Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 1 | |
Fabrizio Indirli | 7203835 | 2023-12-11 11:15:32 +0000 | [diff] [blame] | 2 | // Copyright (c) 2020-2024, ARM Limited. |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 3 | // |
| 4 | // Licensed under the Apache License, Version 2.0 (the "License"); |
| 5 | // you may not use this file except in compliance with the License. |
| 6 | // You may obtain a copy of the License at |
| 7 | // |
| 8 | // http://www.apache.org/licenses/LICENSE-2.0 |
| 9 | // |
| 10 | // Unless required by applicable law or agreed to in writing, software |
| 11 | // distributed under the License is distributed on an "AS IS" BASIS, |
| 12 | // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| 13 | // See the License for the specific language governing permissions and |
| 14 | // limitations under the License. |
| 15 | |
| 16 | #include "tensor.h" |
| 17 | #include "arith_util.h" |
Grant Watson | 64285a1 | 2022-11-16 15:32:39 +0000 | [diff] [blame] | 18 | #include "array_proxy.h" |
James Ward | 8b39043 | 2022-08-12 20:48:56 +0100 | [diff] [blame] | 19 | #include "half.hpp" |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 20 | |
| 21 | using namespace TosaReference; |
| 22 | using namespace Eigen; |
| 23 | using namespace tosa; |
| 24 | |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 25 | TosaReference::Tensor::Tensor(const std::string tensorName_, |
| 26 | const DType serializationDtype_, |
| 27 | const std::vector<int> shape_) |
| 28 | : tensorName(tensorName_) |
| 29 | , serializationDtype(serializationDtype_) |
| 30 | , shape(shape_) |
| 31 | , tensorDtype(ConvertDType(serializationDtype_)) |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 32 | { |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 33 | producer = nullptr; |
| 34 | isValid = false; |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 35 | consumers.clear(); |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 36 | isSubgraphInput = false; |
| 37 | isSubgraphOutput = false; |
Jerry Ge | 9e94af8 | 2022-10-27 09:57:00 -0700 | [diff] [blame] | 38 | isParentGraphOutput = false; |
Tai Ly | cf84bc9 | 2023-09-07 20:49:09 +0000 | [diff] [blame] | 39 | isVariable = false; |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 40 | } |
| 41 | |
| 42 | TosaReference::Tensor::~Tensor() |
| 43 | {} |
| 44 | |
Jerry Ge | 9e94af8 | 2022-10-27 09:57:00 -0700 | [diff] [blame] | 45 | int TosaReference::Tensor::setIsParentGraphOutput() |
| 46 | { |
| 47 | isParentGraphOutput = true; |
| 48 | return 0; |
| 49 | } |
| 50 | |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 51 | int TosaReference::Tensor::setIsSubgraphInput() |
| 52 | { |
| 53 | isSubgraphInput = true; |
| 54 | return 0; |
| 55 | } |
| 56 | |
| 57 | int TosaReference::Tensor::setIsSubgraphOutput() |
| 58 | { |
| 59 | isSubgraphOutput = true; |
| 60 | return 0; |
| 61 | } |
| 62 | |
Tai Ly | cf84bc9 | 2023-09-07 20:49:09 +0000 | [diff] [blame] | 63 | int TosaReference::Tensor::setIsVariable() |
| 64 | { |
| 65 | isVariable = true; |
| 66 | return 0; |
| 67 | } |
| 68 | |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 69 | int TosaReference::Tensor::setProducer(GraphNode* node) |
| 70 | { |
| 71 | ASSERT_MSG(node, "Tensor::setProducer: no node passed in"); |
| 72 | ASSERT_MSG(!producer, "Tensor::setProducer: producer node already set, tensor %s", tensorName.c_str()); |
| 73 | producer = node; |
| 74 | |
| 75 | return 0; |
| 76 | } |
| 77 | |
| 78 | int TosaReference::Tensor::addConsumer(GraphNode* node) |
| 79 | { |
| 80 | ASSERT_MSG(node, "Tensor::addConsumer: no node passed in"); |
| 81 | consumers.push_back(node); |
| 82 | |
| 83 | return 0; |
| 84 | } |
| 85 | |
| 86 | int TosaReference::Tensor::dumpTensorParams(FILE* out) const |
| 87 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 88 | fprintf(out, "Name: %s DType=%s isValid=%d Rank=%d Shape=%s\n", tensorName.c_str(), EnumNameTOSAREFTYPE(getDtype()), |
Kevin Cheng | 550ccc5 | 2021-03-03 11:21:43 -0800 | [diff] [blame] | 89 | getIsValid(), getRank(), getShapeAsString().c_str()); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 90 | |
| 91 | return 0; |
| 92 | } |
| 93 | |
| 94 | int TosaReference::Tensor::dumpTensorParams(std::ostream& out) const |
| 95 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 96 | out << "Name: " << getName() << " DType=" << EnumNameTOSAREFTYPE(getDtype()) << " isValid=" << getIsValid() |
Kevin Cheng | 550ccc5 | 2021-03-03 11:21:43 -0800 | [diff] [blame] | 97 | << " Rank=" << getRank() << " Shape=" << getShapeAsString() << "\n"; |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 98 | |
| 99 | return 0; |
| 100 | } |
| 101 | |
| 102 | int TosaReference::Tensor::readFromNpyFile(const char* filename) |
| 103 | { |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 104 | uint32_t elements = getElementCount(); |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 105 | double* f64databuf = nullptr; |
| 106 | float* f32databuf = nullptr; |
James Ward | 8b39043 | 2022-08-12 20:48:56 +0100 | [diff] [blame] | 107 | half_float::half* f16databuf = nullptr; |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 108 | int32_t* i32databuf = nullptr; |
| 109 | int64_t* i64databuf = nullptr; |
| 110 | bool* bdatabuf = nullptr; |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 111 | NumpyUtilities::NPError nperror; |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 112 | TOSA_REF_TYPE dtype = getDtype(); |
| 113 | DType serialization_dtype = getSerializationDtype(); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 114 | |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 115 | assert(dtype == ConvertDType(serialization_dtype)); |
| 116 | // if dtype is FP64, serialization_dtype must be one of FP32, FP16, BF16 |
| 117 | assert(dtype != TOSA_REF_TYPE_FP64 || serialization_dtype == DType_FP32 || serialization_dtype == DType_FP16 || |
| 118 | serialization_dtype == DType_BF16); |
| 119 | |
| 120 | switch (serialization_dtype) |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 121 | { |
Jeremy Johnson | bc2a3db | 2022-09-27 13:50:00 +0100 | [diff] [blame] | 122 | case DType_FP32: |
James Ward | 24dbc42 | 2022-10-19 12:20:31 +0100 | [diff] [blame] | 123 | case DType_BF16: |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 124 | f32databuf = (float*)calloc(sizeof(float), elements); |
| 125 | ASSERT_MEM(f32databuf); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 126 | |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 127 | nperror = NumpyUtilities::readFromNpyFile(filename, elements, f32databuf); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 128 | break; |
James Ward | 8b39043 | 2022-08-12 20:48:56 +0100 | [diff] [blame] | 129 | case DType_FP16: |
| 130 | f16databuf = (half_float::half*)calloc(sizeof(half_float::half), elements); |
| 131 | ASSERT_MEM(f16databuf); |
James Ward | 8b39043 | 2022-08-12 20:48:56 +0100 | [diff] [blame] | 132 | |
| 133 | nperror = NumpyUtilities::readFromNpyFile(filename, elements, f16databuf); |
| 134 | break; |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 135 | case DType_INT32: |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 136 | case DType_UINT8: |
| 137 | case DType_INT4: |
| 138 | case DType_INT8: |
| 139 | case DType_INT16: |
Jeremy Johnson | f7f78ae | 2022-05-25 15:26:38 +0100 | [diff] [blame] | 140 | case DType_UINT16: |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 141 | i32databuf = (int32_t*)calloc(sizeof(int32_t), elements); |
| 142 | ASSERT_MEM(i32databuf); |
| 143 | |
| 144 | nperror = NumpyUtilities::readFromNpyFile(filename, elements, i32databuf); |
| 145 | break; |
| 146 | case DType_INT48: |
Won Jeon | a21b2e8 | 2023-08-10 10:33:01 +0000 | [diff] [blame] | 147 | case DType_SHAPE: |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 148 | i64databuf = (int64_t*)calloc(sizeof(int64_t), elements); |
| 149 | ASSERT_MEM(i64databuf); |
| 150 | |
| 151 | nperror = NumpyUtilities::readFromNpyFile(filename, elements, i64databuf); |
| 152 | break; |
| 153 | case DType_BOOL: |
| 154 | bdatabuf = (bool*)calloc(sizeof(bool), elements); |
| 155 | ASSERT_MEM(bdatabuf); |
| 156 | |
| 157 | nperror = NumpyUtilities::readFromNpyFile(filename, elements, bdatabuf); |
| 158 | break; |
| 159 | default: |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 160 | FATAL_ERROR("unknown tensor type=%s", EnumNameDType(serialization_dtype)); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 161 | } |
| 162 | |
| 163 | switch (nperror) |
| 164 | { |
| 165 | case NumpyUtilities::NO_ERROR: |
| 166 | break; |
| 167 | case NumpyUtilities::FILE_NOT_FOUND: |
| 168 | FATAL_ERROR("readFromNpyFile: Cannot open file %s", filename); |
| 169 | case NumpyUtilities::FILE_IO_ERROR: |
| 170 | FATAL_ERROR("readFromNpyFile: IO error reading file: %s", filename); |
| 171 | case NumpyUtilities::FILE_TYPE_MISMATCH: |
| 172 | FATAL_ERROR("readFromNpyFile: Tensor type %s and Numpy file type mismatch for tensor %s filename %s", |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 173 | EnumNameTOSAREFTYPE(getDtype()), getName().c_str(), filename); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 174 | case NumpyUtilities::HEADER_PARSE_ERROR: |
| 175 | FATAL_ERROR("Numpy header parsing error for file: %s", filename); |
| 176 | case NumpyUtilities::BUFFER_SIZE_MISMATCH: |
| 177 | FATAL_ERROR("Buffer size does not match numpy file size for tensor %s filename %s", getName().c_str(), |
| 178 | filename); |
| 179 | default: |
| 180 | FATAL_ERROR("Unknown error parsing Numpy file: %s", filename); |
| 181 | } |
| 182 | |
James Ward | 24dbc42 | 2022-10-19 12:20:31 +0100 | [diff] [blame] | 183 | switch (dtype) |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 184 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 185 | case TOSA_REF_TYPE_FP16: |
James Ward | ee25669 | 2022-11-15 11:36:47 +0000 | [diff] [blame] | 186 | // Convert from fp16 to fp32 so that fp16 values can be manipulated as float |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 187 | f32databuf = (float*)calloc(sizeof(float), elements); |
| 188 | ASSERT_MEM(f32databuf); |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 189 | for (uint32_t i = 0; i < elements; i++) |
| 190 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 191 | f32databuf[i] = half_float::half_cast<float, half_float::half>(f16databuf[i]); |
James Ward | 8b39043 | 2022-08-12 20:48:56 +0100 | [diff] [blame] | 192 | } |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 193 | if (setTensorValueFloat(elements, f32databuf)) |
James Ward | 24dbc42 | 2022-10-19 12:20:31 +0100 | [diff] [blame] | 194 | { |
| 195 | free(f16databuf); |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 196 | free(f32databuf); |
James Ward | 24dbc42 | 2022-10-19 12:20:31 +0100 | [diff] [blame] | 197 | return 1; |
| 198 | } |
| 199 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 200 | case TOSA_REF_TYPE_BF16: |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 201 | for (uint32_t i = 0; i < elements; i++) |
James Ward | 24dbc42 | 2022-10-19 12:20:31 +0100 | [diff] [blame] | 202 | { |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 203 | ASSERT_MSG(checkValidBFloat(f32databuf[i]), "Input float value not a valid bfloat16 value."); |
James Ward | 24dbc42 | 2022-10-19 12:20:31 +0100 | [diff] [blame] | 204 | } |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 205 | if (setTensorValueFloat(elements, f32databuf)) |
