Lines Matching full:tensor
7 func.func @armax_fold_dim_size_1(%arg0: tensor<2x1x3xf32>) -> tensor<2x3xi32> {
8 // CHECK: "tosa.const"() <{value = dense<0> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
9 %0 = tosa.argmax %arg0 {axis = 1 : i32}: (tensor<2x1x3xf32>) -> tensor<2x3xi32>
10 return %0 : tensor<2x3xi32>
14 func.func @argmax_dynamic_shape_no_fold_dim_size_1(%arg0: tensor<?x1x3xf32>) -> tensor<?x3xi32> {
16 %0 = tosa.argmax %arg0 {axis = 1 : i32}: (tensor<?x1x3xf32>) -> tensor<?x3xi32>
17 return %0 : tensor<?x3xi32>
21 func.func @transpose_fold(%arg0: tensor<3x4xf32>) -> tensor<3x4xf32> {
23 %0 = arith.constant dense<[0, 1]> : tensor<2xi32>
24 %1 = tosa.transpose %arg0, %0 { perms = [1, 0] }: (tensor<3x4xf32>, tensor<2xi32>) -> tensor<3x4xf32>
25 return %1 : tensor<3x4xf32>
29 func.func @transpose_nofold(%arg0: tensor<3x3xf32>) -> tensor<3x3xf32> {
31 %0 = arith.constant dense<[1, 0]> : tensor<2xi32>
32 %1 = tosa.transpose %arg0, %0 { perms = [1, 0] }: (tensor<3x3xf32>, tensor<2xi32>) -> tensor<3x3xf32>
33 return %1 : tensor<3x3xf32>
37 func.func @transpose_nofold_shape(%arg0: tensor<3x4xf32>) -> tensor<?x?xf32> {
39 %0 = arith.constant dense<[1, 0]> : tensor<2xi32>
40 %1 = tosa.transpose %arg0, %0 { perms = [1, 0] }: (tensor<3x4xf32>, tensor<2xi32>) -> tensor<?x?xf32>
41 return %1 : tensor<?x?xf32>
45 func.func @transpose_fold_splat() -> tensor<3x2xf32> {
46 %input = "tosa.const"() {value = dense<4.0> : tensor<2x3xf32>} : () -> tensor<2x3xf32>
47 %perms = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
49 // CHECK-SAME{LITERAL}: value = dense<4.000000e+00> : tensor<3x2xf32>
50 %1 = tosa.transpose %input, %perms : (tensor<2x3xf32>, tensor<2xi32>) -> tensor<3x2xf32>
52 return %1 : tensor<3x2xf32>
56 func.func @transpose_fold_2d_float() -> tensor<3x2xf32> {
57 %input = "tosa.const"() {value = dense<[[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]> : tensor<2x3xf32>} : () -> tensor<2x3xf32>
58 %perms = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
60 // CHECK-SAME{LITERAL}: value = dense<[[0.000000e+00, 3.000000e+00], [1.000000e+00, 4.000000e+00], [2.000000e+00, 5.000000e+00]]> : tensor<3x2xf32>
61 %1 = tosa.transpose %input, %perms : (tensor<2x3xf32>, tensor<2xi32>) -> tensor<3x2xf32>
63 return %1 : tensor<3x2xf32>
67 func.func @transpose_fold_2d_bool() -> tensor<3x2xi1> {
68 %input = "tosa.const"() {value = dense<[[true, false, false], [false, false, true]]> : tensor<2x3xi1>} : () -> tensor<2x3xi1>
69 %perms = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
71 // CHECK-SAME{LITERAL}: value = dense<[[true, false], [false, false], [false, true]]> : tensor<3x2xi1>
72 %1 = tosa.transpose %input, %perms : (tensor<2x3xi1>, tensor<2xi32>) -> tensor<3x2xi1>
74 return %1 : tensor<3x2xi1>
78 func.func @transpose_fold_4d_int() -> tensor<3x1x4x2xi32> {
82 ]]> : tensor<1x2x3x4xi32>} : () -> tensor<1x2x3x4xi32>
83 %perms = "tosa.const"() {value = dense<[2, 0, 3, 1]> : tensor<4xi32>} : () -> tensor<4xi32>
90 %1 = tosa.transpose %input, %perms : (tensor<1x2x3x4xi32>, tensor<4xi32>) -> tensor<3x1x4x2xi32>
92 return %1 : tensor<3x1x4x2xi32>
96 func.func @transpose_nofold_non_cst_input(%input: tensor<2x3xf32>) -> tensor<3x2xf32> {
97 %perms = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
99 %1 = tosa.transpose %input, %perms : (tensor<2x3xf32>, tensor<2xi32>) -> tensor<3x2xf32>
100 return %1 : tensor<3x2xf32>
104 func.func @transpose_nofold_non_cst_perms(%perms: tensor<2xi32>) -> tensor<3x2xf32> {
105 %input = "tosa.const"() {value = dense<[[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]> : tensor<2x3xf32>} : () -> tensor<2x3xf32>
107 %1 = tosa.transpose %input, %perms : (tensor<2x3xf32>, tensor<2xi32>) -> tensor<3x2xf32>
108 return %1 : tensor<3x2xf32>
112 func.func @transpose_nofold_multi_users() -> (tensor<3x2xf32>, tensor<2x3xf32>) {
113 %input = "tosa.const"() {value = dense<[[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]> : tensor<2x3xf32>} : () -> tensor<2x3xf32>
114 %perms = "tosa.const"() {value = dense<[1, 0]> : tensor<2xi32>} : () -> tensor<2xi32>
116 %1 = tosa.transpose %input, %perms : (tensor<2x3xf32>, tensor<2xi32>) -> tensor<3x2xf32>
117 return %1, %input : tensor<3x2xf32>, tensor<2x3xf32>
121 func.func @transpose_nofold_dense_resource() -> tensor<2x2xf32> {
122 %0 = "tosa.const"() <{value = dense_resource<resource> : tensor<2x2xf32>}> : () -> tensor<2x2xf32>
123 %1 = "tosa.const"() <{value = dense<[1, 0]> : tensor<2xi32>}> : () -> tensor<2xi32>
126 %2 = tosa.transpose %0, %1 : (tensor<2x2xf32>, tensor<2xi32>) -> tensor<2x2xf32>
127 return %2 : tensor<2x2xf32>
140 func.func @fold_add_zero_rhs_f32(%arg0: tensor<f32>) -> tensor<f32> {
141 %zero = "tosa.const"() {value = dense<0.0> : tensor<f32>} : () -> tensor<f32>
142 %add = tosa.add %arg0, %zero : (tensor<f32>, tensor<f32>) -> tensor<f32>
144 return %add : tensor<f32>
150 func.func @fold_add_zero_lhs_f32(%arg0: tensor<f32>) -> tensor<f32> {
151 %zero = "tosa.const"() {value = dense<0.0> : tensor<f32>} : () -> tensor<f32>
152 %add = tosa.add %zero, %arg0 : (tensor<f32>, tensor<f32>) -> tensor<f32>
154 return %add : tensor<f32>
160 func.func @fold_add_zero_rhs_i32(%arg0: tensor<i32>) -> tensor<i32> {
161 %zero = "tosa.const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>
162 %add = tosa.add %arg0, %zero : (tensor<i32>, tensor<i32>) -> tensor<i32>
164 return %add : tensor<i32>
170 func.func @fold_add_zero_lhs_i32(%arg0: tensor<i32>) -> tensor<i32> {
171 %zero = "tosa.const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>
172 %add = tosa.add %zero, %arg0 : (tensor<i32>, tensor<i32>) -> tensor<i32>
174 return %add : tensor<i32>
180 func.func @fold_add_splat_i32() -> tensor<10xi32> {
181 %one = "tosa.const"() {value = dense<1> : tensor<10xi32>} : () -> tensor<10xi32>
182 %two = "tosa.const"() {value = dense<2> : tensor<10xi32>} : () -> tensor<10xi32>
183 %add = tosa.add %one, %two : (tensor<10xi32>, tensor<10xi32>) -> tensor<10xi32>
184 // CHECK: %[[THREE:.+]] = "tosa.const"() <{value = dense<3> : tensor<10xi32>}
186 return %add : tensor<10xi32>
192 func.func @fold_add_splat_f32() -> tensor<10xf32> {
193 %one = "tosa.const"() {value = dense<1.0> : tensor<10xf32>} : () -> tensor<10xf32>
