Lines Matching full:tensor
1 // RUN: mlir-opt --split-input-file --tosa-to-tensor %s -o -| FileCheck %s
6 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<f32>
7 // CHECK: return %[[ARG_0]] : tensor<f32>
8 func.func @test_reshape_0d_same_s2s_explicit(%arg0: tensor<f32>) -> tensor<f32> {
9 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64>} : (tensor<f32>) -> tensor<f32>
10 return %0 : tensor<f32>
16 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<f32>
17 // CHECK: %[[VAL_0:.*]] = tensor.expand_shape %[[ARG_0]] [] output_shape [1] : tensor<f32> into tensor<1xf32>
18 // CHECK: %[[VAL_1:.*]] = tensor.cast %[[VAL_0]] : tensor<1xf32> to tensor<?xf32>
19 // CHECK: return %[[VAL_1]] : tensor<?xf32>
20 func.func @test_reshape_0d_up_s2d_auto(%arg0: tensor<f32>) -> tensor<?xf32> {
21 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: -1>} : (tensor<f32>) -> tensor<?xf32>
22 return %0 : tensor<?xf32>
28 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<f32>
29 // CHECK: %[[VAL_0:.*]] = tensor.expand_shape %[[ARG_0]] [] output_shape [1] : tensor<f32> into tensor<1xf32>
30 // CHECK: %[[VAL_1:.*]] = tensor.cast %[[VAL_0]] : tensor<1xf32> to tensor<?xf32>
31 // CHECK: return %[[VAL_1]] : tensor<?xf32>
32 func.func @test_reshape_0d_up_s2d_explicit(%arg0: tensor<f32>) -> tensor<?xf32> {
33 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 1>} : (tensor<f32>) -> tensor<?xf32>
34 return %0 : tensor<?xf32>
40 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<f32>
41 // CHECK: %[[VAL_0:.*]] = tensor.expand_shape %[[ARG_0]] [] output_shape [1] : tensor<f32> into tensor<1xf32>
42 // CHECK: return %[[VAL_0]] : tensor<1xf32>
43 func.func @test_reshape_0d_up_s2s_auto(%arg0: tensor<f32>) -> tensor<1xf32> {
44 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: -1>} : (tensor<f32>) -> tensor<1xf32>
45 return %0 : tensor<1xf32>
51 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<f32>
52 // CHECK: %[[VAL_0:.*]] = tensor.expand_shape %[[ARG_0]] [] output_shape [1] : tensor<f32> into tensor<1xf32>
53 // CHECK: return %[[VAL_0]] : tensor<1xf32>
54 func.func @test_reshape_0d_up_s2s_explicit(%arg0: tensor<f32>) -> tensor<1xf32> {
55 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 1>} : (tensor<f32>) -> tensor<1xf32>
56 return %0 : tensor<1xf32>
62 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<?xf32>
63 // CHECK: %[[VAL_0:.*]] = tensor.cast %[[ARG_0]] : tensor<?xf32> to tensor<1xf32>
64 // CHECK: %[[VAL_1:.*]] = tensor.collapse_shape %[[VAL_0]] [] : tensor<1xf32> into tensor<f32>
65 // CHECK: return %[[VAL_1]] : tensor<f32>
66 func.func @test_reshape_1d_down_d2s_explicit(%arg0: tensor<?xf32>) -> tensor<f32> {
67 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64>} : (tensor<?xf32>) -> tensor<f32>
68 return %0 : tensor<f32>
74 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<1xf32>
75 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] [] : tensor<1xf32> into tensor<f32>
76 // CHECK: return %[[VAL_0]] : tensor<f32>
77 func.func @test_reshape_1d_down_s2s_explicit(%arg0: tensor<1xf32>) -> tensor<f32> {
78 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64>} : (tensor<1xf32>) -> tensor<f32>
79 return %0 : tensor<f32>
85 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<?xf32>
87 // CHECK: %[[DIM:.*]] = tensor.dim %arg0, %[[C0]] : tensor<?xf32>
90 // CHECK: %[[EXPANDED:.*]] = tensor.expand_shape %[[ARG_0]] {{\[\[}}0, 1]] output_shape [2, %[[VAL_0]]] : tensor<?xf32> into tensor<2x?xf32>
