Bug fix for get device_context.

paddle/operators/gemm_conv2d_op.h

@@ -75,8 +75,7 @@ class GemmConv2DKernel : public framework::OpKernel {
     framework::DDim output_matrix_shape = {output_channels,
                                            output_height * output_width};
 
-    auto* device_context =
-        const_cast<platform::DeviceContext*>(context.device_context_);
+    auto device_context = context.device_context();
 
     // convolution operator: im2col + gemm
     int in_step = input_channels / groups;
@@ -93,8 +92,8 @@ class GemmConv2DKernel : public framework::OpKernel {
         // gemm
         Tensor out_slice = out_batch.Slice<T>(g * out_step, (g + 1) * out_step);
         Tensor filter_slice = filter.Slice<T>(g * out_step, (g + 1) * out_step);
-        math::matmul<Place, T>(filter_slice, false, col_matrix, false, T(1.0),
-                               &out_slice, T(0.0), device_context);
+        math::matmul<Place, T>(device_context, filter_slice, false, col_matrix,
+                               false, T(1.0), &out_slice, T(0.0));
       }
     }
   }
@@ -160,8 +159,7 @@ class GemmConvGrad2DKernel : public framework::OpKernel {
                                            filter.numel() / filter.dims()[0]};
     filter.Resize(filter_matrix_shape);
 
-    auto* device_context =
-        const_cast<platform::DeviceContext*>(context.device_context_);
+    auto device_context = context.device_context();
 
     // convolution backward input operator:  gemm + col2im
     // convolution backward weight operator: im2col + gemm
@@ -184,8 +182,9 @@ class GemmConvGrad2DKernel : public framework::OpKernel {
               out_grad_batch.Slice<T>(g * out_step, (g + 1) * out_step);
           Tensor filter_slice =
               filter.Slice<T>(g * out_step, (g + 1) * out_step);
-          math::matmul<Place, T>(filter_slice, true, out_grad_slice, false,
-                                 T(1.0), &col_matrix, T(0.0), device_context);
+          math::matmul<Place, T>(device_context, filter_slice, true,
+                                 out_grad_slice, false, T(1.0), &col_matrix,
+                                 T(0.0));
 
           // col2im
           Tensor in_grad_slice =
@@ -218,9 +217,9 @@ class GemmConvGrad2DKernel : public framework::OpKernel {
           // gemm
           Tensor filter_grad_slice =
               filter_grad_.Slice<T>(g * out_step, (g + 1) * out_step);
-          math::matmul<Place, T>(out_grad_slice, false, col_matrix, true,
-                                 T(1.0), &filter_grad_slice, T(1.0),
-                                 device_context);
+          math::matmul<Place, T>(device_context, out_grad_slice, false,
+                                 col_matrix, true, T(1.0), &filter_grad_slice,
+                                 T(1.0));
         }
       }
     }

paddle/operators/math/im2col.cc

@@ -29,7 +29,7 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
  public:
   void operator()(const framework::Tensor& im, framework::Tensor& col,
                   int stride_height, int stride_width, int padding_height,
-                  int padding_width, platform::DeviceContext* context) {
+                  int padding_width, const platform::DeviceContext& context) {
     PADDLE_ENFORCE(im.dims().size() == 3);
     PADDLE_ENFORCE(col.dims().size() == 5);
 
@@ -81,7 +81,7 @@ class Col2ImFunctor<paddle::operators::math::ColFormat::kCFO,
  public:
   void operator()(framework::Tensor& im, const framework::Tensor& col,
                   int stride_height, int stride_width, int padding_height,
-                  int padding_width, platform::DeviceContext* context) {
+                  int padding_width, const platform::DeviceContext& context) {
     PADDLE_ENFORCE(im.dims().size() == 3);
     PADDLE_ENFORCE(col.dims().size() == 5);
     int input_channels = im.dims()[0];
@@ -139,7 +139,7 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF,
  public:
   void operator()(const framework::Tensor& im, framework::Tensor& col,
                   int stride_height, int stride_width, int padding_height,
-                  int padding_width, platform::DeviceContext* context) {
+                  int padding_width, const platform::DeviceContext& context) {
     PADDLE_ENFORCE(im.dims().size() == 3);
     PADDLE_ENFORCE(col.dims().size() == 5);
     int input_channels = im.dims()[0];
@@ -199,7 +199,7 @@ class Col2ImFunctor<paddle::operators::math::ColFormat::kOCF,
  public:
   void operator()(framework::Tensor& im, const framework::Tensor& col,
                   int stride_height, int stride_width, int padding_height,
-                  int padding_width, platform::DeviceContext* context) {
+                  int padding_width, const platform::DeviceContext& context) {
     PADDLE_ENFORCE(im.dims().size() == 3);
     PADDLE_ENFORCE(col.dims().size() == 5);
     int input_channels = im.dims()[0];

paddle/operators/math/im2col.cu

@@ -66,7 +66,7 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
  public:
   void operator()(const framework::Tensor& im, framework::Tensor& col,
                   int stride_height, int stride_width, int padding_height,
-                  int padding_width, platform::DeviceContext* context) {
+                  int padding_width, const platform::DeviceContext& context) {
     PADDLE_ENFORCE(im.dims().size() == 3);
     PADDLE_ENFORCE(col.dims().size() == 5);
 
