Poplar and PopLibs
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▼ include | |
► gcl | |
CollectiveBalancedReorder.hpp | |
Collectives.hpp | |
TileAllocation.hpp | |
► intrinsics | |
ipu_intrinsics | Functions that target single IPU instructions |
ipu_memory_intrinsics | Functions that target IPU memory instructions |
ipu_vector_math | IPU vector math functions |
► popfloat | |
► experimental | |
CastToGfloat.hpp | |
CastToHalf.hpp | |
codelets.hpp | |
GfloatExpr.hpp | |
GfloatExprUtil.hpp | |
► poplar | |
ArrayRef.hpp | References to arrays |
CallbackTraits.hpp | |
CodeletFileType.hpp | |
CSRFunctions.hpp | |
CycleCount.hpp | |
DataStream.hpp | |
DataStreamType.hpp | |
DebugContext.hpp | |
Device.hpp | |
DeviceManager.hpp | |
Engine.hpp | |
EngineOptions.hpp | |
Error.hpp | |
exceptions.hpp | |
Executable.hpp | |
FunctionBufferMappingType.hpp | |
GlobalExchangeConstraints.hpp | |
Graph.hpp | |
GraphElements.hpp | |
HostFunctionCallback.hpp | |
Interval.hpp | |
IpuLinkConfiguration.hpp | |
IpuLinkTopology.hpp | |
IPUModel.hpp | |
LateInitCallback.hpp | |
Module.hpp | |
OptionFlags.hpp | |
PerfEstimateFunc.hpp | |
Preallocations.hpp | |
ProfileValue.hpp | |
Program.hpp | |
Quarter.hpp | |
RandomSeed.hpp | |
ReplicatedStreamMode.hpp | |
replication_factor.hpp | |
RuntimeOptions.hpp | |
SerializationFormat.hpp | |
SSOPointer.hpp | |
StreamCallback.hpp | |
StringRef.hpp | |
SyncType.hpp | |
Target.hpp | |
TargetType.hpp | |
Tensor.hpp | |
TensorCloneMethod.hpp | |
TensorRearranger.hpp | |
Type.hpp | |
TypeConversion.hpp | |
TypeTraits.hpp | |
VariableMappingMethod.hpp | |
VariableRef.hpp | |
VectorLayout.hpp | |
VertexIntrospector.hpp | |
► poplin | |
Cholesky.hpp | Factorise a positive definite matrix using Cholesky decomposition |
codelets.hpp | |
Convolution.hpp | Functions and data types to support performing convolutions |
ConvParams.hpp | Data types for convolution parameters |
ConvPreplan.hpp | Functions and data types to support performing convolution preplanning |
ConvUtil.hpp | A collection of utility functions to assist calculation of input/output ranges when moving a 2-dimensional kernel over a larger 2-dimensional space (for example in convolution or pooling layers) |
FullyConnected.hpp | Functions and data types to for performing operations on fully-connected layers |
MatMul.hpp | Functions and data types for performing matrix multiplies on the IPU |
MeshGrid.hpp | Functions to populate arrays with linear sequences of values |
MultiConvolution.hpp | Support performing convolutions in parallel |
Norms.hpp | Functions to support normalising values in a tensor |
TriangularSolve.hpp | Solving linear equations using triangular matrices |
► popnn | |
► experimental | |
ROIAlign.hpp | |
BatchNorm.hpp | Batch normalization operations |
codelets.hpp | |
CTCInference.hpp | Support for Connectionist Temporal Classification (CTC) Beam search decoder |
CTCLoss.hpp | Support for Connectionist Temporal Classification (CTC) Loss |
CTCPlan.hpp | Support for planning Connectionist Temporal Classification (CTC) Operations |
GroupNorm.hpp | Group normalization operations |
Gru.hpp | Support for gated recurrent units |
GruDef.hpp | Definitions for GRU cell operations |
InstanceNorm.hpp | Instance normalization operations |
LayerNorm.hpp | Layer normalisation operations |
LogSoftmax.hpp | Log of softmax functions |
Loss.hpp | Loss and gradient calculations |
Lstm.hpp | Support for Long short-term memory cells |
LstmDef.hpp | Definitions for LSTM cell operations |
NonLinearity.hpp | Non-linearity operations |
NonLinearityDef.hpp | Definitions for non-linearity operations |
NonLinearityDefUtil.hpp | Definitions for non-linearity operations |
Norms.hpp | Normalisation operations |
Pooling.hpp | Support for pooling operations |
PoolingDef.hpp | Definitions for pooling operations |
Recurrent.hpp | Functions for recurrent neural networks (RNN) |
Rnn.hpp | Functions for recurrent neural networks (RNN) |
SpatialSoftMax.hpp | Functions for spatial softmax |
► popops | |
AllTrue.hpp | Perform logical AND of tensor elements |