91 // CHECK: return %[[EXPANDED]] : tensor<2x?xf32>
92 func.func @test_reshape_1d_up_d2d_auto(%arg0: tensor<?xf32>) -> tensor<2x?xf32> {
93 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 2, -1>} : (tensor<?xf32>) -> tensor<2x?xf32>
94 return %0 : tensor<2x?xf32>
100 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<6xf32>
101 // CHECK: %[[VAL_0:.*]] = tensor.expand_shape %[[ARG_0]] {{\[\[}}0, 1]] output_shape [2, 3] : tensor<6xf32> into tensor<2x3xf32>
102 // CHECK: return %[[VAL_0]] : tensor<2x3xf32>
103 func.func @test_reshape_1d_up_s2s_explicit(%arg0: tensor<6xf32>) -> tensor<2x3xf32> {
104 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 2, 3>} : (tensor<6xf32>) -> tensor<2x3xf32>
105 return %0 : tensor<2x3xf32>
111 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<2x?xf32>
112 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1]] : tensor<2x?xf32> into tensor<?xf32>
113 // CHECK: return %[[VAL_0]] : tensor<?xf32>
114 func.func @test_reshape_2d_down_d2d_auto(%arg0: tensor<2x?xf32>) -> tensor<?xf32> {
115 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: -1>} : (tensor<2x?xf32>) -> tensor<?xf32>
116 return %0 : tensor<?xf32>
122 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<2x3xf32>
123 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1]] : tensor<2x3xf32> into tensor<6xf32>
124 // CHECK: return %[[VAL_0]] : tensor<6xf32>
125 func.func @test_reshape_2d_down_s2s_explicit(%arg0: tensor<2x3xf32>) -> tensor<6xf32> {
126 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 6>} : (tensor<2x3xf32>) -> tensor<6xf32>
127 return %0 : tensor<6xf32>
133 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<?x2xf32>
134 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1]] : tensor<?x2xf32> into tensor<?xf32>
136 // CHECK: %[[DIM:.*]] = tensor.dim %[[VAL_0]], %[[C0]] : tensor<?xf32>
139 // CHECK: %[[EXPANDED:.*]] = tensor.expand_shape %[[VAL_0]] {{\[\[}}0, 1]] output_shape [2, %[[DIV]]] : tensor<?xf32> into tensor<2x?xf32>
140 // CHECK: return %[[EXPANDED]] : tensor<2x?xf32>
141 func.func @test_reshape_2d_same_d2d_auto(%arg0: tensor<?x2xf32>) -> tensor<2x?xf32> {
142 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 2, -1>} : (tensor<?x2xf32>) -> tensor<2x?xf32>
143 return %0 : tensor<2x?xf32>
149 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<2x4xf32>
150 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1]] : tensor<2x4xf32> into tensor<8xf32>
151 // CHECK: %[[VAL_1:.*]] = tensor.expand_shape %[[VAL_0]] {{\[\[}}0, 1]] output_shape [4, 2] : tensor<8xf32> into tensor<4x2xf32>
152 // CHECK: %[[VAL_2:.*]] = tensor.cast %[[VAL_1]] : tensor<4x2xf32> to tensor<?x2xf32>
153 // CHECK: return %[[VAL_2]] : tensor<?x2xf32>
154 func.func @test_reshape_2d_same_s2d_auto(%arg0: tensor<2x4xf32>) -> tensor<?x2xf32> {
155 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: -1, 2>} : (tensor<2x4xf32>) -> tensor<?x2xf32>
156 return %0 : tensor<?x2xf32>
162 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<2x4xf32>
163 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1]] : tensor<2x4xf32> into tensor<8xf32>
164 // CHECK: %[[VAL_1:.*]] = tensor.expand_shape %[[VAL_0]] {{\[\[}}0, 1]] output_shape [4, 2] : tensor<8xf32> into tensor<4x2xf32>
165 // CHECK: %[[VAL_2:.*]] = tensor.cast %[[VAL_1]] : tensor<4x2xf32> to tensor<?x2xf32>
166 // CHECK: return %[[VAL_2]] : tensor<?x2xf32>
167 func.func @test_reshape_2d_same_s2d_explicit(%arg0: tensor<2x4xf32>) -> tensor<?x2xf32> {
