/// <summary>
///
/// </summary>
/// <param name="context"></param>
public SpatialTransformerDescriptor(CudaDNNContext context)
{
_handle = context.Handle;
_desc = new cudnnSpatialTransformerDescriptor();
res = CudaDNNNativeMethods.cudnnCreateSpatialTransformerDescriptor(ref _desc);
Debug.WriteLine(String.Format("{0:G}, {1}: {2}", DateTime.Now, "cudnnCreateSpatialTransformerDescriptor", res));
if (res != cudnnStatus.Success) throw new CudaDNNException(res);
}
/// <summary>
/// </summary>
public LRNDescriptor(CudaDNNContext context)
{
_handle = context.Handle;
_desc = new cudnnLRNDescriptor();
res = CudaDNNNativeMethods.cudnnCreateLRNDescriptor(ref _desc);
Debug.WriteLine(String.Format("{0:G}, {1}: {2}", DateTime.Now, "cudnnCreateLRNDescriptor", res));
if (res != cudnnStatus.Success)
{
throw new CudaDNNException(res);
}
}
public SizeT GetAlgorithmSpaceSize(CudaDNNContext ctx)
{
SizeT size = new SizeT();
res = CudaDNNNativeMethods.cudnnGetAlgorithmSpaceSize(ctx.Handle, _desc, ref size);
Debug.WriteLine(String.Format("{0:G}, {1}: {2}", DateTime.Now, "cudnnGetAlgorithmSpaceSize", res));
if (res != cudnnStatus.Success)
{
throw new CudaDNNException(res);
}
return(size);
}
public void RestoreAlgorithm(CudaDNNContext ctx, byte[] algoSpace)
{
GCHandle handle = GCHandle.Alloc(algoSpace, GCHandleType.Pinned);
try
{
IntPtr ptr = handle.AddrOfPinnedObject();
res = CudaDNNNativeMethods.cudnnRestoreAlgorithm(ctx.Handle, ptr, algoSpace.Length, _desc);
Debug.WriteLine(String.Format("{0:G}, {1}: {2}", DateTime.Now, "cudnnRestoreAlgorithm", res));
}
finally
{
handle.Free();
}
if (res != cudnnStatus.Success)
{
throw new CudaDNNException(res);
}
}
/// <summary>
/// return the workspace size needed for ctc
/// </summary>
/// <param name="handle">Handle to a previously created cuDNN context.</param>
/// <param name="probsDesc">Handle to the previously initialized probabilities tensor descriptor.</param>
/// <param name="gradientsDesc">Handle to a previously initialized gradients tensor descriptor.</param>
/// <param name="labels">Pointer to a previously initialized labels list.</param>
/// <param name="labelLengths">Pointer to a previously initialized lengths list, to walk the above labels list.</param>
/// <param name="inputLengths">Pointer to a previously initialized list of the lengths of the timing steps in each batch.</param>
/// <param name="algo">Enumerant that specifies the chosen CTC loss algorithm</param>
/// <returns>Amount of GPU memory needed as workspace to be able to execute the CTC
/// loss computation with the specified algo.</returns>
public SizeT CTCLoss(CudaDNNContext handle,
TensorDescriptor probsDesc, /* Tensor descriptor for probabilities, the dimensions are T,N,A (T is the timing steps, N is the mini batch size, A is the alphabet size) */
int[] labels, /* labels, in CPU memory */
int[] labelLengths, /* the length of each label, in CPU memory */
int[] inputLengths, /* the lengths of timing steps in each batch, in CPU memory */
TensorDescriptor gradientsDesc, /* Tensor descriptor for gradients, the dimensions are T,N,A */
cudnnCTCLossAlgo algo /* algorithm selected, supported now 0 and 1 */
)
{
SizeT size = new SizeT();
res = CudaDNNNativeMethods.cudnnGetCTCLossWorkspaceSize(handle.Handle, probsDesc.Desc, gradientsDesc.Desc, labels, labelLengths, inputLengths,
algo, _desc, ref size);
Debug.Write("");//Line(String.Format("{0:G}, {1}: {2}", DateTime.Now, "cudnnGetCTCLossWorkspaceSize", res));
if (res != cudnnStatus.Success)
{
throw new CudaDNNException(res);
}
return(size);
}
/// <summary>
/// This function returns the ctc costs and gradients, given the probabilities and labels.
/// </summary>
/// <param name="handle">Handle to a previously created cuDNN context.</param>
/// <param name="probsDesc">Handle to the previously initialized probabilities tensor descriptor.</param>
/// <param name="probs">Pointer to a previously initialized probabilities tensor.</param>
/// <param name="labels">Pointer to a previously initialized labels list.</param>
/// <param name="labelLengths">Pointer to a previously initialized lengths list, to walk the above labels list.</param>
/// <param name="inputLengths">Pointer to a previously initialized list of the lengths of the timing steps in each batch.</param>
/// <param name="costs">Pointer to the computed costs of CTC.</param>
/// <param name="gradientsDesc">Handle to a previously initialized gradients tensor descriptor.</param>
/// <param name="gradients">Pointer to the computed gradients of CTC.</param>
/// <param name="algo">Enumerant that specifies the chosen CTC loss algorithm.</param>
/// <param name="workspace">Pointer to GPU memory of a workspace needed to able to execute the specified algorithm.</param>
public void CTCLoss(CudaDNNContext handle,
TensorDescriptor probsDesc, /* Tensor descriptor for probabilities, the dimensions are T,N,A (T is the timing steps, N is the mini batch size, A is the alphabet size) */
CudaDeviceVariable <double> probs, /* probabilities after softmax, in GPU memory */
int[] labels, /* labels, in CPU memory */
int[] labelLengths, /* the length of each label, in CPU memory */
int[] inputLengths, /* the lengths of timing steps in each batch, in CPU memory */
CudaDeviceVariable <double> costs, /* the returned costs of CTC, in GPU memory */
TensorDescriptor gradientsDesc, /* Tensor descriptor for gradients, the dimensions are T,N,A */
CudaDeviceVariable <double> gradients, /* the returned CTC gradients, in GPU memory, to compute costs only, set it to NULL */
cudnnCTCLossAlgo algo, /* algorithm selected, supported now 0 and 1 */
CudaDeviceVariable <byte> workspace /* pointer to the workspace, in GPU memory */
)
{
res = CudaDNNNativeMethods.cudnnCTCLoss(handle.Handle, probsDesc.Desc, probs.DevicePointer, labels, labelLengths, inputLengths, costs.DevicePointer,
gradientsDesc.Desc, gradients.DevicePointer, algo, _desc, workspace.DevicePointer, workspace.SizeInBytes);
Debug.Write("");//Line(String.Format("{0:G}, {1}: {2}", DateTime.Now, "cudnnCTCLoss", res));
if (res != cudnnStatus.Success)
{
throw new CudaDNNException(res);
}
}