; \
+        size_t _workspace_size;                                               \
+                                                                              \
+    public:                                                                   \
+        Descriptor(                                                           \
+            infiniDtype_t dtype,                                              \
+            op::elementwise::ElementwiseInfo info,                            \
+            op::elementwise::NAMESPACE::DeviceImpl *device_info,              \
+            size_t workspace_size,                                            \
+            infiniDevice_t device_type,                                       \
+            int device_id)                                                    \
+            : InfiniopDescriptor{device_type, device_id},                     \
+              _dtype(dtype),                                                  \
+              _info(std::move(info)),                                         \
+              _device_info(std::move(device_info)),                           \
+              _workspace_size(workspace_size) {}                              \
+                                                                              \
+        ~Descriptor();                                                        \
+                                                                              \
+        size_t workspaceSize() const { return _workspace_size; }              \
+                                                                              \
+        infiniStatus_t calculate(                                             \
+            void *workspace, size_t workspace_size,                           \
+            void *output,                                                     \
+            std::vector<const void *> inputs,                                 \
+            void *stream) const;                                              \
+    };                                                                        \
+    }
+
+#endif // __CLIP_H__

src/infiniop/ops/clip/cpu/clip_cpu.cc

+#include "clip_cpu.h"
+
+namespace op::clip::cpu {
+
+Descriptor::~Descriptor() = default;
+
+infiniStatus_t createClipDescriptor(
+    infiniopHandle_t handle_,
+    Descriptor **desc_ptr,
+    infiniopTensorDescriptor_t out_desc,
+    std::vector<infiniopTensorDescriptor_t> input_desc_vec) {
+
+    auto handle = reinterpret_cast<device::cpu::Handle *>(handle_);
+    auto dtype = out_desc->dtype();
+
+    const auto &in_desc = input_desc_vec.at(0);
+    const auto &min_desc = input_desc_vec.at(1);
+    const auto &max_desc = input_desc_vec.at(2);
+    const auto &out_shape = out_desc->shape();
+    const auto &in_shape = in_desc->shape();
+    const auto &min_shape = min_desc->shape();
+    const auto &max_shape = max_desc->shape();
+
+    CHECK_DTYPE(dtype, INFINI_DTYPE_F16, INFINI_DTYPE_F32, INFINI_DTYPE_F64);
+    CHECK_SAME_SHAPE(out_shape, in_shape);
+    CHECK_SAME_SHAPE(out_shape, min_shape);
+    CHECK_SAME_SHAPE(out_shape, max_shape);
+
+    CREATE_ELEMENTWISE_CPU_DESCRIPTOR(handle, dtype, out_desc, input_desc_vec);
+
+    return INFINI_STATUS_SUCCESS;
+}
+
+infiniStatus_t Descriptor::calculate(
+    void *workspace,
+    size_t workspace_size,
+    void *output,
+    std::vector<const void *> inputs,
+    void *stream) const {
+
+    switch (_dtype) {
+    case INFINI_DTYPE_F16:
+        return _device_info->calculate<ClipOp, fp16_t>(_info, output, inputs, stream);
+    case INFINI_DTYPE_F32:
+        return _device_info->calculate<ClipOp, float>(_info, output, inputs, stream);
+    case INFINI_DTYPE_F64:
+        return _device_info->calculate<ClipOp, double>(_info, output, inputs, stream);
+    default:
+        return INFINI_STATUS_BAD_TENSOR_DTYPE;
+    }
+
+    return INFINI_STATUS_SUCCESS;
+}
+} // namespace op::clip::cpu

src/infiniop/ops/clip/cpu/clip_cpu.h

+#ifndef __CLIP_CPU_H__
+#define __CLIP_CPU_H__
+
+#include "../../../elementwise/cpu/elementwise_cpu.h"
+#include "../clip.h"
+
+CLIP_DESCRIPTOR(clip, cpu)
+
+namespace op::clip::cpu {
+
+typedef struct ClipOp {
+public:
+    static constexpr size_t num_inputs = 3;
+
+    template <typename T>
+    T operator()(const T &x, const T &min_val, const T &max_val) const {
+        return std::max(std::min(x, max_val), min_val);
+    }
+} ClipOp;
+
+// Create clip descriptor
+infiniStatus_t createClipDescriptor(
+    infiniopHandle_t handle,
+    Descriptor **desc_ptr,
+    infiniopTensorDescriptor_t out_desc,
+    std::vector<infiniopTensorDescriptor_t> input_desc_vec);
+
+} // namespace op::clip::cpu
+
+#endif // __CLIP_CPU_H__