168 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 4, 2>} : (tensor<2x4xf32>) -> tensor<?x2xf32>
169 return %0 : tensor<?x2xf32>
175 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<3x2xf32>
176 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1]] : tensor<3x2xf32> into tensor<6xf32>
177 // CHECK: %[[VAL_1:.*]] = tensor.expand_shape %[[VAL_0]] {{\[\[}}0, 1]] output_shape [2, 3] : tensor<6xf32> into tensor<2x3xf32>
178 // CHECK: return %[[VAL_1]] : tensor<2x3xf32>
179 func.func @test_reshape_2d_same_s2s_explicit(%arg0: tensor<3x2xf32>) -> tensor<2x3xf32> {
180 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 2, 3>} : (tensor<3x2xf32>) -> tensor<2x3xf32>
181 return %0 : tensor<2x3xf32>
187 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<3x2x?xf32>
188 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1, 2]] : tensor<3x2x?xf32> into tensor<?xf32>
190 // CHECK: %[[DIM:.*]] = tensor.dim %[[VAL_0]], %[[C0]] : tensor<?xf32>
193 // CHECK: %[[VAL_1:.*]] = tensor.expand_shape %[[VAL_0]] {{\[\[}}0, 1, 2]] output_shape [0, 3, %[[DIV]]] : tensor<?xf32> into tensor<0x3x?xf32>
194 // CHECK: %[[VAL_2:.*]] = tensor.cast %[[VAL_1]] : tensor<0x3x?xf32> to tensor<?x?x?xf32>
195 // CHECK: return %[[VAL_2]] : tensor<?x?x?xf32>
196 func.func @test_reshape_3d_same_d2d_auto_empty(%arg0: tensor<3x2x?xf32>) -> tensor<?x?x?xf32> {
197 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 0, 3, -1>} : (tensor<3x2x?xf32>) -> tensor<?x?x?xf32>
198 return %0 : tensor<?x?x?xf32>
204 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<2x?x?xf32>
205 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1, 2]] : tensor<2x?x?xf32> into tensor<?xf32>
207 // CHECK: %[[DIM:.*]] = tensor.dim %[[VAL_0]], %[[C0]] : tensor<?xf32>
210 // CHECK: %[[VAL_1:.*]] = tensor.expand_shape %[[VAL_0]] {{\[\[}}0, 1, 2]] output_shape [2, %[[DIV]], 4] : tensor<?xf32> into tensor<2x?x4xf32>
211 // CHECK: %[[VAL_2:.*]] = tensor.cast %[[VAL_1]] : tensor<2x?x4xf32> to tensor<?x?x?xf32>
212 // CHECK: return %[[VAL_2]] : tensor<?x?x?xf32>
213 func.func @test_reshape_3d_same_d2d_auto(%arg0: tensor<2x?x?xf32>) -> tensor<?x?x?xf32> {
214 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 2, -1, 4>} : (tensor<2x?x?xf32>) -> tensor<?x?x?xf32>
215 return %0 : tensor<?x?x?xf32>
221 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<?x3x4xf32>
222 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1, 2]] : tensor<?x3x4xf32> into tensor<?xf32>
224 // CHECK: %[[DIM:.*]] = tensor.dim %[[VAL_0]], %[[C0]] : tensor<?xf32>
227 // CHECK: %[[VAL_1:.*]] = tensor.expand_shape %[[VAL_0]] {{\[\[}}0, 1, 2]] output_shape [2, 3, %[[DIV]]] : tensor<?xf32> into tensor<2x3x?xf32>
228 // CHECK: return %[[VAL_1]] : tensor<2x3x?xf32>
229 func.func @test_reshape_3d_same_d2d_auto_identity(%arg0: tensor<?x3x4xf32>) -> tensor<2x3x?xf32> {
230 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 2, 3, -1>} : (tensor<?x3x4xf32>) -> tensor<2x3x?xf32>
231 return %0 : tensor<2x3x?xf32>
237 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<3x2x?xf32>
238 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1, 2]] : tensor<3x2x?xf32> into tensor<?xf32>
240 // CHECK: %[[DIM:.*]] = tensor.dim %[[VAL_0]], %[[C0]] : tensor<?xf32>
243 // CHECK: %[[EXPANDED:.*]] = tensor.expand_shape %[[VAL_0]] {{\[\[}}0, 1, 2]] output_shape [%[[DIV]], 3, 2] : tensor<?xf32> into tensor<?x3x2xf32>
244 // CHECK: %[[VAL_2:.*]] = tensor.cast %[[EXPANDED]] : tensor<?x3x2xf32> to tensor<?x?x?xf32>