@@ -84,9 +84,9 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
     int block_y = (blocks + 512 - 1) / 512;
     dim3 threads(1024, 1);
     dim3 grid(block_x, block_y);
-    im2col<T><<<
-        grid, threads, 0,
-        reinterpret_cast<platform::CUDADeviceContext*>(context)->stream()>>>(
+    im2col<T><<<grid, threads, 0,
+                reinterpret_cast<const platform::CUDADeviceContext&>(context)
+                    .stream()>>>(
         im.data<T>(), num_outputs, input_height, input_width, filter_height,
         filter_width, stride_height, stride_width, padding_height,
         padding_width, output_height, output_width, col.data<T>());
@@ -151,7 +151,7 @@ class Col2ImFunctor<paddle::operators::math::ColFormat::kCFO,
  public:
   void operator()(framework::Tensor& im, const framework::Tensor& col,
                   int stride_height, int stride_width, int padding_height,
-                  int padding_width, platform::DeviceContext* context) {
+                  int padding_width, const platform::DeviceContext& context) {
     PADDLE_ENFORCE(im.dims().size() == 3);
     PADDLE_ENFORCE(col.dims().size() == 5);
 
@@ -174,9 +174,9 @@ class Col2ImFunctor<paddle::operators::math::ColFormat::kCFO,
 
     // To avoid involving atomic operations, we will launch one kernel per
     // bottom dimension, and then in the kernel add up the top dimensions.
-    col2im<T><<<
-        grid, threads, 0,
-        reinterpret_cast<platform::CUDADeviceContext*>(context)->stream()>>>(
+    col2im<T><<<grid, threads, 0,
+                reinterpret_cast<const platform::CUDADeviceContext&>(context)
+                    .stream()>>>(
         num_kernels, col.data<T>(), input_height + 2 * padding_height,
         input_width + 2 * padding_width, input_channels, filter_height,
         filter_width, stride_height, stride_width, padding_height,
@@ -237,7 +237,7 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF,
  public:
   void operator()(const framework::Tensor& im, framework::Tensor& col,
                   int stride_height, int stride_width, int padding_height,
-                  int padding_width, platform::DeviceContext* context) {
+                  int padding_width, const platform::DeviceContext& context) {
     PADDLE_ENFORCE(im.dims().size() == 3);
     PADDLE_ENFORCE(col.dims().size() == 5);
     int input_channels = im.dims()[0];
@@ -268,9 +268,9 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kOCF,
     dim3 threads(block_dim_x, block_dim_y,
                  std::min(block_dim_z, input_channels));
     dim3 grid(output_width, output_height);
-    im2colOCF<T><<<
-        grid, threads, 0,
-        reinterpret_cast<platform::CUDADeviceContext*>(context)->stream()>>>(
+    im2colOCF<T><<<grid, threads, 0,
+                   reinterpret_cast<const platform::CUDADeviceContext&>(context)
+                       .stream()>>>(
         im.data<T>(), col.data<T>(), input_channels, input_height, input_width,
         filter_height, filter_width, stride_height, stride_width,
         padding_height, padding_width, output_height, output_width);
@@ -320,7 +320,7 @@ class Col2ImFunctor<paddle::operators::math::ColFormat::kOCF,
  public:
   void operator()(framework::Tensor& im, const framework::Tensor& col,
                   int stride_height, int stride_width, int padding_height,
-                  int padding_width, platform::DeviceContext* context) {
+                  int padding_width, const platform::DeviceContext& context) {
     PADDLE_ENFORCE(im.dims().size() == 3);
     PADDLE_ENFORCE(col.dims().size() == 5);
     int input_channels = im.dims()[0];
@@ -351,9 +351,9 @@ class Col2ImFunctor<paddle::operators::math::ColFormat::kOCF,
     dim3 threads(block_dim_x, block_dim_y,
                  std::min(block_dim_z, input_channels));
     dim3 grid(output_width, output_height);
-    col2imOCF<T><<<
-        grid, threads, 0,
-        reinterpret_cast<platform::CUDADeviceContext*>(context)->stream()>>>(
+    col2imOCF<T><<<grid, threads, 0,
+                   reinterpret_cast<const platform::CUDADeviceContext&>(context)
+                       .stream()>>>(
         im.data<T>(), col.data<T>(), input_channels, input_height, input_width,
         filter_height, filter_width, stride_height, stride_width,
         padding_height, padding_width, output_height, output_width);

paddle/operators/math/im2col.h

@@ -74,7 +74,7 @@ class Im2ColFunctor {
  public:
   void operator()(const framework::Tensor& im, framework::Tensor& col,
                   int stride_height, int stride_width, int padding_height,
-                  int padding_width, platform::DeviceContext* context);
+                  int padding_width, const platform::DeviceContext& context);
 };
 
 template <ColFormat Format, typename Place, typename T>
@@ -82,7 +82,7 @@ class Col2ImFunctor {
  public:
   void operator()(framework::Tensor& im, const framework::Tensor& col,
                   int stride_height, int stride_width, int padding_height,
-                  int padding_width, platform::DeviceContext* context);
+                  int padding_width, const platform::DeviceContext& context);
 };
 
 }  // namespace math

paddle/operators/math/im2col_test.cc

@@ -78,8 +78,8 @@ void testIm2col() {
     PADDLE_THROW("no GPU support");
 #endif  // PADDLE_ONLY_CPU
   }
-  im2col(input, output_cfo, stride, stride, padding, padding, context);
-  im2col_ocf(input, output_ocf, stride, stride, padding, padding, context);
+  im2col(input, output_cfo, stride, stride, padding, padding, *context);
+  im2col_ocf(input, output_ocf, stride, stride, padding, padding, *context);
 
   float* out_cfo_ptr;
   if (paddle::platform::is_cpu_place(*place)) {