194 %two = "tosa.const"() {value = dense<2.0> : tensor<10xf32>} : () -> tensor<10xf32>
195 %add = tosa.add %one, %two : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xf32>
198 return %add : tensor<10xf32>
204 func.func @fold_div_zero_lhs_i32(%arg0: tensor<i32>) -> tensor<i32> {
205 %zero = "tosa.const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>
207 %div = tosa.int_div %zero, %arg0 : (tensor<i32>, tensor<i32>) -> tensor<i32>
209 return %div : tensor<i32>
215 func.func @fold_div_one_rhs_i32(%arg0: tensor<i32>) -> tensor<i32> {
216 %one = "tosa.const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
217 %div = tosa.int_div %arg0, %one : (tensor<i32>, tensor<i32>) -> tensor<i32>
219 return %div : tensor<i32>
225 func.func @fold_div_splat_i32() -> tensor<i32> {
226 %lhs = "tosa.const"() {value = dense<10> : tensor<i32>} : () -> tensor<i32>
227 %rhs = "tosa.const"() {value = dense<-3> : tensor<i32>} : () -> tensor<i32>
229 %div = tosa.int_div %lhs, %rhs : (tensor<i32>, tensor<i32>) -> tensor<i32>
231 return %div : tensor<i32>
238 func.func @fold_mul_zero_rhs_f32(%arg0: tensor<f32>) -> tensor<f32> {
239 %zero = "tosa.const"() {value = dense<0.0> : tensor<f32>} : () -> tensor<f32>
241 %mul = tosa.mul %arg0, %zero : (tensor<f32>, tensor<f32>) -> tensor<f32>
243 return %mul : tensor<f32>
249 func.func @fold_mul_zero_lhs_f32(%arg0: tensor<f32>) -> tensor<f32> {
250 %zero = "tosa.const"() {value = dense<0.0> : tensor<f32>} : () -> tensor<f32>
252 %mul = tosa.mul %zero, %arg0 : (tensor<f32>, tensor<f32>) -> tensor<f32>
254 return %mul : tensor<f32>
260 func.func @fold_mul_zero_rhs_i32(%arg0: tensor<i32>) -> tensor<i32> {
261 %zero = "tosa.const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>
262 %shift = "tosa.const"() <{value = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
264 %mul = tosa.mul %arg0, %zero, %shift : (tensor<i32>, tensor<i32>, tensor<1xi8>) -> tensor<i32>
266 return %mul : tensor<i32>
272 func.func @fold_mul_zero_lhs_i32(%arg0: tensor<i32>) -> tensor<i32> {
273 %zero = "tosa.const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>
274 %shift = "tosa.const"() <{value = dense<0> : tensor<1xi8>}> : () -> tensor<1xi8>
276 %mul = tosa.mul %zero, %arg0, %shift : (tensor<i32>, tensor<i32>, tensor<1xi8>) -> tensor<i32>
278 return %mul : tensor<i32>
284 func.func @fold_mul_one_rhs_f32(%arg0: tensor<f32>) -> tensor<f32> {
285 %one = "tosa.const"() {value = dense<1.0> : tensor<f32>} : () -> tensor<f32>
286 %mul = tosa.mul %arg0, %one : (tensor<f32>, tensor<f32>) -> tensor<f32>
288 return %mul : tensor<f32>
294 func.func @fold_mul_one_lhs_f32(%arg0: tensor<f32>) -> tensor<f32> {
295 %one = "tosa.const"() {value = dense<1.0> : tensor<f32>} : () -> tensor<f32>
296 %mul = tosa.mul %one, %arg0 : (tensor<f32>, tensor<f32>) -> tensor<f32>
298 return %mul : tensor<f32>
304 func.func @fold_mul_one_rhs_i32(%arg0: tensor<i32>) -> tensor<i32> {
305 %one = "tosa.const"() {value = dense<64> : tensor<i32>} : () -> tensor<i32>
306 %shift = "tosa.const"() {value = dense<6> : tensor<1xi8>} : () -> tensor<1xi8>
307 %mul = tosa.mul %arg0, %one, %shift : (tensor<i32>, tensor<i32>, tensor<1xi8>) -> tensor<i32>
309 return %mul : tensor<i32>
315 func.func @fold_mul_one_lhs_i32(%arg0: tensor<i32>) -> tensor<i32> {
316 %one = "tosa.const"() {value = dense<64> : tensor<i32>} : () -> tensor<i32>
317 %shift = "tosa.const"() {value = dense<6> : tensor<1xi8>} : () -> tensor<1xi8>
318 %mul = tosa.mul %one, %arg0, %shift : (tensor<i32>, tensor<i32>, tensor<1xi8>) -> tensor<i32>
320 return %mul : tensor<i32>
326 func.func @fold_mul_splat_i8() -> tensor<10xi32> {
327 %one = "tosa.const"() {value = dense<17> : tensor<10xi8>} : () -> tensor<10xi8>
328 %two = "tosa.const"() {value = dense<32> : tensor<10xi8>} : () -> tensor<10xi8>
329 %shift = "tosa.const"() {value = dense<3> : tensor<1xi8>} : () -> tensor<1xi8>
330 %mul = tosa.mul %one, %two, %shift : (tensor<10xi8>, tensor<10xi8>, tensor<1xi8>) -> tensor<10xi32>
331 // CHECK: %[[THREE:.+]] = "tosa.const"() <{value = dense<68> : tensor<10xi32>}
333 return %mul : tensor<10xi32>
339 func.func @fold_mul_splat_f32() -> tensor<10xf32> {
340 %one = "tosa.const"() {value = dense<3.0> : tensor<10xf32>} : () -> tensor<10xf32>
341 %two = "tosa.const"() {value = dense<2.0> : tensor<10xf32>} : () -> tensor<10xf32>
342 %mul = tosa.mul %one, %two : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xf32>
343 // CHECK: %[[THREE:.+]] = "tosa.const"() <{value = dense<6.000000e+00> : tensor<10xf32>}
345 return %mul : tensor<10xf32>
351 func.func @fold_sub_zero_rhs_f32(%arg0: tensor<f32>) -> tensor<f32> {
352 %zero = "tosa.const"() {value = dense<0.0> : tensor<f32>} : () -> tensor<f32>
353 %sub = tosa.sub %arg0, %zero : (tensor<f32>, tensor<f32>) -> tensor<f32>
355 return %sub : tensor<f32>
361 func.func @fold_sub_zero_rhs_i32(%arg0: tensor<i32>) -> tensor<i32> {
362 %zero = "tosa.const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>
363 %sub = tosa.sub %arg0, %zero : (tensor<i32>, tensor<i32>) -> tensor<i32>
365 return %sub : tensor<i32>
371 func.func @fold_sub_splat_i32() -> tensor<10xi32> {
372 %one = "tosa.const"() {value = dense<1> : tensor<10xi32>} : () -> tensor<10xi32>
373 %two = "tosa.const"() {value = dense<2> : tensor<10xi32>} : () -> tensor<10xi32>
374 %sub = tosa.sub %one, %two : (tensor<10xi32>, tensor<10xi32>) -> tensor<10xi32>
375 // CHECK: %[[THREE:.+]] = "tosa.const"() <{value = dense<-1> : tensor<10xi32>}
377 return %sub : tensor<10xi32>
383 func.func @fold_sub_splat_f32() -> tensor<10xf32> {
384 %one = "tosa.const"() {value = dense<1.0> : tensor<10xf32>} : () -> tensor<10xf32>
385 %two = "tosa.const"() {value = dense<2.0> : tensor<10xf32>} : () -> tensor<10xf32>
386 %sub = tosa.sub %one, %two : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xf32>
387 // CHECK: %[[THREE:.+]] = "tosa.const"() <{value = dense<-1.000000e+00> : tensor<10xf32>}
389 return %sub : tensor<10xf32>
395 func.func @fold_greater_splat_f32() -> (tensor<10xi1>, tensor<10xi1>) {
396 %0 = "tosa.const"() {value = dense<4.0> : tensor<10xf32>} : () -> tensor<10xf32>
397 %1 = "tosa.const"() {value = dense<2.0> : tensor<10xf32>} : () -> tensor<10xf32>
398 %2 = "tosa.const"() {value = dense<1.0> : tensor<10xf32>} : () -> tensor<10xf32>
