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/llvm-project-15.0.7/mlir/test/Dialect/Tosa/
H A Dtosa-infer-shapes.mlir6 // CHECK: tensor.cast [[LOG]] : tensor<4xf32> to tensor<*xf32>
1046 // CHECK: (tensor<i1>, tensor<f32>, tensor<f32>) -> tensor<f32>
1053 }) : (tensor<i1>, tensor<*xf32>, tensor<*xf32>) -> (tensor<*xf32>)
1061 // CHECK: (tensor<i1>, tensor<2xf32>, tensor<3xf32>) -> tensor<?xf32>
1068 }) : (tensor<i1>, tensor<2xf32>, tensor<3xf32>) -> (tensor<*xf32>)
1076 // CHECK: (tensor<i1>, tensor<f32>, tensor<3xf32>) -> tensor<*xf32>
1083 }) : (tensor<i1>, tensor<f32>, tensor<3xf32>) -> (tensor<*xf32>)
1091 // CHECK: (tensor<i1>, tensor<f32>, tensor<f32>) -> tensor<f32>
1100 }) : (tensor<i1>, tensor<f32>, tensor<f32>) -> (tensor<*xf32>)
1184 // CHECK: (tensor<i32>, tensor<1xi32>) -> (tensor<i32>, tensor<?xi32>)
[all …]
H A Dops.mlir42 func.func @test_conv2d(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<8x1x1x4xf32>, %arg2: tensor<8xf32>…
402 …%1 = "tosa.pad"(%arg0, %arg1, %0) : (tensor<13x21x3xf32>, tensor<3x2xi32>, tensor<f32>) -> tensor<…
507 func.func @test_cond_if(%arg0: tensor<f32>, %arg1: tensor<f32>, %arg2: tensor<i1>) -> tensor<f32> {
510 %1 = "tosa.add"(%arg3, %arg4) : (tensor<f32>, tensor<f32>) -> tensor<f32>
514 %1 = "tosa.sub"(%arg3, %arg4) : (tensor<f32>, tensor<f32>) -> tensor<f32>
516 }) : (tensor<i1>, tensor<f32>, tensor<f32>) -> tensor<f32>
525 ^bb0(%arg2: tensor<i32>, %arg3: tensor<i32>, %arg4: tensor<10xi32>):
530 ^bb0(%arg2: tensor<i32>, %arg3: tensor<i32>, %arg4: tensor<10xi32>):
532 %3 = "tosa.add"(%arg3, %2) : (tensor<i32>, tensor<i32>) -> tensor<i32>
535 %6 = "tosa.add"(%arg2, %2) : (tensor<i32>, tensor<i32>) -> tensor<i32>
[all …]
H A Dcanonicalize.mlir4 func.func @argmax_nofold(%arg0: tensor<?x1xf32>) -> tensor<?x1xf32> {
14 %1 = "tosa.add"(%arg0, %zeros) : (tensor<2x3xi32>, tensor<4x2x3xi32>) -> tensor<4x2x3xi32>
24 %1 = "tosa.add"(%arg0, %zeros) : (tensor<2x3xi32>, tensor<2x3xi32>) -> tensor<2x3xi32>
148 %1 = "tosa.pad"(%arg0, %0) : (tensor<?x?xf32>, tensor<2x2xi32>) -> tensor<?x?xf32>
157 %1 = "tosa.pad"(%arg0, %arg1) : (tensor<?x?xi32>, tensor<2x2xi32>) -> tensor<?x?xi32>
166 %1 = "tosa.pad"(%arg0, %arg1) : (tensor<?x?xf32>, tensor<2x2xi32>) -> tensor<?x?xf32>
207 …%0 = "tosa.select"(%arg0, %arg1, %arg1) : (tensor<2x3xi1>, tensor<2x3xi32>, tensor<2x3xi32>) -> te…
216 …%0 = "tosa.select"(%c1, %arg0, %arg1) : (tensor<2x3xi1>, tensor<2x3xi32>, tensor<2x3xi32>) -> tens…
225 …%0 = "tosa.select"(%c0, %arg0, %arg1) : (tensor<2x3xi1>, tensor<2x3xi32>, tensor<2x3xi32>) -> tens…
232 func.func @select_not_pred(%arg0: tensor<2x3xi1>, %arg1: tensor<2x3xi32>, %arg2: tensor<2x3xi32>) -…
[all …]
H A Dinlining.mlir10 func.func @inlined_if_fn(%arg0: tensor<f32>, %arg1: tensor<f32>, %arg2: tensor<i1>) -> tensor<f32> {
13 %1 = call @add(%arg3, %arg4) : (tensor<f32>, tensor<f32>) -> tensor<f32>