James Ward | 24dbc42 | 2022-10-19 12:20:31 +0100 | [diff] [blame] | 206 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 207 | free(f32databuf); |
James Ward | 24dbc42 | 2022-10-19 12:20:31 +0100 | [diff] [blame] | 208 | return 1; |
| 209 | } |
| 210 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 211 | case TOSA_REF_TYPE_FP32: |
| 212 | if (setTensorValueFloat(elements, f32databuf)) |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 213 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 214 | free(f32databuf); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 215 | return 1; |
| 216 | } |
| 217 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 218 | case TOSA_REF_TYPE_INT32: |
| 219 | case TOSA_REF_TYPE_UINT8: |
| 220 | case TOSA_REF_TYPE_INT4: |
| 221 | case TOSA_REF_TYPE_INT8: |
| 222 | case TOSA_REF_TYPE_INT16: |
| 223 | case TOSA_REF_TYPE_UINT16: |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 224 | if (setTensorValueInt32(elements, i32databuf)) |
| 225 | { |
| 226 | free(i32databuf); |
| 227 | return 1; |
| 228 | } |
| 229 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 230 | case TOSA_REF_TYPE_INT48: |
Won Jeon | a21b2e8 | 2023-08-10 10:33:01 +0000 | [diff] [blame] | 231 | case TOSA_REF_TYPE_SHAPE: |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 232 | if (setTensorValueInt64(elements, i64databuf)) |
| 233 | { |
| 234 | free(i64databuf); |
| 235 | return 1; |
| 236 | } |
| 237 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 238 | case TOSA_REF_TYPE_BOOL: |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 239 | if (setTensorValueBool(elements, bdatabuf)) |
| 240 | { |
| 241 | free(i32databuf); |
| 242 | return 1; |
| 243 | } |
| 244 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 245 | case TOSA_REF_TYPE_FP64: |
| 246 | switch (serialization_dtype) |
| 247 | { |
| 248 | case DType_FP16: |
| 249 | // FP16 -> FP64 |
| 250 | f64databuf = (double*)calloc(sizeof(double), elements); |
| 251 | ASSERT_MEM(f64databuf); |
| 252 | for (uint32_t i = 0; i < elements; i++) |
| 253 | { |
| 254 | f64databuf[i] = half_float::half_cast<double, half_float::half>(f16databuf[i]); |
| 255 | } |
| 256 | if (setTensorValueDouble(elements, f64databuf)) |
| 257 | { |
| 258 | free(f16databuf); |
| 259 | free(f64databuf); |
| 260 | return 1; |
| 261 | } |
| 262 | break; |
| 263 | case DType_BF16: |
| 264 | // BF16 -> FP64 |
| 265 | f64databuf = (double*)calloc(sizeof(double), elements); |
| 266 | ASSERT_MEM(f64databuf); |
| 267 | for (uint32_t i = 0; i < elements; i++) |
| 268 | { |
| 269 | ASSERT_MSG(checkValidBFloat(f32databuf[i]), "Input float value not a valid bfloat16 value."); |
| 270 | f64databuf[i] = static_cast<double>(f32databuf[i]); |
| 271 | } |
| 272 | if (setTensorValueDouble(elements, f64databuf)) |
| 273 | { |
| 274 | free(f32databuf); |
| 275 | free(f64databuf); |
| 276 | return 1; |
| 277 | } |
| 278 | break; |
| 279 | case DType_FP32: |
| 280 | // FP32 -> FP64 |
| 281 | f64databuf = (double*)calloc(sizeof(double), elements); |
| 282 | ASSERT_MEM(f64databuf); |
| 283 | for (uint32_t i = 0; i < elements; i++) |
| 284 | { |
| 285 | f64databuf[i] = static_cast<double>(f32databuf[i]); |
| 286 | } |
| 287 | if (setTensorValueDouble(elements, f64databuf)) |
| 288 | { |
| 289 | free(f32databuf); |
| 290 | free(f64databuf); |
| 291 | return 1; |
| 292 | } |
| 293 | break; |
| 294 | default: |
| 295 | FATAL_ERROR("unexpected tensor type=%s and original tensor type=%s", EnumNameTOSAREFTYPE(dtype), |
| 296 | EnumNameDType(serialization_dtype)); |
| 297 | } |
| 298 | break; |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 299 | default: |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 300 | FATAL_ERROR("unsupported tensor type=%s", EnumNameTOSAREFTYPE(dtype)); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 301 | } |
| 302 | |
| 303 | setIsValid(); |
| 304 | |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 305 | if (f32databuf) |
| 306 | free(f32databuf); |
James Ward | 8b39043 | 2022-08-12 20:48:56 +0100 | [diff] [blame] | 307 | if (f16databuf) |
| 308 | free(f16databuf); |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 309 | if (f64databuf) |
| 310 | free(f64databuf); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 311 | if (i32databuf) |
| 312 | free(i32databuf); |
| 313 | if (i64databuf) |
| 314 | free(i64databuf); |
| 315 | if (bdatabuf) |
| 316 | free(bdatabuf); |
| 317 | |
| 318 | return 0; |
| 319 | } |
| 320 | |
| 321 | int TosaReference::Tensor::writeToNpyFile(const char* filename) const |
| 322 | { |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 323 | float* f32databuf = nullptr; |
| 324 | double* f64databuf = nullptr; |
| 325 | half_float::half* f16databuf = nullptr; |
Jerry Ge | c529169 | 2024-01-02 22:29:08 +0000 | [diff] [blame] | 326 | uint8_t* ui8databuf = nullptr; |
| 327 | int8_t* i8databuf = nullptr; |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 328 | int32_t* i32databuf = nullptr; |
| 329 | int64_t* i64databuf = nullptr; |
| 330 | bool* bdatabuf = nullptr; |
Eric Kunze | edac6ab | 2023-06-28 13:29:38 -0700 | [diff] [blame] | 331 | NumpyUtilities::NPError nperror = NumpyUtilities::NO_ERROR; |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 332 | uint32_t elements = getElementCount(); |
| 333 | const TOSA_REF_TYPE dtype = getDtype(); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 334 | |
James Ward | 24dbc42 | 2022-10-19 12:20:31 +0100 | [diff] [blame] | 335 | switch (dtype) |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 336 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 337 | case TOSA_REF_TYPE_FP32: |
| 338 | case TOSA_REF_TYPE_BF16: |
| 339 | f32databuf = (float*)calloc(sizeof(float), elements); |
| 340 | ASSERT_MEM(f32databuf); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 341 | |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 342 | if (getTensorValueFloat(elements, f32databuf)) |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 343 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 344 | free(f32databuf); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 345 | return 1; |
| 346 | } |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 347 | nperror = NumpyUtilities::writeToNpyFile(filename, shape, f32databuf); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 348 | |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 349 | free(f32databuf); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 350 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 351 | case TOSA_REF_TYPE_FP16: |
| 352 | f32databuf = (float*)calloc(sizeof(float), elements); |
| 353 | ASSERT_MEM(f32databuf); |
James Ward | 8b39043 | 2022-08-12 20:48:56 +0100 | [diff] [blame] | 354 | f16databuf = (half_float::half*)calloc(sizeof(half_float::half), elements); |
| 355 | ASSERT_MEM(f16databuf); |
| 356 | |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 357 | if (getTensorValueFloat(elements, f32databuf)) |
James Ward | 8b39043 | 2022-08-12 20:48:56 +0100 | [diff] [blame] | 358 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 359 | free(f32databuf); |
James Ward | 8b39043 | 2022-08-12 20:48:56 +0100 | [diff] [blame] | 360 | free(f16databuf); |
| 361 | return 1; |
| 362 | } |
James Ward | ee25669 | 2022-11-15 11:36:47 +0000 | [diff] [blame] | 363 | // Convert fp32 to fp16 so that output file contains valid fp16 data |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 364 | for (uint32_t i = 0; i < elements; i++) |
| 365 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 366 | f16databuf[i] = half_float::half_cast<half_float::half, float>(f32databuf[i]); |
James Ward | 8b39043 | 2022-08-12 20:48:56 +0100 | [diff] [blame] | 367 | } |
| 368 | nperror = NumpyUtilities::writeToNpyFile(filename, shape, f16databuf); |
| 369 | |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 370 | free(f32databuf); |
James Ward | 8b39043 | 2022-08-12 20:48:56 +0100 | [diff] [blame] | 371 | free(f16databuf); |
| 372 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 373 | case TOSA_REF_TYPE_INT32: |
Jerry Ge | c529169 | 2024-01-02 22:29:08 +0000 | [diff] [blame] | 374 | i32databuf = (int32_t*)calloc(sizeof(int32_t), elements); |
| 375 | ASSERT_MEM(i32databuf); |
| 376 | |
| 377 | if (getTensorValueInt32(elements, i32databuf)) |
| 378 | { |
| 379 | free(i32databuf); |
| 380 | return 1; |
| 381 | } |
| 382 | |
| 383 | nperror = NumpyUtilities::writeToNpyFile(filename, shape, i32databuf); |
| 384 | |
| 385 | free(i32databuf); |
| 386 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 387 | case TOSA_REF_TYPE_UINT8: |
Jerry Ge | c529169 | 2024-01-02 22:29:08 +0000 | [diff] [blame] | 388 | ui8databuf = (uint8_t*)calloc(sizeof(uint8_t), elements); |
| 389 | ASSERT_MEM(ui8databuf); |
| 390 | |
| 391 | if (getTensorValueUInt8(elements, ui8databuf)) |
| 392 | { |
| 393 | free(ui8databuf); |
| 394 | return 1; |
| 395 | } |
| 396 | |
| 397 | nperror = NumpyUtilities::writeToNpyFile(filename, shape, ui8databuf); |
| 398 | |
| 399 | free(ui8databuf); |
| 400 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 401 | case TOSA_REF_TYPE_INT4: |
| 402 | case TOSA_REF_TYPE_INT8: |
Jerry Ge | c529169 | 2024-01-02 22:29:08 +0000 | [diff] [blame] | 403 | i8databuf = (int8_t*)calloc(sizeof(int8_t), elements); |
| 404 | ASSERT_MEM(i8databuf); |
| 405 | |
| 406 | if (getTensorValueInt8(elements, i8databuf)) |
| 407 | { |
| 408 | free(i8databuf); |
| 409 | return 1; |
| 410 | } |
| 411 | |
| 412 | nperror = NumpyUtilities::writeToNpyFile(filename, shape, i8databuf); |
| 413 | |
| 414 | free(i8databuf); |
| 415 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 416 | case TOSA_REF_TYPE_INT16: |
| 417 | case TOSA_REF_TYPE_UINT16: |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 418 | i32databuf = (int32_t*)calloc(sizeof(int32_t), elements); |
| 419 | ASSERT_MEM(i32databuf); |
| 420 | |
| 421 | if (getTensorValueInt32(elements, i32databuf)) |
| 422 | { |
| 423 | free(i32databuf); |
| 424 | return 1; |
| 425 | } |
| 426 | |
| 427 | nperror = NumpyUtilities::writeToNpyFile(filename, shape, i32databuf); |
| 428 | |
| 429 | free(i32databuf); |
| 430 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 431 | case TOSA_REF_TYPE_INT48: |
Won Jeon | a21b2e8 | 2023-08-10 10:33:01 +0000 | [diff] [blame] | 432 | case TOSA_REF_TYPE_SHAPE: |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 433 | i64databuf = (int64_t*)calloc(sizeof(int64_t), elements); |
| 434 | ASSERT_MEM(i64databuf); |
| 435 | |
| 436 | if (getTensorValueInt64(elements, i64databuf)) |
| 437 | { |
| 438 | free(i64databuf); |
| 439 | return 1; |
| 440 | } |
| 441 | |
| 442 | nperror = NumpyUtilities::writeToNpyFile(filename, shape, i64databuf); |
| 443 | |
| 444 | free(i64databuf); |
| 445 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 446 | case TOSA_REF_TYPE_BOOL: |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 447 | bdatabuf = (bool*)calloc(sizeof(bool), elements); |
| 448 | ASSERT_MEM(bdatabuf); |
| 449 | |
| 450 | if (getTensorValueBool(elements, bdatabuf)) |
| 451 | { |
| 452 | free(bdatabuf); |
| 453 | return 1; |
| 454 | } |
| 455 | |
| 456 | nperror = NumpyUtilities::writeToNpyFile(filename, shape, bdatabuf); |
| 457 | |
| 458 | free(bdatabuf); |
| 459 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 460 | case TOSA_REF_TYPE_FP64: |
| 461 | // @todo : support FP64 dtype |