399 %3 = "tosa.const"() {value = dense<2.0> : tensor<10xf32>} : () -> tensor<10xf32>
400 %true = tosa.greater %0, %1 : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xi1>
401 %false = tosa.greater %2, %3 : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xi1>
402 // CHECK-DAG: %[[TRUE:.+]] = "tosa.const"() <{value = dense<true> : tensor<10xi1>}
403 // CHECK-DAG: %[[FALSE:.+]] = "tosa.const"() <{value = dense<false> : tensor<10xi1>}
405 return %true, %false : tensor<10xi1>, tensor<10xi1>
411 func.func @fold_greater_splat_i32() -> (tensor<10xi1>, tensor<10xi1>) {
412 %0 = "tosa.const"() {value = dense<-10> : tensor<10xi32>} : () -> tensor<10xi32>
413 %1 = "tosa.const"() {value = dense<8> : tensor<10xi32>} : () -> tensor<10xi32>
414 %2 = "tosa.const"() {value = dense<-10> : tensor<10xi32>} : () -> tensor<10xi32>
415 %3 = "tosa.const"() {value = dense<-12> : tensor<10xi32>} : () -> tensor<10xi32>
416 %false = tosa.greater %0, %1 : (tensor<10xi32>, tensor<10xi32>) -> tensor<10xi1>
417 %true = tosa.greater %2, %3 : (tensor<10xi32>, tensor<10xi32>) -> tensor<10xi1>
418 // CHECK-DAG: %[[FALSE:.+]] = "tosa.const"() <{value = dense<false> : tensor<10xi1>}
419 // CHECK-DAG: %[[TRUE:.+]] = "tosa.const"() <{value = dense<true> : tensor<10xi1>}
421 return %false, %true : tensor<10xi1>, tensor<10xi1>
427 func.func @fold_greater_eq_splat_f32() -> (tensor<10xi1>, tensor<10xi1>) {
428 %0 = "tosa.const"() {value = dense<4.0> : tensor<10xf32>} : () -> tensor<10xf32>
429 %1 = "tosa.const"() {value = dense<4.0> : tensor<10xf32>} : () -> tensor<10xf32>
430 %2 = "tosa.const"() {value = dense<1.0> : tensor<10xf32>} : () -> tensor<10xf32>
431 %3 = "tosa.const"() {value = dense<2.0> : tensor<10xf32>} : () -> tensor<10xf32>
432 %true = tosa.greater_equal %0, %1 : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xi1>
433 %false = tosa.greater_equal %2, %3 : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xi1>
434 // CHECK-DAG: %[[TRUE:.+]] = "tosa.const"() <{value = dense<true> : tensor<10xi1>}
435 // CHECK-DAG: %[[FALSE:.+]] = "tosa.const"() <{value = dense<false> : tensor<10xi1>}
437 return %true, %false : tensor<10xi1>, tensor<10xi1>
443 func.func @fold_greater_eq_splat_i32() -> (tensor<10xi1>, tensor<10xi1>) {
444 %0 = "tosa.const"() {value = dense<-10> : tensor<10xi32>} : () -> tensor<10xi32>
445 %1 = "tosa.const"() {value = dense<8> : tensor<10xi32>} : () -> tensor<10xi32>
446 %2 = "tosa.const"() {value = dense<-10> : tensor<10xi32>} : () -> tensor<10xi32>
447 %3 = "tosa.const"() {value = dense<-10> : tensor<10xi32>} : () -> tensor<10xi32>
448 %true = tosa.greater_equal %2, %3 : (tensor<10xi32>, tensor<10xi32>) -> tensor<10xi1>
449 %false = tosa.greater_equal %0, %1 : (tensor<10xi32>, tensor<10xi32>) -> tensor<10xi1>
450 // CHECK-DAG: %[[TRUE:.+]] = "tosa.const"() <{value = dense<true> : tensor<10xi1>}
451 // CHECK-DAG: %[[FALSE:.+]] = "tosa.const"() <{value = dense<false> : tensor<10xi1>}
453 return %true, %false : tensor<10xi1>, tensor<10xi1>
459 func.func @fold_eq_splat_f32() -> (tensor<10xi1>, tensor<10xi1>) {
460 %0 = "tosa.const"() {value = dense<4.0> : tensor<10xf32>} : () -> tensor<10xf32>
461 %1 = "tosa.const"() {value = dense<4.0> : tensor<10xf32>} : () -> tensor<10xf32>
462 %2 = "tosa.const"() {value = dense<1.0> : tensor<10xf32>} : () -> tensor<10xf32>
463 %3 = "tosa.const"() {value = dense<2.0> : tensor<10xf32>} : () -> tensor<10xf32>
464 %true = tosa.equal %0, %1 : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xi1>
465 %false = tosa.equal %2, %3 : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xi1>
466 // CHECK-DAG: %[[TRUE:.+]] = "tosa.const"() <{value = dense<true> : tensor<10xi1>}
467 // CHECK-DAG: %[[FALSE:.+]] = "tosa.const"() <{value = dense<false> : tensor<10xi1>}
469 return %true, %false : tensor<10xi1>, tensor<10xi1>
475 func.func @fold_eq_splat_i32() -> (tensor<10xi1>, tensor<10xi1>) {
476 %0 = "tosa.const"() {value = dense<-10> : tensor<10xi32>} : () -> tensor<10xi32>
477 %1 = "tosa.const"() {value = dense<8> : tensor<10xi32>} : () -> tensor<10xi32>
478 %2 = "tosa.const"() {value = dense<-10> : tensor<10xi32>} : () -> tensor<10xi32>
479 %3 = "tosa.const"() {value = dense<-10> : tensor<10xi32>} : () -> tensor<10xi32>
480 %true = tosa.equal %2, %3 : (tensor<10xi32>, tensor<10xi32>) -> tensor<10xi1>
481 %false = tosa.equal %0, %1 : (tensor<10xi32>, tensor<10xi32>) -> tensor<10xi1>
482 // CHECK-DAG: %[[TRUE:.+]] = "tosa.const"() <{value = dense<true> : tensor<10xi1>}
483 // CHECK-DAG: %[[FALSE:.+]] = "tosa.const"() <{value = dense<false> : tensor<10xi1>}
485 return %true, %false : tensor<10xi1>, tensor<10xi1>
491 func.func @fold_eq_i32(%arg0 : tensor<10xi32>) -> (tensor<10xi1>) {
492 // CHECK: %[[TRUE:.+]] = "tosa.const"() <{value = dense<true> : tensor<10xi1>}
493 %0 = tosa.equal %arg0, %arg0 : (tensor<10xi32>, tensor<10xi32>) -> tensor<10xi1>
495 return %0 : tensor<10xi1>
500 func.func @reshape_splat() -> tensor<6x5x4xi32> {
501 // CHECK: %[[SPLAT:.+]] = "tosa.const"() <{value = dense<42> : tensor<6x5x4xi32>}
502 %splat = "tosa.const"() {value = dense<42> : tensor<4x5x6xi32>} : () -> tensor<4x5x6xi32>
503 %reshape = tosa.reshape %splat { new_shape = array<i64: 6, 5, 4> } : (tensor<4x5x6xi32>) -> tensor<6x5x4xi32>
505 return %reshape : tensor<6x5x4xi32>
511 func.func @slice_splat() -> tensor<1x1x1xi32> {
512 // CHECK: %[[SLICE:.+]] = "tosa.const"() <{value = dense<42> : tensor<1x1x1xi32>}
513 %splat = "tosa.const"() {value = dense<42> : tensor<4x5x6xi32>} : () -> tensor<4x5x6xi32>
514 %start = tosa.const_shape {value = dense<[1, 2, 3]> : tensor<3xindex>} : () -> !tosa.shape<3>
515 %size = tosa.const_shape {value = dense<[1, 1, 1]> : tensor<3xindex>} : () -> !tosa.shape<3>
516 %slice= tosa.slice %splat, %start, %size : (tensor<4x5x6xi32>, !tosa.shape<3>, !tosa.shape<3>) -> tensor<1x1x1xi32>
519 return %slice : tensor<1x1x1xi32>
525 func.func @slice_singleton() -> tensor<1x1xi32> {
526 %splat = "tosa.const"() {value = dense<[[0, 1, 2], [3, 4, 5], [6, 7 ,8]]> : tensor<3x3xi32>} : () -> tensor<3x3xi32>
527 // CHECK: %[[SLICE:.+]] = "tosa.const"() <{value = dense<4> : tensor<1x1xi32>}
528 %start = tosa.const_shape {value = dense<[1, 1]> : tensor<2xindex>} : () -> !tosa.shape<2>
529 %size = tosa.const_shape {value = dense<[1, 1]> : tensor<2xindex>} : () -> !tosa.shape<2>
