1f77f01c65
This operation is a NavigationOp that simplifies the writing of transform IR. Since there is no way of refering to an interface by name, the current implementation uses an EnumAttr and depends on the interfaces it supports. In the future, it would be worthwhile to remove this dependence and generalize. Differential Revision: https://reviews.llvm.org/D130267
111 lines
3.5 KiB
MLIR
111 lines
3.5 KiB
MLIR
// RUN: mlir-opt --test-transform-dialect-interpreter %s -split-input-file -verify-diagnostics | FileCheck %s
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// Test One-Shot Bufferize.
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transform.with_pdl_patterns {
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^bb0(%arg0: !pdl.operation):
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sequence %arg0 {
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^bb0(%arg1: !pdl.operation):
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%0 = transform.structured.match ops{["func.func"]} in %arg1
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transform.bufferization.one_shot_bufferize %0
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{target_is_module = false}
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}
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}
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// CHECK-LABEL: func @test_function(
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// CHECK-SAME: %[[A:.*]]: tensor<?xf32>
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func.func @test_function(%A : tensor<?xf32>, %v : vector<4xf32>) -> (tensor<?xf32>) {
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%c0 = arith.constant 0 : index
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// CHECK: %[[A_memref:.*]] = bufferization.to_memref %[[A]]
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// CHECK: %[[dim:.*]] = memref.dim %[[A_memref]]
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// CHECK: %[[alloc:.*]] = memref.alloc(%[[dim]])
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// CHECK: memref.copy %[[A_memref]], %[[alloc]]
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// CHECK: vector.transfer_write %{{.*}}, %[[alloc]]
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// CHECK: %[[res_tensor:.*]] = bufferization.to_tensor %[[alloc]]
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%0 = vector.transfer_write %v, %A[%c0] : vector<4xf32>, tensor<?xf32>
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// CHECK: memref.dealloc %[[alloc]]
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// CHECK: return %[[res_tensor]]
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return %0 : tensor<?xf32>
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}
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// -----
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// Test analysis of One-Shot Bufferize only.
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transform.with_pdl_patterns {
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^bb0(%arg0: !pdl.operation):
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sequence %arg0 {
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^bb0(%arg1: !pdl.operation):
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%0 = transform.structured.match ops{["func.func"]} in %arg1
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transform.bufferization.one_shot_bufferize %0
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{target_is_module = false, test_analysis_only = true}
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}
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}
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// CHECK-LABEL: func @test_function_analysis(
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// CHECK-SAME: %[[A:.*]]: tensor<?xf32>
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func.func @test_function_analysis(%A : tensor<?xf32>, %v : vector<4xf32>) -> (tensor<?xf32>) {
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%c0 = arith.constant 0 : index
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// CHECK: vector.transfer_write
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// CHECK-SAME: {__inplace_operands_attr__ = ["none", "false", "none"]}
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// CHECK-SAME: tensor<?xf32>
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%0 = vector.transfer_write %v, %A[%c0] : vector<4xf32>, tensor<?xf32>
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return %0 : tensor<?xf32>
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}
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// -----
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// Test One-Shot Bufferize transform failure with an unknown op. This would be
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// allowed with `allow_unknown_ops`.
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transform.with_pdl_patterns {
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^bb0(%arg0: !pdl.operation):
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sequence %arg0 {
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^bb0(%arg1: !pdl.operation):
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%0 = transform.structured.match ops{["func.func"]} in %arg1
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// expected-error @+1 {{bufferization failed}}
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transform.bufferization.one_shot_bufferize %0 {target_is_module = false}
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}
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}
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func.func @test_unknown_op_failure() -> (tensor<?xf32>) {
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// expected-error @+1 {{op was not bufferized}}
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%0 = "test.dummy_op"() : () -> (tensor<?xf32>)
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return %0 : tensor<?xf32>
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}
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// -----
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// Test One-Shot Bufferize transform failure with a module op.
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transform.with_pdl_patterns {
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^bb0(%arg0: !pdl.operation):
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sequence %arg0 {
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^bb0(%arg1: !pdl.operation):
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// %arg1 is the module
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transform.bufferization.one_shot_bufferize %arg1
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}
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}
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module {
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// CHECK-LABEL: func @test_function(
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// CHECK-SAME: %[[A:.*]]: tensor<?xf32>
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func.func @test_function(%A : tensor<?xf32>, %v : vector<4xf32>) -> (tensor<?xf32>) {
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%c0 = arith.constant 0 : index
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// CHECK: %[[A_memref:.*]] = bufferization.to_memref %[[A]]
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// CHECK: %[[dim:.*]] = memref.dim %[[A_memref]]
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// CHECK: %[[alloc:.*]] = memref.alloc(%[[dim]])
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// CHECK: memref.copy %[[A_memref]], %[[alloc]]
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// CHECK: vector.transfer_write %{{.*}}, %[[alloc]]
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// CHECK: %[[res_tensor:.*]] = bufferization.to_tensor %[[alloc]]
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%0 = vector.transfer_write %v, %A[%c0] : vector<4xf32>, tensor<?xf32>
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// CHECK: memref.dealloc %[[alloc]]
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// CHECK: return %[[res_tensor]]
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return %0 : tensor<?xf32>
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}
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}
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