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diff --git a/‎paddle/cinn/runtime/buffer.cc
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+14-5Lines changed: 14 additions & 5 deletions b/‎paddle/cinn/runtime/buffer.cc
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100755100644
+14-5Lines changed: 14 additions & 5 deletions
diff --git a/‎paddle/cinn/runtime/buffer.h
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+22-5Lines changed: 22 additions & 5 deletions b/‎paddle/cinn/runtime/buffer.h
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+22-5Lines changed: 22 additions & 5 deletions
diff --git a/‎paddle/cinn/runtime/cpu/cblas.cc
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+24-8Lines changed: 24 additions & 8 deletions b/‎paddle/cinn/runtime/cpu/cblas.cc
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+24-8Lines changed: 24 additions & 8 deletions
diff --git a/‎paddle/cinn/runtime/cpu/mkl_math.cc
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+25-12Lines changed: 25 additions & 12 deletions b/‎paddle/cinn/runtime/cpu/mkl_math.cc
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+25-12Lines changed: 25 additions & 12 deletions
diff --git a/‎paddle/cinn/runtime/cpu/mkl_math_test.cc
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+9-1Lines changed: 9 additions & 1 deletion b/‎paddle/cinn/runtime/cpu/mkl_math_test.cc
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+9-1Lines changed: 9 additions & 1 deletion
diff --git a/‎paddle/cinn/runtime/cpu/mkldnn_math.cc
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+5-1Lines changed: 5 additions & 1 deletion b/‎paddle/cinn/runtime/cpu/mkldnn_math.cc
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+5-1Lines changed: 5 additions & 1 deletion
diff --git a/‎paddle/cinn/runtime/cpu/thread_backend.cc
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+1Lines changed: 1 addition & 0 deletions b/‎paddle/cinn/runtime/cpu/thread_backend.cc
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+1Lines changed: 1 addition & 0 deletions
diff --git a/‎paddle/cinn/runtime/cuda/cuda_module.cc
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+9-3Lines changed: 9 additions & 3 deletions b/‎paddle/cinn/runtime/cuda/cuda_module.cc
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+9-3Lines changed: 9 additions & 3 deletions
diff --git a/‎paddle/cinn/runtime/cuda/cuda_module_test.cc
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+16-5Lines changed: 16 additions & 5 deletions b/‎paddle/cinn/runtime/cuda/cuda_module_test.cc
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+16-5Lines changed: 16 additions & 5 deletions
@@ -25,21 +25,30 @@ Shape::Shape(const Shape &other)
 }
 
 void Shape::Resize(int ndim) {
-  CHECK_GT(ndim, 0);
+  PADDLE_ENFORCE_GT(ndim,
+                    0,
+                    phi::errors::InvalidArgument(
+                        "Target dimension to resize must be greater than 0."));
   ndims_ = ndim;
   if (data_) delete data_;
   data_ = new value_type[ndim];
 }
 
 Shape::value_type &Shape::operator[](int i) {
-  CHECK_GT(ndims_, 0) << "shape is empty";
-  CHECK_LT(i, ndims_) << "index " << i << "out of range " << ndims_;
+  PADDLE_ENFORCE_GT(ndims_, 0, phi::errors::InvalidArgument("Shape is empty."));
+  PADDLE_ENFORCE_LT(
+      i,
+      ndims_,
+      phi::errors::OutOfRange("Index %d out of range %d.", i, ndims_));
   return data_[i];
 }
 
 Shape::value_type Shape::operator[](int i) const {
-  CHECK_GT(ndims_, 0) << "shape is empty";
-  CHECK_LT(i, ndims_) << "index " << i << "out of range " << ndims_;
+  PADDLE_ENFORCE_GT(ndims_, 0, phi::errors::InvalidArgument("Shape is empty."));
+  PADDLE_ENFORCE_LT(
+      i,
+      ndims_,
+      phi::errors::OutOfRange("Index %d out of range %d.", i, ndims_));
   return data_[i];
 }
 
 
@@ -16,6 +16,7 @@
 #include <glog/logging.h>
 
 #include <string>
+#include "paddle/common/enforce.h"
 /**
  * runtime::Buffer is an encapsulation of memory operations.
  */
@@ -68,9 +69,13 @@ class Buffer {
 
   //! Allocate the memory in host device.
   void AllocHost() {
-    CHECK(shape_.defined());
+    PADDLE_ENFORCE_EQ(
+        shape_.defined(),
+        true,
+        phi::errors::InvalidArgument("shape haven't been defined."));
     data_ = new T[shape_.num_elements()];
-    CHECK(data_) << "alloc buffer failed";
+    PADDLE_ENFORCE_NOT_NULL(data_,
+                            phi::errors::NotFound("alloc buffer failed."));
   }
   //! Deallocate the memory in host device.
   void DeallocHost() {
@@ -79,15 +84,27 @@ class Buffer {
   }
 