245 // CHECK: return %[[VAL_2]] : tensor<?x?x?xf32>
246 func.func @test_reshape_3d_same_d2d_explicit_empty(%arg0: tensor<3x2x?xf32>) -> tensor<?x?x?xf32> {
247 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 0, 3, 2>} : (tensor<3x2x?xf32>) -> tensor<?x?x?xf32>
248 return %0 : tensor<?x?x?xf32>
254 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<?x?x?xf32>
255 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1, 2]] : tensor<?x?x?xf32> into tensor<?xf32>
257 // CHECK: %[[DIM:.*]] = tensor.dim %[[VAL_0]], %[[C0]] : tensor<?xf32>
260 // CHECK: %[[EXPANDED:.*]] = tensor.expand_shape %[[VAL_0]] {{\[\[}}0, 1, 2]] output_shape [%[[DIV]], 3, 4] : tensor<?xf32> into tensor<?x3x4xf32>
261 // CHECK: %[[VAL_2:.*]] = tensor.cast %[[EXPANDED]] : tensor<?x3x4xf32> to tensor<?x?x?xf32>
262 // CHECK: return %[[VAL_2]] : tensor<?x?x?xf32>
263 func.func @test_reshape_3d_same_d2d_explicit(%arg0: tensor<?x?x?xf32>) -> tensor<?x?x?xf32> {
264 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 2, 3, 4>} : (tensor<?x?x?xf32>) -> tensor<?x?x?xf32>
265 return %0 : tensor<?x?x?xf32>
271 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<?x3x4xf32>
272 // CHECK: %[[VAL_0:.*]] = tensor.cast %[[ARG_0]] : tensor<?x3x4xf32> to tensor<2x3x?xf32>
273 // CHECK: return %[[VAL_0]] : tensor<2x3x?xf32>
274 func.func @test_reshape_3d_same_d2d_explicit_identity(%arg0: tensor<?x3x4xf32>) -> tensor<2x3x?xf32> {
275 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 2, 3, 4>} : (tensor<?x3x4xf32>) -> tensor<2x3x?xf32>
276 return %0 : tensor<2x3x?xf32>
282 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<?x?x?xf32>
283 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1, 2]] : tensor<?x?x?xf32> into tensor<?xf32>
285 // CHECK: %[[DIM:.*]] = tensor.dim %[[VAL_0]], %[[C0]] : tensor<?xf32>
288 // CHECK: %[[EXPANDED:.*]] = tensor.expand_shape %[[VAL_0]] {{\[\[}}0, 1, 2]] output_shape [2, %[[DIV]], 4] : tensor<?xf32> into tensor<2x?x4xf32>
289 // CHECK: %[[VAL_2:.*]] = tensor.cast %[[EXPANDED]] : tensor<2x?x4xf32> to tensor<2x3x4xf32>
290 // CHECK: return %[[VAL_2]] : tensor<2x3x4xf32>
291 func.func @test_reshape_3d_same_d2s_auto(%arg0: tensor<?x?x?xf32>) -> tensor<2x3x4xf32> {
292 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 2, -1, 4>} : (tensor<?x?x?xf32>) -> tensor<2x3x4xf32>
293 return %0 : tensor<2x3x4xf32>
299 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<?x?x?xf32>
300 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1, 2]] : tensor<?x?x?xf32> into tensor<?xf32>
302 // CHECK: %[[DIM:.*]] = tensor.dim %[[VAL_0]], %[[C0]] : tensor<?xf32>
305 // CHECK: %[[EXPANDED:.*]] = tensor.expand_shape %[[VAL_0]] {{\[\[}}0, 1, 2]] output_shape [%[[DIV]], 3, 4] : tensor<?xf32> into tensor<?x3x4xf32>
306 // CHECK: %[[VAL_2:.*]] = tensor.cast %[[EXPANDED]] : tensor<?x3x4xf32> to tensor<2x3x4xf32>
307 // CHECK: return %[[VAL_2]] : tensor<2x3x4xf32>
308 func.func @test_reshape_3d_same_d2s_explicit(%arg0: tensor<?x?x?xf32>) -> tensor<2x3x4xf32> {
309 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 2, 3, 4>} : (tensor<?x?x?xf32>) -> tensor<2x3x4xf32>
310 return %0 : tensor<2x3x4xf32>
316 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<2x3x4xf32>
317 // CHECK: return %[[ARG_0]] : tensor<2x3x4xf32>
318 func.func @test_reshape_3d_same_s2s_explicit_identity(%arg0: tensor<2x3x4xf32>) -> tensor<2x3x4xf32> {