19 }) : (tensor<i1>, tensor<f32>, tensor<f32>) -> tensor<f32>
34 …unc.func @inlined_while_fn(%arg0: tensor<i32>, %arg1: tensor<i32>, %arg2: tensor<i32>, %arg3: tens…
38 ^bb0(%arg4: tensor<i32>, %arg5: tensor<i32>, %arg6: tensor<i32>, %arg7: tensor<10xi32>):
39 …hile_cond_40(%arg4, %arg5, %arg6, %arg7) : (tensor<i32>, tensor<i32>, tensor<i32>, tensor<10xi32>)…
42 ^bb0(%arg4: tensor<i32>, %arg5: tensor<i32>, %arg6: tensor<i32>, %arg7: tensor<10xi32>):
43 …%arg5, %arg6, %arg7) : (tensor<i32>, tensor<i32>, tensor<i32>, tensor<10xi32>) -> (tensor<i32>, te…
45 …}) : (tensor<i32>, tensor<i32>, tensor<i32>, tensor<10xi32>) -> (tensor<i32>, tensor<i32>, tensor<…
48 …ody_50(%arg0: tensor<i32>, %arg1: tensor<i32>, %arg2: tensor<i32>, %arg3: tensor<10xi32>) -> (tens…
[all …]
H A Dbroadcast.mlir5 func.func @test_broadcast0(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>) -> tensor<1xf32> {
7 %0 = "tosa.add"(%arg0, %arg1) : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
13 func.func @test_broadcast1(%arg0: tensor<1xf32>, %arg1: tensor<2x1xf32>) -> tensor<2x1xf32> {
16 %0 = "tosa.add"(%arg0, %arg1) : (tensor<1xf32>, tensor<2x1xf32>) -> tensor<2x1xf32>
22 func.func @test_broadcast2(%arg0: tensor<2x1xf32>, %arg1: tensor<1xf32>) -> tensor<2x1xf32> {
25 %0 = "tosa.add"(%arg0, %arg1) : (tensor<2x1xf32>, tensor<1xf32>) -> tensor<2x1xf32>
31 func.func @test_broadcast3(%arg0: tensor<2x1x1x1xf32>, %arg1: tensor<1xf32>) -> tensor<2x1x1x1xf32>…
34 %0 = "tosa.add"(%arg0, %arg1) : (tensor<2x1x1x1xf32>, tensor<1xf32>) -> tensor<2x1x1x1xf32>
43 %0 = "tosa.add"(%arg0, %arg1) : (tensor<1x1x1x2xf32>, tensor<1xf32>) -> tensor<1x1x1x2xf32>
52 %0 = "tosa.add"(%arg0, %arg1) : (tensor<1x1x2x1xf32>, tensor<1xf32>) -> tensor<1x1x2x1xf32>
[all …]
/llvm-project-15.0.7/mlir/test/IR/
H A Drepro_b120295301.mlir3 func.func @testType(tensor<1x224x224x3xf32>) -> tensor<96xf32> {
5 %1 = "arith.constant"() {value = dense<0.1> : tensor<1xf32>} : () -> (tensor<1xf32>)
6 %2 = "arith.constant"() {value = dense<0.1> : tensor<2xf32>} : () -> (tensor<2xf32>)
7 %3 = "arith.constant"() {value = dense<0.1> : tensor<3xf32>} : () -> (tensor<3xf32>)
8 %4 = "arith.constant"() {value = dense<0.1> : tensor<4xf32>} : () -> (tensor<4xf32>)
9 %5 = "arith.constant"() {value = dense<0.1> : tensor<5xf32>} : () -> (tensor<5xf32>)
10 %6 = "arith.constant"() {value = dense<0.1> : tensor<6xf32>} : () -> (tensor<6xf32>)
11 %7 = "arith.constant"() {value = dense<0.1> : tensor<7xf32>} : () -> (tensor<7xf32>)
12 %8 = "arith.constant"() {value = dense<0.1> : tensor<8xf32>} : () -> (tensor<8xf32>)
13 %9 = "arith.constant"() {value = dense<0.1> : tensor<9xf32>} : () -> (tensor<9xf32>)
[all …]
H A Dop-stats-json.mlir3 func.func @main(tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> {
4 ^bb0(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>):