src/infiniop/ops/clip/cuda/clip_cuda.cu

+#include "clip_cuda.cuh"
+#include "clip_cuda_internal.cuh"
+
+namespace op::clip::cuda {
+
+Descriptor::~Descriptor() = default;
+
+infiniStatus_t createClipDescriptor(
+    infiniopHandle_t handle_,
+    Descriptor **desc_ptr,
+    infiniopTensorDescriptor_t out_desc,
+    std::vector<infiniopTensorDescriptor_t> input_desc_vec) {
+
+    auto handle = reinterpret_cast<device::cuda::Handle *>(handle_);
+    auto dtype = out_desc->dtype();
+
+    const auto &in_desc = input_desc_vec.at(0);
+    const auto &min_desc = input_desc_vec.at(1);
+    const auto &max_desc = input_desc_vec.at(2);
+    const auto &out_shape = out_desc->shape();
+    const auto &in_shape = in_desc->shape();
+    const auto &min_shape = min_desc->shape();
+    const auto &max_shape = max_desc->shape();
+
+    CHECK_DTYPE(dtype, INFINI_DTYPE_F16, INFINI_DTYPE_F32, INFINI_DTYPE_F64);
+    CHECK_SAME_SHAPE(out_shape, in_shape);
+    CHECK_SAME_SHAPE(out_shape, min_shape);
+    CHECK_SAME_SHAPE(out_shape, max_shape);
+
+    CREATE_ELEMENTWISE_CUDA_DESCRIPTOR(handle, dtype, out_desc, input_desc_vec);
+
+    return INFINI_STATUS_SUCCESS;
+}
+
+infiniStatus_t Descriptor::calculate(
+    void *workspace,
+    size_t workspace_size,
+    void *output,
+    std::vector<const void *> inputs,
+    void *stream) const {
+
+    if (workspace_size < _workspace_size) {
+        return INFINI_STATUS_INSUFFICIENT_WORKSPACE;
+    }
+
+    switch (_dtype) {
+    case INFINI_DTYPE_F16:
+        return _device_info->calculate<256, ClipOp, half>(_info, workspace, output, inputs, stream);
+    case INFINI_DTYPE_F32:
+        return _device_info->calculate<256, ClipOp, float>(_info, workspace, output, inputs, stream);
+    case INFINI_DTYPE_F64:
+        return _device_info->calculate<256, ClipOp, double>(_info, workspace, output, inputs, stream);
+    default:
+        return INFINI_STATUS_BAD_TENSOR_DTYPE;
+    }
+
+    return INFINI_STATUS_SUCCESS;
+}
+} // namespace op::clip::cuda

src/infiniop/ops/clip/cuda/clip_cuda.cuh

+#ifndef __CLIP_CUDA_API_H__
+#define __CLIP_CUDA_API_H__
+
+#include "../../../elementwise/cuda/elementwise_cuda_api.cuh"
+#include "../clip.h"
+
+CLIP_DESCRIPTOR(clip, cuda)
+
+namespace op::clip::cuda {
+
+infiniStatus_t createClipDescriptor(
+    infiniopHandle_t handle,
+    Descriptor **desc_ptr,
+    infiniopTensorDescriptor_t out_desc,
+    std::vector<infiniopTensorDescriptor_t> input_desc_vec);
+
+} // namespace op::clip::cuda
+
+#endif // __CLIP_CUDA_API_H__

