drop-unit-extent-dims.mlir
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// RUN: mlir-opt %s -linalg-fold-unit-extent-dims -split-input-file | FileCheck %s
#accesses = [
affine_map<(i, j, k, l, m) -> (i, k, m)>,
affine_map<(i, j, k, l, m) -> (i, k, j, l, m)>
]
#trait = {
args_in = 1,
args_out = 1,
iterator_types = ["parallel", "parallel", "parallel", "parallel", "parallel"],
indexing_maps = #accesses,
library_call = "some_external_func"
}
func @drop_one_trip_loops(%arg0 : tensor<?x1x?xf32>) -> tensor<?x1x?x1x?xf32>
{
%0 = linalg.generic #trait %arg0 {
^bb0(%arg1 : f32) :
linalg.yield %arg1 : f32
} : tensor<?x1x?xf32> -> tensor<?x1x?x1x?xf32>
return %0 : tensor<?x1x?x1x?xf32>
}
// CHECK-DAG: #[[$MAP0:.*]] = affine_map<(d0, d1, d2) -> (d0, d1)>
// CHECK-DAG: #[[$MAP1:.*]] = affine_map<(d0, d1, d2) -> (d2)>
// CHECK-DAG: #[[$MAP2:.*]] = affine_map<(d0, d1, d2) -> (d0, d2)>
// CHECK-DAG: #[[$MAP3:.*]] = affine_map<(d0, d1, d2) -> (d0, d1, d2)>
// CHECK-DAG: #[[$MAP4:.*]] = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1)>
// CHECK-DAG: #[[$MAP5:.*]] = affine_map<(d0, d1, d2, d3, d4) -> (d2, d3)>
// CHECK-DAG: #[[$MAP6:.*]] = affine_map<(d0, d1, d2, d3, d4) -> (d4)>
// CHECK-LABEL: func @drop_one_trip_loops
// CHECK: linalg.tensor_reshape %{{.*}} [#[[$MAP0]], #[[$MAP1]]]
// CHECK: linalg.generic
// CHECK-SAME: indexing_maps = [#[[$MAP2]], #[[$MAP3]]]
// CHECK-SAME: iterator_types = ["parallel", "parallel", "parallel"]
// CHECK: linalg.tensor_reshape %{{.*}} [#[[$MAP4]], #[[$MAP5]], #[[$MAP6]]]
// -----
#map0 = affine_map<(i, j) -> (i, j)>
#access = [#map0, #map0]
#trait = {
args_in = 1,
args_out = 1,
iterator_types = ["parallel", "parallel"],
indexing_maps = #access,
library_call = "some_external_func"
}
func @drop_all_loops(%arg0 : tensor<1x1xf32>) -> tensor<1x1xf32>
{
%0 = linalg.generic #trait %arg0 {
^bb0(%arg1: f32) :
linalg.yield %arg1 : f32
} : tensor<1x1xf32> -> tensor<1x1xf32>
return %0 : tensor<1x1xf32>
}
// CHECK-DAG: #[[$MAP0:.*]] = affine_map<() -> ()>
// CHECK-LABEL: func @drop_all_loops
// CHECK: linalg.tensor_reshape %{{.*}} []
// CHECK: linalg.generic
// CHECK-SAME: indexing_maps = [#[[$MAP0]], #[[$MAP0]]]
// CHECK-SAME: iterator_types = []
// -----
#accesses = [
affine_map<(d0) -> (0, d0)>,
affine_map<(d0) -> (d0)>
]
#trait = {
args_in = 1,
args_out = 1,
indexing_maps = #accesses,
iterator_types = ["parallel"],
library_call = "some_external_fn"
}
func @leading_dim_1_canonicalization(%arg0: tensor<1x5xf32>) -> tensor<5xf32> {
%0 = linalg.generic #trait %arg0 {