| 462 | f64databuf = (double*)calloc(sizeof(double), elements); |
| 463 | ASSERT_MEM(f64databuf); |
| 464 | |
| 465 | if (getTensorValueDouble(elements, f64databuf)) |
| 466 | { |
| 467 | free(f64databuf); |
| 468 | return 1; |
| 469 | } |
| 470 | nperror = NumpyUtilities::writeToNpyFile(filename, shape, f64databuf); |
| 471 | |
| 472 | free(f64databuf); |
| 473 | break; |
| 474 | case TOSA_REF_TYPE_UNKNOWN: |
| 475 | FATAL_ERROR("unsupported tensor type=%s", EnumNameTOSAREFTYPE(getDtype())); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 476 | } |
| 477 | |
| 478 | switch (nperror) |
| 479 | { |
| 480 | case NumpyUtilities::NO_ERROR: |
| 481 | break; |
| 482 | case NumpyUtilities::FILE_NOT_FOUND: |
| 483 | FATAL_ERROR("writeToNpyFile: Cannot open output file %s", filename); |
| 484 | case NumpyUtilities::FILE_IO_ERROR: |
| 485 | FATAL_ERROR("writeToNpyFile: IO error writing file: %s", filename); |
| 486 | case NumpyUtilities::FILE_TYPE_MISMATCH: |
| 487 | FATAL_ERROR("writeToNpyFile: Tensor type and Numpy file type mismatch for tensor %s filename %s", |
| 488 | getName().c_str(), filename); |
| 489 | case NumpyUtilities::HEADER_PARSE_ERROR: |
| 490 | FATAL_ERROR("Numpy header parsing error for file: %s", filename); |
| 491 | case NumpyUtilities::BUFFER_SIZE_MISMATCH: |
| 492 | FATAL_ERROR("Buffer size does not match numpy file size for tensor %s filename %s", getName().c_str(), |
| 493 | filename); |
| 494 | default: |
| 495 | FATAL_ERROR("Unknown error writing Numpy file: %s", filename); |
| 496 | } |
| 497 | |
| 498 | return 0; |
| 499 | } |
| 500 | |
| 501 | template <class T> |
| 502 | int TosaReference::TensorTemplate<T>::copyValueFrom(TosaReference::Tensor* src) |
| 503 | { |
| 504 | FATAL_ERROR("TensorTemplate<T>::copyValueFrom should not be called. " |
| 505 | "Implement template specialization version."); |
| 506 | return 0; |
| 507 | } |
| 508 | |
| 509 | #define DEF_CTENSOR_COPY_VALUE_FROM(RANK, TYPE) \ |
| 510 | template <> \ |
| 511 | int TosaReference::Tensor##RANK<TYPE>::copyValueFrom(TosaReference::Tensor* src) \ |
| 512 | { \ |
| 513 | TosaReference::Tensor##RANK<TYPE>* t = dynamic_cast<Tensor##RANK<TYPE>*>(src); \ |
| 514 | if (!t) \ |
| 515 | { \ |
| 516 | WARNING("tensor %s templated class does not match %s", src->getName().c_str(), this->getName().c_str()); \ |
| 517 | return 1; \ |
| 518 | } \ |
| 519 | \ |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 520 | const uint32_t src_rank = src->getRank(); \ |
| 521 | const uint32_t dst_rank = this->getRank(); \ |
| 522 | const TOSA_REF_TYPE src_dtype = src->getDtype(); \ |
| 523 | const TOSA_REF_TYPE dst_dtype = this->getDtype(); \ |
| 524 | bool tensor_match = true; \ |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 525 | \ |
| 526 | if ((src_rank != dst_rank) || (src_dtype != dst_dtype)) \ |
| 527 | { \ |
| 528 | tensor_match = false; \ |
| 529 | } \ |
| 530 | else \ |
| 531 | { \ |
| 532 | for (uint32_t i = 0; i < src_rank; i++) \ |
| 533 | { \ |
| 534 | int src_dim = src->getShape()[i]; \ |
| 535 | int dst_dim = this->getShape()[i]; \ |
| 536 | if (src_dim != dst_dim) \ |
| 537 | { \ |
| 538 | tensor_match = false; \ |
| 539 | } \ |
| 540 | } \ |
| 541 | } \ |
| 542 | \ |
| 543 | if (!tensor_match) \ |
| 544 | { \ |
| 545 | WARNING("source tensor %s (rank=%u, dtype=%s, shape=%s) doesn't match destination tensor %s (rank=%u, " \ |
| 546 | "dtype=%s, shape=%s)", \ |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 547 | src->getName().c_str(), src_rank, EnumNameTOSAREFTYPE(src_dtype), src->getShapeAsString().c_str(), \ |
| 548 | this->getName().c_str(), dst_rank, EnumNameTOSAREFTYPE(dst_dtype), \ |
| 549 | this->getShapeAsString().c_str()); \ |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 550 | return 1; \ |
| 551 | } \ |
| 552 | \ |
| 553 | this->getTensor() = t->getTensor(); \ |
| 554 | return 0; \ |
| 555 | } |
| 556 | |
| 557 | DEF_CTENSOR_COPY_VALUE_FROM(0, float) |
| 558 | DEF_CTENSOR_COPY_VALUE_FROM(1, float) |
| 559 | DEF_CTENSOR_COPY_VALUE_FROM(2, float) |
| 560 | DEF_CTENSOR_COPY_VALUE_FROM(3, float) |
| 561 | DEF_CTENSOR_COPY_VALUE_FROM(4, float) |
| 562 | DEF_CTENSOR_COPY_VALUE_FROM(5, float) |
| 563 | DEF_CTENSOR_COPY_VALUE_FROM(6, float) |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 564 | DEF_CTENSOR_COPY_VALUE_FROM(0, double) |
| 565 | DEF_CTENSOR_COPY_VALUE_FROM(1, double) |
| 566 | DEF_CTENSOR_COPY_VALUE_FROM(2, double) |
| 567 | DEF_CTENSOR_COPY_VALUE_FROM(3, double) |
| 568 | DEF_CTENSOR_COPY_VALUE_FROM(4, double) |
| 569 | DEF_CTENSOR_COPY_VALUE_FROM(5, double) |
| 570 | DEF_CTENSOR_COPY_VALUE_FROM(6, double) |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 571 | DEF_CTENSOR_COPY_VALUE_FROM(0, int32_t) |
| 572 | DEF_CTENSOR_COPY_VALUE_FROM(1, int32_t) |
| 573 | DEF_CTENSOR_COPY_VALUE_FROM(2, int32_t) |
| 574 | DEF_CTENSOR_COPY_VALUE_FROM(3, int32_t) |
| 575 | DEF_CTENSOR_COPY_VALUE_FROM(4, int32_t) |
| 576 | DEF_CTENSOR_COPY_VALUE_FROM(5, int32_t) |
| 577 | DEF_CTENSOR_COPY_VALUE_FROM(6, int32_t) |
| 578 | DEF_CTENSOR_COPY_VALUE_FROM(0, int64_t) |
| 579 | DEF_CTENSOR_COPY_VALUE_FROM(1, int64_t) |
| 580 | DEF_CTENSOR_COPY_VALUE_FROM(2, int64_t) |
| 581 | DEF_CTENSOR_COPY_VALUE_FROM(3, int64_t) |
| 582 | DEF_CTENSOR_COPY_VALUE_FROM(4, int64_t) |
| 583 | DEF_CTENSOR_COPY_VALUE_FROM(5, int64_t) |
| 584 | DEF_CTENSOR_COPY_VALUE_FROM(6, int64_t) |
| 585 | DEF_CTENSOR_COPY_VALUE_FROM(0, bool) |
| 586 | DEF_CTENSOR_COPY_VALUE_FROM(1, bool) |
| 587 | DEF_CTENSOR_COPY_VALUE_FROM(2, bool) |
| 588 | DEF_CTENSOR_COPY_VALUE_FROM(3, bool) |
| 589 | DEF_CTENSOR_COPY_VALUE_FROM(4, bool) |
| 590 | DEF_CTENSOR_COPY_VALUE_FROM(5, bool) |
| 591 | DEF_CTENSOR_COPY_VALUE_FROM(6, bool) |
| 592 | |
| 593 | #undef DEF_CTENSOR_COPY_VALUE_FROM |
| 594 | |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 595 | int TosaReference::Tensor::readfromVector(const ArrayProxy<double> vals) |
| 596 | { |
| 597 | uint32_t elements = getElementCount(); |
| 598 | switch (getDtype()) |
| 599 | { |
| 600 | case TOSA_REF_TYPE_FP64: |
| 601 | if (vals.size() != elements) |
| 602 | { |
| 603 | WARNING("The input size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 604 | vals.size(), elements); |
| 605 | return -1; |
| 606 | } |
| 607 | |
| 608 | setTensorValueDouble(elements, vals.data()); |
| 609 | break; |
| 610 | default: |
| 611 | WARNING("The input type (float) doesn't match the data type assigned to the tensor (%s).", |
| 612 | EnumNameTOSAREFTYPE(getDtype())); |
| 613 | return -2; |
| 614 | } |
| 615 | setIsValid(); |
| 616 | return 0; |
| 617 | } |
| 618 | |
Grant Watson | 64285a1 | 2022-11-16 15:32:39 +0000 | [diff] [blame] | 619 | int TosaReference::Tensor::readfromVector(const ArrayProxy<float> vals) |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 620 | { |
| 621 | uint32_t elements = getElementCount(); |
| 622 | switch (getDtype()) |
| 623 | { |
Fabrizio Indirli | 7203835 | 2023-12-11 11:15:32 +0000 | [diff] [blame] | 624 | case TOSA_REF_TYPE_FP64: |
| 625 | if (!g_func_config.precise_mode) |
| 626 | { |
| 627 | WARNING("The input type (float) doesn't match the data type assigned to the tensor (%s).", |
| 628 | EnumNameTOSAREFTYPE(getDtype())); |
| 629 | return -2; |
| 630 | } |
| 631 | // continue with setting float vals in the tensor |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 632 | case TOSA_REF_TYPE_FP16: |
| 633 | case TOSA_REF_TYPE_FP32: |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 634 | if (vals.size() != elements) |
| 635 | { |
| 636 | WARNING("The input size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 637 | vals.size(), elements); |
| 638 | return -1; |
| 639 | } |
| 640 | |
| 641 | setTensorValueFloat(elements, vals.data()); |
| 642 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 643 | case TOSA_REF_TYPE_BF16: |
James Ward | 3d3d45d | 2022-11-28 16:45:36 +0000 | [diff] [blame] | 644 | if (vals.size() != elements) |
| 645 | { |
| 646 | WARNING("The input size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 647 | vals.size(), elements); |
| 648 | return -1; |
| 649 | } |
| 650 | |
| 651 | for (auto v : vals) |
| 652 | { |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 653 | ASSERT_MSG(checkValidBFloat(v), "Input float value not a valid bfloat16 value."); |
James Ward | 3d3d45d | 2022-11-28 16:45:36 +0000 | [diff] [blame] | 654 | } |
| 655 | |
| 656 | setTensorValueFloat(elements, vals.data()); |
| 657 | break; |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 658 | default: |
| 659 | WARNING("The input type (float) doesn't match the data type assigned to the tensor (%s).", |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 660 | EnumNameTOSAREFTYPE(getDtype())); |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 661 | return -2; |
| 662 | } |
| 663 | setIsValid(); |
| 664 | return 0; |
| 665 | } |
| 666 | |
Grant Watson | 64285a1 | 2022-11-16 15:32:39 +0000 | [diff] [blame] | 667 | int TosaReference::Tensor::readfromVector(const ArrayProxy<half_float::half> vals) |
Matthew Sloyan | 2e4d889 | 2022-10-18 18:02:48 +0100 | [diff] [blame] | 668 | { |
| 669 | uint32_t elements = getElementCount(); |
| 670 | std::vector<float> tensor(elements); |
| 671 | |
| 672 | switch (getDtype()) |
| 673 | { |
Fabrizio Indirli | 7203835 | 2023-12-11 11:15:32 +0000 | [diff] [blame] | 674 | case TOSA_REF_TYPE_FP64: |
| 675 | if (!g_func_config.precise_mode) |
| 676 | { |
| 677 | WARNING("The input type (float) doesn't match the data type assigned to the tensor (%s).", |
| 678 | EnumNameTOSAREFTYPE(getDtype())); |
| 679 | return -2; |
| 680 | } |
| 681 | // continue with setting float vals in the tensor |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 682 | case TOSA_REF_TYPE_FP16: |
Matthew Sloyan | 2e4d889 | 2022-10-18 18:02:48 +0100 | [diff] [blame] | 683 | if (vals.size() != elements) |
| 684 | { |
| 685 | WARNING("The input size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 686 | vals.size(), elements); |
| 687 | return -1; |
| 688 | } |
| 689 | |
| 690 | // Convert from fp16 to fp32 |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 691 | for (uint32_t i = 0; i < elements; i++) |
Matthew Sloyan | 2e4d889 | 2022-10-18 18:02:48 +0100 | [diff] [blame] | 692 | { |
| 693 | tensor[i] = half_float::half_cast<float, half_float::half>(vals[i]); |
| 694 | } |
| 695 | |
| 696 | setTensorValueFloat(elements, tensor.data()); |
| 697 | break; |
| 698 | default: |
| 699 | WARNING("The input type doesn't match the data type assigned to the tensor (%s).", |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 700 | EnumNameTOSAREFTYPE(getDtype())); |
Matthew Sloyan | 2e4d889 | 2022-10-18 18:02:48 +0100 | [diff] [blame] | 701 | return -2; |
| 702 | } |
| 703 | setIsValid(); |
| 704 | return 0; |
| 705 | } |
| 706 | |
Jerry Ge | c529169 | 2024-01-02 22:29:08 +0000 | [diff] [blame] | 707 | int TosaReference::Tensor::readfromVector(const ArrayProxy<int8_t> vals) |
| 708 | { |
| 709 | uint32_t elements = getElementCount(); |
| 710 | switch (getDtype()) |
| 711 | { |
| 712 | case TOSA_REF_TYPE_INT8: |
| 713 | case TOSA_REF_TYPE_UINT8: |
| 714 | if (vals.size() != elements) |
| 715 | { |
| 716 | WARNING("The input size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 717 | vals.size(), elements); |
| 718 | return -1; |
| 719 | } |
| 720 | |
| 721 | setTensorValueInt8(elements, vals.data()); |
| 722 | break; |
| 723 | default: |
