mirror of https://github.com/llvm/torch-mlir
46 lines
1.5 KiB
MLIR
46 lines
1.5 KiB
MLIR
// RUN: npcomp-opt -torch-globalize-object-graph -verify-diagnostics -split-input-file %s
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torch.class_type @c1 {}
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torch.class_type @c2 {}
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// expected-note @+1 {{see other root module here}}
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torch.nn_module {} : !torch.nn.Module<"c1">
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// expected-error @+1 {{found more than one root module (module that is not a child of any other module)}}
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torch.nn_module {} : !torch.nn.Module<"c2">
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// -----
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torch.class_type @child {
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torch.attr "float" : f64
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}
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torch.class_type @parent {
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torch.attr "m" : !torch.nn.Module<"child">
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torch.attr "m2" : !torch.nn.Module<"child">
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}
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%c42 = std.constant 42.0 : f64
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// expected-error @+1 {{reachable by multiple paths from root object: '<root>.m' and '<root>.m2'}}
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%child = torch.nn_module {
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torch.slot "float", %c42 : f64
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} : !torch.nn.Module<"child">
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%parent = torch.nn_module {
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torch.slot "m", %child : !torch.nn.Module<"child">
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torch.slot "m2", %child : !torch.nn.Module<"child">
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} : !torch.nn.Module<"parent">
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// -----
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torch.class_type @c {
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torch.attr "a1" : !numpy.ndarray<*:!numpy.any_dtype>
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torch.attr "a2" : !numpy.ndarray<*:!numpy.any_dtype>
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}
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%cst = constant dense<1.000000e+00> : tensor<1xf32>
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// expected-error @+1 {{potentially-aliased value used to initialize multiple slots}}
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%a = numpy.create_array_from_tensor %cst : (tensor<1xf32>) -> !numpy.ndarray<*:!numpy.any_dtype>
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torch.nn_module {
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torch.slot "a1", %a : !numpy.ndarray<*:!numpy.any_dtype>
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torch.slot "a2", %a : !numpy.ndarray<*:!numpy.any_dtype>
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} : !torch.nn.Module<"c">
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