mirror of https://github.com/llvm/torch-mlir
42 lines
1.0 KiB
Python
42 lines
1.0 KiB
Python
# RUN: %PYTHON %s | npcomp-opt -split-input-file | FileCheck %s --dump-input=fail
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from npcomp.compiler.frontend import *
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def import_global(f):
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fe = ImportFrontend()
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fe.import_global_function(f)
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print("// -----")
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print(fe.ir_module.to_asm())
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return f
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# CHECK-LABEL: func @positional_args
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# CHECK-SAME: (%arg0: !basicpy.UnknownType, %arg1: !basicpy.UnknownType) -> !basicpy.UnknownType
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@import_global
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def positional_args(a, b):
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# CHECK: basicpy.binary_expr %arg0 "Add" %arg1
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return a + b
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# CHECK-LABEL: func @pass_no_return
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@import_global
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def pass_no_return():
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# CHECK: %[[NONE:.*]] = basicpy.singleton : !basicpy.NoneType
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# CHECK: %[[NONE_CAST:.*]] = basicpy.unknown_cast %[[NONE]] : !basicpy.NoneType -> !basicpy.UnknownType
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# CHECK: return %[[NONE_CAST]]
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# CHECK-NOT: return
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pass
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# CHECK-LABEL: func @expr_statement
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@import_global
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def expr_statement():
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# CHECK: basicpy.exec {
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# CHECK: %[[V:.*]] = basicpy.binary_expr
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# CHECK: basicpy.exec_discard %[[V]]
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# CHECK: }
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# CHECK: return
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a = 1
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a + 2
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