torch-mlir/test/E2E/lower-constant-tensors-to-m...

61 lines
1.5 KiB
MLIR

// RUN: npcomp-opt -split-input-file -lower-constant-tensors-to-memrefs <%s | FileCheck %s
// CHECK-LABEL: module {
// We check the debug name too since we put some effort into making that readable.
// The name isn't load-bearing though.
// CHECK: tcp.global @__constant_3x4xf32 dense<7.000000e+00> : tensor<3x4xf32>
// CHECK: func @basic
func @basic() -> tensor<3x4xf32> {
// CHECK: %[[MEMREF:.*]] = tcp.get_global_memref @__constant_3x4xf32 : memref<3x4xf32>
// CHECK: %[[TENSOR:.*]] = tensor_load %[[MEMREF]]
%0 = constant dense<7.0> : tensor<3x4xf32>
// CHECK: return %[[TENSOR]]
return %0 : tensor<3x4xf32>
}
// CHECK: }
// -----
// CHECK-LABEL: module {
// Only one global is created.
// CHECK: tcp.global
// CHECK-NOT: tcp.global
func @duplicate_constants() -> (tensor<3x4xf32>, tensor<3x4xf32>) {
%0 = constant dense<7.0> : tensor<3x4xf32>
%1 = constant dense<7.0> : tensor<3x4xf32>
// CHECK: return %[[TENSOR]]
return %0, %1 : tensor<3x4xf32>, tensor<3x4xf32>
}
// CHECK: }
// -----
// CHECK-LABEL: module {
// Two globals are created.
// CHECK: tcp.global
// CHECK: tcp.global
// CHECK-NOT: tcp.global
func @multiple_constants() -> (tensor<3x4xf32>, tensor<3x4xf32>) {
%0 = constant dense<7.0> : tensor<3x4xf32>
%1 = constant dense<8.0> : tensor<3x4xf32>
// CHECK: return %[[TENSOR]]
return %0, %1 : tensor<3x4xf32>, tensor<3x4xf32>
}
// CHECK: }
// -----
// CHECK-LABEL: module {
// We don't convert non-tensor globals.
// CHECK-NOT: tcp.global
func @non_tensor() {
%0 = constant 7 : i32
return
}
// CHECK: }