| 724 | WARNING("The input type doesn't match the data type assigned to the tensor (%s).", |
| 725 | EnumNameTOSAREFTYPE(getDtype())); |
| 726 | return -2; |
| 727 | } |
| 728 | setIsValid(); |
| 729 | return 0; |
| 730 | } |
| 731 | |
Georgios Pinitas | e905977 | 2023-12-06 18:52:30 +0000 | [diff] [blame] | 732 | int TosaReference::Tensor::readfromVector(const ArrayProxy<int16_t> vals) |
| 733 | { |
| 734 | uint32_t elements = getElementCount(); |
| 735 | switch (getDtype()) |
| 736 | { |
| 737 | case TOSA_REF_TYPE_INT16: |
| 738 | case TOSA_REF_TYPE_UINT16: |
| 739 | if (vals.size() != elements) |
| 740 | { |
| 741 | WARNING("The input size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 742 | vals.size(), elements); |
| 743 | return -1; |
| 744 | } |
| 745 | |
| 746 | setTensorValueInt16(elements, vals.data()); |
| 747 | break; |
| 748 | default: |
| 749 | WARNING("The input type doesn't match the data type assigned to the tensor (%s).", |
| 750 | EnumNameTOSAREFTYPE(getDtype())); |
| 751 | return -2; |
| 752 | } |
| 753 | setIsValid(); |
| 754 | return 0; |
| 755 | } |
| 756 | |
Grant Watson | 64285a1 | 2022-11-16 15:32:39 +0000 | [diff] [blame] | 757 | int TosaReference::Tensor::readfromVector(const ArrayProxy<int32_t> vals) |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 758 | { |
| 759 | uint32_t elements = getElementCount(); |
| 760 | switch (getDtype()) |
| 761 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 762 | case TOSA_REF_TYPE_INT32: |
| 763 | case TOSA_REF_TYPE_UINT8: |
| 764 | case TOSA_REF_TYPE_INT4: |
| 765 | case TOSA_REF_TYPE_INT8: |
| 766 | case TOSA_REF_TYPE_INT16: |
| 767 | case TOSA_REF_TYPE_UINT16: |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 768 | if (vals.size() != elements) |
| 769 | { |
| 770 | WARNING("The input size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 771 | vals.size(), elements); |
| 772 | return -1; |
| 773 | } |
| 774 | |
| 775 | setTensorValueInt32(elements, vals.data()); |
| 776 | break; |
| 777 | default: |
| 778 | WARNING("The input type doesn't match the data type assigned to the tensor (%s).", |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 779 | EnumNameTOSAREFTYPE(getDtype())); |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 780 | return -2; |
| 781 | } |
| 782 | setIsValid(); |
| 783 | return 0; |
| 784 | } |
| 785 | |
Grant Watson | 64285a1 | 2022-11-16 15:32:39 +0000 | [diff] [blame] | 786 | int TosaReference::Tensor::readfromVector(const ArrayProxy<int64_t> vals) |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 787 | { |
| 788 | uint32_t elements = getElementCount(); |
| 789 | switch (getDtype()) |
| 790 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 791 | case TOSA_REF_TYPE_INT48: |
Won Jeon | a21b2e8 | 2023-08-10 10:33:01 +0000 | [diff] [blame] | 792 | case TOSA_REF_TYPE_SHAPE: |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 793 | if (vals.size() != elements) |
| 794 | { |
| 795 | WARNING("The input size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 796 | vals.size(), elements); |
| 797 | return -1; |
| 798 | } |
| 799 | |
| 800 | setTensorValueInt64(elements, vals.data()); |
| 801 | break; |
| 802 | default: |
| 803 | WARNING("The input type doesn't match the data type assigned to the tensor (%s).", |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 804 | EnumNameTOSAREFTYPE(getDtype())); |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 805 | return -2; |
| 806 | } |
| 807 | setIsValid(); |
| 808 | return 0; |
| 809 | } |
| 810 | |
Grant Watson | 64285a1 | 2022-11-16 15:32:39 +0000 | [diff] [blame] | 811 | int TosaReference::Tensor::readfromVector(const ArrayProxy<unsigned char> vals) |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 812 | { |
| 813 | uint32_t elements = getElementCount(); |
| 814 | |
| 815 | switch (getDtype()) |
| 816 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 817 | case TOSA_REF_TYPE_BOOL: |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 818 | if (vals.size() != elements) |
| 819 | { |
| 820 | WARNING("The input size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 821 | vals.size(), elements); |
| 822 | return -1; |
| 823 | } |
| 824 | |
| 825 | setTensorValueBool(elements, reinterpret_cast<const bool*>(vals.data())); |
| 826 | break; |
| 827 | default: |
| 828 | WARNING("The input type (bool) doesn't match the data type assigned to the tensor (%s).", |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 829 | EnumNameTOSAREFTYPE(getDtype())); |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 830 | return -2; |
| 831 | } |
| 832 | setIsValid(); |
| 833 | return 0; |
| 834 | } |
| 835 | |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 836 | int TosaReference::Tensor::writeToVector(ArrayProxy<double> vals) |
| 837 | { |
| 838 | uint32_t elements = getElementCount(); |
| 839 | |
| 840 | switch (getDtype()) |
| 841 | { |
| 842 | case TOSA_REF_TYPE_FP64: |
| 843 | if (vals.size() != elements) |
| 844 | { |
| 845 | WARNING("The output size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 846 | vals.size(), elements); |
| 847 | return -1; |
| 848 | } |
| 849 | |
| 850 | getTensorValueDouble(elements, vals.data()); |
| 851 | break; |
| 852 | default: |
| 853 | WARNING("The output type (float) doesn't match the data type assigned to the tensor (%s).", |
| 854 | EnumNameTOSAREFTYPE(getDtype())); |
| 855 | return -2; |
| 856 | } |
| 857 | return 0; |
| 858 | } |
| 859 | |
Grant Watson | 64285a1 | 2022-11-16 15:32:39 +0000 | [diff] [blame] | 860 | int TosaReference::Tensor::writeToVector(ArrayProxy<float> vals) |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 861 | { |
| 862 | uint32_t elements = getElementCount(); |
| 863 | |
| 864 | switch (getDtype()) |
| 865 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 866 | case TOSA_REF_TYPE_FP16: |
| 867 | case TOSA_REF_TYPE_FP32: |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 868 | if (vals.size() != elements) |
| 869 | { |
| 870 | WARNING("The output size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 871 | vals.size(), elements); |
| 872 | return -1; |
| 873 | } |
| 874 | |
| 875 | getTensorValueFloat(elements, vals.data()); |
| 876 | break; |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 877 | case TOSA_REF_TYPE_BF16: |
James Ward | 3d3d45d | 2022-11-28 16:45:36 +0000 | [diff] [blame] | 878 | if (vals.size() != elements) |
| 879 | { |
| 880 | WARNING("The output size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 881 | vals.size(), elements); |
| 882 | return -1; |
| 883 | } |
| 884 | |
| 885 | getTensorValueFloat(elements, vals.data()); |
| 886 | |
| 887 | for (auto v : vals) |
| 888 | { |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 889 | ASSERT_MSG(checkValidBFloat(v), "Float value not a valid bfloat16 value."); |
James Ward | 3d3d45d | 2022-11-28 16:45:36 +0000 | [diff] [blame] | 890 | } |
| 891 | |
| 892 | break; |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 893 | default: |
| 894 | WARNING("The output type (float) doesn't match the data type assigned to the tensor (%s).", |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 895 | EnumNameTOSAREFTYPE(getDtype())); |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 896 | return -2; |
| 897 | } |
| 898 | return 0; |
| 899 | } |
| 900 | |
Grant Watson | 64285a1 | 2022-11-16 15:32:39 +0000 | [diff] [blame] | 901 | int TosaReference::Tensor::writeToVector(ArrayProxy<half_float::half> vals) |
Matthew Sloyan | 2e4d889 | 2022-10-18 18:02:48 +0100 | [diff] [blame] | 902 | { |
| 903 | uint32_t elements = getElementCount(); |
| 904 | std::vector<float> tensor(elements); |
| 905 | |
| 906 | switch (getDtype()) |
| 907 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 908 | case TOSA_REF_TYPE_FP16: |
Matthew Sloyan | 2e4d889 | 2022-10-18 18:02:48 +0100 | [diff] [blame] | 909 | if (vals.size() != elements) |
| 910 | { |
| 911 | WARNING("The output size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 912 | vals.size(), elements); |
| 913 | return -1; |
| 914 | } |
| 915 | |
| 916 | getTensorValueFloat(elements, tensor.data()); |
| 917 | |
| 918 | // Convert fp32 to fp16 |
Jerry Ge | 9c9c8da | 2023-07-19 23:08:16 +0000 | [diff] [blame] | 919 | for (uint32_t i = 0; i < elements; i++) |
Matthew Sloyan | 2e4d889 | 2022-10-18 18:02:48 +0100 | [diff] [blame] | 920 | { |
| 921 | vals[i] = half_float::half_cast<half_float::half, float>(tensor[i]); |
| 922 | } |
| 923 | break; |
| 924 | default: |
| 925 | WARNING("The output type doesn't match the data type assigned to the tensor (%s).", |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 926 | EnumNameTOSAREFTYPE(getDtype())); |
Matthew Sloyan | 2e4d889 | 2022-10-18 18:02:48 +0100 | [diff] [blame] | 927 | return -2; |
| 928 | } |
| 929 | return 0; |
| 930 | } |
| 931 | |
Jerry Ge | c529169 | 2024-01-02 22:29:08 +0000 | [diff] [blame] | 932 | int TosaReference::Tensor::writeToVector(ArrayProxy<int8_t> vals) |
| 933 | { |
| 934 | uint32_t elements = getElementCount(); |
| 935 | switch (getDtype()) |
| 936 | { |
| 937 | case TOSA_REF_TYPE_INT8: |
| 938 | case TOSA_REF_TYPE_UINT8: |
| 939 | if (vals.size() != elements) |
| 940 | { |
| 941 | WARNING("The output size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 942 | vals.size(), elements); |
| 943 | return -1; |
| 944 | } |
| 945 | |
| 946 | getTensorValueInt8(elements, vals.data()); |
| 947 | break; |
| 948 | default: |
| 949 | WARNING("The output type doesn't match the data type assigned to the tensor (%s).", |
| 950 | EnumNameTOSAREFTYPE(getDtype())); |
| 951 | return -2; |
| 952 | } |
| 953 | return 0; |
| 954 | } |
| 955 | |
Georgios Pinitas | e905977 | 2023-12-06 18:52:30 +0000 | [diff] [blame] | 956 | int TosaReference::Tensor::writeToVector(ArrayProxy<int16_t> vals) |
| 957 | { |
| 958 | uint32_t elements = getElementCount(); |
| 959 | |
| 960 | switch (getDtype()) |
| 961 | { |
| 962 | case TOSA_REF_TYPE_INT16: |
| 963 | case TOSA_REF_TYPE_UINT16: |
| 964 | if (vals.size() != elements) |
| 965 | { |
| 966 | WARNING("The output size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 967 | vals.size(), elements); |
| 968 | return -1; |
| 969 | } |
| 970 | |
| 971 | getTensorValueInt16(elements, vals.data()); |
| 972 | break; |
| 973 | default: |
| 974 | WARNING("The output type doesn't match the data type assigned to the tensor (%s).", |
| 975 | EnumNameTOSAREFTYPE(getDtype())); |
| 976 | return -2; |
| 977 | } |
| 978 | return 0; |
| 979 | } |
| 980 | |
Grant Watson | 64285a1 | 2022-11-16 15:32:39 +0000 | [diff] [blame] | 981 | int TosaReference::Tensor::writeToVector(ArrayProxy<int32_t> vals) |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 982 | { |
| 983 | uint32_t elements = getElementCount(); |
| 984 | |
| 985 | switch (getDtype()) |
| 986 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 987 | case TOSA_REF_TYPE_INT32: |
| 988 | case TOSA_REF_TYPE_UINT8: |
| 989 | case TOSA_REF_TYPE_INT4: |
| 990 | case TOSA_REF_TYPE_INT8: |
| 991 | case TOSA_REF_TYPE_INT16: |
| 992 | case TOSA_REF_TYPE_UINT16: |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 993 | if (vals.size() != elements) |
| 994 | { |
| 995 | WARNING("The output size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 996 | vals.size(), elements); |
| 997 | return -1; |
| 998 | } |
| 999 | |
| 1000 | getTensorValueInt32(elements, vals.data()); |
| 1001 | break; |
| 1002 | default: |
