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// 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
// CHECK-LABEL: func @buffer_forwarding_conflict
func.func @buffer_forwarding_conflict(%arg0: tensor<?xf32> {bufferization.writable = true}, %arg1: index) -> (tensor<?xf32>, tensor<?xf32>) {
%cst = arith.constant 0.000000e+00 : f32
// CHECK: tensor.extract_slice
// CHECK-SAME: {__inplace_operands_attr__ = ["false", "none"]
// Instead of allocating, share buffer with some inplace bufferization?
%0 = tensor.empty(%arg1) : tensor<?xf32>
// CHECK: linalg.fill
// CHECK-SAME: {__inplace_operands_attr__ = ["none", "true"]
%1 = linalg.fill ins(%cst : f32) outs(%0 : tensor<?xf32>) -> tensor<?xf32>
// CHECK: tensor.insert_slice
// CHECK-SAME: {__inplace_operands_attr__ = ["true", "false", "none"]
%2 = tensor.insert_slice %1 into %arg0[0] [%arg1] [1] : tensor<?xf32> into tensor<?xf32>
// CHECK: tensor.insert_slice
// CHECK-SAME: {__inplace_operands_attr__ = ["true", "true", "none"]
%3 = tensor.insert_slice %1 into %arg0[42] [%arg1] [1] : tensor<?xf32> into tensor<?xf32>
// CHECK: return
// CHECK-SAME: __equivalent_func_args__ = [-1, 0]
return %2, %3 : tensor<?xf32>, tensor<?xf32>
}
// -----
// CHECK-LABEL: func @buffer_forwarding_no_conflict
func.func @buffer_forwarding_no_conflict(%arg0: tensor<?xf32> {bufferization.writable = true}, %arg1: index) -> (tensor<?xf32>, tensor<?xf32>) {
%cst = arith.constant 0.000000e+00 : f32
// CHECK: tensor.extract_slice
// CHECK-SAME: {__inplace_operands_attr__ = ["true", "none"]
// Instead of allocating, share buffer with some inplace bufferization?
%0 = tensor.empty(%arg1) : tensor<?xf32>
// CHECK: linalg.fill
// CHECK-SAME: {__inplace_operands_attr__ = ["none", "true"]
%1 = linalg.fill ins(%cst : f32) outs(%0 : tensor<?xf32>) -> tensor<?xf32>
// CHECK: tensor.insert_slice
// CHECK-SAME: {__inplace_operands_attr__ = ["true", "true", "none"]
%2 = tensor.insert_slice %1 into %arg0[42] [%arg1] [1] : tensor<?xf32> into tensor<?xf32>
// CHECK: return
// CHECK-SAME: __equivalent_func_args__ = [0, 0]
return %2, %2 : tensor<?xf32>, tensor<?xf32>
}
// -----
// CHECK-LABEL: func @buffer_forwarding_conflict_with_different_element_type
func.func @buffer_forwarding_conflict_with_different_element_type(%arg0: tensor<?xf32> {bufferization.writable = true}, %arg1: index) -> (tensor<?xf32>, tensor<?xf32>) {
// CHECK: tensor.extract_slice
// CHECK-SAME: {__inplace_operands_attr__ = ["true", "none"]
%cst = arith.constant 0.000000e+00 : f32
%0 = tensor.empty(%arg1) : tensor<?xf32>
// CHECK: bufferization.alloc_tensor(%arg1)
%1 = tensor.empty(%arg1) : tensor<?xbf16>
// CHECK: linalg.copy
// CHECK-SAME: {__inplace_operands_attr__ = ["true", "true"]
%2 = linalg.copy ins(%0 : tensor<?xf32>) outs(%1 : tensor<?xbf16>) -> tensor<?xbf16>
// CHECK: linalg.copy
// CHECK-SAME: {__inplace_operands_attr__ = ["true", "true"]
%3 = linalg.copy ins(%2 : tensor<?xbf16>) outs(%0 : tensor<?xf32>) -> tensor<?xf32>
// CHECK: tensor.insert_slice
// CHECK-SAME: {__inplace_operands_attr__ = ["true", "true", "none"]
%4 = tensor.insert_slice %3 into %arg0[42] [%arg1] [1] : tensor<?xf32> into tensor<?xf32>
// CHECK: return
// CHECK-SAME: __equivalent_func_args__ = [0, 0]
return %4, %4 : tensor<?xf32>, tensor<?xf32>
}
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