530 %slice= tosa.slice %splat, %start, %size : (tensor<3x3xi32>, !tosa.shape<2>, !tosa.shape<2>) -> tensor<1x1xi32>
532 return %slice : tensor<1x1xi32>
538 func.func @cast_float_to_float() -> tensor<f16> {
539 %splat = "tosa.const"() {value = dense<42.0> : tensor<f32>} : () -> tensor<f32>
540 // CHECK: %[[SPLAT:.+]] = "tosa.const"() <{value = dense<4.200000e+01> : tensor<f16>}
541 %cast = tosa.cast %splat : (tensor<f32>) -> tensor<f16>
543 return %cast : tensor<f16>
549 func.func @cast_int_to_float() -> tensor<f16> {
550 %splat = "tosa.const"() {value = dense<4> : tensor<i32>} : () -> tensor<i32>
551 // CHECK: %[[SPLAT:.+]] = "tosa.const"() <{value = dense<4.000000e+00> : tensor<f16>}
552 %cast = tosa.cast %splat : (tensor<i32>) -> tensor<f16>
554 return %cast : tensor<f16>
560 func.func @cast_float_to_int() -> tensor<i16> {
561 %splat = "tosa.const"() {value = dense<-4.0> : tensor<f32>} : () -> tensor<f32>
562 // CHECK: %[[SPLAT:.+]] = "tosa.const"() <{value = dense<-4> : tensor<i16>}
563 %cast = tosa.cast %splat : (tensor<f32>) -> tensor<i16>
565 return %cast : tensor<i16>
571 func.func @cast_float_to_int_round() -> tensor<i16> {
572 %splat = "tosa.const"() {value = dense<-3.5> : tensor<f32>} : () -> tensor<f32>
573 // CHECK: %[[SPLAT:.+]] = "tosa.const"() <{value = dense<-4> : tensor<i16>}
574 %cast = tosa.cast %splat : (tensor<f32>) -> tensor<i16>
576 return %cast : tensor<i16>
582 func.func @cast_int_to_int_trunc() -> tensor<i16> {
583 %splat = "tosa.const"() {value = dense<-1> : tensor<i32>} : () -> tensor<i32>
584 // CHECK: %[[SPLAT:.+]] = "tosa.const"() <{value = dense<-1> : tensor<i16>}
585 %cast = tosa.cast %splat : (tensor<i32>) -> tensor<i16>
587 return %cast : tensor<i16>
593 func.func @cast_int_to_int_sign() -> tensor<i32> {
594 %splat = "tosa.const"() {value = dense<-1> : tensor<i16>} : () -> tensor<i16>
595 // CHECK: %[[SPLAT:.+]] = "tosa.const"() <{value = dense<-1> : tensor<i32>}
596 %cast = tosa.cast %splat : (tensor<i16>) -> tensor<i32>
598 return %cast : tensor<i32>
604 func.func @reverse_splat() -> tensor<10xi32> {
605 // CHECK: %[[SPLAT:.+]] = "tosa.const"() <{value = dense<42> : tensor<10xi32>}
606 %splat = "tosa.const"() {value = dense<42> : tensor<10xi32>} : () -> tensor<10xi32>
607 %reverse = tosa.reverse %splat { axis = 0 : i32 } : (tensor<10xi32>) -> tensor<10xi32>
609 return %reverse : tensor<10xi32>
615 func.func @reverse_length_one(%arg0 : tensor<10x1xi32>) -> (tensor<10x1xi32>, tensor<10x1xi32>) {
616 %nofold = tosa.reverse %arg0 { axis = 0 : i32 } : (tensor<10x1xi32>) -> tensor<10x1xi32>
617 %fold = tosa.reverse %arg0 { axis = 1 : i32 } : (tensor<10x1xi32>) -> tensor<10x1xi32>
620 return %nofold, %fold : tensor<10x1xi32>, tensor<10x1xi32>
625 func.func @reduce_sum_constant() -> tensor<1x3xi32> {
626 // CHECK-LABEL: func.func @reduce_sum_constant() -> tensor<1x3xi32> {
627 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}5, 7, 9]]> : tensor<1x3xi32>}> : () -> tensor<1x3xi32>
628 // CHECK: return %[[VAL_0]] : tensor<1x3xi32>
630 %const = "tosa.const"() {value = dense<[[1,2,3], [4,5,6]]> : tensor<2x3xi32>} : () -> tensor<2x3xi32>
631 %0 = tosa.reduce_sum %const {axis = 0 : i32} : (tensor<2x3xi32>) -> tensor<1x3xi32>
632 return %0 : tensor<1x3xi32>
637 func.func @reduce_sum_constant() -> tensor<2x1xi32> {
638 // CHECK-LABEL: func.func @reduce_sum_constant() -> tensor<2x1xi32> {
639 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}6], [15]]> : tensor<2x1xi32>}> : () -> tensor<2x1xi32>
640 // CHECK: return %[[VAL_0]] : tensor<2x1xi32>
642 %const = "tosa.const"() <{value = dense<[[1,2,3], [4,5,6]]> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
643 %0 = tosa.reduce_sum %const {axis = 1 : i32} : (tensor<2x3xi32>) -> tensor<2x1xi32>
644 return %0 : tensor<2x1xi32>
650 func.func @reduce_sum_constant() -> tensor<3x1xi32> {
651 // CHECK-LABEL: func.func @reduce_sum_constant() -> tensor<3x1xi32> {
652 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}6], [15], [24]]> : tensor<3x1xi32>}> : () -> tensor<3x1xi32>
653 // CHECK: return %[[VAL_0]] : tensor<3x1xi32>
655 %const = "tosa.const"() <{value = dense<[[1, 2, 3], [4, 5, 6], [7, 8, 9]]> : tensor<3x3xi32>}> : () -> tensor<3x3xi32>
656 %0 = tosa.reduce_sum %const {axis = 1 : i32} : (tensor<3x3xi32>) -> tensor<3x1xi32>
657 return %0 : tensor<3x1xi32>
662 func.func @reduce_sum_constant() -> tensor<2x1x4xi32> {
663 // CHECK-LABEL: func.func @reduce_sum_constant() -> tensor<2x1x4xi32> {
664 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}[15, 18, 21, 24]], {{\[\[}}51, 54, 57, 60]]]> : tensor<2x1x4xi32>}> : () -> tensor<2x1x4xi32>
665 // CHECK: return %[[VAL_0]] : tensor<2x1x4xi32>
667 %const = "tosa.const"() <{value = dense<[[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]], [[13, 14, 15, 16], [17, 18, 19, 20], [21, 22, 23, 24]]]> : tensor<2x3x4xi32>}> : () -> tensor<2x3x4xi32>
668 %0 = tosa.reduce_sum %const {axis = 1 : i32} : (tensor<2x3x4xi32>) -> tensor<2x1x4xi32>
669 return %0 : tensor<2x1x4xi32>
674 func.func @reduce_sum_constant() -> tensor<1x3x3xi32> {
675 // CHECK-LABEL: func.func @reduce_sum_constant() -> tensor<1x3x3xi32> {
676 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}[30, 33, 36], [39, 42, 45], [48, 51, 54]]]> : tensor<1x3x3xi32>}> : () -> tensor<1x3x3xi32>
677 // CHECK: return %[[VAL_0]] : tensor<1x3x3xi32>
679 %const = "tosa.const"() <{value = dense<[[[1, 2, 3], [4, 5, 6], [7, 8, 9]], [[10, 11, 12], [13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24], [25, 26, 27]]]> : tensor<3x3x3xi32>}> : () -> tensor<3x3x3xi32>
680 %0 = tosa.reduce_sum %const {axis = 0 : i32} : (tensor<3x3x3xi32>) -> tensor<1x3x3xi32>
681 return %0 : tensor<1x3x3xi32>
686 func.func @reduce_sum_constant() -> tensor<2x2x2x1xi32> {
687 // CHECK-LABEL: func.func @reduce_sum_constant() -> tensor<2x2x2x1xi32> {
688 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}{{\[\[}}3], [7]], {{\[\[}}11], [15]]], {{\[\[}}[19], [23]], {{\[\[}}27], [31]]]]> : tensor<2x2x2x1xi32>}> : () -> tensor<2x2x2x1xi32>
689 // CHECK: return %[[VAL_0]] : tensor<2x2x2x1xi32>
691 %const = "tosa.const"() <{value = dense<[[[[1, 2], [3, 4]], [[5, 6], [7, 8]]], [[[9, 10], [11, 12]], [[13, 14], [15, 16]]]]> : tensor<2x2x2x2xi32>}> : () -> tensor<2x2x2x2xi32>