src/infiniop/ops/clip/cuda/clip_cuda_internal.cuh

+#ifndef __CLIP_CUDA_H__
+#define __CLIP_CUDA_H__
+
+#include "../../../elementwise/cuda/elementwise_cuda.cuh"
+#include <cuda_fp16.h>
+
+namespace op::clip::cuda {
+
+typedef struct ClipOp {
+public:
+    static constexpr size_t num_inputs = 3;
+
+    template <typename T>
+    __device__ __forceinline__ T operator()(const T &x, const T &min_val, const T &max_val) const {
+        if constexpr (std::is_same_v<T, half2>) {
+            return __hmax2(__hmin2(x, max_val), min_val);
+        } else if constexpr (std::is_same_v<T, half>) {
+            return __hmax(__hmin(x, max_val), min_val);
+        } else if constexpr (std::is_same_v<T, float>) {
+            return fmaxf(fminf(x, max_val), min_val);
+        } else if constexpr (std::is_same_v<T, double>) {
+            return fmax(fmin(x, max_val), min_val);
+        } else {
+            return std::max(std::min(x, max_val), min_val);
+        }
+    }
+} ClipOp;
+} // namespace op::clip::cuda
+
+#endif // __CLIP_CUDA_H__

src/infiniop/ops/clip/operator.cc

+#include "../../operator.h"
+#include "../../handle.h"
+#include "infiniop/ops/clip.h"
+
+#ifdef ENABLE_CPU_API
+#include "cpu/clip_cpu.h"
+#endif
+#ifdef ENABLE_CUDA_API
+#include "cuda/clip_cuda.cuh"
+#endif
+
+__C infiniStatus_t infiniopCreateClipDescriptor(
+    infiniopHandle_t handle,
+    infiniopClipDescriptor_t *desc_ptr,
+    infiniopTensorDescriptor_t y,
+    infiniopTensorDescriptor_t x,
+    infiniopTensorDescriptor_t min_val,
+    infiniopTensorDescriptor_t max_val) {
+
+#define CREATE(CASE, NAMESPACE)                                             \
+    case CASE:                                                              \
+        return op::clip::NAMESPACE::createClipDescriptor(                   \
+            handle,                                                         \
+            reinterpret_cast<op::clip::NAMESPACE::Descriptor **>(desc_ptr), \
+            y,                                                              \
+            {x, min_val, max_val})
+
+    switch (handle->device) {
+
+#ifdef ENABLE_CPU_API
+        CREATE(INFINI_DEVICE_CPU, cpu);
+#endif
+#ifdef ENABLE_CUDA_API
+        CREATE(INFINI_DEVICE_NVIDIA, cuda);
+#endif
+
+    default:
+        return INFINI_STATUS_DEVICE_TYPE_NOT_SUPPORTED;
+    }
+
+#undef CREATE
+}
+
+__C infiniStatus_t infiniopGetClipWorkspaceSize(infiniopClipDescriptor_t desc, size_t *size) {
+
+#define GET(CASE, NAMESPACE)                                                                \
+    case CASE:                                                                              \
+        *size = reinterpret_cast<op::clip::NAMESPACE::Descriptor *>(desc)->workspaceSize(); \
+        return INFINI_STATUS_SUCCESS;
+
+    switch (desc->device_type) {
+#ifdef ENABLE_CPU_API
+        GET(INFINI_DEVICE_CPU, cpu)
+#endif
+#ifdef ENABLE_CUDA_API
+        GET(INFINI_DEVICE_NVIDIA, cuda)
+#endif
+    }
+
+#undef GET
+
+    return INFINI_STATUS_DEVICE_TYPE_NOT_SUPPORTED;
+}
+
+__C infiniStatus_t infiniopClip(
+    infiniopClipDescriptor_t desc,
+    void *workspace,
+    size_t workspace_size,
+    void *y,
+    const void *x,
+    const void *min_val,
+    const void *max_val,
+    void *stream) {
+
+#define CALCULATE(CASE, NAMESPACE)                                             \
+    case CASE:                                                                 \
+        return reinterpret_cast<const op::clip::NAMESPACE::Descriptor *>(desc) \
+            ->calculate(workspace, workspace_size, y, {x, min_val, max_val}, stream)
+
+    switch (desc->device_type) {
+
+#ifdef ENABLE_CPU_API
+        CALCULATE(INFINI_DEVICE_CPU, cpu);
+#endif
+#ifdef ENABLE_CUDA_API
+        CALCULATE(INFINI_DEVICE_NVIDIA, cuda);
+#endif
+
+    default:
+        return INFINI_STATUS_DEVICE_TYPE_NOT_SUPPORTED;
+    }
+
+#undef CALCULATE
+}
+
+__C infiniStatus_t
+infiniopDestroyClipDescriptor(infiniopClipDescriptor_t desc) {
+
+#define DELETE(CASE, NAMESPACE)                                                 \
+    case CASE:                                                                  \
+        delete reinterpret_cast<const op::clip::NAMESPACE::Descriptor *>(desc); \
+        return INFINI_STATUS_SUCCESS;
+
+    switch (desc->device_type) {
+
+#ifdef ENABLE_CPU_API
+        DELETE(INFINI_DEVICE_CPU, cpu);
+#endif
+#ifdef ENABLE_CUDA_API
+        DELETE(INFINI_DEVICE_NVIDIA, cuda);
+#endif
+
+    default:
+        return INFINI_STATUS_DEVICE_TYPE_NOT_SUPPORTED;
+    }
+
+#undef DELETE
+}