319 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 2, 3, 4>} : (tensor<2x3x4xf32>) -> tensor<2x3x4xf32>
320 return %0 : tensor<2x3x4xf32>
326 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<?x?x?xf32>
327 // CHECK: %[[COLLAPSED:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1, 2]] : tensor<?x?x?xf32> into tensor<?xf32>
329 // CHECK: %[[DIM:.*]] = tensor.dim %[[COLLAPSED]], %[[C0]] : tensor<?xf32>
332 // CHECK: %[[EXPANDED:.*]] = tensor.expand_shape %[[COLLAPSED]] {{\[\[}}0, 1, 2, 3]] output_shape [%[[VAL_0]], 3, 2, 1] : tensor<?xf32> into tensor<?x3x2x1xf32>
333 // CHECK: %[[CAST:.*]] = tensor.cast %[[EXPANDED]] : tensor<?x3x2x1xf32> to tensor<1x3x2x1xf32>
334 // CHECK: return %[[CAST]] : tensor<1x3x2x1xf32>
335 func.func @test_reshape_3d_up_d2s_explicit(%input: tensor<?x?x?xf32>) -> tensor<1x3x2x1xf32> {
336 %0 = tosa.reshape %input {new_shape = array<i64: 1, 3, 2, 1>} : (tensor<?x?x?xf32>) -> tensor<1x3x2x1xf32>
337 return %0 : tensor<1x3x2x1xf32>
343 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<?x?x?x?xf32>
344 // CHECK: %[[VAL_0:.*]] = tensor.cast %[[ARG_0]] : tensor<?x?x?x?xf32> to tensor<1x1x1x1xf32>
345 // CHECK: %[[VAL_1:.*]] = tensor.collapse_shape %[[VAL_0]] [] : tensor<1x1x1x1xf32> into tensor<f32>
346 // CHECK: return %[[VAL_1]] : tensor<f32>
347 func.func @test_reshape_4d_down_d2s_explicit(%arg0: tensor<?x?x?x?xf32>) -> tensor<f32> {
348 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64>} : (tensor<?x?x?x?xf32>) -> tensor<f32>
349 return %0 : tensor<f32>
355 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<?x?x?x2x3xf32>
356 // CHECK: %[[COLLAPSED:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1, 2, 3, 4]] : tensor<?x?x?x2x3xf32> into tensor<?xf32>
358 // CHECK: %[[DIM:.*]] = tensor.dim %[[COLLAPSED]], %[[C0]] : tensor<?xf32>
361 // CHECK: %[[EXPANDED:.*]] = tensor.expand_shape %[[COLLAPSED]] {{\[\[}}0, 1, 2]] output_shape [%[[VAL_0]], 2, 3] : tensor<?xf32> into tensor<?x2x3xf32>
362 // CHECK: return %[[EXPANDED]] : tensor<?x2x3xf32>
363 func.func @test_reshape_5d_down_d2d_auto(%arg0: tensor<?x?x?x2x3xf32>) -> tensor<?x2x3xf32> {
364 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: -1, 2, 3>} : (tensor<?x?x?x2x3xf32>) -> tensor<?x2x3xf32>
365 return %0 : tensor<?x2x3xf32>
371 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<1x2x?x5x7x11xf32>
372 // CHECK: %[[COLLAPSED:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1, 2, 3, 4, 5]] : tensor<1x2x?x5x7x11xf32> into tensor<?xf32>
374 // CHECK: %[[DIM:.*]] = tensor.dim %[[COLLAPSED]], %[[C0]] : tensor<?xf32>
377 // CHECK: %[[EXPANDED:.*]] = tensor.expand_shape %[[COLLAPSED]] {{\[\[}}0, 1, 2]] output_shape [%[[VAL_0]], 5, 77] : tensor<?xf32> into tensor<?x5x77xf32>
378 // CHECK: return %[[EXPANDED]] : tensor<?x5x77xf32>
379 func.func @test_reshape_6d_down_d2d_auto(%arg0: tensor<1x2x?x5x7x11xf32>) -> tensor<?x5x77xf32> {
380 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: -1, 5, 77>} : (tensor<1x2x?x5x7x11xf32>) -> tensor<?x5x77xf32>
381 return %0 : tensor<?x5x77xf32>
387 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<1x2x3x5x7x11xf32>
388 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1, 2], [3], [4, 5]] : tensor<1x2x3x5x7x11xf32> into tensor<6x5x77xf32>
389 // CHECK: return %[[VAL_0]] : tensor<6x5x77xf32>
390 func.func @test_reshape_6d_down_s2s_auto(%arg0: tensor<1x2x3x5x7x11xf32>) -> tensor<6x5x77xf32> {
391 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 6, 5, -1>} : (tensor<1x2x3x5x7x11xf32>) -> tensor<6x5x77xf32>