692 %0 = tosa.reduce_sum %const {axis = 3 : i32} : (tensor<2x2x2x2xi32>) -> tensor<2x2x2x1xi32>
693 return %0 : tensor<2x2x2x1xi32>
698 func.func @reduce_sum_constant() -> tensor<1x1x1xi32> {
699 // CHECK-LABEL: func.func @reduce_sum_constant() -> tensor<1x1x1xi32> {
700 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<42> : tensor<1x1x1xi32>}> : () -> tensor<1x1x1xi32>
701 // CHECK: return %[[VAL_0]] : tensor<1x1x1xi32>
703 %const = "tosa.const"() <{value = dense<[[[42]]]> : tensor<1x1x1xi32>}> : () -> tensor<1x1x1xi32>
704 %0 = tosa.reduce_sum %const {axis = 0 : i32} : (tensor<1x1x1xi32>) -> tensor<1x1x1xi32>
705 return %0 : tensor<1x1x1xi32>
710 func.func @reduce_sum_constant() -> tensor<2x3x1x5xi32> {
711 // CHECK-LABEL: func.func @reduce_sum_constant() -> tensor<2x3x1x5xi32> {
712 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}{{\[\[}}34, 38, 42, 46, 50]], {{\[\[}}114, 118, 122, 126, 130]], {{\[\[}}194, 198, 202, 206, 210]]], {{\[\[}}[274, 278, 282, 286, 290]], {{\[\[}}354, 358, 362, 366, 370]], {{\[\[}}434, 438, 442, 446, 450]]]]> : tensor<2x3x1x5xi32>}> : () -> tensor<2x3x1x5xi32>
713 // CHECK: return %[[VAL_0]] : tensor<2x3x1x5xi32>
715 %const = "tosa.const"() <{value = dense<[[[[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14, 15], [16, 17, 18, 19, 20]], [[21, 22, 23, 24, 25], [26, 27, 28, 29, 30], [31, 32, 33, 34, 35], [36, 37, 38, 39, 40]], [[41, 42, 43, 44, 45], [46, 47, 48, 49, 50], [51, 52, 53, 54, 55], [56, 57, 58, 59, 60]]], [[[61, 62, 63, 64, 65], [66, 67, 68, 69, 70], [71, 72, 73, 74, 75], [76, 77, 78, 79, 80]], [[81, 82, 83, 84, 85], [86, 87, 88, 89, 90], [91, 92, 93, 94, 95], [96, 97, 98, 99, 100]], [[101, 102, 103, 104, 105], [106, 107, 108, 109, 110], [111, 112, 113, 114, 115], [116, 117, 118, 119, 120]]]]> : tensor<2x3x4x5xi32>}> : () -> tensor<2x3x4x5xi32>
716 %0 = tosa.reduce_sum %const {axis = 2 : i32} : (tensor<2x3x4x5xi32>) -> tensor<2x3x1x5xi32>
717 return %0 : tensor<2x3x1x5xi32>
722 func.func @reduce_prod_constant() -> tensor<1x3xi32> {
723 // CHECK-LABEL: func.func @reduce_prod_constant() -> tensor<1x3xi32> {
724 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}4, 10, 18]]> : tensor<1x3xi32>}> : () -> tensor<1x3xi32>
725 // CHECK: return %[[VAL_0]] : tensor<1x3xi32>
727 %const = "tosa.const"() <{value = dense<[[1,2,3], [4,5,6]]> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
728 %0 = tosa.reduce_prod %const {axis = 0 : i32} : (tensor<2x3xi32>) -> tensor<1x3xi32>
729 return %0 : tensor<1x3xi32>
734 func.func @reduce_prod_constant() -> tensor<2x1xi32> {
735 // CHECK-LABEL: func.func @reduce_prod_constant() -> tensor<2x1xi32> {
736 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}6], [120]]> : tensor<2x1xi32>}> : () -> tensor<2x1xi32>
737 // CHECK: return %[[VAL_0]] : tensor<2x1xi32>
740 %const = "tosa.const"() <{value = dense<[[1,2,3], [4,5,6]]> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
741 %0 = tosa.reduce_prod %const {axis = 1 : i32} : (tensor<2x3xi32>) -> tensor<2x1xi32>
742 return %0 : tensor<2x1xi32>
747 func.func @reduce_prod_constant() -> tensor<3x1xi32> {
748 // CHECK-LABEL: func.func @reduce_prod_constant() -> tensor<3x1xi32> {
749 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}6], [120], [504]]> : tensor<3x1xi32>}> : () -> tensor<3x1xi32>
750 // CHECK: return %[[VAL_0]] : tensor<3x1xi32>
752 %const = "tosa.const"() <{value = dense<[[1, 2, 3], [4, 5, 6], [7, 8, 9]]> : tensor<3x3xi32>}> : () -> tensor<3x3xi32>
753 %0 = tosa.reduce_prod %const {axis = 1 : i32} : (tensor<3x3xi32>) -> tensor<3x1xi32>
754 return %0 : tensor<3x1xi32>
759 func.func @reduce_prod_constant() -> tensor<2x1x4xi32> {
760 // CHECK-LABEL: func.func @reduce_prod_constant() -> tensor<2x1x4xi32> {
761 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}[45, 120, 231, 384]], {{\[\[}}4641, 5544, 6555, 7680]]]> : tensor<2x1x4xi32>}> : () -> tensor<2x1x4xi32>
762 // CHECK: return %[[VAL_0]] : tensor<2x1x4xi32>
764 %const = "tosa.const"() <{value = dense<[[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]], [[13, 14, 15, 16], [17, 18, 19, 20], [21, 22, 23, 24]]]> : tensor<2x3x4xi32>}> : () -> tensor<2x3x4xi32>
765 %0 = tosa.reduce_prod %const {axis = 1 : i32} : (tensor<2x3x4xi32>) -> tensor<2x1x4xi32>
766 return %0 : tensor<2x1x4xi32>
771 func.func @reduce_prod_constant() -> tensor<1x3x3xi32> {
772 // CHECK-LABEL: func.func @reduce_prod_constant() -> tensor<1x3x3xi32> {
773 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}[190, 440, 756], [1144, 1610, 2160], [2800, 3536, 4374]]]> : tensor<1x3x3xi32>}> : () -> tensor<1x3x3xi32>
774 // CHECK: return %[[VAL_0]] : tensor<1x3x3xi32>
776 %const = "tosa.const"() <{value = dense<[[[1, 2, 3], [4, 5, 6], [7, 8, 9]], [[10, 11, 12], [13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24], [25, 26, 27]]]> : tensor<3x3x3xi32>}> : () -> tensor<3x3x3xi32>
777 %0 = tosa.reduce_prod %const {axis = 0 : i32} : (tensor<3x3x3xi32>) -> tensor<1x3x3xi32>
778 return %0 : tensor<1x3x3xi32>
783 func.func @reduce_prod_constant() -> tensor<2x2x2x1xi32> {
784 // CHECK-LABEL: func.func @reduce_prod_constant() -> tensor<2x2x2x1xi32> {
785 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}{{\[\[}}2], [12]], {{\[\[}}30], [56]]], {{\[\[}}[90], [132]], {{\[\[}}182], [240]]]]> : tensor<2x2x2x1xi32>}> : () -> tensor<2x2x2x1xi32>
786 // CHECK: return %[[VAL_0]] : tensor<2x2x2x1xi32>
788 %const = "tosa.const"() <{value = dense<[[[[1, 2], [3, 4]], [[5, 6], [7, 8]]], [[[9, 10], [11, 12]], [[13, 14], [15, 16]]]]> : tensor<2x2x2x2xi32>}> : () -> tensor<2x2x2x2xi32>
789 %0 = tosa.reduce_prod %const {axis = 3 : i32} : (tensor<2x2x2x2xi32>) -> tensor<2x2x2x1xi32>
790 return %0 : tensor<2x2x2x1xi32>
795 func.func @reduce_prod_constant() -> tensor<1x1x1xi32> {
796 // CHECK-LABEL: func.func @reduce_prod_constant() -> tensor<1x1x1xi32> {
797 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<42> : tensor<1x1x1xi32>}> : () -> tensor<1x1x1xi32>
798 // CHECK: return %[[VAL_0]] : tensor<1x1x1xi32>
800 %const = "tosa.const"() <{value = dense<[[[42]]]> : tensor<1x1x1xi32>}> : () -> tensor<1x1x1xi32>
801 %0 = tosa.reduce_prod %const {axis = 0 : i32} : (tensor<1x1x1xi32>) -> tensor<1x1x1xi32>
802 return %0 : tensor<1x1x1xi32>