test/infiniop/clip.py

+#!/usr/bin/env python3
+
+import torch
+import ctypes
+from ctypes import POINTER, Structure, c_int32, c_size_t, c_uint64, c_void_p, c_float
+from libinfiniop import (
+    infiniopHandle_t,
+    infiniopTensorDescriptor_t,
+    open_lib,
+    to_tensor,
+    get_test_devices,
+    check_error,
+    rearrange_if_needed,
+    create_workspace,
+    test_operator,
+    get_args,
+    debug,
+    get_tolerance,
+    profile_operation,
+)
+from enum import Enum, auto
+
+# ==============================================================================
+#  Configuration (Internal Use Only)
+# ==============================================================================
+# These are not meant to be imported from other modules
+_TEST_CASES_ = [
+    # shape, x_stride, y_stride, min_val, max_val
+    # 基本形状测试
+    ((10,), None, None, -1.0, 1.0),
+    ((5, 10), None, None, -1.0, 1.0),
+    ((2, 3, 4), None, None, -1.0, 1.0),
+    # 不同的min_val和max_val
+    ((10,), None, None, 0.0, 2.0),
+    ((5, 10), None, None, 0.0, 2.0),
+    ((2, 3, 4), None, None, 0.0, 2.0),
+    ((10,), None, None, -2.0, 0.0),
+    ((5, 10), None, None, -2.0, 0.0),
+    ((2, 3, 4), None, None, -2.0, 0.0),
+    # 奇怪形状测试
+    ((7, 13), None, None, -1.0, 1.0),     # 质数维度
+    ((3, 5, 7), None, None, -1.0, 1.0),   # 三维质数
+    # 非标准形状测试
+    ((1, 1), None, None, -1.0, 1.0),       # 最小形状
+    ((100, 100), None, None, -1.0, 1.0),   # 大形状
+    ((16, 16, 16), None, None, -1.0, 1.0), # 大三维
+    # 极端值测试
+    ((10,), None, None, -1000.0, 1000.0),  # 大范围
+    ((10,), None, None, -0.001, 0.001),    # 小范围
+    ((10,), None, None, 0.0, 0.0),         # min=max
+    # 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]
+
+
+_TOLERANCE_MAP = {
+    torch.float32: {"atol": 1e-7, "rtol": 1e-6},
+    torch.float64: {"atol": 1e-10, "rtol": 1e-10},
+}
+
+
+class Inplace(Enum):
+    OUT_OF_PLACE = auto()
+    INPLACE_X = auto()
+
+
+_INPLACE = [
+    Inplace.INPLACE_X,
+    Inplace.OUT_OF_PLACE,
+]
+
+_TEST_CASES = [
+    test_case + (inplace_item,)
+    for test_case in _TEST_CASES_
+    for inplace_item in _INPLACE
+]
+
+DEBUG = False
+PROFILE = False
+NUM_PRERUN = 10
+NUM_ITERATIONS = 1000
+
+
+class ClipDescriptor(Structure):
+    _fields_ = [("device_type", c_int32), ("device_id", c_int32)]
+
+
+infiniopClipDescriptor_t = POINTER(ClipDescriptor)
+
+
+def clip(x, min_val, max_val):
+    return torch.clamp(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
+
+
+def test(
+    lib,
+    handle,
+    torch_device,
+    shape,
+    x_stride=None,
+    y_stride=None,
+    min_val=-1.0,
+    max_val=1.0,
+    inplace=Inplace.OUT_OF_PLACE,
+    dtype=torch.float32,
+):
+    print(
+        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
+        )
+    )
+
+    workspace_size = c_uint64(0)
+    check_error(
