mirror of https://github.com/llvm/torch-mlir
43 lines
1.0 KiB
MLIR
43 lines
1.0 KiB
MLIR
// RUN: npcomp-opt -split-input-file -verify-diagnostics <%s
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// -----
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tcp.global @g dense<0.0> : tensor<2xf32>
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func @f() {
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// expected-error @+1 {{must reference a valid symbol}}
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tcp.get_global_memref @nonexistent_symbol : memref<3xf32>
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return
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}
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// -----
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tcp.global @g dense<0.0> : tensor<2xf32>
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func @f() {
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// expected-error @+1 {{inconsistent with shape of global}}
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tcp.get_global_memref @g : memref<3xf32>
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return
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}
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// -----
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tcp.global @g dense<0.0> : tensor<2xf32>
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func @f() {
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// expected-error @+1 {{inconsistent with element type of global}}
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tcp.get_global_memref @g : memref<2xi8>
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return
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}
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// -----
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func @g(%arg0: tensor<?x?xf32>, %arg1: tensor<?xindex>) -> tensor<?x?xf32> {
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// expected-error @+1 {{number of operands must equal number of results}}
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%add = tcp.shaped_results %arg1, %arg1 {
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%0 = tcp.add %arg0, %arg0 : (tensor<?x?xf32>, tensor<?x?xf32>) -> tensor<?x?xf32>
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tcp.yield %0 : tensor<?x?xf32>
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} : tensor<?xindex>, tensor<?xindex> -> tensor<?x?xf32>
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return %add : tensor<?x?xf32>
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}
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