392 return %0 : tensor<6x5x77xf32>
398 // The GCC issue would cause invalid IR after tosa-to-tensor, so this test
399 // locks down that the code goes through tosa-to-tensor and verifies.
404 // CHECK: tensor.expand_shape
405 func.func @reshape_bug_fix(%arg0: tensor<?xf32>) -> tensor<1x1x1x?xf32> {
406 %0 = tosa.reshape %arg0 {new_shape = array<i64: 1, 1, 1, -1>} : (tensor<?xf32>) -> tensor<1x1x1x?xf32>
407 return %0 : tensor<1x1x1x?xf32>
413 // CHECK-SAME: %[[ARG_0:[a-zA-Z0-9_]+]]: tensor<1x2x3x5x7x11xf32>
414 // CHECK: %[[VAL_0:.*]] = tensor.collapse_shape %[[ARG_0]] {{\[\[}}0, 1, 2], [3], [4, 5]] : tensor<1x2x3x5x7x11xf32> into tensor<6x5x77xf32>
415 // CHECK: return %[[VAL_0]] : tensor<6x5x77xf32>
416 func.func @test_reshape_6d_down_s2s_explicit(%arg0: tensor<1x2x3x5x7x11xf32>) -> tensor<6x5x77xf32> {
417 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 6, 5, 77>} : (tensor<1x2x3x5x7x11xf32>) -> tensor<6x5x77xf32>
418 return %0 : tensor<6x5x77xf32>
424 // CHECK-SAME: (%[[ARG0:.*]]: tensor<3x2xui8>)
425 func.func @test_reshape_samerank_unsigned(%arg0: tensor<3x2xui8>) -> tensor<2x3xui8> {
426 // CHECK-NEXT: %[[CAST1:.*]] = builtin.unrealized_conversion_cast %[[ARG0]] : tensor<3x2xui8> to tensor<3x2xi8>
427 // CHECK-NEXT: %[[RESHAPE1:.*]] = tensor.collapse_shape %[[CAST1]] {{\[}}[0, 1]] : tensor<3x2xi8> into tensor<6xi8>
428 // CHECK-NEXT: %[[RESHAPE2:.*]] = tensor.expand_shape %[[RESHAPE1]] {{\[}}[0, 1]] output_shape {{\[}}2, 3] : tensor<6xi8> into tensor<2x3xi8>
429 // CHECK-NEXT: %[[CAST2:.*]] = builtin.unrealized_conversion_cast %[[RESHAPE2]] : tensor<2x3xi8> to tensor<2x3xui8
430 %0 = "tosa.reshape"(%arg0) {new_shape = array<i64: 2, 3>} : (tensor<3x2xui8>) -> tensor<2x3xui8>
432 return %0 : tensor<2x3xui8>
438 func.func @slice(%arg0: tensor<6xf32>) ->() {
439 // CHECK: [[SLICE:%.+]] = tensor.extract_slice %arg0[2] [1] [1]
440 %0 = tosa.const_shape {value = dense<2> : tensor<1xindex>} : () -> !tosa.shape<1>
441 %1 = tosa.const_shape {value = dense<1> : tensor<1xindex>} : () -> !tosa.shape<1>
442 %2 = tosa.slice %arg0, %0, %1 : (tensor<6xf32>, !tosa.shape<1>, !tosa.shape<1>) -> tensor<1xf32>
449 func.func @slice_dyn(%arg0: tensor<?xf32>) -> (tensor<?xf32>) {
451 // CHECK: %[[DIM:.+]] = tensor.dim %arg0, %[[C0]]
454 // CHECK: tensor.extract_slice %arg0[2] [%[[SUB]]] [1]
455 %0 = tosa.const_shape {value = dense<2> : tensor<1xindex>} : () -> !tosa.shape<1>
456 %1 = tosa.const_shape {value = dense<-1> : tensor<1xindex>} : () -> !tosa.shape<1>
457 %2 = tosa.slice %arg0, %0, %1 : (tensor<?xf32>, !tosa.shape<1>, !tosa.shape<1>) -> tensor<?xf32>
458 return %2 : tensor<?xf32>
465 func.func @pad_float(%arg0 : tensor<1x2xf32>) -> (tensor<4x9xf32>) {
466 %0 = tosa.const_shape {value = dense<[1, 2, 3, 4]> : tensor<4xindex>} : () -> !tosa.shape<4>
472 // CHECK: tensor.pad %[[ARG0]] low{{\[}}[[INDEX1]], [[INDEX3]]] high{{\[}}[[INDEX2]], [[INDEX4]]] {
473 // CHECK: tensor.yield [[CST]]
474 // CHECK: } : tensor<1x2xf32> to tensor<4x9xf32>
475 %1 = "tosa.pad"(%arg0, %0) : (tensor<1x2xf32>, !tosa.shape<4>) -> (tensor<4x9xf32>)
476 return %1 : tensor<4x9xf32>
480 func.func @pad_int(%arg0 : tensor<1x2xi32>) -> (tensor<4x9xi32>) {
481 %0 = tosa.const_shape {value = dense<[1, 2, 3, 4]> : tensor<4xindex>} : () -> !tosa.shape<4>
483 // CHECK: tensor.pad
484 // CHECK: tensor.yield [[CST]]
485 %1 = "tosa.pad"(%arg0, %0) : (tensor<1x2xi32>, !tosa.shape<4>) -> (tensor<4x9xi32>)
486 return %1 : tensor<4x9xi32>
