Embedding
#include <popsparse/Embedding.hpp>
Functions for slicing and mapping sparse tensors.
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namespace popsparse
Support for sparse matrices.
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namespace dynamic
Support for dynamic sparse matrices.
Functions
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poplar::Tensor createIndicesTensor(poplar::Graph &graph, const FullyConnectedParams ¶ms, std::size_t numIndices, const poplar::OptionFlags &options = {}, const poplar::DebugContext &debugContext = {})
Create and map a tensor to contain indices for slicing/updating a tensor efficiently.
- Parameters
graph – The Poplar graph.
params – Parameters for the fully connected layer which defines the embedding operation. Used to decide on layout for the indices.
options – Implementation options for the fully connected layer.
numIndices – The number of indices this tensor should contain
debugContext – Optional debug information.
- Returns
A 1D tensor of shape [
numIndices]. Element type is always UNSIGNED_INT.
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poplar::Tensor createSliceTensor(poplar::Graph &graph, const poplar::Type &dataType, const FullyConnectedParams ¶ms, std::size_t numIndices, const poplar::DebugContext &debugContext = {}, const poplar::OptionFlags &options = {}, PlanningCache *cache = nullptr)
Create and map a tensor to be updated from efficiently.
Memory layout is based on the planned split of the sparse tensor.
- Parameters
graph – The Poplar graph.
dataType – The data type of the returned tensor.
params – Parameters for the fully connected layer which will provide the planned memory layout for the sparse tensor being updated
numIndices – The number of slices this tensor should contain.
debugContext – Optional debug information.
options – Implementation options for the fully connected layer.
cache – Optional pointer to planning cache to use.
- Returns
A 2D tensor with shape [numIndices,
params.getInputChannels()] with layout optimised for slicing into/updating from.
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poplar::Tensor embeddingSlice(poplar::Graph &graph, const SparseTensor &t, const poplar::Tensor &indices, poplar::program::Sequence &prog, const FullyConnectedParams ¶ms, const poplar::DebugContext &debugContext = {}, const poplar::OptionFlags &options = {}, PlanningCache *cache = nullptr)
Take multiple slices from a base tensor.
The returned tensor will have dimensions [offsets, k (from params)]
- Parameters
graph – The Poplar graph.
t – The sparse tensor being sliced.
indices – The indices of rows of
tto be sliced.prog – The program to be extended.
params – Parameters for the fully connected layer which will provide the planned memory layout for the sparse tensor being sliced.
debugContext – Optional debug information.
options – Implementation options for the fully connected layer.
cache – Optional pointer to planning cache to use.
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void embeddingUpdateAdd(poplar::Graph &graph, const SparseTensor &t, const poplar::Tensor &slices, const poplar::Tensor &indices, const poplar::Tensor &scale, poplar::program::Sequence &prog, const FullyConnectedParams ¶ms, const poplar::DebugContext &debugContext = {}, const poplar::OptionFlags &options = {}, PlanningCache *cache = nullptr)
Update a sparse tensor with a set of slices at the given row indices.
- Parameters
graph – The Poplar graph.
t – The sparse tensor being updated.
slices – The slices to accumulate.
indices – The indices of rows of
tto accumulate each slice inslicesinto.scale – The scaling to apply to the update.
prog – The program to be extended.
params – Parameters for the fully connected layer which will provide the planned memory layout for the sparse tensor being updated
debugContext – Optional debug information.
options – Implementation options for the fully connected layer.
cache – Optional pointer to planning cache to use.
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poplar::Tensor createIndicesTensor(poplar::Graph &graph, const FullyConnectedParams ¶ms, std::size_t numIndices, const poplar::OptionFlags &options = {}, const poplar::DebugContext &debugContext = {})
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namespace dynamic