11 %10 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
12 %11 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
13 %12 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
14 %13 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
15 %14 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
16 %15 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
17 %16 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
18 %17 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
[all …]
H A Dop-stats.mlir3 func.func @main(tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> {
4 ^bb0(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>):
11 %10 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
12 %11 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
13 %12 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
14 %13 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
15 %14 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
16 %15 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
17 %16 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
18 %17 = "xla.add"(%0, %arg1) : (tensor<4xf32>,tensor<4xf32>)-> tensor<4xf32>
[all …]
/llvm-project-15.0.7/mlir/test/Dialect/Quant/
H A Dquant_region.mlir4 func.func @source(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>, %arg2: tensor<4xf32>) -> (tensor<4xf3…
6 ^bb0(%10: tensor<4xf32>, %11: tensor<4xf32>, %12: tensor<4xf32>):
11 : (tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>)
24 : (tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>)
37 : (tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>)
52 : (tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>)
67 : (tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>)
82 : (tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>)
97 : (tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>)
112 : (tensor<4xf32>, tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>)
[all …]
H A Dconvert-fakequant.mlir14 } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
29 } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
44 } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
59 } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
74 } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
89 } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
104 } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
119 } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
134 } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
149 } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
[all …]
H A Dconvert-const.mlir19 return %2 : tensor<4xf32>
31 return %2 : tensor<4xf32>
43 return %2 : tensor<4xf32>
54 return %2 : tensor<4xf32>
65 return %2 : tensor<7xf32>
103 return %2 : tensor<7xf32>
115 return %2 : tensor<7xf32>
145 func.func @zero_tensors_to_zero_points() -> (tensor<7xf32>, tensor<7xf32>, tensor<7xf32>, tensor<7x…