   T& operator()(int i0) {
-    CHECK_EQ(shape_.ndims(), 1);
+    PADDLE_ENFORCE_EQ(shape_.ndims(),
+                      1,
+                      phi::errors::InvalidArgument(
+                          "Expected shape has 1 dimension, but recevied %d.",
+                          shape_.ndims()));
     return static_cast<T*>(data_)[i0];
   }
   T& operator()(int i0, int i1) {
-    CHECK_EQ(shape_.ndims(), 2);
+    PADDLE_ENFORCE_EQ(shape_.ndims(),
+                      2,
+                      phi::errors::InvalidArgument(
+                          "Expected shape has 2 dimensions, but recevied %d.",
+                          shape_.ndims()));
     return static_cast<T*>(data_)[i0 * shape_[0] + i1];
   }
   T& operator()(int i0, int i1, int i2) {
-    CHECK_EQ(shape_.ndims(), 3);
+    PADDLE_ENFORCE_EQ(shape_.ndims(),
+                      3,
+                      phi::errors::InvalidArgument(
+                          "Expected shape has 3 dimensions, but recevied %d.",
+                          shape_.ndims()));
     return static_cast<T*>(
         data_)[i0 * shape_[1] * shape_[2] + i1 * shape_[2] + i2];
   }
 
@@ -18,6 +18,7 @@
 
 #include "paddle/cinn/backends/extern_func_jit_register.h"
 #include "paddle/cinn/common/cas.h"
+#include "paddle/common/enforce.h"
 
 namespace {
 
@@ -117,8 +118,11 @@ void cinn_call_cholesky_host(
   memcpy(out->memory, x->memory, x->memory_size);
 
   uint8_t bits = x->type.bits;
-  CHECK(bits == 32 || bits == 64)
-      << "Unsupported bits = " << bits << " float data type for cholesky";
+  PADDLE_ENFORCE_EQ(
+      bits == 32 || bits == 64,
+      true,
+      phi::errors::InvalidArgument(
+          "Unsupported bits = %d float data type for cholesky.", bits));
   char uplo = upper ? 'U' : 'L';
   for (int i = 0; i < batch_size; i++) {
     if (bits == 32) {
@@ -141,8 +145,12 @@ CINN_REGISTER_HELPER(cinn_cpu_mkl) {
 
   FunctionProto::shape_inference_t inference_shape_gemm =
       [](const std::vector<Expr>& args, int offset) {
-        CHECK_EQ(offset, 0UL) << "Only one output";
-        CHECK_EQ(args.size(), 12UL) << "Wrong number of arguments passed in";
+        PADDLE_ENFORCE_EQ(
+            offset, 0UL, phi::errors::InvalidArgument("Only one output."));
+        PADDLE_ENFORCE_EQ(args.size(),
+                          12UL,
+                          phi::errors::InvalidArgument(
+                              "Wrong number of arguments passed in."));
         auto M = cinn::common::AutoSimplify(args[1]);
         auto N = cinn::common::AutoSimplify(args[2]);
         std::vector<Expr> shape;
@@ -153,11 +161,16 @@ CINN_REGISTER_HELPER(cinn_cpu_mkl) {
 
   FunctionProto::shape_inference_t inference_shape_gemm_batch =
       [](const std::vector<Expr>& args, int offset) {
-        CHECK_EQ(offset, 0UL) << "Only one output";
-        CHECK_EQ(args.size(), 16UL) << "Wrong number of arguments passed in";
+        PADDLE_ENFORCE_EQ(
+            offset, 0UL, phi::errors::InvalidArgument("Only one output."));
+        PADDLE_ENFORCE_EQ(args.size(),
+                          16UL,
+                          phi::errors::InvalidArgument(
+                              "Wrong number of arguments passed in."));
         auto& A = args[14];
         auto A_tensor = A.as_tensor();
-        CHECK(A_tensor);
+        PADDLE_ENFORCE_NOT_NULL(
+            A_tensor, phi::errors::InvalidArgument("expected type is tensor."));
 
         auto batch_size = cinn::common::AutoSimplify(args[1]);
         int32_t batch_size_val = batch_size.as_int32();
@@ -169,7 +182,10 @@ CINN_REGISTER_HELPER(cinn_cpu_mkl) {
         int total = 1;
         for (auto& v : A_tensor->shape) {
           auto val = cinn::common::AutoSimplify(v);
-          CHECK(val.is_constant());
+          PADDLE_ENFORCE_EQ(
+              val.is_constant(),
+              true,
+              phi::errors::InvalidArgument("expected type is constant."));
           shape.push_back(val);
           total *= val.as_int32();
           if (total >= batch_size_val) break;
 
