abc362a107
Suggested by @lattner in https://discourse.llvm.org/t/rfc-define-precise-arith-semantics/65507/22. Tested with: `ninja check-mlir check-mlir-integration check-mlir-mlir-spirv-cpu-runner check-mlir-mlir-vulkan-runner check-mlir-examples` and `bazel build --config=generic_clang @llvm-project//mlir:all`. Reviewed By: lattner, Mogball, rriddle, jpienaar, mehdi_amini Differential Revision: https://reviews.llvm.org/D134762
62 lines
2.8 KiB
MLIR
62 lines
2.8 KiB
MLIR
// RUN: mlir-opt %s -one-shot-bufferize="allow-return-allocs bufferize-function-boundaries" -split-input-file | FileCheck %s
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// Run fuzzer with different seeds.
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// RUN: mlir-opt %s -one-shot-bufferize="allow-return-allocs test-analysis-only analysis-fuzzer-seed=23 bufferize-function-boundaries" -split-input-file -o /dev/null
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// RUN: mlir-opt %s -one-shot-bufferize="allow-return-allocs test-analysis-only analysis-fuzzer-seed=59 bufferize-function-boundaries" -split-input-file -o /dev/null
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// RUN: mlir-opt %s -one-shot-bufferize="allow-return-allocs test-analysis-only analysis-fuzzer-seed=91 bufferize-function-boundaries" -split-input-file -o /dev/null
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// Test bufferization using memref types that have no layout map.
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// RUN: mlir-opt %s -one-shot-bufferize="allow-return-allocs unknown-type-conversion=identity-layout-map function-boundary-type-conversion=identity-layout-map bufferize-function-boundaries" -split-input-file -o /dev/null
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// CHECK-LABEL: func @write_to_select_op_source
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// CHECK-SAME: %[[t1:.*]]: memref<?xf32, strided{{.*}}>, %[[t2:.*]]: memref<?xf32, strided{{.*}}>
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func.func @write_to_select_op_source(
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%t1 : tensor<?xf32> {bufferization.writable = true},
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%t2 : tensor<?xf32> {bufferization.writable = true},
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%c : i1)
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-> (tensor<?xf32>, tensor<?xf32>)
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{
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%cst = arith.constant 0.0 : f32
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%idx = arith.constant 0 : index
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// CHECK: %[[alloc:.*]] = memref.alloc
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// CHECK: memref.copy %[[t1]], %[[alloc]]
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// CHECK: memref.store %{{.*}}, %[[alloc]]
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%w = tensor.insert %cst into %t1[%idx] : tensor<?xf32>
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// CHECK: %[[select:.*]] = arith.select %{{.*}}, %[[t1]], %[[t2]]
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%s = arith.select %c, %t1, %t2 : tensor<?xf32>
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// CHECK: return %[[select]], %[[alloc]]
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return %s, %w : tensor<?xf32>, tensor<?xf32>
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}
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// -----
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// Due to the out-of-place bufferization of %t1, buffers with different layout
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// maps are passed to arith.select. A cast must be inserted.
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// CHECK-LABEL: func @write_after_select_read_one
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// CHECK-SAME: %[[t1:.*]]: memref<?xf32, strided{{.*}}>, %[[t2:.*]]: memref<?xf32, strided{{.*}}>
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func.func @write_after_select_read_one(
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%t1 : tensor<?xf32> {bufferization.writable = true},
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%t2 : tensor<?xf32> {bufferization.writable = true},
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%c : i1)
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-> (f32, tensor<?xf32>)
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{
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%cst = arith.constant 0.0 : f32
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%idx = arith.constant 0 : index
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// CHECK: %[[alloc:.*]] = memref.alloc
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// CHECK-DAG: %[[casted:.*]] = memref.cast %[[alloc]]
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// CHECK-DAG: memref.copy %[[t1]], %[[alloc]]
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// CHECK: %[[select:.*]] = arith.select %{{.*}}, %[[casted]], %[[t2]]
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%s = arith.select %c, %t1, %t2 : tensor<?xf32>
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// CHECK: memref.store %{{.*}}, %[[select]]
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%w = tensor.insert %cst into %s[%idx] : tensor<?xf32>
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// CHECK: %[[f:.*]] = memref.load %[[t1]]
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%f = tensor.extract %t1[%idx] : tensor<?xf32>
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// CHECK: return %[[f]], %[[select]]
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return %f, %w : f32, tensor<?xf32>
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}
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