171 return %2, %4, %6, %8 : tensor<7xf32>, tensor<7xf32>, tensor<7xf32>, tensor<7xf32>
177 func.func @per_axis_dense_quantization() -> (tensor<2x3xf32>, tensor<2x3xf32>) {
[all …]
/llvm-project-15.0.7/mlir/test/Dialect/
H A Dtraits.mlir6 func.func @broadcast_scalar_scalar_scalar(tensor<i32>, tensor<i32>) -> tensor<i32> {
7 ^bb0(%arg0: tensor<i32>, %arg1: tensor<i32>):
8 %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<i32>, tensor<i32>) -> tensor<i32>
14 func.func @broadcast_tensor_scalar_tensor(tensor<4xi32>, tensor<i32>) -> tensor<4xi32> {
15 ^bb0(%arg0: tensor<4xi32>, %arg1: tensor<i32>):
16 %0 = "test.broadcastable"(%arg0, %arg1) : (tensor<4xi32>, tensor<i32>) -> tensor<4xi32>
24 ^bb0(%arg0: tensor<4x3x2xi32>, %arg1: tensor<3x1xi32>):
60 ^bb0(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>):
99 ^bb0(%arg0: tensor<2xi32>, %arg1: tensor<2xi32>):
133 …= "test.broadcastable"(%arg0, %arg0, %arg1) : (tensor<3x2xi32>, tensor<3x2xi32>, tensor<*xi32>) ->…
[all …]
/llvm-project-15.0.7/mlir/test/Dialect/Tensor/
H A Dops.mlir4 func.func @cast(%arg0: tensor<*xf32>, %arg1 : tensor<4x4xf32>, %arg2: tensor<?x?xf32>) {
5 // CHECK: tensor.cast %arg0 : tensor<*xf32> to tensor<?x?xf32>
6 %0 = tensor.cast %arg0 : tensor<*xf32> to tensor<?x?xf32>
7 // CHECK: tensor.cast %arg1 : tensor<4x4xf32> to tensor<*xf32>
8 %1 = tensor.cast %arg1 : tensor<4x4xf32> to tensor<*xf32>
9 // CHECK: tensor.cast %arg2 : tensor<?x?xf32> to tensor<4x?xf32>
10 %2 = tensor.cast %arg2 : tensor<?x?xf32> to tensor<4x?xf32>
11 // CHECK: tensor.cast %2 : tensor<4x?xf32> to tensor<?x?xf32>
12 %3 = tensor.cast %2 : tensor<4x?xf32> to tensor<?x?xf32>
79 : (tensor<*xf32>, tensor<1xi32>) -> tensor<?xf32>
[all …]
H A Dcanonicalize.mlir7 %0 = tensor.cast %arg0 : tensor<*xi32> to tensor<*xi32>
9 %2 = tensor.cast %0 : tensor<*xi32> to tensor<2xi32>
11 %4 = tensor.cast %2 : tensor<2xi32> to tensor<2xi32>
22 %0 = tensor.cast %input : tensor<*xi32> to tensor<4x?xi32>
23 %1 = tensor.cast %0 : tensor<4x?xi32> to tensor<4x8xi32>
33 %0 = tensor.cast %input : tensor<4xi32> to tensor<?xi32>
34 %1 = tensor.cast %0 : tensor<?xi32> to tensor<4xi32>
123 %casted = tensor.cast %tensor : tensor<*xf32> to tensor<?xf32>
258 %size = tensor.rank %tensor : tensor<*xf32>
275 %size = tensor.rank %tensor : tensor<*xf32>
[all …]
H A Dinvalid.mlir5 tensor.dim %arg, %c2 : tensor<1x?xf32> // expected-error {{'tensor.dim' op index is out of range}}
13 %0 = tensor.cast %arg0 : tensor<1xf32> to tensor<2xf32>
21 %0 = tensor.extract %arg0[] : tensor<?xf32>
38 %0 = tensor.from_elements %c0 : tensor<*xi32>
120 tensor.reshape %buf(%shape) : (tensor<*xf32>, tensor<1xi32>) -> tensor<?xi32>
128 tensor.reshape %buf(%shape) : (tensor<*xf32>, tensor<?xi32>) -> tensor<?xf32>
137 : (tensor<*xf32>, tensor<1xi32>) -> tensor<?x?xf32>
146 : (tensor<1xf32>, tensor<1xi32>) -> tensor<10xf32>
