Add compat for v2 stuff.

theano/sandbox/gpuarray/cudnn_helper.h

@@ -4,193 +4,110 @@
 #include <cudnn.h>
 
 #ifndef CUDNN_VERSION
-#include <assert.h>
-
-// Here we define the R2 API in terms of functions in the R1 interface
-// This is only for what we use
 
-static inline const char *cudnnGetErrorString(cudnnStatus_t err) {
-  switch (err) {
-  case CUDNN_STATUS_SUCCESS:
-    return "The operation completed successfully.";
-  case CUDNN_STATUS_NOT_INITIALIZED:
-    return "The handle was not initialized(Is your driver recent enought?).";
-  case CUDNN_STATUS_ALLOC_FAILED:
-    return "Ressource allocation failed inside the library.";
-  case CUDNN_STATUS_BAD_PARAM:
-    return "An incorrect value was passed in.";
-  case CUDNN_STATUS_ARCH_MISMATCH:
-    return "The current GPU does not support the required features (only cc 3.0+ are supported).";
-  case CUDNN_STATUS_MAPPING_ERROR:
-    return "An access to GPU memory space failed (probably due to a failure to bind texture).";
-  case CUDNN_STATUS_EXECUTION_FAILED:
-    return "A kernel failed to execute.";
-  case CUDNN_STATUS_INTERNAL_ERROR:
-    return "An internal cuDNN operation failed.";
-  case CUDNN_STATUS_NOT_SUPPORTED:
-    return "The combination of parameters is not currently supported.";
-  default:
-    return "Unknown error code.";
-  }
+#define CUDNN_VERSION -1
+static inline int cudnnGetVersion() {
+  return -1;
 }
+#endif
 
-// some macros to help support cudnn R1 while using R2 code.
-#define cudnnCreateTensorDescriptor cudnnCreateTensor4dDescriptor
-#define cudnnDestroyTensorDescriptor cudnnDestroyTensor4dDescriptor
-#define cudnnSetFilter4dDescriptor cudnnSetFilterDescriptor
-
-typedef cudnnTensor4dDescriptor_t cudnnTensorDescriptor_t;
+#include <assert.h>
 
-static inline cudnnStatus_t
-cudnnGetConvolution2dForwardOutputDim(
-  const cudnnConvolutionDescriptor_t convDesc,
-  const cudnnTensorDescriptor_t inputTensorDesc,
-  const cudnnFilterDescriptor_t filterDesc,
-  int *n,
-  int *c,
-  int *h,
-  int *w) {
-  return cudnnGetOutputTensor4dDim(convDesc, CUDNN_CONVOLUTION_FWD,
-				   n, c, h, w);
-}
+#if CUDNN_VERSION < 3000
+// Here we define the R3 API in terms of functions in the R2 interface
+// This is only for what we use
 
-typedef int cudnnConvolutionFwdAlgo_t;
-typedef int cudnnConvolutionFwdPreference_t;
+typedef int cudnnConvolutionBwdDataAlgo_t;
 
-#define CUDNN_CONVOLUTION_FWD_NO_WORKSPACE 0
+#define CUDNN_CONVOLUTION_BWD_DATA_ALGO_0 0
+#define CUDNN_CONVOLUTION_BWD_DATA_ALGO_1 1
+#define CUDNN_CONVOLUTION_BWD_DATA_ALGO_FFT 2
 
-static inline cudnnStatus_t
-cudnnGetConvolutionForwardAlgorithm(
+static cudnnStatus_t cudnnGetConvolutionBackwardDataWorkspaceSize(
   cudnnHandle_t handle,
-  const cudnnTensorDescriptor_t srcDesc,
   const cudnnFilterDescriptor_t filterDesc,
+  const cudnnTensorDescriptor_t diffDesc,
   const cudnnConvolutionDescriptor_t convDesc,
-  const cudnnTensorDescriptor_t destDesc,
-  cudnnConvolutionFwdPreference_t preference,
-  size_t memoryLimitInbytes,
-  cudnnConvolutionFwdAlgo_t *algo) {
-  *algo = 0;
-  return CUDNN_STATUS_SUCCESS;
-}
-
-static inline cudnnStatus_t
-cudnnGetConvolutionForwardWorkspaceSize(
- cudnnHandle_t handle,
- const cudnnTensorDescriptor_t srcDesc,
- const cudnnFilterDescriptor_t filterDesc,
- const cudnnConvolutionDescriptor_t convDesc,
- const cudnnTensor4dDescriptor_t destDesc,
- cudnnConvolutionFwdAlgo_t algo,
- size_t *sizeInBytes) {
+  const cudnnTensorDescriptor_t gradDesc,
+  cudnnConvolutionBwdDataAlgo_t algo,
+  size_t *sizeInBytes) {
   *sizeInBytes = 0;
   return CUDNN_STATUS_SUCCESS;
 }
 