@@ -23,19 +23,32 @@
 #include "paddle/cinn/backends/extern_func_jit_register.h"
 #include "paddle/cinn/backends/function_prototype.h"
 #include "paddle/cinn/runtime/cpu/host_intrinsics.h"
+#include "paddle/common/enforce.h"
 
-#define CINN_MKL_VECTOR_MATH_FP(fn__, name__)                             \
-  void cinn_mkl_##name__##_v_fp32(cinn_buffer_t *x, cinn_buffer_t *out) { \
-    CHECK_EQ(x->num_elements(), out->num_elements());                     \
-    vs##fn__(x->num_elements(),                                           \
-             reinterpret_cast<float *>(x->memory),                        \
-             reinterpret_cast<float *>(out->memory));                     \
-  }                                                                       \
-  void cinn_mkl_##name__##_v_fp64(cinn_buffer_t *x, cinn_buffer_t *out) { \
-    CHECK_EQ(x->num_elements(), out->num_elements());                     \
-    vd##fn__(x->num_elements(),                                           \
-             reinterpret_cast<double *>(x->memory),                       \
-             reinterpret_cast<double *>(out->memory));                    \
+#define CINN_MKL_VECTOR_MATH_FP(fn__, name__)                              \
+  void cinn_mkl_##name__##_v_fp32(cinn_buffer_t *x, cinn_buffer_t *out) {  \
+    PADDLE_ENFORCE_EQ(                                                     \
+        x->num_elements(),                                                 \
+        out->num_elements(),                                               \
+        phi::errors::InvalidArgument("X's number of elements (%d) should " \
+                                     "be equal to output's (%d).",         \
+                                     x->num_elements(),                    \
+                                     out->num_elements()));                \
+    vs##fn__(x->num_elements(),                                            \
+             reinterpret_cast<float *>(x->memory),                         \
+             reinterpret_cast<float *>(out->memory));                      \
+  }                                                                        \
+  void cinn_mkl_##name__##_v_fp64(cinn_buffer_t *x, cinn_buffer_t *out) {  \
+    PADDLE_ENFORCE_EQ(                                                     \
+        x->num_elements(),                                                 \
+        out->num_elements(),                                               \
+        phi::errors::InvalidArgument("X's number of elements (%d) should " \
+                                     "be equal to output's (%d).",         \
+                                     x->num_elements(),                    \
+                                     out->num_elements()));                \
+    vd##fn__(x->num_elements(),                                            \
+             reinterpret_cast<double *>(x->memory),                        \
+             reinterpret_cast<double *>(out->memory));                     \
   }
 
 CINN_MKL_VECTOR_MATH_FP(Exp, exp);
 
@@ -24,6 +24,7 @@
 #include "paddle/cinn/common/test_helper.h"
 #include "paddle/cinn/runtime/cpu/host_intrinsics.h"
 #include "paddle/cinn/runtime/cpu/use_extern_funcs.h"
+#include "paddle/common/enforce.h"
 
 namespace cinn {
 namespace runtime {
@@ -89,11 +90,18 @@ void TestCallElementwise(const std::string &fn_name,
 
   jit->Link(module);
   auto fn = jit->Lookup("fn");
-  CHECK(fn);
+  PADDLE_ENFORCE_NOT_NULL(fn, phi::errors::NotFound("fn is not found."));
   auto fn_ = reinterpret_cast<void (*)(void *, int32_t)>(fn);
 
   cinn_buffer_t *A_buf;
   if (set_value != 0) {
+    PADDLE_ENFORCE_EQ(
+        x->num_elements(),
+        out->num_elements(),
+        phi::errors::InvalidArgument("X's number of elements (%d) should "
+                                     "be equal to output's (%d).",
+                                     x->num_elements(),
+                                     out->num_elements()));
     A_buf = CreateBuffer({10, 10}, false, set_value);
   } else {
     A_buf = CreateBuffer({10, 10});
 
@@ -18,6 +18,7 @@
 
 #include "paddle/cinn/backends/extern_func_jit_register.h"
 #include "paddle/cinn/common/cas.h"
+#include "paddle/common/enforce.h"
 
 using dnnl::algorithm;
 using dnnl::memory;
@@ -163,7 +164,10 @@ CINN_REGISTER_HELPER(cinn_cpu_mkldnn) {
 
   FunctionProto::shape_inference_t inference_shape_conv2d_nchw =
       [](const std::vector<Expr>& args, int offset) {
-        CHECK_EQ(args.size(), 16UL) << "Wrong number of arguments passed in";
+        PADDLE_ENFORCE_EQ(args.size(),
+                          16UL,
+                          phi::errors::InvalidArgument(
+                              "Wrong number of arguments passed in."));
         auto N = cinn::common::AutoSimplify(args[0]);
         int input_h = cinn::common::AutoSimplify(args[2]).as_int32();
         int input_w = cinn::common::AutoSimplify(args[3]).as_int32();
 