153 %0 = tensor.extract_slice %t[0][4][1] : tensor<?xf32> to tensor<?x?xf32>
162 %0 = tensor.extract_slice %t[0][4][1] : tensor<?xf32> to tensor<4xi8>
[all …]
/llvm-project-15.0.7/mlir/test/Dialect/Linalg/
H A Dsubtensor-of-padtensor.mlir12 } : tensor<4x5xf32> to tensor<11x13xf32>
13 %1 = tensor.extract_slice %0[1, 2] [2, 1] [1, 1] : tensor<11x13xf32> to tensor<2x1xf32>
31 } : tensor<4x5xf32> to tensor<11x13xf32>
50 } : tensor<4x5xf32> to tensor<14x20xf32>
69 } : tensor<4x5xf32> to tensor<14x20xf32>
88 } : tensor<4x5xf32> to tensor<11x13xf32>
107 } : tensor<4x5xf32> to tensor<14x20xf32>
125 } : tensor<4x5xf32> to tensor<13x16xf32>
150 } : tensor<?x5xf32> to tensor<?x13xf32>
195 } : tensor<?x?xf32> to tensor<?x?xf32>
[all …]
H A Dcanonicalize.mlir52 func.func @tensor.cast(%a : tensor<3x4xf32>, %b : tensor<4x?xf32>, %c : tensor<3x?xf32>)
55 %ta = tensor.cast %a : tensor<3x4xf32> to tensor<?x?xf32>
56 %tb = tensor.cast %b : tensor<4x?xf32> to tensor<?x?xf32>
57 %tc = tensor.cast %c : tensor<3x?xf32> to tensor<?x?xf32>
64 %1 = tensor.cast %0 : tensor<?x?xf32> to tensor<3x?xf32>
267 %1 = tensor.cast %0 : tensor<?x12xf32> to tensor<1x12xf32>
565 %5 = tensor.cast %4 : tensor<?x?x?xf32> to tensor<2x3x4xf32>
596 %6 = tensor.cast %5 : tensor<?x?x?xf32> to tensor<2x3x4xf32>
617 %4 = tensor.cast %3 : tensor<?x?x?xf32> to tensor<2x3x4xf32>
833 %1 = tensor.cast %0 : tensor<?x?xf32> to tensor<4x8xf32>
[all …]
H A Done-shot-bufferize-analysis-2fill-extract-matmul-all-perms.mlir25 %3 = tensor.extract_slice %1[0, 0] [256, 16] [1, 1] : tensor<256x256xf32> to tensor<256x16xf32>
27 %4 = tensor.extract_slice %2[0, 0] [16, 256] [1, 1] : tensor<256x256xf32> to tensor<16x256xf32>
29 …%5 = linalg.matmul ins(%3, %4 : tensor<256x16xf32>, tensor<16x256xf32>) outs(%arg2 : tensor<256x25…
52 %4 = tensor.extract_slice %2[0, 0] [16, 256] [1, 1] : tensor<256x256xf32> to tensor<16x256xf32>
56 …%5 = linalg.matmul ins(%3, %4 : tensor<256x16xf32>, tensor<16x256xf32>) outs(%arg2 : tensor<256x25…
83 …%5 = linalg.matmul ins(%3, %4 : tensor<256x16xf32>, tensor<16x256xf32>) outs(%arg2 : tensor<256x25…
110 …%5 = linalg.matmul ins(%3, %2 : tensor<256x16xf32>, tensor<16x256xf32>) outs(%arg2 : tensor<256x25…
137 …%5 = linalg.matmul ins(%3, %2 : tensor<256x16xf32>, tensor<16x256xf32>) outs(%arg2 : tensor<256x25…
164 …%5 = linalg.matmul ins(%3, %2 : tensor<256x16xf32>, tensor<16x256xf32>) outs(%arg2 : tensor<256x25…
191 …%5 = linalg.matmul ins(%3, %4 : tensor<256x16xf32>, tensor<16x256xf32>) outs(%arg2 : tensor<256x25…
[all …]
H A Dbubble-up-extract-slice-op.mlir9 } ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?xf32>)
16 : tensor<?x?xf32> to tensor<?x?xf32>
30 func.func @static(%arg0: tensor<16x8xf32>, %arg1: tensor<8xf32>) -> tensor<4x2xf32> {
36 } ins(%arg0, %arg1 : tensor<16x8xf32>, tensor<8xf32>)
43 : tensor<16x8xf32> to tensor<4x2xf32>