| 1003 | WARNING("The output type doesn't match the data type assigned to the tensor (%s).", |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 1004 | EnumNameTOSAREFTYPE(getDtype())); |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 1005 | return -2; |
| 1006 | } |
| 1007 | return 0; |
| 1008 | } |
| 1009 | |
Grant Watson | 64285a1 | 2022-11-16 15:32:39 +0000 | [diff] [blame] | 1010 | int TosaReference::Tensor::writeToVector(ArrayProxy<int64_t> vals) |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 1011 | { |
| 1012 | uint32_t elements = getElementCount(); |
| 1013 | |
| 1014 | switch (getDtype()) |
| 1015 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 1016 | case TOSA_REF_TYPE_INT48: |
Won Jeon | a21b2e8 | 2023-08-10 10:33:01 +0000 | [diff] [blame] | 1017 | case TOSA_REF_TYPE_SHAPE: |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 1018 | if (vals.size() != elements) |
| 1019 | { |
| 1020 | WARNING("The output size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 1021 | vals.size(), elements); |
| 1022 | return -1; |
| 1023 | } |
| 1024 | |
| 1025 | getTensorValueInt64(elements, vals.data()); |
| 1026 | break; |
| 1027 | default: |
| 1028 | WARNING("The output type doesn't match the data type assigned to the tensor (%s).", |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 1029 | EnumNameTOSAREFTYPE(getDtype())); |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 1030 | return -2; |
| 1031 | } |
| 1032 | return 0; |
| 1033 | } |
| 1034 | |
Grant Watson | 64285a1 | 2022-11-16 15:32:39 +0000 | [diff] [blame] | 1035 | int TosaReference::Tensor::writeToVector(ArrayProxy<unsigned char> vals) |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 1036 | { |
| 1037 | uint32_t elements = getElementCount(); |
| 1038 | |
| 1039 | switch (getDtype()) |
| 1040 | { |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 1041 | case TOSA_REF_TYPE_BOOL: |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 1042 | if (vals.size() != elements) |
| 1043 | { |
| 1044 | WARNING("The output size (%ld) doesn't match the number of elements (%d) assigned to the tensor.", |
| 1045 | vals.size(), elements); |
| 1046 | return -1; |
| 1047 | } |
| 1048 | |
| 1049 | getTensorValueBool(elements, reinterpret_cast<bool*>(vals.data())); |
| 1050 | break; |
| 1051 | default: |
| 1052 | WARNING("The output type (bool) doesn't match the data type assigned to the tensor (%s).", |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 1053 | EnumNameTOSAREFTYPE(getDtype())); |
Matthew Sloyan | ba5fad3 | 2022-09-26 13:31:43 +0100 | [diff] [blame] | 1054 | return -2; |
| 1055 | } |
| 1056 | return 0; |
| 1057 | } |
| 1058 | |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 1059 | template <class T> |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 1060 | int TosaReference::TensorTemplate<T>::setTensorValueDouble(const size_t buflen, const double* vals) |
| 1061 | { |
Fabrizio Indirli | 7203835 | 2023-12-11 11:15:32 +0000 | [diff] [blame] | 1062 | FATAL_ERROR("TensorTemplate<T>::setTensorValueDouble should not be called. " |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 1063 | "Implement template specialization version."); |
| 1064 | return 0; |
| 1065 | } |
| 1066 | |
| 1067 | template <> |
| 1068 | int TosaReference::Tensor0<double>::setTensorValueDouble(const size_t bufLen, const double* vals) |
| 1069 | { |
| 1070 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1071 | |
| 1072 | (*tensor)(0) = vals[0]; |
| 1073 | |
| 1074 | return 0; |
| 1075 | } |
| 1076 | |
| 1077 | template <> |
| 1078 | int TosaReference::Tensor1<double>::setTensorValueDouble(const size_t bufLen, const double* vals) |
| 1079 | { |
| 1080 | uint32_t idx = 0; |
| 1081 | |
| 1082 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1083 | |
| 1084 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1085 | { |
| 1086 | (*tensor)(i0) = vals[idx++]; |
| 1087 | } |
| 1088 | |
| 1089 | return 0; |
| 1090 | } |
| 1091 | |
| 1092 | template <> |
| 1093 | int TosaReference::Tensor2<double>::setTensorValueDouble(const size_t bufLen, const double* vals) |
| 1094 | { |
| 1095 | uint32_t idx = 0; |
| 1096 | |
| 1097 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1098 | |
| 1099 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1100 | { |
| 1101 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1102 | { |
| 1103 | (*tensor)(i0, i1) = vals[idx++]; |
| 1104 | } |
| 1105 | } |
| 1106 | |
| 1107 | return 0; |
| 1108 | } |
| 1109 | |
| 1110 | template <> |
| 1111 | int TosaReference::Tensor3<double>::setTensorValueDouble(const size_t bufLen, const double* vals) |
| 1112 | { |
| 1113 | uint32_t idx = 0; |
| 1114 | |
| 1115 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1116 | |
| 1117 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1118 | { |
| 1119 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1120 | { |
| 1121 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1122 | { |
| 1123 | (*tensor)(i0, i1, i2) = vals[idx++]; |
| 1124 | } |
| 1125 | } |
| 1126 | } |
| 1127 | |
| 1128 | return 0; |
| 1129 | } |
| 1130 | |
| 1131 | template <> |
| 1132 | int TosaReference::Tensor4<double>::setTensorValueDouble(const size_t bufLen, const double* vals) |
| 1133 | { |
| 1134 | uint32_t idx = 0; |
| 1135 | |
| 1136 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1137 | |
| 1138 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1139 | { |
| 1140 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1141 | { |
| 1142 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1143 | { |
| 1144 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1145 | { |
| 1146 | (*tensor)(i0, i1, i2, i3) = vals[idx++]; |
| 1147 | } |
| 1148 | } |
| 1149 | } |
| 1150 | } |
| 1151 | |
| 1152 | return 0; |
| 1153 | } |
| 1154 | |
| 1155 | template <> |
| 1156 | int TosaReference::Tensor5<double>::setTensorValueDouble(const size_t bufLen, const double* vals) |
| 1157 | { |
| 1158 | uint32_t idx = 0; |
| 1159 | |
| 1160 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1161 | |
| 1162 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1163 | { |
| 1164 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1165 | { |
| 1166 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1167 | { |
| 1168 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1169 | { |
| 1170 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 1171 | { |
| 1172 | (*tensor)(i0, i1, i2, i3, i4) = vals[idx++]; |
| 1173 | } |
| 1174 | } |
| 1175 | } |
| 1176 | } |
| 1177 | } |
| 1178 | |
| 1179 | return 0; |
| 1180 | } |
| 1181 | |
| 1182 | template <> |
| 1183 | int TosaReference::Tensor6<double>::setTensorValueDouble(const size_t bufLen, const double* vals) |
| 1184 | { |
| 1185 | uint32_t idx = 0; |
| 1186 | |
| 1187 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1188 | |
| 1189 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1190 | { |
| 1191 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1192 | { |
| 1193 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1194 | { |
| 1195 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1196 | { |
| 1197 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 1198 | { |
| 1199 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 1200 | { |
| 1201 | (*tensor)(i0, i1, i2, i3, i4, i5) = vals[idx++]; |
| 1202 | } |
| 1203 | } |
| 1204 | } |
| 1205 | } |
| 1206 | } |
| 1207 | } |
| 1208 | return 0; |
| 1209 | } |
| 1210 | |
| 1211 | template <class T> |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 1212 | int TosaReference::TensorTemplate<T>::setTensorValueFloat(const size_t buflen, const float* vals) |
| 1213 | { |
| 1214 | FATAL_ERROR("TensorTemplate<T>::setTensorValueFloat should not be called. " |
| 1215 | "Implement template specialization version."); |
| 1216 | return 0; |
| 1217 | } |
| 1218 | |
| 1219 | template <> |
| 1220 | int TosaReference::Tensor0<float>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1221 | { |
| 1222 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1223 | |
| 1224 | (*tensor)(0) = vals[0]; |
| 1225 | |
| 1226 | return 0; |
| 1227 | } |
| 1228 | |
| 1229 | template <> |
| 1230 | int TosaReference::Tensor1<float>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1231 | { |
| 1232 | uint32_t idx = 0; |
| 1233 | |
| 1234 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1235 | |
| 1236 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1237 | { |
| 1238 | (*tensor)(i0) = vals[idx++]; |
| 1239 | } |
| 1240 | |
| 1241 | return 0; |
| 1242 | } |
| 1243 | |
| 1244 | template <> |
| 1245 | int TosaReference::Tensor2<float>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1246 | { |
| 1247 | uint32_t idx = 0; |
| 1248 | |
| 1249 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1250 | |
| 1251 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1252 | { |
| 1253 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1254 | { |
| 1255 | (*tensor)(i0, i1) = vals[idx++]; |
| 1256 | } |
| 1257 | } |
| 1258 | |
| 1259 | return 0; |
| 1260 | } |
| 1261 | |
| 1262 | template <> |
| 1263 | int TosaReference::Tensor3<float>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1264 | { |
| 1265 | uint32_t idx = 0; |
| 1266 | |
| 1267 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1268 | |
| 1269 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1270 | { |
| 1271 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1272 | { |
| 1273 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1274 | { |
| 1275 | (*tensor)(i0, i1, i2) = vals[idx++]; |
| 1276 | } |
| 1277 | } |
| 1278 | } |
| 1279 | |
| 1280 | return 0; |
| 1281 | } |
| 1282 | |
| 1283 | template <> |
| 1284 | int TosaReference::Tensor4<float>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1285 | { |
| 1286 | uint32_t idx = 0; |
| 1287 | |
| 1288 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1289 | |
| 1290 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1291 | { |
| 1292 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1293 | { |
| 1294 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1295 | { |
| 1296 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1297 | { |
| 1298 | (*tensor)(i0, i1, i2, i3) = vals[idx++]; |
| 1299 | } |
| 1300 | } |
| 1301 | } |
| 1302 | } |
| 1303 | |
| 1304 | return 0; |
| 1305 | } |
| 1306 | |
| 1307 | template <> |
| 1308 | int TosaReference::Tensor5<float>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1309 | { |
| 1310 | uint32_t idx = 0; |
| 1311 | |
| 1312 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1313 | |
| 1314 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1315 | { |
| 1316 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1317 | { |
| 1318 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1319 | { |
| 1320 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1321 | { |
| 1322 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 1323 | { |
| 1324 | (*tensor)(i0, i1, i2, i3, i4) = vals[idx++]; |
| 1325 | } |
| 1326 | } |
| 1327 | } |
| 1328 | } |
| 1329 | } |
| 1330 | |
| 1331 | return 0; |
| 1332 | } |
| 1333 | |
| 1334 | template <> |
| 1335 | int TosaReference::Tensor6<float>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1336 | { |
| 1337 | uint32_t idx = 0; |
| 1338 | |
| 1339 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1340 | |
| 1341 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1342 | { |
| 1343 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1344 | { |