807 func.func @reduce_max_constant() -> tensor<1x3xi32> {
808 // CHECK-LABEL: func.func @reduce_max_constant() -> tensor<1x3xi32> {
809 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}4, 5, 6]]> : tensor<1x3xi32>}> : () -> tensor<1x3xi32>
810 // CHECK: return %[[VAL_0]] : tensor<1x3xi32>
812 %const = "tosa.const"() <{value = dense<[[1,2,3], [4,5,6]]> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
813 %0 = tosa.reduce_max %const {axis = 0 : i32} : (tensor<2x3xi32>) -> tensor<1x3xi32>
814 return %0 : tensor<1x3xi32>
819 func.func @reduce_max_constant() -> tensor<2x1xi32> {
820 // CHECK-LABEL: func.func @reduce_max_constant() -> tensor<2x1xi32> {
821 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}3], [6]]> : tensor<2x1xi32>}> : () -> tensor<2x1xi32>
822 // CHECK: return %[[VAL_0]] : tensor<2x1xi32>
825 %const = "tosa.const"() <{value = dense<[[1,2,3], [4,5,6]]> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
826 %0 = tosa.reduce_max %const {axis = 1 : i32} : (tensor<2x3xi32>) -> tensor<2x1xi32>
827 return %0 : tensor<2x1xi32>
832 func.func @reduce_max_constant() -> tensor<3x1xi32> {
833 // CHECK-LABEL: func.func @reduce_max_constant() -> tensor<3x1xi32> {
834 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}3], [6], [9]]> : tensor<3x1xi32>}> : () -> tensor<3x1xi32>
835 // CHECK: return %[[VAL_0]] : tensor<3x1xi32>
837 %const = "tosa.const"() <{value = dense<[[1, 2, 3], [4, 5, 6], [7, 8, 9]]> : tensor<3x3xi32>}> : () -> tensor<3x3xi32>
838 %0 = tosa.reduce_max %const {axis = 1 : i32} : (tensor<3x3xi32>) -> tensor<3x1xi32>
839 return %0 : tensor<3x1xi32>
844 func.func @reduce_max_constant() -> tensor<2x1x4xi32> {
845 // CHECK-LABEL: func.func @reduce_max_constant() -> tensor<2x1x4xi32> {
846 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}[9, 10, 11, 12]], {{\[\[}}21, 22, 23, 24]]]> : tensor<2x1x4xi32>}> : () -> tensor<2x1x4xi32>
847 // CHECK: return %[[VAL_0]] : tensor<2x1x4xi32>
849 %const = "tosa.const"() <{value = dense<[[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]], [[13, 14, 15, 16], [17, 18, 19, 20], [21, 22, 23, 24]]]> : tensor<2x3x4xi32>}> : () -> tensor<2x3x4xi32>
850 %0 = tosa.reduce_max %const {axis = 1 : i32} : (tensor<2x3x4xi32>) -> tensor<2x1x4xi32>
851 return %0 : tensor<2x1x4xi32>
856 func.func @reduce_max_constant() -> tensor<1x3x3xi32> {
857 // CHECK-LABEL: func.func @reduce_max_constant() -> tensor<1x3x3xi32> {
858 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}[19, 20, 21], [22, 23, 24], [25, 26, 27]]]> : tensor<1x3x3xi32>}> : () -> tensor<1x3x3xi32>
859 // CHECK: return %[[VAL_0]] : tensor<1x3x3xi32>
861 %const = "tosa.const"() <{value = dense<[[[1, 2, 3], [4, 5, 6], [7, 8, 9]], [[10, 11, 12], [13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24], [25, 26, 27]]]> : tensor<3x3x3xi32>}> : () -> tensor<3x3x3xi32>
862 %0 = tosa.reduce_max %const {axis = 0 : i32} : (tensor<3x3x3xi32>) -> tensor<1x3x3xi32>
863 return %0 : tensor<1x3x3xi32>
868 func.func @reduce_max_constant() -> tensor<2x2x2x1xi32> {
869 // CHECK-LABEL: func.func @reduce_max_constant() -> tensor<2x2x2x1xi32> {
870 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}{{\[\[}}2], [4]], {{\[\[}}6], [8]]], {{\[\[}}[10], [12]], {{\[\[}}14], [16]]]]> : tensor<2x2x2x1xi32>}> : () -> tensor<2x2x2x1xi32>
871 // CHECK: return %[[VAL_0]] : tensor<2x2x2x1xi32>
873 %const = "tosa.const"() <{value = dense<[[[[1, 2], [3, 4]], [[5, 6], [7, 8]]], [[[9, 10], [11, 12]], [[13, 14], [15, 16]]]]> : tensor<2x2x2x2xi32>}> : () -> tensor<2x2x2x2xi32>
874 %0 = tosa.reduce_max %const {axis = 3 : i32} : (tensor<2x2x2x2xi32>) -> tensor<2x2x2x1xi32>
875 return %0 : tensor<2x2x2x1xi32>
880 func.func @reduce_max_constant() -> tensor<1x1x1xi32> {
881 // CHECK-LABEL: func.func @reduce_max_constant() -> tensor<1x1x1xi32> {
882 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<42> : tensor<1x1x1xi32>}> : () -> tensor<1x1x1xi32>
883 // CHECK: return %[[VAL_0]] : tensor<1x1x1xi32>
885 %const = "tosa.const"() <{value = dense<[[[42]]]> : tensor<1x1x1xi32>}> : () -> tensor<1x1x1xi32>
886 %0 = tosa.reduce_max %const {axis = 0 : i32} : (tensor<1x1x1xi32>) -> tensor<1x1x1xi32>
887 return %0 : tensor<1x1x1xi32>
892 func.func @reduce_min_constant() -> tensor<1x3xi32> {
893 // CHECK-LABEL: func.func @reduce_min_constant() -> tensor<1x3xi32> {
894 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}1, 2, 3]]> : tensor<1x3xi32>}> : () -> tensor<1x3xi32>
895 // CHECK: return %[[VAL_0]] : tensor<1x3xi32>
896 %const = "tosa.const"() <{value = dense<[[1,2,3], [4,5,6]]> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
897 %0 = tosa.reduce_min %const {axis = 0 : i32} : (tensor<2x3xi32>) -> tensor<1x3xi32>
898 return %0 : tensor<1x3xi32>
904 func.func @reduce_min_constant() -> tensor<2x1xi32> {
905 // CHECK-LABEL: func.func @reduce_min_constant() -> tensor<2x1xi32> {
906 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}1], [4]]> : tensor<2x1xi32>}> : () -> tensor<2x1xi32>
907 // CHECK: return %[[VAL_0]] : tensor<2x1xi32>
910 %const = "tosa.const"() <{value = dense<[[1,2,3], [4,5,6]]> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
911 %0 = tosa.reduce_min %const {axis = 1 : i32} : (tensor<2x3xi32>) -> tensor<2x1xi32>
912 return %0 : tensor<2x1xi32>
917 func.func @reduce_min_constant() -> tensor<3x1xi32> {
918 // CHECK-LABEL: func.func @reduce_min_constant() -> tensor<3x1xi32> {
919 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}1], [4], [7]]> : tensor<3x1xi32>}> : () -> tensor<3x1xi32>
920 // CHECK: return %[[VAL_0]] : tensor<3x1xi32>
922 %const = "tosa.const"() <{value = dense<[[1, 2, 3], [4, 5, 6], [7, 8, 9]]> : tensor<3x3xi32>}> : () -> tensor<3x3xi32>
923 %0 = tosa.reduce_min %const {axis = 1 : i32} : (tensor<3x3xi32>) -> tensor<3x1xi32>
924 return %0 : tensor<3x1xi32>
929 func.func @reduce_min_constant() -> tensor<2x1x4xi32> {
930 // CHECK-LABEL: func.func @reduce_min_constant() -> tensor<2x1x4xi32> {
931 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}[1, 2, 3, 4]], {{\[\[}}13, 14, 15, 16]]]> : tensor<2x1x4xi32>}> : () -> tensor<2x1x4xi32>
932 // CHECK: return %[[VAL_0]] : tensor<2x1x4xi32>
934 %const = "tosa.const"() <{value = dense<[[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]], [[13, 14, 15, 16], [17, 18, 19, 20], [21, 22, 23, 24]]]> : tensor<2x3x4xi32>}> : () -> tensor<2x3x4xi32>