Cast.hpp | Casts between tensor types |
CircBuf.hpp | Circular buffer support |
codelets.hpp | |
DynamicSlice.hpp | Support for dynamic slices |
ElementWise.hpp | These functions perform the same operation on each element of one or more tensors |
ElementWiseUtil.hpp | Supporting functions for element-wise operations |
Encoding.hpp | Encoding and generating ranges of integers |
EncodingConstants.hpp | Constants used by encoding functions |
Expr.hpp | Expressions with elements of tensors |
ExprOp.hpp | Operators used in expressions with elements of tensors |
ExprOpUtils.hpp | |
Fill.hpp | Functions to fill tensors with values |
Gather.hpp | Support for gather operations |
GatherStatistics.hpp | Functions to generate histograms of data |
HostSliceTensor.hpp | Create tensor layouts that are optimised for host transfers |
Loop.hpp | Functions to provide counted loops of programs |
NaN.hpp | Test for NaN values in a tensor |
NormaliseImage.hpp | Functions for padding and normalising image tensors |
Operation.hpp | Read/write types of operations used in a reduce |
OperationDef.hpp | Define types of operations used in Reduce/MultiUpdate |
OperationDefUtil.hpp | Utilities for Operation types |
Pad.hpp | Functions for padding a tensor |
PerformanceEstimation.hpp | This file is for internal use only and should not be used |
Rearrange.hpp | Operations to rearrange tensors on tiles |
Reduce.hpp | Define types of operations used in a reduce |
ScaledAdd.hpp | Functions for scaling and adding tensors |
Scatter.hpp | Scatter operations |
SelectScalarFromRows.hpp | Select values from rows of a tensor |
SequenceSlice.hpp | Support for dynamic slices |
Sort.hpp | Functions for sorting tensors |
SortOrder.hpp | Defintions of sort ordering |
TopK.hpp | Functions for finding the top k elements |
UpdateScalarInRows.hpp | Functions for updating values in tensors |
Zero.hpp | Set elements of tensor to zero |
► poprand | |
codelets.hpp | |
RandomGen.hpp | Functions for random number generation and applying random functions to tensors |
► popsparse | |
► experimental | |
BlockSparse.hpp | Block sparse operations |
BlockSparseMatMul.hpp | Block sparse matrix multiply |
codelets.hpp | |
Embedding.hpp | Functions for slicing and mapping sparse tensors |
FullyConnected.hpp | Fully-connected layers using sparse tensors |
FullyConnectedParams.hpp | Parameters used for fully-connected layers using sparse tensors |
MatMul.hpp | Sparse matrix multiply operations |
MatMulParams.hpp | Definitions for sparse matrix multiply operations |
PlanningCache.hpp | Caching of plans for dynamically sparse operations |
SparsePartitioner.hpp | Translation and encoding of sparsity information for a fully connected layer |
SparseStorageFormats.hpp | Storage formats for a block sparse matrix |
SparseTensor.hpp | Basic representation of a sparse tensor |
SparsityParams.hpp | Parameters used for sparse tensors |
► poputil | |
Broadcast.hpp | Functions to provide numpy-like tensor matching and broadcasting |
cyclesTables.hpp | This file is for internal use only and should not be used |
DebugInfo.hpp | Poplibs generic debug info structure |
exceptions.hpp | Define a PopLibs exception |
GraphFunction.hpp | Definitions for reusing graph structures |
OptionParsing.hpp | OptionSpec and OptionHandler used to build up a specification of what options and their values should be, and to translate the value strings to real values |
TensorMetaData.hpp | Class to allow extra data to be associated with a tensor |
TileMapping.hpp | Functions for handling the mapping of tensors to tiles |
Util.hpp | General operations on tensors |
VarStructure.hpp | Manage partitioning and grouping in tensors |
VertexTemplates.hpp | Generate a string describing a vertex type |
► pva | |
analysis.h | |
► runtime | |
Alignment.hpp | |
AvailableVTypes.h | |
Checking.hpp | |
FieldTypes.hpp | |
FieldTypeTraits.hpp | |
HalfFloat.hpp | |
IeeeHalf.hpp | |
InOutTypes.hpp | |
Iterators.hpp | |
Loops.hpp | |
QuarterFloat.hpp | |
StackSizeDefs.hpp | |
TileConstants.hpp | |
VectorListTypes.hpp | |
VectorTypes.hpp | |
Vertex.hpp |