| 1345 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1346 | { |
| 1347 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1348 | { |
| 1349 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 1350 | { |
| 1351 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 1352 | { |
| 1353 | (*tensor)(i0, i1, i2, i3, i4, i5) = vals[idx++]; |
| 1354 | } |
| 1355 | } |
| 1356 | } |
| 1357 | } |
| 1358 | } |
| 1359 | } |
| 1360 | return 0; |
| 1361 | } |
| 1362 | |
Fabrizio Indirli | 7203835 | 2023-12-11 11:15:32 +0000 | [diff] [blame] | 1363 | template <> |
| 1364 | int TosaReference::Tensor0<double>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1365 | { |
| 1366 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1367 | |
| 1368 | (*tensor)(0) = vals[0]; |
| 1369 | |
| 1370 | return 0; |
| 1371 | } |
| 1372 | |
| 1373 | template <> |
| 1374 | int TosaReference::Tensor1<double>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1375 | { |
| 1376 | uint32_t idx = 0; |
| 1377 | |
| 1378 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1379 | |
| 1380 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1381 | { |
| 1382 | (*tensor)(i0) = vals[idx++]; |
| 1383 | } |
| 1384 | |
| 1385 | return 0; |
| 1386 | } |
| 1387 | |
| 1388 | template <> |
| 1389 | int TosaReference::Tensor2<double>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1390 | { |
| 1391 | uint32_t idx = 0; |
| 1392 | |
| 1393 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1394 | |
| 1395 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1396 | { |
| 1397 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1398 | { |
| 1399 | (*tensor)(i0, i1) = vals[idx++]; |
| 1400 | } |
| 1401 | } |
| 1402 | |
| 1403 | return 0; |
| 1404 | } |
| 1405 | |
| 1406 | template <> |
| 1407 | int TosaReference::Tensor3<double>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1408 | { |
| 1409 | uint32_t idx = 0; |
| 1410 | |
| 1411 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1412 | |
| 1413 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1414 | { |
| 1415 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1416 | { |
| 1417 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1418 | { |
| 1419 | (*tensor)(i0, i1, i2) = vals[idx++]; |
| 1420 | } |
| 1421 | } |
| 1422 | } |
| 1423 | |
| 1424 | return 0; |
| 1425 | } |
| 1426 | |
| 1427 | template <> |
| 1428 | int TosaReference::Tensor4<double>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1429 | { |
| 1430 | uint32_t idx = 0; |
| 1431 | |
| 1432 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1433 | |
| 1434 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1435 | { |
| 1436 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1437 | { |
| 1438 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1439 | { |
| 1440 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1441 | { |
| 1442 | (*tensor)(i0, i1, i2, i3) = vals[idx++]; |
| 1443 | } |
| 1444 | } |
| 1445 | } |
| 1446 | } |
| 1447 | |
| 1448 | return 0; |
| 1449 | } |
| 1450 | |
| 1451 | template <> |
| 1452 | int TosaReference::Tensor5<double>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1453 | { |
| 1454 | uint32_t idx = 0; |
| 1455 | |
| 1456 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1457 | |
| 1458 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1459 | { |
| 1460 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1461 | { |
| 1462 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1463 | { |
| 1464 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1465 | { |
| 1466 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 1467 | { |
| 1468 | (*tensor)(i0, i1, i2, i3, i4) = vals[idx++]; |
| 1469 | } |
| 1470 | } |
| 1471 | } |
| 1472 | } |
| 1473 | } |
| 1474 | |
| 1475 | return 0; |
| 1476 | } |
| 1477 | |
| 1478 | template <> |
| 1479 | int TosaReference::Tensor6<double>::setTensorValueFloat(const size_t bufLen, const float* vals) |
| 1480 | { |
| 1481 | uint32_t idx = 0; |
| 1482 | |
| 1483 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1484 | |
| 1485 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1486 | { |
| 1487 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1488 | { |
| 1489 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1490 | { |
| 1491 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1492 | { |
| 1493 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 1494 | { |
| 1495 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 1496 | { |
| 1497 | (*tensor)(i0, i1, i2, i3, i4, i5) = vals[idx++]; |
| 1498 | } |
| 1499 | } |
| 1500 | } |
| 1501 | } |
| 1502 | } |
| 1503 | } |
| 1504 | return 0; |
| 1505 | } |
| 1506 | |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 1507 | template <class T> |
Jerry Ge | c529169 | 2024-01-02 22:29:08 +0000 | [diff] [blame] | 1508 | int TosaReference::TensorTemplate<T>::setTensorValueUInt8(const size_t bufLen, const uint8_t* vals) |
| 1509 | { |
| 1510 | FATAL_ERROR("TensorTemplate<T>::setTensorValueUInt8 should not be called. " |
| 1511 | "Implement template specialization version."); |
| 1512 | return 0; |
| 1513 | } |
| 1514 | |
| 1515 | template <> |
| 1516 | int TosaReference::Tensor0<int32_t>::setTensorValueUInt8(const size_t bufLen, const uint8_t* vals) |
| 1517 | { |
| 1518 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1519 | |
| 1520 | (*tensor)(0) = static_cast<int32_t>(vals[0]); |
| 1521 | |
| 1522 | return 0; |
| 1523 | } |
| 1524 | |
| 1525 | template <> |
| 1526 | int TosaReference::Tensor1<int32_t>::setTensorValueUInt8(const size_t bufLen, const uint8_t* vals) |
| 1527 | { |
| 1528 | uint32_t idx = 0; |
| 1529 | |
| 1530 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1531 | |
| 1532 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1533 | { |
| 1534 | (*tensor)(i0) = static_cast<int32_t>(vals[idx++]); |
| 1535 | } |
| 1536 | |
| 1537 | return 0; |
| 1538 | } |
| 1539 | |
| 1540 | template <> |
| 1541 | int TosaReference::Tensor2<int32_t>::setTensorValueUInt8(const size_t bufLen, const uint8_t* vals) |
| 1542 | { |
| 1543 | uint32_t idx = 0; |
| 1544 | |
| 1545 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1546 | |
| 1547 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1548 | { |
| 1549 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1550 | { |
| 1551 | (*tensor)(i0, i1) = static_cast<int32_t>(vals[idx++]); |
| 1552 | } |
| 1553 | } |
| 1554 | |
| 1555 | return 0; |
| 1556 | } |
| 1557 | |
| 1558 | template <> |
| 1559 | int TosaReference::Tensor3<int32_t>::setTensorValueUInt8(const size_t bufLen, const uint8_t* vals) |
| 1560 | { |
| 1561 | uint32_t idx = 0; |
| 1562 | |
| 1563 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1564 | |
| 1565 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1566 | { |
| 1567 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1568 | { |
| 1569 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1570 | { |
| 1571 | (*tensor)(i0, i1, i2) = static_cast<int32_t>(vals[idx++]); |
| 1572 | } |
| 1573 | } |
| 1574 | } |
| 1575 | |
| 1576 | return 0; |
| 1577 | } |
| 1578 | |
| 1579 | template <> |
| 1580 | int TosaReference::Tensor4<int32_t>::setTensorValueUInt8(const size_t bufLen, const uint8_t* vals) |
| 1581 | { |
| 1582 | uint32_t idx = 0; |
| 1583 | |
| 1584 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1585 | |
| 1586 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1587 | { |
| 1588 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1589 | { |
| 1590 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1591 | { |
| 1592 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1593 | { |
| 1594 | (*tensor)(i0, i1, i2, i3) = static_cast<int32_t>(vals[idx++]); |
| 1595 | } |
| 1596 | } |
| 1597 | } |
| 1598 | } |
| 1599 | |
| 1600 | return 0; |
| 1601 | } |
| 1602 | |
| 1603 | template <> |
| 1604 | int TosaReference::Tensor5<int32_t>::setTensorValueUInt8(const size_t bufLen, const uint8_t* vals) |
| 1605 | { |
| 1606 | uint32_t idx = 0; |
| 1607 | |
| 1608 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1609 | |
| 1610 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1611 | { |
| 1612 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1613 | { |
| 1614 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1615 | { |
| 1616 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1617 | { |
| 1618 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 1619 | { |
| 1620 | (*tensor)(i0, i1, i2, i3, i4) = static_cast<int32_t>(vals[idx++]); |
| 1621 | } |
| 1622 | } |
| 1623 | } |
| 1624 | } |
| 1625 | } |
| 1626 | |
| 1627 | return 0; |
| 1628 | } |
| 1629 | |
| 1630 | template <> |
| 1631 | int TosaReference::Tensor6<int32_t>::setTensorValueUInt8(const size_t bufLen, const uint8_t* vals) |
| 1632 | { |
| 1633 | uint32_t idx = 0; |
| 1634 | |
| 1635 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1636 | |
| 1637 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1638 | { |
| 1639 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1640 | { |
| 1641 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1642 | { |
| 1643 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1644 | { |
| 1645 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 1646 | { |
| 1647 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 1648 | { |
| 1649 | (*tensor)(i0, i1, i2, i3, i4, i5) = static_cast<int32_t>(vals[idx++]); |
| 1650 | } |
| 1651 | } |
| 1652 | } |
| 1653 | } |
| 1654 | } |
| 1655 | } |
| 1656 | return 0; |
| 1657 | } |
| 1658 | |
| 1659 | template <class T> |
| 1660 | int TosaReference::TensorTemplate<T>::setTensorValueInt8(const size_t bufLen, const int8_t* vals) |
| 1661 | { |
| 1662 | FATAL_ERROR("TensorTemplate<T>::setTensorValueInt8 should not be called. " |
| 1663 | "Implement template specialization version."); |
| 1664 | return 0; |
| 1665 | } |
| 1666 | |
| 1667 | template <> |
| 1668 | int TosaReference::Tensor0<int32_t>::setTensorValueInt8(const size_t bufLen, const int8_t* vals) |
| 1669 | { |
| 1670 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1671 | |
| 1672 | (*tensor)(0) = static_cast<int32_t>(vals[0]); |
| 1673 | |
| 1674 | return 0; |
| 1675 | } |
| 1676 | |
| 1677 | template <> |
| 1678 | int TosaReference::Tensor1<int32_t>::setTensorValueInt8(const size_t bufLen, const int8_t* vals) |
| 1679 | { |
| 1680 | uint32_t idx = 0; |
| 1681 | |
| 1682 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1683 | |
| 1684 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1685 | { |
| 1686 | (*tensor)(i0) = static_cast<int32_t>(vals[idx++]); |
| 1687 | } |
| 1688 | |
| 1689 | return 0; |
| 1690 | } |
| 1691 | |
| 1692 | template <> |
| 1693 | int TosaReference::Tensor2<int32_t>::setTensorValueInt8(const size_t bufLen, const int8_t* vals) |
| 1694 | { |
| 1695 | uint32_t idx = 0; |
| 1696 | |
| 1697 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1698 | |
| 1699 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1700 | { |
| 1701 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1702 | { |
| 1703 | (*tensor)(i0, i1) = static_cast<int32_t>(vals[idx++]); |
| 1704 | } |
| 1705 | } |
| 1706 | |
| 1707 | return 0; |
| 1708 | } |
| 1709 | |
| 1710 | template <> |
| 1711 | int TosaReference::Tensor3<int32_t>::setTensorValueInt8(const size_t bufLen, const int8_t* vals) |
| 1712 | { |
| 1713 | uint32_t idx = 0; |
| 1714 | |
| 1715 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1716 | |
