Adding error messaging for unsupported tensor shapes

monai/csrc/filtering/bilateral/bilateral.cpp

@@ -0,0 +1,49 @@
+/*
+Copyright 2020 - 2021 MONAI Consortium
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+    http://www.apache.org/licenses/LICENSE-2.0
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+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 <torch/extension.h>
+#include <stdexcept>
+#include <string>
+
+#include "bilateral.h"
+#include "utils/common_utils.h"
+
+torch::Tensor BilateralFilter(torch::Tensor input, float spatial_sigma, float color_sigma, bool usePHL) {
+  torch::Tensor (*filterFunction)(torch::Tensor, float, float);
+
+#ifdef WITH_CUDA
+
+  if (torch::cuda::is_available() && input.is_cuda()) {
+    CHECK_CONTIGUOUS_CUDA(input);
+
+    if (input.size(1) > BF_CUDA_MAX_CHANNELS) {
+      throw std::runtime_error(
+          "Bilateral filtering not implemented for channel count > " + std::to_string(BF_CUDA_MAX_CHANNELS));
+    }
+
+    if (input.dim() - 2 > BF_CUDA_MAX_SPATIAL_DIMENSION) {
+      throw std::runtime_error(
+          "Bilateral filtering not implemented for spatial dimension > " +
+          std::to_string(BF_CUDA_MAX_SPATIAL_DIMENSION));
+    }
+
+    filterFunction = usePHL ? &BilateralFilterPHLCuda : &BilateralFilterCuda;
+  } else {
+    filterFunction = usePHL ? &BilateralFilterPHLCpu : &BilateralFilterCpu;
+  }
+#else
+  filterFunction = usePHL ? &BilateralFilterPHLCpu : &BilateralFilterCpu;
+#endif
+
+  return filterFunction(input, spatial_sigma, color_sigma);
+}

monai/csrc/filtering/bilateral/bilateral.h

@@ -14,7 +14,9 @@ limitations under the License.
 #pragma once
 
 #include <torch/extension.h>
-#include "utils/common_utils.h"
+
+#define BF_CUDA_MAX_CHANNELS 16
+#define BF_CUDA_MAX_SPATIAL_DIMENSION 3
 
 torch::Tensor BilateralFilterCpu(torch::Tensor input, float spatial_sigma, float color_sigma);
 torch::Tensor BilateralFilterPHLCpu(torch::Tensor input, float spatial_sigma, float color_sigma);
@@ -24,19 +26,4 @@ torch::Tensor BilateralFilterCuda(torch::Tensor input, float spatial_sigma, floa
 torch::Tensor BilateralFilterPHLCuda(torch::Tensor input, float spatial_sigma, float color_sigma);
 #endif
 
-torch::Tensor BilateralFilter(torch::Tensor input, float spatial_sigma, float color_sigma, bool usePHL) {
-  torch::Tensor (*filterFunction)(torch::Tensor, float, float);
-
-#ifdef WITH_CUDA
-  if (torch::cuda::is_available() && input.is_cuda()) {
-    CHECK_CONTIGUOUS_CUDA(input);
-    filterFunction = usePHL ? &BilateralFilterPHLCuda : &BilateralFilterCuda;
-  } else {
-    filterFunction = usePHL ? &BilateralFilterPHLCpu : &BilateralFilterCpu;
-  }
-#else
-  filterFunction = usePHL ? &BilateralFilterPHLCpu : &BilateralFilterCpu;
-#endif
-
-  return filterFunction(input, spatial_sigma, color_sigma);
-}
+torch::Tensor BilateralFilter(torch::Tensor input, float spatial_sigma, float color_sigma, bool usePHL);

monai/csrc/filtering/bilateral/bilateralfilter_cuda.cu

@@ -15,6 +15,7 @@ limitations under the License.
 #include <cuda_runtime.h>
 #include <torch/extension.h>
 
+#include "bilateral.h"
 #include "utils/meta_macros.h"
 #include "utils/tensor_description.h"
 
@@ -253,7 +254,7 @@ torch::Tensor BilateralFilterCuda(torch::Tensor inputTensor, float spatialSigma,
   torch::Tensor outputTensor = torch::zeros_like(inputTensor);
 