-
-static inline cudnnStatus_t
-cudnnConvolutionForward_v2(
+static cudnnStatus_t cudnnConvolutionBackwardData_v3(
   cudnnHandle_t handle,
   const void *alpha,
-  const cudnnTensorDescriptor_t srcDesc,
-  const void *srcData,
   const cudnnFilterDescriptor_t filterDesc,
   const void *filterData,
+  const cudnnTensorDescriptor_t diffDesc,
+  const void *diffData,
   const cudnnConvolutionDescriptor_t convDesc,
-  cudnnConvolutionFwdAlgo_t algo,
-  void *workSpace,
-  size_t workSpaceSizeInBytes,
+  cudnnConvolutionBwdDataAlgo_t algo,
+  void *workspace,
+  size_t workspaceSizeInBytes,
   const void *beta,
-  const cudnnTensorDescriptor_t destDesc,
-  void *destData) {
-  assert(*(float *)alpha == 1.0);
-  cudnnAccumulateResult_t r;
-  if (*(float *)beta == 0.0) {
-    r = CUDNN_RESULT_NO_ACCUMULATE;
-  } else if (*(float *)beta == 1.0) {
-    r = CUDNN_RESULT_ACCUMULATE;
-  } else {
-    assert(0 && "beta must be 0.0 or 1.0");
-  }
-  return cudnnConvolutionForward(handle, srcDesc, srcData,
-				 filterDesc, filterData,
-				 convDesc, destDesc, destData,
-				 r);
+  const cudnnTensorDescriptor_t gradDesc,
+  void *gradData) {
+  return cudnnConvolutionBackwardData(
+    handle,
+    alpha,
+    filterDesc,
+    filterData,
+    diffDesc,
+    diffData,
+    convDesc,
+    beta,
+    gradDesc,
+    gradData);
 }
-#define cudnnConvolutionForward cudnnConvolutionForward_v2
 
-static inline cudnnStatus_t
-cudnnConvolutionBackwardFilter_v2(
-  cudnnHandle_t	handle,
-  const void *alpha,
-  const cudnnTensorDescriptor_t srcDesc,
-  const void *srcData,
+typedef int cudnnConvolutionBwdFilterAlgo_t;
+
+#define CUDNN_CONVOLUTION_BWD_FILTER_ALGO_0 0
+#define CUDNN_CONVOLUTION_BWD_FILTER_ALGO_1 1
+#define CUDNN_CONVOLUTION_BWD_FILTER_ALGO_FFT 2
+#define CUDNN_CONVOLUTION_BWD_FILTER_ALGO_FFT 3
+
+static cudnnStatus_t cudnnGetConvolutionBackwardFilterWorkspaceSize(
+  cudnnHandle_t handle,
+  const cudnnTensorDescriptor_t filterDesc,
   const cudnnTensorDescriptor_t diffDesc,
-  const void *diffData,
   const cudnnConvolutionDescriptor_t convDesc,
-  const void *beta,
   const cudnnFilterDescriptor_t gradDesc,
-  void *gradData) {
-  assert(*(float *)alpha == 1.0);
-  cudnnAccumulateResult_t r;
-  if (*(float *)beta == 0.0) {
-    r = CUDNN_RESULT_NO_ACCUMULATE;
-  } else if (*(float *)beta == 1.0) {
-    r = CUDNN_RESULT_ACCUMULATE;
-  } else {
-    assert(0 && "beta must be 0.0 or 1.0");
-  }
-  return cudnnConvolutionBackwardFilter(handle, srcDesc, srcData,
-					diffDesc, diffData,
-					convDesc, gradDesc, gradData,
-					r);
+  cudnnConvolutionBwdDataAlgo_t algo,
+  size_t *sizeInBytes) {
+  *sizeInBytes = 0;
+  return CUDNN_STATUS_SUCCESS;
 }
 
-#define cudnnConvolutionBackwardFilter cudnnConvolutionBackwardFilter_v2
-
-static inline cudnnStatus_t
-cudnnConvolutionBackwardData_v2(
-  cudnnHandle_t	handle,
+static cudnnStatus_t cudnnConvolutionBackwardFilter_v3(
+  cudnnHandle_t handle,
   const void *alpha,
-  const cudnnFilterDescriptor_t filterDesc,
-  const void *filterData,
+  const cudnnTensorDescriptor_t srcDesc,
+  const void *srcData,
   const cudnnTensorDescriptor_t diffDesc,
   const void *diffData,
   const cudnnConvolutionDescriptor_t convDesc,
+  cudnnConvolutionBwdFilterAlgo_t algo,
+  void *workspace,
+  size_t workspaceSizeInBytes,
   const void *beta,
-  const cudnnTensorDescriptor_t gradDesc,
+  const cudnnFilterDescriptor_t gradDesc,
   void *gradData) {
-  assert(*(float *)alpha == 1.0);
-  cudnnAccumulateResult_t r;
-  if (*(float *)beta == 0.0) {
-    r = CUDNN_RESULT_NO_ACCUMULATE;
-  } else if (*(float *)beta == 1.0) {
-    r = CUDNN_RESULT_ACCUMULATE;
-  } else {
-    assert(0 && "beta must be 0.0 or 1.0");
-  }
-  /* This function needs the casting because its params are not
-     declared as const */
-  return cudnnConvolutionBackwardData(handle,
-				      (cudnnFilterDescriptor_t)filterDesc,
-				      filterData,
-				      (cudnnTensorDescriptor_t)diffDesc,
-				      diffData,
-				      (cudnnConvolutionDescriptor_t)convDesc,
-				      (cudnnTensorDescriptor_t)gradDesc,
-				      gradData,
-				      r);
+  return cudnnConvolutionBackwardFilter(
+    handle,
+    alpha,
+    srcDesc,
+    srcData,
+    diffDesc,
+    diffData,
+    convDesc,
+    beta,
+    gradDesc,
+    gradData);
 }
 
-#define cudnnConvolutionBackwardData cudnnConvolutionBackwardData_v2
-
-//Needed for R2 rc2
-# define CUDNN_POOLING_AVERAGE_COUNT_INCLUDE_PADDING CUDNN_POOLING_AVERAGE
-#else
-
-// r2 rc1 and rc2 do not have the same macro defined
-// I didn't checked if this the right combination, but as we do not wrap the padding interface, it is fine for now.
-# define CUDNN_POOLING_AVERAGE_COUNT_INCLUDE_PADDING ((cudnnPoolingMode_t)1)
-
 #endif
 
 #endif