| 1717 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1718 | { |
| 1719 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1720 | { |
| 1721 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1722 | { |
| 1723 | (*tensor)(i0, i1, i2) = static_cast<int32_t>(vals[idx++]); |
| 1724 | } |
| 1725 | } |
| 1726 | } |
| 1727 | |
| 1728 | return 0; |
| 1729 | } |
| 1730 | |
| 1731 | template <> |
| 1732 | int TosaReference::Tensor4<int32_t>::setTensorValueInt8(const size_t bufLen, const int8_t* vals) |
| 1733 | { |
| 1734 | uint32_t idx = 0; |
| 1735 | |
| 1736 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1737 | |
| 1738 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1739 | { |
| 1740 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1741 | { |
| 1742 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1743 | { |
| 1744 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1745 | { |
| 1746 | (*tensor)(i0, i1, i2, i3) = static_cast<int32_t>(vals[idx++]); |
| 1747 | } |
| 1748 | } |
| 1749 | } |
| 1750 | } |
| 1751 | |
| 1752 | return 0; |
| 1753 | } |
| 1754 | |
| 1755 | template <> |
| 1756 | int TosaReference::Tensor5<int32_t>::setTensorValueInt8(const size_t bufLen, const int8_t* vals) |
| 1757 | { |
| 1758 | uint32_t idx = 0; |
| 1759 | |
| 1760 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1761 | |
| 1762 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1763 | { |
| 1764 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1765 | { |
| 1766 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1767 | { |
| 1768 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1769 | { |
| 1770 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 1771 | { |
| 1772 | (*tensor)(i0, i1, i2, i3, i4) = static_cast<int32_t>(vals[idx++]); |
| 1773 | } |
| 1774 | } |
| 1775 | } |
| 1776 | } |
| 1777 | } |
| 1778 | |
| 1779 | return 0; |
| 1780 | } |
| 1781 | |
| 1782 | template <> |
| 1783 | int TosaReference::Tensor6<int32_t>::setTensorValueInt8(const size_t bufLen, const int8_t* vals) |
| 1784 | { |
| 1785 | uint32_t idx = 0; |
| 1786 | |
| 1787 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1788 | |
| 1789 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1790 | { |
| 1791 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1792 | { |
| 1793 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1794 | { |
| 1795 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1796 | { |
| 1797 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 1798 | { |
| 1799 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 1800 | { |
| 1801 | (*tensor)(i0, i1, i2, i3, i4, i5) = static_cast<int32_t>(vals[idx++]); |
| 1802 | } |
| 1803 | } |
| 1804 | } |
| 1805 | } |
| 1806 | } |
| 1807 | } |
| 1808 | return 0; |
| 1809 | } |
| 1810 | |
| 1811 | template <class T> |
Georgios Pinitas | e905977 | 2023-12-06 18:52:30 +0000 | [diff] [blame] | 1812 | int TosaReference::TensorTemplate<T>::setTensorValueInt16(const size_t bufLen, const int16_t* vals) |
| 1813 | { |
| 1814 | FATAL_ERROR("TensorTemplate<T>::setTensorValueInt32 should not be called. " |
| 1815 | "Implement template specialization version."); |
| 1816 | return 0; |
| 1817 | } |
| 1818 | |
| 1819 | template <> |
| 1820 | int TosaReference::Tensor0<int32_t>::setTensorValueInt16(const size_t bufLen, const int16_t* vals) |
| 1821 | { |
| 1822 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1823 | |
| 1824 | (*tensor)(0) = static_cast<int32_t>(vals[0]); |
| 1825 | |
| 1826 | return 0; |
| 1827 | } |
| 1828 | |
| 1829 | template <> |
| 1830 | int TosaReference::Tensor1<int32_t>::setTensorValueInt16(const size_t bufLen, const int16_t* vals) |
| 1831 | { |
| 1832 | uint32_t idx = 0; |
| 1833 | |
| 1834 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1835 | |
| 1836 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1837 | { |
| 1838 | (*tensor)(i0) = static_cast<int32_t>(vals[idx++]); |
| 1839 | } |
| 1840 | |
| 1841 | return 0; |
| 1842 | } |
| 1843 | |
| 1844 | template <> |
| 1845 | int TosaReference::Tensor2<int32_t>::setTensorValueInt16(const size_t bufLen, const int16_t* vals) |
| 1846 | { |
| 1847 | uint32_t idx = 0; |
| 1848 | |
| 1849 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1850 | |
| 1851 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1852 | { |
| 1853 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1854 | { |
| 1855 | (*tensor)(i0, i1) = static_cast<int32_t>(vals[idx++]); |
| 1856 | } |
| 1857 | } |
| 1858 | |
| 1859 | return 0; |
| 1860 | } |
| 1861 | |
| 1862 | template <> |
| 1863 | int TosaReference::Tensor3<int32_t>::setTensorValueInt16(const size_t bufLen, const int16_t* vals) |
| 1864 | { |
| 1865 | uint32_t idx = 0; |
| 1866 | |
| 1867 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1868 | |
| 1869 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1870 | { |
| 1871 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1872 | { |
| 1873 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1874 | { |
| 1875 | (*tensor)(i0, i1, i2) = static_cast<int32_t>(vals[idx++]); |
| 1876 | } |
| 1877 | } |
| 1878 | } |
| 1879 | |
| 1880 | return 0; |
| 1881 | } |
| 1882 | |
| 1883 | template <> |
| 1884 | int TosaReference::Tensor4<int32_t>::setTensorValueInt16(const size_t bufLen, const int16_t* vals) |
| 1885 | { |
| 1886 | uint32_t idx = 0; |
| 1887 | |
| 1888 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1889 | |
| 1890 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1891 | { |
| 1892 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1893 | { |
| 1894 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1895 | { |
| 1896 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1897 | { |
| 1898 | (*tensor)(i0, i1, i2, i3) = static_cast<int32_t>(vals[idx++]); |
| 1899 | } |
| 1900 | } |
| 1901 | } |
| 1902 | } |
| 1903 | |
| 1904 | return 0; |
| 1905 | } |
| 1906 | |
| 1907 | template <> |
| 1908 | int TosaReference::Tensor5<int32_t>::setTensorValueInt16(const size_t bufLen, const int16_t* vals) |
| 1909 | { |
| 1910 | uint32_t idx = 0; |
| 1911 | |
| 1912 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1913 | |
| 1914 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1915 | { |
| 1916 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1917 | { |
| 1918 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1919 | { |
| 1920 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1921 | { |
| 1922 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 1923 | { |
| 1924 | (*tensor)(i0, i1, i2, i3, i4) = static_cast<int32_t>(vals[idx++]); |
| 1925 | } |
| 1926 | } |
| 1927 | } |
| 1928 | } |
| 1929 | } |
| 1930 | |
| 1931 | return 0; |
| 1932 | } |
| 1933 | |
| 1934 | template <> |
| 1935 | int TosaReference::Tensor6<int32_t>::setTensorValueInt16(const size_t bufLen, const int16_t* vals) |
| 1936 | { |
| 1937 | uint32_t idx = 0; |
| 1938 | |
| 1939 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1940 | |
| 1941 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1942 | { |
| 1943 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 1944 | { |
| 1945 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 1946 | { |
| 1947 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 1948 | { |
| 1949 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 1950 | { |
| 1951 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 1952 | { |
| 1953 | (*tensor)(i0, i1, i2, i3, i4, i5) = static_cast<int32_t>(vals[idx++]); |
| 1954 | } |
| 1955 | } |
| 1956 | } |
| 1957 | } |
| 1958 | } |
| 1959 | } |
| 1960 | return 0; |
| 1961 | } |
| 1962 | |
| 1963 | template <class T> |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 1964 | int TosaReference::TensorTemplate<T>::setTensorValueInt32(const size_t bufLen, const int32_t* vals) |
| 1965 | { |
| 1966 | FATAL_ERROR("TensorTemplate<T>::setTensorValueInt32 should not be called. " |
| 1967 | "Implement template specialization version."); |
| 1968 | return 0; |
| 1969 | } |
| 1970 | |
| 1971 | template <> |
| 1972 | int TosaReference::Tensor0<int32_t>::setTensorValueInt32(const size_t bufLen, const int32_t* vals) |
| 1973 | { |
| 1974 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1975 | |
| 1976 | (*tensor)(0) = vals[0]; |
| 1977 | |
| 1978 | return 0; |
| 1979 | } |
| 1980 | |
| 1981 | template <> |
| 1982 | int TosaReference::Tensor1<int32_t>::setTensorValueInt32(const size_t bufLen, const int32_t* vals) |
| 1983 | { |
| 1984 | uint32_t idx = 0; |
| 1985 | |
| 1986 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 1987 | |
| 1988 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 1989 | { |
| 1990 | (*tensor)(i0) = vals[idx++]; |
| 1991 | } |
| 1992 | |
| 1993 | return 0; |
| 1994 | } |
| 1995 | |
| 1996 | template <> |
| 1997 | int TosaReference::Tensor2<int32_t>::setTensorValueInt32(const size_t bufLen, const int32_t* vals) |
| 1998 | { |
| 1999 | uint32_t idx = 0; |
| 2000 | |
| 2001 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2002 | |
| 2003 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2004 | { |
| 2005 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2006 | { |
| 2007 | (*tensor)(i0, i1) = vals[idx++]; |
| 2008 | } |
| 2009 | } |
| 2010 | |
| 2011 | return 0; |
| 2012 | } |
| 2013 | |
| 2014 | template <> |
| 2015 | int TosaReference::Tensor3<int32_t>::setTensorValueInt32(const size_t bufLen, const int32_t* vals) |
| 2016 | { |
| 2017 | uint32_t idx = 0; |
| 2018 | |
| 2019 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2020 | |
| 2021 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2022 | { |
| 2023 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2024 | { |
| 2025 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2026 | { |
| 2027 | (*tensor)(i0, i1, i2) = vals[idx++]; |
| 2028 | } |
| 2029 | } |
| 2030 | } |
| 2031 | |
| 2032 | return 0; |
| 2033 | } |
| 2034 | |
| 2035 | template <> |
| 2036 | int TosaReference::Tensor4<int32_t>::setTensorValueInt32(const size_t bufLen, const int32_t* vals) |
| 2037 | { |
| 2038 | uint32_t idx = 0; |
| 2039 | |
| 2040 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2041 | |
| 2042 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2043 | { |
| 2044 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2045 | { |
| 2046 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2047 | { |
| 2048 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2049 | { |
| 2050 | (*tensor)(i0, i1, i2, i3) = vals[idx++]; |
| 2051 | } |
| 2052 | } |
| 2053 | } |
| 2054 | } |
| 2055 | |
| 2056 | return 0; |
| 2057 | } |
| 2058 | |
| 2059 | template <> |
| 2060 | int TosaReference::Tensor5<int32_t>::setTensorValueInt32(const size_t bufLen, const int32_t* vals) |
| 2061 | { |
| 2062 | uint32_t idx = 0; |
| 2063 | |
| 2064 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2065 | |
| 2066 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2067 | { |
| 2068 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2069 | { |
| 2070 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2071 | { |
| 2072 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2073 | { |
| 2074 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 2075 | { |
| 2076 | (*tensor)(i0, i1, i2, i3, i4) = vals[idx++]; |
| 2077 | } |
| 2078 | } |
| 2079 | } |
| 2080 | } |
| 2081 | } |
| 2082 | |
| 2083 | return 0; |
| 2084 | } |
| 2085 | |
| 2086 | template <> |
| 2087 | int TosaReference::Tensor6<int32_t>::setTensorValueInt32(const size_t bufLen, const int32_t* vals) |
