Lines Matching defs:tensor

61 // For index reduction loops, since the tensor are sliced into non-continuous
66 static Value genSliceOffset(OpBuilder &builder, Location loc, Value tensor,
68   auto enc = getSparseTensorEncoding(tensor.getType());
69   return createOrFoldSliceOffsetOp(builder, loc, tensor, toDim(enc, lvl));
72 static Value genSliceStride(OpBuilder &builder, Location loc, Value tensor,
74   auto enc = getSparseTensorEncoding(tensor.getType());
75   return createOrFoldSliceStrideOp(builder, loc, tensor, toDim(enc, lvl));
97   auto padOp = t.getDefiningOp<tensor::PadOp>();
104                      m_Op<tensor::YieldOp>(m_Constant(&padCst))) &&
113 // Sparse tensor loop emitter class implementations
160       // Synthetic tensor (conceptually) is an all-dense tensor with rank equal
204   Value tensor = tensors[t];
205   auto stt = getSparseTensorType(tensor);
208   Value folded = tryFoldTensors(tensor);
209   if (folded != tensor) {
210     auto padOp = tensor.getDefiningOp<tensor::PadOp>();
221     Value offset = genSliceOffset(builder, loc, tensor, l);
222     Value stride = genSliceStride(builder, loc, tensor, l);
235   // For every manifest tensor, set up the values buffer.
240     const Value tensor = tryFoldTensors(tensors[t]);
241     const auto rtp = dyn_cast<RankedTensorType>(tensor.getType());
242     // Skips only scalar, zero ranked tensor still need to be bufferized and
247     auto stt = getSparseTensorType(tensor);
262       if (llvm::isa_and_nonnull<tensor::ExtractSliceOp>(tensor.getDefiningOp()))
266           builder.create<bufferization::ToMemrefOp>(loc, denseTp, tensor);
269         denseVal = updater(builder, loc, denseVal, tensor);
276       valBuffer[t] = builder.create<ToValuesOp>(loc, tensor);
285   // For every synthetic tensor, set the high bound by calling the callback.
296   // For every manifest tensor:
305     const Value tensor = tryFoldTensors(tensors[t]);
306     const auto rtp = dyn_cast<RankedTensorType>(tensor.getType());
308       // Skips only scalar, zero ranked tensor still need to be bufferized and
312     auto stt = getSparseTensorType(tensor);
315     // Scan all levels of current tensor.
318       lvls[t][l] = makeSparseTensorLevel(builder, loc, tensor, t, l);
326     // some loop preparation from tensor iteration, but will also (undesirably)
398   // Finds out the tensor level that we should use to generate loops. Amongs all
399   // the tensor levels, there is at most one sparse tensor level.
685   // Enter dense tensor levels.
906   // NOTE: the slice driven tensor-related reduction variable must