Remove debug codes

paddle/framework/tensor_impl.h

@@ -134,17 +134,8 @@ inline void* Tensor::mutable_data(platform::Place place, std::type_index type) {
 #endif
     offset_ = 0;
   }
-  void* buf = reinterpret_cast<void*>(
+  return reinterpret_cast<void*>(reinterpret_cast<uintptr_t>(holder_->ptr()) +
-      reinterpret_cast<uintptr_t>(holder_->ptr()) + offset_);
+                                 offset_);
-  if (type.hash_code() == typeid(float).hash_code() ||
-      type.hash_code() == typeid(double).hash_code()) {
-    float* tmp = (float*)(buf);
-    for (int64_t i = 0; i < numel(); ++i) {
-      tmp[i] = NAN;
-    }
-  }
-
-  return buf;
 }
 
 inline void* Tensor::mutable_data(platform::Place place) {

paddle/operators/fill_constant_op.cc

@@ -51,7 +51,6 @@ class FillConstantOp : public framework::OperatorBase {
 
     platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
     auto &dev_ctx = *pool.Get(dev_place);
-    VLOG(10) << "FillConstant to " << &out;
     math::set_constant(dev_ctx, &out, value);
   }
 };

paddle/operators/shrink_rnn_memory_op.cc

@@ -116,7 +116,6 @@ class ShrinkRNNMemoryGradOp : public ArrayOp {
       auto height = dout_tensor.dims()[0];
       auto slice = dx_tensor.Slice(0, static_cast<int>(height));
       framework::CopyFrom(dout_tensor, dout_tensor.place(), dev_ctx, &slice);
-      VLOG(10) << dx_tensor.dims()[0] << ", " << height;
       if (dx_tensor.dims()[0] > height) {
         auto rest_tensor = dx_tensor.Slice(
             static_cast<int>(height), static_cast<int>(dx_tensor.dims()[0]));

paddle/operators/while_op.cc

@@ -12,7 +12,6 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 
-#include <cmath>
 #include <vector>
 #include "paddle/framework/executor.h"
 #include "paddle/framework/lod_tensor_array.h"
@@ -195,36 +194,14 @@ class WhileGradOp : public framework::OperatorBase {
           }
         }
 
-        auto check_var_no_nan = [](const framework::Scope &scope,
-                                   const std::string &var_name) {
-          auto *var = scope.FindVar(var_name);
-          if (var->IsType<LoDTensor>()) {
-            VLOG(10) << "Checking " << var_name;
-            PADDLE_ENFORCE(!framework::HasNAN(var->Get<framework::LoDTensor>()),
-                           "%s has NAN", var_name);
-            if (var->Get<framework::LoDTensor>().type() ==
-                typeid(float)) {  // NOLINT
-              auto &tensor = var->Get<framework::LoDTensor>();
-              auto *buf = tensor.data<float>();
-              for (int64_t i = 0; i < tensor.numel(); ++i) {
-                PADDLE_ENFORCE(!std::isnan(buf[i]));
-              }
-              VLOG(10) << buf[0];
-            }
-          }
-        };
-        check_var_no_nan(cur_scope, inside_grad_name);
         auto new_inside_name = cur_scope.Rename(inside_grad_name);
-        check_var_no_nan(cur_scope, new_inside_name);
         auto sum_op = framework::OpRegistry::CreateOp(
             "sum", {{"X", {pg_names[param_id], new_inside_name}}},
             {{"Out", {pg_names[param_id]}}}, framework::AttributeMap{});
         sum_op->Run(cur_scope, dev_place);
-        check_var_no_nan(scope, pg_names[param_id]);
         cur_scope.Rename(new_inside_name, inside_grad_name);
       }
     }
-    VLOG(1) << "Complete WhileOpGrad";
   }
 };