mirror of https://github.com/llvm/torch-mlir
44 lines
1.9 KiB
MLIR
44 lines
1.9 KiB
MLIR
// RUN: npcomp-opt -lower-to-npcomprt-abi -split-input-file -verify-diagnostics <%s | FileCheck %s --dump-input=fail
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// CHECK: npcomprt.module_metadata
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// CHECK-NEXT: npcomprt.func_metadata {funcName = @identity, numInputs = 1 : i32, numOutputs = 1 : i32}
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// CHECK-NEXT: npcomprt.func_metadata {funcName = @basic, numInputs = 1 : i32, numOutputs = 1 : i32}
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// CHECK-LABEL: func @identity(
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// CHECK-SAME: %[[VAL_0:.*]]: !npcomprt.tensor) -> !npcomprt.tensor {
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// CHECK: return %[[VAL_0]] : !npcomprt.tensor
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// CHECK: }
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func @identity(%arg0: tensor<?xf32>) -> tensor<?xf32> {
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return %arg0 : tensor<?xf32>
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}
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// CHECK-LABEL: func @basic(
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// CHECK-SAME: %[[VAL_0:.*]]: !npcomprt.tensor) -> !npcomprt.tensor {
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// CHECK: %[[VAL_1:.*]] = constant 0 : i32
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// CHECK: %[[VAL_2:.*]] = npcomprt.get_extent %[[VAL_0]], %[[VAL_1]]
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// CHECK: %[[VAL_3:.*]] = shape.from_extents %[[VAL_2]]
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// CHECK: %[[VAL_4:.*]] = tcp.alloc_memref %[[VAL_3]] : memref<?xf32>
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// CHECK: %[[VAL_5:.*]] = npcomprt.to_memref %[[VAL_0]] : memref<*xf32>
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// CHECK: %[[VAL_6:.*]] = memref_cast %[[VAL_5]] : memref<*xf32> to memref<?xf32>
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// CHECK: linalg.copy(%[[VAL_6]], %[[VAL_4]]) : memref<?xf32>, memref<?xf32>
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// CHECK: %[[VAL_7:.*]] = memref_cast %[[VAL_4]] : memref<?xf32> to memref<*xf32>
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// CHECK: %[[VAL_8:.*]] = npcomprt.from_memref %[[VAL_7]] : memref<*xf32>
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// CHECK: return %[[VAL_8]] : !npcomprt.tensor
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// CHECK: }
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func @basic(%arg0: tensor<?xf32>) -> tensor<?xf32> {
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%shape = shape.shape_of %arg0 : tensor<?xf32>
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%memref = tcp.alloc_memref %shape : memref<?xf32>
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tensor_store %arg0, %memref : memref<?xf32>
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%ret = tensor_load %memref : memref<?xf32>
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return %ret: tensor<?xf32>
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}
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// -----
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// expected-error @+1 {{func not expressible with npcomprt ABI}}
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func @unhandled_abi_type_on_public_func(%arg0: i32) {
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return
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}
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