935 %0 = tosa.reduce_min %const {axis = 1 : i32} : (tensor<2x3x4xi32>) -> tensor<2x1x4xi32>
936 return %0 : tensor<2x1x4xi32>
941 func.func @reduce_min_constant() -> tensor<1x3x3xi32> {
942 // CHECK-LABEL: func.func @reduce_min_constant() -> tensor<1x3x3xi32> {
943 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}[1, 2, 3], [4, 5, 6], [7, 8, 9]]]> : tensor<1x3x3xi32>}> : () -> tensor<1x3x3xi32>
944 // CHECK: return %[[VAL_0]] : tensor<1x3x3xi32>
946 %const = "tosa.const"() <{value = dense<[[[1, 2, 3], [4, 5, 6], [7, 8, 9]], [[10, 11, 12], [13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24], [25, 26, 27]]]> : tensor<3x3x3xi32>}> : () -> tensor<3x3x3xi32>
947 %0 = tosa.reduce_min %const {axis = 0 : i32} : (tensor<3x3x3xi32>) -> tensor<1x3x3xi32>
948 return %0 : tensor<1x3x3xi32>
953 func.func @reduce_min_constant() -> tensor<2x2x2x1xi32> {
954 // CHECK-LABEL: func.func @reduce_min_constant() -> tensor<2x2x2x1xi32> {
955 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}{{\[\[}}1], [3]], {{\[\[}}5], [7]]], {{\[\[}}[9], [11]], {{\[\[}}13], [15]]]]> : tensor<2x2x2x1xi32>}> : () -> tensor<2x2x2x1xi32>
956 // CHECK: return %[[VAL_0]] : tensor<2x2x2x1xi32>
958 %const = "tosa.const"() <{value = dense<[[[[1, 2], [3, 4]], [[5, 6], [7, 8]]], [[[9, 10], [11, 12]], [[13, 14], [15, 16]]]]> : tensor<2x2x2x2xi32>}> : () -> tensor<2x2x2x2xi32>
959 %0 = tosa.reduce_min %const {axis = 3 : i32} : (tensor<2x2x2x2xi32>) -> tensor<2x2x2x1xi32>
960 return %0 : tensor<2x2x2x1xi32>
965 func.func @reduce_min_constant() -> tensor<1x1x1xi32> {
966 // CHECK-LABEL: func.func @reduce_min_constant() -> tensor<1x1x1xi32> {
967 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<42> : tensor<1x1x1xi32>}> : () -> tensor<1x1x1xi32>
968 // CHECK: return %[[VAL_0]] : tensor<1x1x1xi32>
970 %const = "tosa.const"() <{value = dense<[[[42]]]> : tensor<1x1x1xi32>}> : () -> tensor<1x1x1xi32>
971 %0 = tosa.reduce_min %const {axis = 0 : i32} : (tensor<1x1x1xi32>) -> tensor<1x1x1xi32>
972 return %0 : tensor<1x1x1xi32>
977 func.func @reduce_any_constant() -> tensor<1x3xi1> {
978 // CHECK-LABEL: func.func @reduce_any_constant() -> tensor<1x3xi1> {
979 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<true> : tensor<1x3xi1>}> : () -> tensor<1x3xi1>
980 // CHECK: return %[[VAL_0]] : tensor<1x3xi1>
982 %const = "tosa.const"() <{value = dense<[[true,true,true], [true,false,true]]> : tensor<2x3xi1>}> : () -> tensor<2x3xi1>
983 %0 = tosa.reduce_any %const {axis = 0 : i32} : (tensor<2x3xi1>) -> tensor<1x3xi1>
984 return %0 : tensor<1x3xi1>
990 func.func @reduce_any_constant() -> tensor<2x1xi1> {
991 // CHECK-LABEL: func.func @reduce_any_constant() -> tensor<2x1xi1> {
992 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<true> : tensor<2x1xi1>}> : () -> tensor<2x1xi1>
993 // CHECK: return %[[VAL_0]] : tensor<2x1xi1>
996 %const = "tosa.const"() <{value = dense<[[true,true,true], [true,false,true]]> : tensor<2x3xi1>}> : () -> tensor<2x3xi1>
997 %0 = tosa.reduce_any %const {axis = 1 : i32} : (tensor<2x3xi1>) -> tensor<2x1xi1>
998 return %0 : tensor<2x1xi1>
1003 func.func @reduce_any_constant() -> tensor<3x1xi1> {
1004 // CHECK-LABEL: func.func @reduce_any_constant() -> tensor<3x1xi1> {
1005 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}true], [false], [true]]> : tensor<3x1xi1>}> : () -> tensor<3x1xi1>
1006 // CHECK: return %[[VAL_0]] : tensor<3x1xi1>
1008 %const = "tosa.const"() <{value = dense<[[true, false, false], [false, false, false], [false, false, true]]> : tensor<3x3xi1>}> : () -> tensor<3x3xi1>
1009 %0 = tosa.reduce_any %const {axis = 1 : i32} : (tensor<3x3xi1>) -> tensor<3x1xi1>
1010 return %0 : tensor<3x1xi1>
1015 func.func @reduce_any_constant() -> tensor<2x1x4xi1> {
1016 // CHECK-LABEL: func.func @reduce_any_constant() -> tensor<2x1x4xi1> {
1017 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}[true, false, true, true]], {{\[\[}}true, false, true, false]]]> : tensor<2x1x4xi1>}> : () -> tensor<2x1x4xi1>
1018 // CHECK: return %[[VAL_0]] : tensor<2x1x4xi1>
1020 %const = "tosa.const"() <{value = dense<[[[true, false, false, true], [false, false, true, false], [true, false, true, true]], [[false, false, false, false], [false, false, true, false], [true, false, true, false]]]> : tensor<2x3x4xi1>}> : () -> tensor<2x3x4xi1>
1021 %0 = tosa.reduce_any %const {axis = 1 : i32} : (tensor<2x3x4xi1>) -> tensor<2x1x4xi1>
1022 return %0 : tensor<2x1x4xi1>
1027 func.func @reduce_all_constant() -> tensor<1x3xi1> {
1028 // CHECK-LABEL: func.func @reduce_all_constant() -> tensor<1x3xi1> {
1029 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}true, false, true]]> : tensor<1x3xi1>}> : () -> tensor<1x3xi1>
1030 // CHECK: return %[[VAL_0]] : tensor<1x3xi1>
1032 %const = "tosa.const"() <{value = dense<[[true,true,true], [true,false,true]]> : tensor<2x3xi1>}> : () -> tensor<2x3xi1>
1033 %0 = tosa.reduce_all %const {axis = 0 : i32} : (tensor<2x3xi1>) -> tensor<1x3xi1>
1034 return %0 : tensor<1x3xi1>
1039 func.func @reduce_all_constant() -> tensor<2x1xi1> {
1040 // CHECK-LABEL: func.func @reduce_all_constant() -> tensor<2x1xi1> {
1041 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}true], [false]]> : tensor<2x1xi1>}> : () -> tensor<2x1xi1>
1042 // CHECK: return %[[VAL_0]] : tensor<2x1xi1>
1044 %const = "tosa.const"() <{value = dense<[[true,true,true], [true,false,true]]> : tensor<2x3xi1>}> : () -> tensor<2x3xi1>
1045 %0 = tosa.reduce_all %const {axis = 1 : i32} : (tensor<2x3xi1>) -> tensor<2x1xi1>
1046 return %0 : tensor<2x1xi1>
1051 func.func @reduce_all_constant() -> tensor<3x1xi1> {
1052 // CHECK-LABEL: func.func @reduce_all_constant() -> tensor<3x1xi1> {
1053 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<false> : tensor<3x1xi1>}> : () -> tensor<3x1xi1>
1054 // CHECK: return %[[VAL_0]] : tensor<3x1xi1>
1056 %const = "tosa.const"() <{value = dense<[[true, false, false], [false, false, false], [false, false, true]]> : tensor<3x3xi1>}> : () -> tensor<3x3xi1>
1057 %0 = tosa.reduce_all %const {axis = 1 : i32} : (tensor<3x3xi1>) -> tensor<3x1xi1>
1058 return %0 : tensor<3x1xi1>
1063 func.func @reduce_all_constant() -> tensor<2x1x4xi1> {
1064 // CHECK-LABEL: func.func @reduce_all_constant() -> tensor<2x1x4xi1> {
