6bf043e743
This commit removes the deallocation capabilities of one-shot-bufferization. One-shot-bufferization should never deallocate any memrefs as this should be entirely handled by the ownership-based-buffer-deallocation pass going forward. This means the `allow-return-allocs` pass option will default to true now, `create-deallocs` defaults to false and they, as well as the escape attribute indicating whether a memref escapes the current region, will be removed. A new `allow-return-allocs-from-loops` option is added as a temporary workaround for some bufferization limitations.
50 lines
2.2 KiB
MLIR
50 lines
2.2 KiB
MLIR
// RUN: mlir-opt %s -eliminate-empty-tensors -empty-tensor-to-alloc-tensor -one-shot-bufferize="bufferize-function-boundaries test-analysis-only" -split-input-file | FileCheck %s
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// CHECK-LABEL: func @buffer_forwarding_conflict
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func.func @buffer_forwarding_conflict(%arg0: tensor<?xf32> {bufferization.writable = true}, %arg1: index) -> (tensor<?xf32>, tensor<?xf32>) {
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%cst = arith.constant 0.000000e+00 : f32
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// CHECK: tensor.extract_slice
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// CHECK-SAME: {__inplace_operands_attr__ = ["false", "none"]
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// Instead of allocating, share buffer with some inplace bufferization?
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%0 = tensor.empty(%arg1) : tensor<?xf32>
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// CHECK: linalg.fill
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// CHECK-SAME: {__inplace_operands_attr__ = ["none", "true"]
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%1 = linalg.fill ins(%cst : f32) outs(%0 : tensor<?xf32>) -> tensor<?xf32>
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// CHECK: tensor.insert_slice
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// CHECK-SAME: {__inplace_operands_attr__ = ["true", "false", "none"]
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%2 = tensor.insert_slice %1 into %arg0[0] [%arg1] [1] : tensor<?xf32> into tensor<?xf32>
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// CHECK: tensor.insert_slice
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// CHECK-SAME: {__inplace_operands_attr__ = ["true", "true", "none"]
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%3 = tensor.insert_slice %1 into %arg0[42] [%arg1] [1] : tensor<?xf32> into tensor<?xf32>
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// CHECK: return
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// CHECK-SAME: __equivalent_func_args__ = [-1, 0]
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return %2, %3 : tensor<?xf32>, tensor<?xf32>
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}
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// -----
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// CHECK-LABEL: func @buffer_forwarding_no_conflict
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func.func @buffer_forwarding_no_conflict(%arg0: tensor<?xf32> {bufferization.writable = true}, %arg1: index) -> (tensor<?xf32>, tensor<?xf32>) {
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%cst = arith.constant 0.000000e+00 : f32
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// CHECK: tensor.extract_slice
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// CHECK-SAME: {__inplace_operands_attr__ = ["true", "none"]
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// Instead of allocating, share buffer with some inplace bufferization?
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%0 = tensor.empty(%arg1) : tensor<?xf32>
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// CHECK: linalg.fill
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// CHECK-SAME: {__inplace_operands_attr__ = ["none", "true"]
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%1 = linalg.fill ins(%cst : f32) outs(%0 : tensor<?xf32>) -> tensor<?xf32>
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// CHECK: tensor.insert_slice
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// CHECK-SAME: {__inplace_operands_attr__ = ["true", "true", "none"]
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%2 = tensor.insert_slice %1 into %arg0[42] [%arg1] [1] : tensor<?xf32> into tensor<?xf32>
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// CHECK: return
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// CHECK-SAME: __equivalent_func_args__ = [0, 0]
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return %2, %2 : tensor<?xf32>, tensor<?xf32>
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}
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