 #define CASE(c, d) BilateralFilterCuda<c, d>(inputTensor, outputTensor, spatialSigma, colorSigma);
-  SWITCH_AB(CASE, 16, 3, inputTensor.size(1), inputTensor.dim() - 2);
+  SWITCH_AB(CASE, BF_CUDA_MAX_CHANNELS, BF_CUDA_MAX_SPATIAL_DIMENSION, inputTensor.size(1), inputTensor.dim() - 2);
 
   return outputTensor;
 }

monai/csrc/filtering/bilateral/bilateralfilter_cuda_phl.cu

@@ -15,6 +15,7 @@ limitations under the License.
 #include <cuda_runtime.h>
 #include <torch/extension.h>
 
+#include "bilateral.h"
 #include "filtering/permutohedral/permutohedral.h"
 #include "utils/meta_macros.h"
 #include "utils/tensor_description.h"
@@ -135,7 +136,7 @@ torch::Tensor BilateralFilterPHLCuda(torch::Tensor inputTensor, float spatialSig
                                    inputTensor, outputTensor, spatialSigma, colorSigma); \
                              }));
 
-  SWITCH_AB(CASE, 16, 3, inputTensor.size(1), inputTensor.dim() - 2);
+  SWITCH_AB(CASE, BF_CUDA_MAX_CHANNELS, BF_CUDA_MAX_SPATIAL_DIMENSION, inputTensor.size(1), inputTensor.dim() - 2);
 
   return outputTensor;
 }

monai/csrc/filtering/permutohedral/permutohedral.cpp

@@ -11,6 +11,9 @@ See the License for the specific language governing permissions and
 limitations under the License.
 */
 
+#include <stdexcept>
+#include <string>
+
 #include "utils/common_utils.h"
 #include "utils/meta_macros.h"
 
@@ -46,6 +49,16 @@ torch::Tensor PermutohedralFilter(torch::Tensor input, torch::Tensor features) {
   if (torch::cuda::is_available() && data.is_cuda()) {
     CHECK_CONTIGUOUS_CUDA(data);
 
+    if (channelCount > PHL_CUDA_MAX_CHANNELS) {
+      throw std::runtime_error(
+          "PHL filtering not implemented for channel count > " + std::to_string(PHL_CUDA_MAX_CHANNELS));
+    }
+
+    if (featureCount > PHL_CUDA_MAX_FEATURES) {
+      throw std::runtime_error(
+          "PHL filtering not implemented for feature count > " + std::to_string(PHL_CUDA_MAX_FEATURES));
+    }
+
 #define CASE(dc, fc)                                                                                                  \
   AT_DISPATCH_FLOATING_TYPES(data.scalar_type(), "PermutohedralCuda", ([&] {                                          \
                                for (int batchIndex = 0; batchIndex < batchCount; batchIndex++) {                      \
@@ -55,7 +68,7 @@ torch::Tensor PermutohedralFilter(torch::Tensor input, torch::Tensor features) {
                                  PermutohedralCuda<scalar_t, dc, fc>(offsetData, offsetFeatures, elementCount, true); \
                                }                                                                                      \
                              }));
-    SWITCH_AB(CASE, 16, 19, channelCount, featureCount);
+    SWITCH_AB(CASE, PHL_CUDA_MAX_CHANNELS, PHL_CUDA_MAX_FEATURES, channelCount, featureCount);
 
   } else {
 #endif

monai/csrc/filtering/permutohedral/permutohedral.h

@@ -11,9 +11,13 @@ See the License for the specific language governing permissions and
 limitations under the License.
 */
 
+#pragma once
+
 #include <torch/extension.h>
 
-#pragma once
+#define PHL_CUDA_MAX_CHANNELS 16
+#define PHL_CUDA_MAX_FEATURES 19
+
 template <typename scalar_t>
 void PermutohedralCPU(scalar_t* data, scalar_t* features, int dataChannels, int featureChannels, int elementCount);
 #ifdef WITH_CUDA

monai/csrc/filtering/permutohedral/permutohedral_cuda.cu

@@ -38,7 +38,7 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
 */
 
-#define BLOCK_SIZE 64
+#define BLOCK_SIZE 32
 
 #include <cuda.h>
 #include <cuda_runtime.h>
@@ -47,6 +47,7 @@ SOFTWARE.
 #include <THC/THCAtomics.cuh>
 
 #include "hash_table.cuh"
+#include "permutohedral.h"
 #include "utils/meta_macros.h"
 
 template <typename scalar_t>