Lines Matching full:linalg
1 // RUN: mlir-opt %s -split-input-file -linalg-generalize-named-ops | FileCheck %s
5 %0 = linalg.matmul ins(%A, %B: tensor<16x8xf16>, tensor<8x32xf64>)
17 // CHECK-NEXT: linalg.yield %[[ADD]] : f32
24 %0 = linalg.matmul ins(%A, %B: tensor<16x8xi16>, tensor<8x32xi64>)
36 // CHECK-NEXT: linalg.yield %[[ADD]] : i32
44 %0 = linalg.matmul {cast = #linalg.type_fn<cast_unsigned>}
56 %0 = linalg.matmul ins(%A, %B: tensor<16x8xi16>, tensor<8x32xi64>)
69 %0 = linalg.matmul ins(%A, %B: tensor<16x8xf16>, tensor<8x32xf64>)
82 %0 = linalg.matmul { cast = #linalg.type_fn<cast_unsigned> }
96 %0 = linalg.matmul { cast = #linalg.type_fn<cast_unsigned> }
110 %0 = linalg.matmul { cast = #linalg.type_fn<cast_unsigned> }
127 %0 = linalg.contract
143 // CHECK-NEXT: linalg.yield %[[ADD]] : f32
152 %0 = linalg.contract
169 // CHECK-NEXT: linalg.yield %[[ADD]] : f32
176 %0 = linalg.pooling_nhwc_max {dilations = dense<[1, 2]> : tensor<2xi64>, strides = dense<[2, 4]> : tensor<2xi64>}
184 // CHECK-NEXT: linalg.yield %[[MAX]] : f32
190 %0 = linalg.pooling_nwc_max {dilations = dense<[2]> : tensor<1xi64>, strides = dense<[4]> : tensor<1xi64>}
198 // CHECK-NEXT: linalg.yield %[[MAX]] : f32
204 %0 = linalg.pooling_nhwc_max {dilations = dense<[1, 2]> : tensor<2xi64>, strides = dense<[2, 4]> : tensor<2xi64>}
216 %0 = linalg.pooling_nwc_max {dilations = dense<[2]> : tensor<1xi64>, strides = dense<[4]> : tensor<1xi64>}
228 %0 = linalg.pooling_nhwc_max_unsigned {dilations = dense<[1, 2]> : tensor<2xi64>, strides = dense<[2, 4]> : tensor<2xi64>}
240 %0 = linalg.pooling_nwc_max_unsigned {dilations = dense<[2]> : tensor<1xi64>, strides = dense<[4]> : tensor<1xi64>}
252 %0 = linalg.pooling_nhwc_min {dilations = dense<[1, 2]> : tensor<2xi64>, strides = dense<[2, 4]> : tensor<2xi64>}
260 // CHECK-NEXT: linalg.yield %[[MIN]] : f32
266 %0 = linalg.pooling_nwc_min {dilations = dense<[2]> : tensor<1xi64>, strides = dense<[4]> : tensor<1xi64>}
274 // CHECK-NEXT: linalg.yield %[[MIN]] : f32
280 %0 = linalg.pooling_nhwc_min {dilations = dense<[1, 2]> : tensor<2xi64>, strides = dense<[2, 4]> : tensor<2xi64>}
292 %0 = linalg.pooling_nwc_min {dilations = dense<[2]> : tensor<1xi64>, strides = dense<[4]> : tensor<1xi64>}
304 %0 = linalg.pooling_nhwc_min_unsigned {dilations = dense<[1, 2]> : tensor<2xi64>, strides = dense<[2, 4]> : tensor<2xi64>}
316 %0 = linalg.pooling_nwc_min_unsigned {dilations = dense<[2]> : tensor<1xi64>, strides = dense<[4]> : tensor<1xi64>}
328 %0 = linalg.pooling_nhwc_sum {dilations = dense<[1, 2]> : tensor<2xi64>, strides = dense<[2, 4]> : tensor<2xi64>}
336 // CHECK-NEXT: linalg.yield %[[ADD]] : f32
342 %0 = linalg.pooling_nwc_sum {dilations = dense<[2]> : tensor<1xi64>, strides = dense<[4]> : tensor<1xi64>}
350 // CHECK-NEXT: linalg.yield %[[ADD]] : f32
356 %0 = linalg.pooling_nhwc_sum {dilations = dense<[1, 2]> : tensor<2xi64>, strides = dense<[2, 4]> : tensor<2xi64>}
364 // CHECK-NEXT: linalg.yield %[[ADD]] : i32
370 %0 = linalg.pooling_nwc_sum {dilations = dense<[2]> : tensor<1xi64>, strides = dense<[4]> : tensor<1xi64>}
378 // CHECK-NEXT: linalg.yield %[[ADD]] : i32
384 %0 = linalg.fill ins(%value: f64) outs(%O : tensor<f32>) -> tensor<f32>
391 // CHECK: linalg.generic
398 linalg.fill ins(%value: f64) outs(%O : memref<16x32xf32>)
406 // CHECK: linalg.generic
413 %0 = linalg.fill_rng_2d ins(%min, %max, %seed: f64, f64, i32) outs(%O : tensor<16x32xf32>) -> tensor<16x32xf32>
418 // CHECK-DAG: %[[IDX0:.+]] = linalg.index 0 : index
419 // CHECK-DAG: %[[IDX1:.+]] = linalg.index 1 : index
426 %0 = linalg.fill_rng_2d ins(%min, %max, %seed: f64, f64, i32) outs(%O : tensor<16x32xf32>) -> tensor<16x32xf32>
439 %0 = linalg.elemwise_unary ins(%lhs: tensor<4x8xf32>) outs(%output: tensor<4x8xf32>) -> tensor<4x8xf32>
450 %0 = linalg.elemwise_unary {fun = #linalg.unary_fn<log>}
462 %0 = linalg.elemwise_unary {fun = #linalg.unary_fn<abs>}
474 %0 = linalg.elemwise_unary {fun = #linalg.unary_fn<ceil>}
486 %0 = linalg.elemwise_unary {fun = #linalg.unary_fn<floor>}
498 %0 = linalg.elemwise_unary {fun = #linalg.unary_fn<negf>}
510 %0 = linalg.elemwise_binary ins(%lhs, %rhs: tensor<4x8xf32>, tensor<4x8xf32>)
522 %0 = linalg.elemwise_binary {fun = #linalg.binary_fn<mul>}
535 %0 = linalg.elemwise_binary {fun = #linalg.binary_fn<sub>}
542 // CHECK: linalg.generic
550 %0 = linalg.copy ins(%lhs: tensor<4x8xf32>) outs(%output: tensor<4x8xf32>) -> tensor<4x8xf32>
555 // CHECK: linalg.generic
557 // CHECK-NEXT: linalg.yield %[[I]]