63 } ins(%arg0, %arg1 : tensor<?x8xf32>, tensor<8xf32>)
70 : tensor<?x8xf32> to tensor<?x2xf32>
84 func.func @dynamic_to_static(%arg0: tensor<?x?xf32>, %arg1: tensor<?xf32>) -> tensor<4x2xf32> {
97 : tensor<?x?xf32> to tensor<4x2xf32>
115 …%0 = linalg.matmul ins(%lhs, %rhs : tensor<4x4xf32>, tensor<4x4xf32>) outs(%dst : tensor<4x4xf32>)…
[all …]
H A Dgeneralize-named-polymorphic-ops.mlir4 …generalize_matmul_tensor_f16f64f32(%A : tensor<16x8xf16>, %B: tensor<8x32xf64>, %C: tensor<16x32xf…
23 …generalize_matmul_tensor_i16i64i32(%A : tensor<16x8xi16>, %B: tensor<8x32xi64>, %C: tensor<16x32xi…
55 …generalize_matmul_tensor_i16i64f32(%A : tensor<16x8xi16>, %B: tensor<8x32xi64>, %C: tensor<16x32xf…
122 …ins(%input, %shape : tensor<1x4x16x1xf32>, tensor<2x2xf32>) outs(%output : tensor<1x2x4x1xf32>) ->…
136 …ins(%input, %shape : tensor<1x4x16x1xi32>, tensor<2x2xi32>) outs(%output : tensor<1x2x4x1xi32>) ->…
148 …ins(%input, %shape : tensor<1x4x16x1xi32>, tensor<2x2xi32>) outs(%output : tensor<1x2x4x1xi32>) ->…
160 …ins(%input, %shape : tensor<1x4x16x1xf32>, tensor<2x2xf32>) outs(%output : tensor<1x2x4x1xf32>) ->…
174 …ins(%input, %shape : tensor<1x4x16x1xi32>, tensor<2x2xi32>) outs(%output : tensor<1x2x4x1xi32>) ->…
186 …ins(%input, %shape : tensor<1x4x16x1xi32>, tensor<2x2xi32>) outs(%output : tensor<1x2x4x1xi32>) ->…
198 …ins(%input, %shape : tensor<1x4x16x1xf32>, tensor<2x2xf32>) outs(%output : tensor<1x2x4x1xf32>) ->…
[all …]
H A Dnamed-ops.mlir4 func.func @depthwise_conv_1d_nwc_wcm(%input: tensor<1x12x8xf32>, %filter: tensor<3x8x8xf32>) -> ten…
10 ins(%input, %filter : tensor<1x12x8xf32>, tensor<3x8x8xf32>)
11 outs(%fill : tensor<1x10x8x8xf32>) -> tensor<1x10x8x8xf32>
18 func.func @depthwise_conv_1d_nwc_wc(%input: tensor<1x12x8xf32>, %filter: tensor<3x8xf32>) -> tensor…
24 ins(%input, %filter : tensor<1x12x8xf32>, tensor<3x8xf32>)
25 outs(%fill : tensor<1x10x8xf32>) -> tensor<1x10x8xf32>
215 func.func @conv_1d_nwc_wcf(%input: tensor<?x?x?xf32>, %filter: tensor<?x?x?xf32>, %init: tensor<?x?…
247 …func @conv_2d_nhwc_hwcf(%input: tensor<?x?x?x?xf32>, %filter: tensor<?x?x?x?xf32>, %init: tensor<?…
279 …func @conv_2d_nhwc_fhwc(%input: tensor<?x?x?x?xf32>, %filter: tensor<?x?x?x?xf32>, %init: tensor<?…
738 …%arg0 : tensor<?x?x?x?xf32>, %arg2 : tensor<?x?x?x?xf32>, %arg1 : tensor<?x?x?x?xf32>) -> tensor<?…
[all …]
H A Dtile-scalarize-dynamic-dims.mlir8 // CHECK: tensor.dim %[[ARG0]], %[[C0]] : tensor<?x?xf32>
16 …inalg.matmul ins(%[[S1]], %[[S2]] : tensor<1x1xf32>, tensor<1x2000xf32>) outs(%[[S3]] : tensor<1x2…
21 %d0 = tensor.dim %arg0, %c0 : tensor<?x?xf32>
24 ins(%arg0, %arg1: tensor<?x?xf32>, tensor<?x2000xf32>)
25 outs(%out: tensor<?x2000xf32>) -> tensor<?x2000xf32>
34 …ECK: linalg.matmul ins({{.*}} : tensor<32x259xf32>, tensor<259x258xf32>) outs({{.*}} : tensor<32…
35 …HECK: linalg.matmul ins({{.*}} : tensor<1x259xf32>, tensor<259x258xf32>) outs({{.*}} : tensor<1x…