1065 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<false> : tensor<2x1x4xi1>}> : () -> tensor<2x1x4xi1>
1066 // CHECK: return %[[VAL_0]] : tensor<2x1x4xi1>
1068 %const = "tosa.const"() <{value = dense<[[[true, false, false, true], [false, false, true, false], [true, false, true, true]], [[false, false, false, false], [false, false, true, false], [true, false, true, false]]]> : tensor<2x3x4xi1>}> : () -> tensor<2x3x4xi1>
1069 %0 = tosa.reduce_all %const {axis = 1 : i32} : (tensor<2x3x4xi1>) -> tensor<2x1x4xi1>
1070 return %0 : tensor<2x1x4xi1>
1075 func.func @reduce_sum_constant() -> tensor<1x3xi32> {
1076 // CHECK-LABEL: func.func @reduce_sum_constant() -> tensor<1x3xi32> {
1077 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<2> : tensor<1x3xi32>}> : () -> tensor<1x3xi32>
1078 // CHECK: return %[[VAL_0]] : tensor<1x3xi32>
1080 %const = "tosa.const"() <{value = dense<1> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
1081 %0 = tosa.reduce_sum %const {axis = 0 : i32} : (tensor<2x3xi32>) -> tensor<1x3xi32>
1082 return %0 : tensor<1x3xi32>
1087 func.func @reduce_sum_constant() -> tensor<1x3xi32> {
1088 // CHECK-LABEL: func.func @reduce_sum_constant() -> tensor<1x3xi32> {
1089 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<{{\[\[}}1, 2, 3], [4, 5, 6]]> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
1090 // CHECK: %[[VAL_1:.*]] = "tosa.const"() <{value = dense<{{\[\[}}1, 2, 3], [4, 5, 7]]> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
1091 // CHECK: %[[VAL_2:.*]] = tosa.add %[[VAL_0]], %[[VAL_1]] : (tensor<2x3xi32>, tensor<2x3xi32>) -> tensor<2x3xi32>
1092 // CHECK: %[[VAL_3:.*]] = tosa.reduce_sum %[[VAL_2]] {axis = 0 : i32} : (tensor<2x3xi32>) -> tensor<1x3xi32>
1093 // CHECK: return %[[VAL_3]] : tensor<1x3xi32>
1094 %arg0 = "tosa.const"() <{value = dense<[[1,2,3], [4,5,6]]> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
1095 %arg1 = "tosa.const"() <{value = dense<[[1,2,3], [4,5,7]]> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
1096 %arg2 = tosa.add %arg0, %arg1 : (tensor<2x3xi32>, tensor<2x3xi32>) -> tensor<2x3xi32>
1097 %0 = tosa.reduce_sum %arg2 {axis = 0 : i32} : (tensor<2x3xi32>) -> tensor<1x3xi32>
1098 return %0 : tensor<1x3xi32>
1103 func.func @reduce_sum_constant_aggressive() -> tensor<1x3xi32> {
1104 // AGGRESIVE-LABEL: func.func @reduce_sum_constant_aggressive() -> tensor<1x3xi32> {
1105 // AGGRESIVE: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<4> : tensor<1x3xi32>}> : () -> tensor<1x3xi32>
1106 // AGGRESIVE: return %[[VAL_0:.*]] : tensor<1x3xi32>
1108 // CHECK-LABEL: func.func @reduce_sum_constant_aggressive() -> tensor<1x3xi32> {
1109 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<1> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
1110 // CHECK: %[[VAL_1:.*]] = tosa.reduce_sum %[[VAL_0]] {axis = 0 : i32} : (tensor<2x3xi32>) -> tensor<1x3xi32>
1111 // CHECK: %[[VAL_2:.*]] = tosa.reduce_sum %[[VAL_0]] {axis = 0 : i32} : (tensor<2x3xi32>) -> tensor<1x3xi32>
1112 // CHECK: %[[VAL_3:.*]] = tosa.add %[[VAL_1]], %[[VAL_2]] : (tensor<1x3xi32>, tensor<1x3xi32>) -> tensor<1x3xi32>
1113 // CHECK: return %[[VAL_3]] : tensor<1x3xi32>
1115 %const = "tosa.const"() {value = dense<1> : tensor<2x3xi32>} : () -> tensor<2x3xi32>
1116 %0 = tosa.reduce_sum %const {axis = 0 : i32} : (tensor<2x3xi32>) -> tensor<1x3xi32>
1117 %1 = tosa.reduce_sum %const {axis = 0 : i32} : (tensor<2x3xi32>) -> tensor<1x3xi32>
1118 %res = tosa.add %0, %1 : (tensor<1x3xi32>, tensor<1x3xi32>) -> tensor<1x3xi32>
1119 return %res : tensor<1x3xi32>
1124 func.func @reduce_sum_constant_aggressive() -> tensor<2x3xi32> {
1125 // AGGRESIVE-LABEL: func.func @reduce_sum_constant_aggressive() -> tensor<2x3xi32> {
1126 // AGGRESIVE-DAG: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<2> : tensor<1x2x3xi32>}> : () -> tensor<1x2x3xi32>
1127 // AGGRESIVE-DAG: %[[VAL_1:.*]] = "tosa.const"() <{value = dense<1> : tensor<2x2x3xi32>}> : () -> tensor<2x2x3xi32>
1128 // AGGRESIVE-DAG: %[[VAL_2:.*]] = "tosa.const"() <{value = dense<2> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
1129 // AGGRESIVE: %[[VAL_3:.*]] = tosa.argmax %[[VAL_0]] {axis = 1 : i32} : (tensor<1x2x3xi32>) -> tensor<1x3xi32>
1130 // AGGRESIVE: %[[VAL_4:.*]] = tosa.argmax %[[VAL_1]] {axis = 0 : i32} : (tensor<2x2x3xi32>) -> tensor<2x3xi32>
1131 // AGGRESIVE: %[[VAL_5:.*]] = tosa.add %[[VAL_3]], %[[VAL_2]] : (tensor<1x3xi32>, tensor<2x3xi32>) -> tensor<2x3xi32>
1132 // AGGRESIVE: %[[VAL_6:.*]] = tosa.add %[[VAL_5]], %[[VAL_4]] : (tensor<2x3xi32>, tensor<2x3xi32>) -> tensor<2x3xi32>
1133 // AGGRESIVE: return %[[VAL_6]] : tensor<2x3xi32>
1135 // CHECK-LABEL: func.func @reduce_sum_constant_aggressive() -> tensor<2x3xi32> {
1136 // CHECK: %[[VAL_0:.*]] = "tosa.const"() <{value = dense<1> : tensor<2x2x3xi32>}> : () -> tensor<2x2x3xi32>
1137 // CHECK: %[[VAL_1:.*]] = "tosa.const"() <{value = dense<2> : tensor<2x3xi32>}> : () -> tensor<2x3xi32>
1138 // CHECK: %[[VAL_2:.*]] = tosa.reduce_sum %[[VAL_0]] {axis = 0 : i32} : (tensor<2x2x3xi32>) -> tensor<1x2x3xi32>
1139 // CHECK: %[[VAL_3:.*]] = tosa.argmax %[[VAL_2]] {axis = 1 : i32} : (tensor<1x2x3xi32>) -> tensor<1x3xi32>
1140 // CHECK: %[[VAL_4:.*]] = tosa.argmax %[[VAL_0]] {axis = 0 : i32} : (tensor<2x2x3xi32>) -> tensor<2x3xi32>
1141 // CHECK: %[[VAL_5:.*]] = tosa.add %[[VAL_3]], %[[VAL_1]] : (tensor<1x3xi32>, tensor<2x3xi32>) -> tensor<2x3xi32>
1142 // CHECK: %[[VAL_6:.*]] = tosa.add %[[VAL_5]], %[[VAL_4]] : (tensor<2x3xi32>, tensor<2x3xi32>) -> tensor<2x3xi32>
1143 // CHECK: return %[[VAL_6]] : tensor<2x3xi32>
1145 %const0 = "tosa.const"() {value = dense<1> : tensor<2x2x3xi32>} : () -> tensor<2x2x3xi32>
1146 %const1 = "tosa.const"() {value = dense<2> : tensor<2x3xi32>} : () -> tensor<2x3xi32>
1147 %reduce0 = tosa.reduce_sum %const0 {axis = 0 : i32} : (tensor<2x2x3xi32>) -> tensor<1x2x3xi32>
1148 %argmax0 = tosa.argmax %reduce0 {axis = 1 : i32} : (tensor<1x2x3xi32>) -> tensor<1x3xi32>
1149 %argmax1 = tosa.argmax %const0 {axis = 0 : i32} : (tensor<2x2x3xi32>) -> tensor<2x3xi32>
1150 %res0 = tosa.add %argmax0, %const1 : (tensor<1x3xi32>, tensor<2x3xi32>) -> tensor<2x3xi32>
1151 %res1 = tosa.add %res0, %argmax1 : (tensor<2x3xi32>, tensor<2x3xi32>) -> tensor<2x3xi32>
1152 return %res1 : tensor<2x3xi32>