+        lib.infiniopGetClipWorkspaceSize(
+            descriptor, ctypes.byref(workspace_size)
+        )
+    )
+    workspace = create_workspace(workspace_size.value, x.device)
+
+    def lib_clip():
+        check_error(
+            lib.infiniopClip(
+                descriptor,
+                workspace.data_ptr() if workspace is not None else None,
+                workspace_size.value,
+                y_tensor.data,
+                x_tensor.data,
+                min_tensor_desc.data,
+                max_tensor_desc.data,
+                None,
+            )
+        )
+
+    lib_clip()
+
+    # 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)
+
+    atol, rtol = get_tolerance(_TOLERANCE_MAP, dtype)
+    if DEBUG or not torch.allclose(y, ans, atol=atol, rtol=rtol):
+        print("\nExpected:")
+        print(ans)
+        print("\nActual:")
+        print(y)
+        print("\nDifference:")
+        print(torch.abs(y - ans))
+        print("\nMax difference:", torch.max(torch.abs(y - ans)).item())
+        debug(y, ans, atol=atol, rtol=rtol)
+    assert torch.allclose(y, ans, atol=atol, rtol=rtol)
+
+    # Profiling workflow
+    if PROFILE:
+        # fmt: off
+        profile_operation("PyTorch", lambda: clip(x, min_val, max_val), torch_device, NUM_PRERUN, NUM_ITERATIONS)
+        profile_operation("    lib", lambda: lib_clip(), torch_device, NUM_PRERUN, NUM_ITERATIONS)
+        # fmt: on
+
+    check_error(lib.infiniopDestroyClipDescriptor(descriptor))
+
+
+if __name__ == "__main__":
+    args = get_args()
+    lib = open_lib()
+
+    lib.infiniopCreateClipDescriptor.restype = c_int32
+    lib.infiniopCreateClipDescriptor.argtypes = [
+        infiniopHandle_t,
+        POINTER(infiniopClipDescriptor_t),
+        infiniopTensorDescriptor_t,
+        infiniopTensorDescriptor_t,
+        infiniopTensorDescriptor_t,
+        infiniopTensorDescriptor_t,
+    ]
+
+    lib.infiniopGetClipWorkspaceSize.restype = c_int32
+    lib.infiniopGetClipWorkspaceSize.argtypes = [
+        infiniopClipDescriptor_t,
+        POINTER(c_uint64),
+    ]
+
+    lib.infiniopClip.restype = c_int32
+    lib.infiniopClip.argtypes = [
+        infiniopClipDescriptor_t,
+        c_void_p,
+        c_uint64,
+        c_void_p,
+        c_void_p,
+        c_void_p,
+        c_void_p,
+        c_void_p,
+    ]
+
+    lib.infiniopDestroyClipDescriptor.restype = c_int32
+    lib.infiniopDestroyClipDescriptor.argtypes = [
+        infiniopClipDescriptor_t,
+    ]
+
+    # Configure testing options
+    DEBUG = args.debug
+    PROFILE = args.profile
+    NUM_PRERUN = args.num_prerun
+    NUM_ITERATIONS = args.num_iterations
+
+    for device in get_test_devices(args):
+        test_operator(lib, device, test, _TEST_CASES, _TENSOR_DTYPES)
+
+    print("\033[92mTest passed!\033[0m")