40 … @tiled_and_peeled_matmul(%arg0: tensor<257x259xf32>, %arg1: tensor<259x258xf32>, %arg2: tensor<25…
53 … %10 = tensor.extract_slice %3[%arg5, 0] [32, 259] [1, 1] : tensor<?x259xf32> to tensor<32x259xf32>
62 … %11 = tensor.extract_slice %3[%5, 0] [%10, 259] [1, 1] : tensor<?x259xf32> to tensor<?x259xf32>
[all …]
/llvm-project-15.0.7/mlir/test/Dialect/SparseTensor/
H A Drewriting.mlir12 // CHECK-SAME: %[[A:.*]]: tensor<12xf64>) -> tensor<3x4xf64> {
13 // CHECK: %[[E:.*]] = tensor.expand_shape %[[A]] {{.*}} : tensor<12xf64> into tensor<3x4xf6…
17 %0 = tensor.expand_shape %arg0 [[0, 1]] : tensor<12xf64> into tensor<3x4xf64>
24 // CHECK: %[[E:.*]] = tensor.expand_shape %[[C]] {{.*}} : tensor<12xf64> into tensor<3x4xf6…
28 %0 = tensor.expand_shape %arg0 [[0, 1]] : tensor<12xf64, #SparseVector> into tensor<3x4xf64>
34 // CHECK: %[[E:.*]] = tensor.expand_shape %[[A]] {{.*}} : tensor<12xf64> into tensor<3x4xf6…
39 %0 = tensor.expand_shape %arg0 [[0, 1]] : tensor<12xf64> into tensor<3x4xf64, #SparseMatrix>
58 // CHECK: %[[R:.*]] = tensor.collapse_shape %[[A]] {{.*}} : tensor<3x4xf64> into tensor<12x…
62 %0 = tensor.collapse_shape %arg0 [[0, 1]] : tensor<3x4xf64> into tensor<12xf64>
73 %0 = tensor.collapse_shape %arg0 [[0, 1]] : tensor<3x4xf64, #SparseMatrix> into tensor<12xf64>
[all …]
/llvm-project-15.0.7/mlir/test/Integration/Dialect/SparseTensor/CPU/
H A Dsparse_conversion_sparse2dense.mlir57 %0 = tensor.cast %arg0 : tensor<?x3x4xf64> to tensor<2x3x4xf64>
62 %0 = tensor.cast %arg0 : tensor<2x?x4xf64> to tensor<2x3x4xf64>
67 %0 = tensor.cast %arg0 : tensor<2x3x?xf64> to tensor<2x3x4xf64>
72 %0 = tensor.cast %arg0 : tensor<2x?x?xf64> to tensor<2x3x4xf64>
77 %0 = tensor.cast %arg0 : tensor<?x3x?xf64> to tensor<2x3x4xf64>
82 %0 = tensor.cast %arg0 : tensor<?x?x4xf64> to tensor<2x3x4xf64>
87 %0 = tensor.cast %arg0 : tensor<?x?x?xf64> to tensor<2x3x4xf64>
106 ]> : tensor<2x3x4xf64>
111 %s2341 = sparse_tensor.convert %src : tensor<2x3x4xf64> to tensor<2x3x4xf64, #Tensor1>
112 %s2342 = sparse_tensor.convert %src : tensor<2x3x4xf64> to tensor<2x3x4xf64, #Tensor2>
[all …]
/llvm-project-15.0.7/mlir/test/Integration/Dialect/Linalg/CPU/
H A Dtest-one-shot-bufferize.mlir23 %10 = tensor.cast %9 : tensor<2xf32> to tensor<?xf32>
32 // %B = tensor.cast %3 : tensor<?x2xf32> to tensor<*xf32>
40 %10 = tensor.cast %9 : tensor<2xf32> to tensor<?xf32>
49 // %A = tensor.cast %6 : tensor<?x2xf32> to tensor<*xf32>
52 // %C = tensor.cast %0 : tensor<f32> to tensor<*xf32>
57 %9 = tensor.cast %8 : tensor<2xf32> to tensor<?xf32>
59 %11 = tensor.cast %10 : tensor<2xf32> to tensor<?xf32>
66 // %AA = tensor.cast %13 : tensor<2xf32> to tensor<*xf32>
70 // %CC = tensor.cast %16 : tensor<f32> to tensor<*xf32>
91 (tensor<64xf32>, tensor<64xf32>, tensor<f32>) -> tensor<f32>
[all …]

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