^bb0(%arg2: f32): // no predecessors
linalg.yield %arg2 : f32
} : tensor<1x5xf32> -> tensor<5xf32>
return %0 : tensor<5xf32>
}
// CHECK-DAG: #[[$MAP0:.*]] = affine_map<(d0, d1) -> (d0, d1)>
// CHECK-LABEL: func @leading_dim_1_canonicalization
// CHECK: linalg.tensor_reshape %{{.*}} [#[[$MAP0]]]
// CHECK: linalg.generic
// CHECK-SAME: indexing_maps = [#[[$MAP1]], #[[$MAP1]]]
// CHECK-SAME: iterator_types = ["parallel"]
// -----
#accesses = [
affine_map<(d0, d1) -> (0, d1)>,
affine_map<(d0, d1) -> (d0, 0)>,
affine_map<(d0, d1) -> (d0, d1)>
]
#trait = {
args_in = 2,
args_out = 1,
indexing_maps = #accesses,
iterator_types = ["parallel", "parallel"],
library_call = "some_external_fn"
}
func @broadcast_test(%arg0 : tensor<5xf32>, %arg1 : tensor<5xf32>) -> tensor<5x5xf32>
{
%0 = linalg.tensor_reshape %arg0 [affine_map<(d0, d1) -> (d0, d1)>] :
tensor<5xf32> into tensor<1x5xf32>
%1 = linalg.tensor_reshape %arg1 [affine_map<(d0, d1) -> (d0, d1)>] :
tensor<5xf32> into tensor<5x1xf32>
%2 = linalg.generic #trait %0, %1 {
^bb0(%arg2: f32, %arg3: f32):
%3 = addf %arg2, %arg3 : f32
linalg.yield %3 : f32
} : tensor<1x5xf32>, tensor<5x1xf32> -> tensor<5x5xf32>
return %2 : tensor<5x5xf32>
}
// CHECK-DAG: #[[$MAP0:.*]] = affine_map<(d0, d1) -> (d1)>
// CHECK-DAG: #[[$MAP1:.*]] = affine_map<(d0, d1) -> (d0)>
// CHECK-DAG: #[[$MAP2:.*]] = affine_map<(d0, d1) -> (d0, d1)>
// CHECK-LABEL: func @broadcast_test
// CHECK-NOT: linalg.tensor_reshape
// CHECK: linalg.generic
// CHECK-SAME: indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP2]]]
// CHECK-SAME: iterator_types = ["parallel", "parallel"]
// CHECK-NOT: linalg.tensor_reshape
// -----
#accesses = [
affine_map<(d0, d1) -> (0, 0)>,
affine_map<(d0, d1) -> (d0, d1)>
]
#trait = {
args_in = 1,
args_out = 1,
indexing_maps = #accesses,
iterator_types = ["parallel", "parallel"],
library_call = "some_external_fn"
}
func @broadcast_scalar(%arg0 : tensor<1x1xf32>) -> tensor<?x?xf32>
{
%0 = linalg.generic #trait %arg0 {
^bb0(%arg1 : f32):
linalg.yield %arg1 : f32
} : tensor<1x1xf32> -> tensor<?x?xf32>
return %0 : tensor<?x?xf32>
}
// CHECK-DAG: #[[$MAP0:.*]] = affine_map<(d0, d1) -> ()>
// CHECK-DAG: #[[$MAP1:.*]] = affine_map<(d0, d1) -> (d0, d1)>
// CHECK-LABEL: func @broadcast_scalar
// CHECK-SAME: %[[ARG0:.*]]: tensor<1x1xf32>
// CHECK: %[[A:.*]] = linalg.tensor_reshape %[[ARG0]] []
// CHECK-SAME: tensor<1x1xf32> into tensor<f32>
// CHECK: linalg.generic
// CHECK-SAME: indexing_maps = [#[[$MAP0]], #[[$MAP1]]]
// CHECK-SAME: iterator_types = ["parallel", "parallel"]
// CHECK-SAME: %[[A]]