@@ -25,6 +25,7 @@
 #include "paddle/cinn/backends/llvm/runtime_symbol_registry.h"
 #include "paddle/cinn/common/cas.h"
 #include "paddle/cinn/runtime/intrinsic.h"
+#include "paddle/common/enforce.h"
 
 int max_concurrency() {
   int max_concurrency = 1;
 
@@ -27,17 +27,20 @@
 #include "paddle/cinn/runtime/cuda/cuda_util.h"
 #include "paddle/cinn/runtime/flags.h"
 #include "paddle/cinn/utils/profiler.h"
+#include "paddle/common/enforce.h"
 
 namespace cinn {
 namespace runtime {
 namespace cuda {
 
 CUDAModule::CUDAModule(const std::string& data, Kind kind)
     : data_(data), kind_(kind) {
-  CHECK(!data.empty());
+  PADDLE_ENFORCE_NE(
+      data.empty(), true, phi::errors::PreconditionNotMet("data is is empty!"));
 
   cudaGetDeviceCount(&num_devices_);
-  CHECK_GT(num_devices_, 0) << "No available devices";
+  PADDLE_ENFORCE_GT(
+      num_devices_, 0, phi::errors::ResourceExhausted("No available devices!"));
 
   // TODO(Superjomn) Determine whether to initialize all the devices.
   int current_device_id;
@@ -61,7 +64,10 @@ void CUDAModule::LaunchKernel(int device_id,
           << ", blockDim.y:" << blockDim.y << ", blockDim.z:" << blockDim.z
           << ", share_memory_size:" << share_memory_size;
   auto function = GetFunction(device_id, func_name);
-  CHECK(function);
+  PADDLE_ENFORCE_NOT_NULL(
+      function,
+      phi::errors::NotFound(
+          "%s function not found on device %d.", func_name, device_id));
   cinn::utils::RecordEvent record_run("cuLaunchKernel",
                                       cinn::utils::EventType::kInstruction);
   CUDA_DRIVER_CALL(cuLaunchKernel(function,
 
@@ -23,6 +23,7 @@
 #include "paddle/cinn/runtime/cuda/cuda_util.h"
 #include "paddle/cinn/runtime/cuda/test_util.h"
 #include "paddle/cinn/runtime/cuda/use_extern_funcs.h"
+#include "paddle/common/enforce.h"
 
 namespace cinn {
 namespace runtime {
@@ -43,7 +44,7 @@ void saxpy(float a, float *x, float *y, float *out, size_t n)
 )ROC";
 
   auto ptx = compiler(source_code);
-  CHECK(!ptx.empty());
+  PADDLE_ENFORCE_NE(ptx.empty(), true, phi::errors::NotFound("ptx is empty!"));
 
   CUDAModule module(ptx, CUDAModule::Kind::PTX);
   auto func = module.GetFunction(0, "saxpy");
@@ -73,7 +74,8 @@ TEST(CUDAModule, float16) {
   )";
 
     auto ptx = compiler(source_code);
-    CHECK(!ptx.empty());
+    PADDLE_ENFORCE_NE(
+        ptx.empty(), true, phi::errors::NotFound("ptx is empty!"));
     return ptx;
   };
 
@@ -116,7 +118,11 @@ TEST(CUDAModule, float16) {
                         [](float x, float16 y) -> bool {
                           return std::abs(x - static_cast<float>(y)) < 1e-2f;
                         });
-  CHECK(res) << "The difference between two arrays exceeds the bound.";
+  PADDLE_ENFORCE_EQ(
+      res,
+      true,
+      phi::errors::PreconditionNotMet(
+          "The difference between two arrays exceeds the bound."));
 }
 
 TEST(CUDAModule, bfloat16) {
@@ -142,7 +148,8 @@ TEST(CUDAModule, bfloat16) {
   )";
 
     auto ptx = compiler(source_code);
-    CHECK(!ptx.empty());
+    PADDLE_ENFORCE_NE(
+        ptx.empty(), true, phi::errors::NotFound("ptx is empty!"));
     return ptx;
   };
 
@@ -185,7 +192,11 @@ TEST(CUDAModule, bfloat16) {
                         [](float x, bfloat16 y) -> bool {
                           return std::abs(x - static_cast<float>(y)) < 1e-2f;
                         });
-  CHECK(res) << "The difference between two arrays exceeds the bound.";
+  PADDLE_ENFORCE_EQ(
+      res,
+      true,
+      phi::errors::PreconditionNotMet(
+          "The difference between two arrays exceeds the bound."));
 }
 
 }  // namespace cuda