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"Finish" tensor -> memref conversion. There's a lot of details to flesh out here, but the basic approach seems promising (see comments in createE2ELoweringPipeline). This approach will be put to the test when we try to do our first fusions since that tickles some of the nasty phase ordering issues involved here. But we're not there yet.
2020-05-12 05:24:57 +08:00
// RUN: npcomp-opt -resolve-tensor-load-store-ops <%s | FileCheck %s --dump-input=fail
// CHECK-LABEL: func @basic
func @basic(%arg0: tensor<?xf32>) -> tensor<?xf32> {
%shape = "shape.shape_of"(%arg0) : (tensor<?xf32>) -> !shape.shape
Add custom assembly format for tcp.alloc_memref/tcp.get_extent This makes the IR a bit easier to scan.
2020-05-12 06:20:49 +08:00
// CHECK: %[[SRCMEMREF:.+]] = tcp.alloc_memref
%src_memref = tcp.alloc_memref %shape : memref<?xf32>
"Finish" tensor -> memref conversion. There's a lot of details to flesh out here, but the basic approach seems promising (see comments in createE2ELoweringPipeline). This approach will be put to the test when we try to do our first fusions since that tickles some of the nasty phase ordering issues involved here. But we're not there yet.
2020-05-12 05:24:57 +08:00
// tensor_store of argument remains.
// CHECK: tensor_store %arg0, %[[SRCMEMREF]]
tensor_store %arg0, %src_memref : memref<?xf32>
%src = tensor_load %src_memref : memref<?xf32>
Add custom assembly format for tcp.alloc_memref/tcp.get_extent This makes the IR a bit easier to scan.
2020-05-12 06:20:49 +08:00
// CHECK: %[[DSTMEMREF:.+]] = tcp.alloc_memref
%dst_memref = tcp.alloc_memref %shape : memref<?xf32>
"Finish" tensor -> memref conversion. There's a lot of details to flesh out here, but the basic approach seems promising (see comments in createE2ELoweringPipeline). This approach will be put to the test when we try to do our first fusions since that tickles some of the nasty phase ordering issues involved here. But we're not there yet.
2020-05-12 05:24:57 +08:00
// tensor_store of internally created tensor is eliminated.
// CHECK-NOT: tensor_store
// CHECK: linalg.copy(%[[SRCMEMREF]], %[[DSTMEMREF]])
tensor_store %src, %dst_memref : memref<?xf32>
%ret = tensor_load %dst_memref : memref<?xf32>
// The tensor_load feeding into the return remains.
// %[[RET:.+]] = tensor_load %[[DSTMEMREF]]
// return %[[RET]]
return %ret : tensor<?xf32>
}