490 func.func @pad_quant(%arg0 : tensor<1x2xi32>) -> (tensor<4x9xi32>) {
491 %0 = tosa.const_shape {value = dense<[1, 2, 3, 4]> : tensor<4xindex>} : () -> !tosa.shape<4>
493 // CHECK: tensor.pad
494 // CHECK: tensor.yield [[CST]]
495 %1 = "tosa.pad"(%arg0, %0) {quantization_info = #tosa.pad_quant<input_zp = 42>} : (tensor<1x2xi32>, !tosa.shape<4>) -> (tensor<4x9xi32>)
496 return %1 : tensor<4x9xi32>
501 func.func @pad_float_explicit(%arg0 : tensor<1x2xf32>) -> (tensor<4x9xf32>) {
502 %0 = tosa.const_shape {value = dense<[1, 2, 3, 4]> : tensor<4xindex>} : () -> !tosa.shape<4>
508 // CHECK: tensor.pad %[[ARG0]] low{{\[}}[[INDEX1]], [[INDEX3]]] high{{\[}}[[INDEX2]], [[INDEX4]]] {
509 // CHECK: tensor.yield [[CST]]
510 // CHECK: } : tensor<1x2xf32> to tensor<4x9xf32>
511 %1 = arith.constant dense<42.0> : tensor<f32>
512 %2 = "tosa.pad"(%arg0, %0, %1) : (tensor<1x2xf32>, !tosa.shape<4>, tensor<f32>) -> (tensor<4x9xf32>)
513 return %2 : tensor<4x9xf32>
518 func.func @pad_dyn_input(%arg0 : tensor<?x2xf32>) -> (tensor<?x9xf32>) {
519 %0 = tosa.const_shape {value = dense<[1, 2, 3, 4]> : tensor<4xindex>} : () -> !tosa.shape<4>
525 // CHECK: tensor.pad %[[ARG0]] low{{\[}}[[INDEX1]], [[INDEX3]]] high{{\[}}[[INDEX2]], [[INDEX4]]] {
526 // CHECK: tensor.yield [[CST]]
527 // CHECK: } : tensor<?x2xf32> to tensor<?x9xf32>
528 %1 = "tosa.pad"(%arg0, %0) : (tensor<?x2xf32>, !tosa.shape<4>) -> (tensor<?x9xf32>)
529 return %1 : tensor<?x9xf32>
533 func.func @pad_dyn_padding(%arg0 : tensor<1x2xf32>) -> (tensor<?x9xf32>) {
534 %0 = tosa.const_shape {value = dense<[-1, 2, 3, 4]> : tensor<4xindex>} : () -> !tosa.shape<4>
540 // CHECK: tensor.pad %[[ARG0]] low{{\[}}[[INDEX1]], [[INDEX3]]] high{{\[}}[[INDEX2]], [[INDEX4]]] {
541 // CHECK: tensor.yield [[CST]]
542 // CHECK: } : tensor<1x2xf32> to tensor<?x9xf32>
543 %1 = "tosa.pad"(%arg0, %0) : (tensor<1x2xf32>, !tosa.shape<4>) -> (tensor<?x9xf32>)
544 return %1 : tensor<?x9xf32>
550 // CHECK-SAME: %[[ARG0:.+]]: tensor<5x1xf32>
551 // CHECK-SAME: %[[ARG1:.+]]: tensor<6x1xf32>
552 func.func @concat(%arg0: tensor<5x1xf32>, %arg1: tensor<6x1xf32>) -> () {
553 // CHECK-DAG: [[INIT:%.+]] = tensor.empty() : tensor<11x1xf32>
554 // CHECK-DAG: [[INSERT0:%.+]] = tensor.insert_slice %[[ARG0]] into [[INIT]][0, 0] [5, 1] [1, 1]
555 // CHECK-DAG: [[INSERT1:%.+]] = tensor.insert_slice %[[ARG1]] into [[INSERT0]][5, 0] [6, 1] [1, 1]
556 %0 = "tosa.concat"(%arg0, %arg1) { axis = 0 : i32} : (tensor<5x1xf32>, tensor<6x1xf32>) -> (tensor<11x1xf32>)
558 // CHECK-DAG: [[INIT:%.+]] = tensor.empty() : tensor<5x2xf32>
559 // CHECK-DAG: [[INSERT0:%.+]] = tensor.insert_slice %[[ARG0]] into [[INIT]][0, 0] [5, 1] [1, 1]
560 // CHECK: [[INSERT1:%.+]] = tensor.insert_slice %[[ARG0]] into [[INSERT0]][0, 1] [5, 1] [1, 1]
561 %1 = "tosa.concat"(%arg0, %arg0) { axis = 1 : i32} : (tensor<5x1xf32>, tensor<5x1xf32>) -> (tensor<5x2xf32>)
570 func.func @concat_non_axis_dyn(%arg0: tensor<5x?xf32>, %arg1: tensor<6x?xf32>) -> () {
573 // CHECK-DAG: %[[DIM0:.+]] = tensor.dim %[[ARG0]], %[[IDX1]]
574 // CHECK-DAG: %[[INIT:.+]] = tensor.empty(%[[DIM0]]) : tensor<11x?xf32>
576 // CHECK-DAG: %[[DIM1:.+]] = tensor.dim %[[ARG0]], %[[IDX1_1]]
577 // CHECK-DAG: %[[INSERT0:.+]] = tensor.insert_slice %[[ARG0]] into %[[INIT]][0, 0] [5, %[[DIM1]]] [1, 1]
579 // CHECK-DAG: %[[DIM2:.+]] = tensor.dim %[[ARG1]], %[[IDX1_2]] : tensor<6x?xf32>
580 // CHECK: %[[INSERT1:.+]] = tensor.insert_slice %[[ARG1]] into %[[INSERT0]][5, 0] [6, %[[DIM2]]] [1, 1]
