mirror of https://github.com/llvm/torch-mlir
54 lines
3.1 KiB
MLIR
54 lines
3.1 KiB
MLIR
|
// RUN: npcomp-opt -npcomp-verify-backend-contract -split-input-file -verify-diagnostics -allow-unregistered-dialect %s | FileCheck %s
|
||
|
|
|
||
|
|
// CHECK: func @mm
|
||
|
|
func @mm(%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>) -> tensor<?x?xf32> attributes {iree.module.export} {
|
||
|
|
%c0 = constant 0 : index
|
||
|
|
%c1 = constant 1 : index
|
||
|
|
%cst = constant 0.000000e+00 : f32
|
||
|
|
%0 = memref.dim %arg0, %c0 : tensor<?x?xf32>
|
||
|
|
%1 = memref.dim %arg0, %c1 : tensor<?x?xf32>
|
||
|
|
%2 = memref.dim %arg1, %c0 : tensor<?x?xf32>
|
||
|
|
%3 = memref.dim %arg1, %c1 : tensor<?x?xf32>
|
||
|
|
%4 = cmpi eq, %1, %2 : index
|
||
|
|
assert %4, "mismatching contracting dimension for aten.mm"
|
||
|
|
%5 = linalg.init_tensor [%0, %3] : tensor<?x?xf32>
|
||
|
|
%6 = linalg.fill(%5, %cst) : tensor<?x?xf32>, f32 -> tensor<?x?xf32>
|
||
|
|
%7 = linalg.matmul ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>) outs(%6 : tensor<?x?xf32>) -> tensor<?x?xf32>
|
||
|
|
return %7 : tensor<?x?xf32>
|
||
|
|
}
|
||
|
|
|
||
|
|
// -----
|
||
|
|
|
||
|
|
// Basic check of error reporting.
|
||
|
|
|
||
|
|
// expected-error@+1 {{Module does not conform to npcomp's backend contract.}}
|
||
|
|
module {
|
||
|
|
func @disallowed() {
|
||
|
|
// expected-error@+1 {{failed to legalize operation 'unknown_dialect.unknown_op'}}
|
||
|
|
"unknown_dialect.unknown_op"() : () -> ()
|
||
|
|
return
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
// -----
|
||
|
|
|
||
|
|
// TODO: Improve these errors to give more exact reporting.
|
||
|
|
//
|
||
|
|
// The reporting we inherit from dialect conversion is not precise.
|
||
|
|
// For example, here we want it to explicitly call out that
|
||
|
|
// `tensor<?x!numpy.any_dtype>` is the problem here, which suggests
|
||
|
|
// that type inference didn't succeed, or insufficient type information
|
||
|
|
// was available.
|
||
|
|
//
|
||
|
|
// Ultimately, the output of this pass needs to be conveyed to the user
|
||
|
|
// in an understandable way, such as suggesting a particular place where
|
||
|
|
// a shape annotation is needed.
|
||
|
|
|
||
|
|
// expected-error@+1 {{Module does not conform to npcomp's backend contract.}}
|
||
|
|
module {
|
||
|
|
func @disallowed(%arg0: tensor<?x!numpy.any_dtype>) -> tensor<?x!numpy.any_dtype> {
|
||
|
|
// expected-error@+1 {{failed to legalize operation 'std.return'}}
|
||
|
|
return %arg0 : tensor<?x!numpy.any_dtype>
|
||
|
|
}
|
||
|
|
}
|