581 %0 = "tosa.concat"(%arg0, %arg1) { axis = 0 : i32} : (tensor<5x?xf32>, tensor<6x?xf32>) -> (tensor<11x?xf32>)
590 func.func @concat_axis_dyn(%arg0: tensor<?x3xf32>, %arg1: tensor<?x3xf32>) -> () {
593 // CHECK-DAG: %[[DIM0:.+]] = tensor.dim %[[ARG0]], %[[IDX0]] : tensor<?x3xf32>
594 // CHECK-DAG: %[[DIM1:.+]] = tensor.dim %[[ARG1]], %[[AXIS]] : tensor<?x3xf32>
596 // CHECK-DAG: %[[INIT:.+]] = tensor.empty(%[[SUM]]) : tensor<?x3xf32>
598 // CHECK-DAG: %[[DIM2:.+]] = tensor.dim %[[ARG0]], %[[IDX0_1]] : tensor<?x3xf32>
599 // CHECK-DAG: %[[INSERT0:.+]] = tensor.insert_slice %[[ARG0]] into %[[INIT]][0, 0] [%[[DIM2]], 3] [1, 1] : tensor<?x3xf32> into tensor<?x3xf32>
601 // CHECK-DAG: %[[DIM3:.+]] = tensor.dim %[[ARG1]], %[[IDX0_2]] : tensor<?x3xf32>
602 // CHECK: %[[INSERT1:.+]] = tensor.insert_slice %[[ARG1]] into %[[INSERT0]][%[[DIM0]], 0] [%[[DIM3]], 3] [1, 1] : tensor<?x3xf32> into tensor<?x3xf32>
604 %0 = "tosa.concat"(%arg0, %arg1) { axis = 0 : i32} : (tensor<?x3xf32>, tensor<?x3xf32>) -> (tensor<?x3xf32>)
614 func.func @concat_axis_dyn_mixed(%arg0: tensor<?x1xf32>, %arg1: tensor<?x1xf32>, %arg2: tensor<?x1xf32>) -> () {
617 // CHECK-DAG: %[[OFFSET0:.+]] = tensor.dim %[[ARG0]], %[[C0_0]] : tensor<?x1xf32>
618 // CHECK-DAG: %[[DIM1_0:.+]] = tensor.dim %[[ARG1]], %[[C0]] : tensor<?x1xf32>
620 // CHECK-DAG: %[[DIM2_2:.+]] = tensor.dim %[[ARG2]], %[[C0]] : tensor<?x1xf32>
622 // CHECK-DAG: %[[INIT:.+]] = tensor.empty() : tensor<5x1xf32>
624 // CHECK-DAG: %[[DIM_4:.+]] = tensor.dim %[[ARG0]], %[[C0_3]] : tensor<?x1xf32>
625 // CHECK-DAG: %[[INSERT0:.+]] = tensor.insert_slice %[[ARG0]] into %[[INIT]][0, 0] [%[[DIM_4]], 1] [1, 1] : tensor<?x1xf32> into tensor<5x1xf32>
627 // CHECK-DAG: %[[DIM_6:.+]] = tensor.dim %[[ARG1]], %[[C0_4]] : tensor<?x1xf32>
628 // CHECK-DAG: %[[INSERT1:.+]] = tensor.insert_slice %[[ARG1]] into %[[INSERT0]][%[[OFFSET0]], 0] [%[[DIM_6]], 1] [1, 1] : tensor<?x1xf32> into tensor<5x1xf32>
630 // CHECK-DAG: %[[DIM_9:.+]] = tensor.dim %[[ARG2]], %[[C0_8]] : tensor<?x1xf32>
631 // CHECK-DAG: %[[INSERT3:.+]] = tensor.insert_slice %[[ARG2]] into %[[INSERT1]][%[[OFFSET1]], 0] [%[[DIM_9]], 1] [1, 1] : tensor<?x1xf32> into tensor<5x1xf32>
635 %0 = "tosa.concat"(%arg0, %arg1, %arg2) <{axis = 0 : i32}> : (tensor<?x1xf32>, tensor<?x1xf32>, tensor<?x1xf32>) -> tensor<5x1xf32>
645 func.func @concat_non_axis_dyn_mixed(%arg0: tensor<?x1xf32>, %arg1: tensor<?x1xf32>, %arg2: tensor<?x1xf32>) -> () {
647 // CHECK-DAG: %[[UNUSED1:.+]] = tensor.dim %[[ARG0]], %[[UNUSED0]] : tensor<?x1xf32>
649 // CHECK-DAG: %[[INIT:.+]] = tensor.empty() : tensor<5x3xf32>
651 // CHECK-DAG: %[[DIM0_0:.+]] = tensor.dim %[[ARG0]], %[[C0_0]] : tensor<?x1xf32>
652 // CHECK-DAG: %[[INSERT0:.+]] = tensor.insert_slice %[[ARG0]] into %[[INIT]][0, 0] [%[[DIM0_0]], 1] [1, 1] : tensor<?x1xf32> into tensor<5x3xf32>
654 // CHECK-DAG: %[[DIM1_0:.+]] = tensor.dim %[[ARG1]], %[[C0_1]] : tensor<?x1xf32>
655 // CHECK-DAG: %[[INSERT1:.+]] = tensor.insert_slice %[[ARG1]] into %[[INSERT0]][0, 1] [%[[DIM1_0]], 1] [1, 1] : tensor<?x1xf32> into tensor<5x3xf32>
657 // CHECK-DAG: %[[DIM2_0:.+]] = tensor.dim %[[ARG2]], %[[C0_2]] : tensor<?x1xf32>
658 // CHECK-DAG: %[[INSERT2:.+]] = tensor.insert_slice %[[ARG2]] into %[[INSERT1]][0, 2] [%[[DIM2_0]], 1] [1, 1] : tensor<?x1xf32> into tensor<5x3xf32>
661 %0 = "tosa.concat"(%arg0, %arg1, %arg2) <{axis = 1 : i32}> : (tensor<?x1xf32>, tensor<?x1xf32>, tensor<?x1xf32>) -> tensor<5x3xf32>