| 2088 | { |
| 2089 | uint32_t idx = 0; |
| 2090 | |
| 2091 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2092 | |
| 2093 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2094 | { |
| 2095 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2096 | { |
| 2097 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2098 | { |
| 2099 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2100 | { |
| 2101 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 2102 | { |
| 2103 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 2104 | { |
| 2105 | (*tensor)(i0, i1, i2, i3, i4, i5) = vals[idx++]; |
| 2106 | } |
| 2107 | } |
| 2108 | } |
| 2109 | } |
| 2110 | } |
| 2111 | } |
| 2112 | return 0; |
| 2113 | } |
| 2114 | |
| 2115 | template <class T> |
| 2116 | int TosaReference::TensorTemplate<T>::setTensorValueInt64(const size_t bufLen, const int64_t* vals) |
| 2117 | { |
| 2118 | FATAL_ERROR("TensorTemplate<T>::setTensorValueInt64 should not be called. " |
| 2119 | "Implement template specialization version."); |
| 2120 | return 0; |
| 2121 | } |
| 2122 | |
| 2123 | template <> |
| 2124 | int TosaReference::Tensor0<int64_t>::setTensorValueInt64(const size_t bufLen, const int64_t* vals) |
| 2125 | { |
| 2126 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2127 | |
| 2128 | (*tensor)(0) = vals[0]; |
| 2129 | |
| 2130 | return 0; |
| 2131 | } |
| 2132 | |
| 2133 | template <> |
| 2134 | int TosaReference::Tensor1<int64_t>::setTensorValueInt64(const size_t bufLen, const int64_t* vals) |
| 2135 | { |
| 2136 | uint32_t idx = 0; |
| 2137 | |
| 2138 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2139 | |
| 2140 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2141 | { |
| 2142 | (*tensor)(i0) = vals[idx++]; |
| 2143 | } |
| 2144 | |
| 2145 | return 0; |
| 2146 | } |
| 2147 | |
| 2148 | template <> |
| 2149 | int TosaReference::Tensor2<int64_t>::setTensorValueInt64(const size_t bufLen, const int64_t* vals) |
| 2150 | { |
| 2151 | uint32_t idx = 0; |
| 2152 | |
| 2153 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2154 | |
| 2155 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2156 | { |
| 2157 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2158 | { |
| 2159 | (*tensor)(i0, i1) = vals[idx++]; |
| 2160 | } |
| 2161 | } |
| 2162 | |
| 2163 | return 0; |
| 2164 | } |
| 2165 | |
| 2166 | template <> |
| 2167 | int TosaReference::Tensor3<int64_t>::setTensorValueInt64(const size_t bufLen, const int64_t* vals) |
| 2168 | { |
| 2169 | uint32_t idx = 0; |
| 2170 | |
| 2171 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2172 | |
| 2173 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2174 | { |
| 2175 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2176 | { |
| 2177 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2178 | { |
| 2179 | (*tensor)(i0, i1, i2) = vals[idx++]; |
| 2180 | } |
| 2181 | } |
| 2182 | } |
| 2183 | |
| 2184 | return 0; |
| 2185 | } |
| 2186 | |
| 2187 | template <> |
| 2188 | int TosaReference::Tensor4<int64_t>::setTensorValueInt64(const size_t bufLen, const int64_t* vals) |
| 2189 | { |
| 2190 | uint32_t idx = 0; |
| 2191 | |
| 2192 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2193 | |
| 2194 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2195 | { |
| 2196 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2197 | { |
| 2198 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2199 | { |
| 2200 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2201 | { |
| 2202 | (*tensor)(i0, i1, i2, i3) = vals[idx++]; |
| 2203 | } |
| 2204 | } |
| 2205 | } |
| 2206 | } |
| 2207 | |
| 2208 | return 0; |
| 2209 | } |
| 2210 | |
| 2211 | template <> |
| 2212 | int TosaReference::Tensor5<int64_t>::setTensorValueInt64(const size_t bufLen, const int64_t* vals) |
| 2213 | { |
| 2214 | uint32_t idx = 0; |
| 2215 | |
| 2216 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2217 | |
| 2218 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2219 | { |
| 2220 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2221 | { |
| 2222 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2223 | { |
| 2224 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2225 | { |
| 2226 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 2227 | { |
| 2228 | (*tensor)(i0, i1, i2, i3, i4) = vals[idx++]; |
| 2229 | } |
| 2230 | } |
| 2231 | } |
| 2232 | } |
| 2233 | } |
| 2234 | |
| 2235 | return 0; |
| 2236 | } |
| 2237 | |
| 2238 | template <> |
| 2239 | int TosaReference::Tensor6<int64_t>::setTensorValueInt64(const size_t bufLen, const int64_t* vals) |
| 2240 | { |
| 2241 | uint32_t idx = 0; |
| 2242 | |
| 2243 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2244 | |
| 2245 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2246 | { |
| 2247 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2248 | { |
| 2249 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2250 | { |
| 2251 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2252 | { |
| 2253 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 2254 | { |
| 2255 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 2256 | { |
| 2257 | (*tensor)(i0, i1, i2, i3, i4, i5) = vals[idx++]; |
| 2258 | } |
| 2259 | } |
| 2260 | } |
| 2261 | } |
| 2262 | } |
| 2263 | } |
| 2264 | return 0; |
| 2265 | } |
| 2266 | |
| 2267 | template <class T> |
| 2268 | int TosaReference::TensorTemplate<T>::setTensorValueBool(const size_t buflen, const bool* vals) |
| 2269 | { |
| 2270 | FATAL_ERROR("TensorTemplate<T>::setTensorValueBool should not be called. " |
| 2271 | "Implement template specialization version."); |
| 2272 | return 0; |
| 2273 | } |
| 2274 | |
| 2275 | template <> |
| 2276 | int TosaReference::Tensor0<bool>::setTensorValueBool(const size_t bufLen, const bool* vals) |
| 2277 | { |
| 2278 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2279 | |
| 2280 | (*tensor)(0) = vals[0]; |
| 2281 | |
| 2282 | return 0; |
| 2283 | } |
| 2284 | |
| 2285 | template <> |
| 2286 | int TosaReference::Tensor1<bool>::setTensorValueBool(const size_t bufLen, const bool* vals) |
| 2287 | { |
| 2288 | uint32_t idx = 0; |
| 2289 | |
| 2290 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2291 | |
| 2292 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2293 | { |
| 2294 | (*tensor)(i0) = vals[idx++]; |
| 2295 | } |
| 2296 | |
| 2297 | return 0; |
| 2298 | } |
| 2299 | |
| 2300 | template <> |
| 2301 | int TosaReference::Tensor2<bool>::setTensorValueBool(const size_t bufLen, const bool* vals) |
| 2302 | { |
| 2303 | uint32_t idx = 0; |
| 2304 | |
| 2305 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2306 | |
| 2307 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2308 | { |
| 2309 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2310 | { |
| 2311 | (*tensor)(i0, i1) = vals[idx++]; |
| 2312 | } |
| 2313 | } |
| 2314 | |
| 2315 | return 0; |
| 2316 | } |
| 2317 | |
| 2318 | template <> |
| 2319 | int TosaReference::Tensor3<bool>::setTensorValueBool(const size_t bufLen, const bool* vals) |
| 2320 | { |
| 2321 | uint32_t idx = 0; |
| 2322 | |
| 2323 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2324 | |
| 2325 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2326 | { |
| 2327 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2328 | { |
| 2329 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2330 | { |
| 2331 | (*tensor)(i0, i1, i2) = vals[idx++]; |
| 2332 | } |
| 2333 | } |
| 2334 | } |
| 2335 | |
| 2336 | return 0; |
| 2337 | } |
| 2338 | |
| 2339 | template <> |
| 2340 | int TosaReference::Tensor4<bool>::setTensorValueBool(const size_t bufLen, const bool* vals) |
| 2341 | { |
| 2342 | uint32_t idx = 0; |
| 2343 | |
| 2344 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2345 | |
| 2346 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2347 | { |
| 2348 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2349 | { |
| 2350 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2351 | { |
| 2352 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2353 | { |
| 2354 | (*tensor)(i0, i1, i2, i3) = vals[idx++]; |
| 2355 | } |
| 2356 | } |
| 2357 | } |
| 2358 | } |
| 2359 | |
| 2360 | return 0; |
| 2361 | } |
| 2362 | |
| 2363 | template <> |
| 2364 | int TosaReference::Tensor5<bool>::setTensorValueBool(const size_t bufLen, const bool* vals) |
| 2365 | { |
| 2366 | uint32_t idx = 0; |
| 2367 | |
| 2368 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2369 | |
| 2370 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2371 | { |
| 2372 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2373 | { |
| 2374 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2375 | { |
| 2376 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2377 | { |
| 2378 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 2379 | { |
| 2380 | (*tensor)(i0, i1, i2, i3, i4) = vals[idx++]; |
| 2381 | } |
| 2382 | } |
| 2383 | } |
| 2384 | } |
| 2385 | } |
| 2386 | |
| 2387 | return 0; |
| 2388 | } |
| 2389 | |
| 2390 | template <> |
| 2391 | int TosaReference::Tensor6<bool>::setTensorValueBool(const size_t bufLen, const bool* vals) |
| 2392 | { |
| 2393 | uint32_t idx = 0; |
| 2394 | |
| 2395 | ASSERT_MSG(bufLen == getElementCount(), "Total elements must match"); |
| 2396 | |
| 2397 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2398 | { |
| 2399 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2400 | { |
| 2401 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2402 | { |
| 2403 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2404 | { |
| 2405 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 2406 | { |
| 2407 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 2408 | { |
| 2409 | (*tensor)(i0, i1, i2, i3, i4, i5) = vals[idx++]; |
| 2410 | } |
| 2411 | } |
| 2412 | } |
| 2413 | } |
| 2414 | } |
| 2415 | } |
| 2416 | return 0; |
| 2417 | } |
| 2418 | |
| 2419 | template <class T> |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 2420 | int TosaReference::TensorTemplate<T>::getTensorValueDouble(const size_t bufLen, double* vals) const |
| 2421 | { |
| 2422 | FATAL_ERROR("TensorTemplate<T>::getTensorValueDouble should not be called. " |
| 2423 | "Implement template specialization version."); |
| 2424 | return 0; |
| 2425 | } |
| 2426 | |
| 2427 | template <> |
| 2428 | int TosaReference::Tensor0<double>::getTensorValueDouble(const size_t bufLen, double* vals) const |
| 2429 | { |
| 2430 | int totalVals = 1; |
| 2431 | |
| 2432 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2433 | |
| 2434 | vals[0] = (*tensor)(0); |
| 2435 | |
| 2436 | return 0; |
| 2437 | } |
| 2438 | |
| 2439 | template <> |
| 2440 | int TosaReference::Tensor1<double>::getTensorValueDouble(const size_t bufLen, double* vals) const |
| 2441 | { |
| 2442 | uint32_t idx = 0; |
| 2443 | int totalVals = 1; |
| 2444 | |
| 2445 | for (size_t i = 0; i < shape.size(); i++) |
| 2446 | { |
| 2447 | totalVals *= shape[i]; |
| 2448 | } |
| 2449 | |
| 2450 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2451 | |
| 2452 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2453 | { |
| 2454 | vals[idx++] = (*tensor)(i0); |
| 2455 | } |
| 2456 | |
| 2457 | return 0; |
| 2458 | } |
| 2459 | |
| 2460 | template <> |
| 2461 | int TosaReference::Tensor2<double>::getTensorValueDouble(const size_t bufLen, double* vals) const |
| 2462 | { |
| 2463 | uint32_t idx = 0; |
| 2464 | int totalVals = 1; |
| 2465 | |
| 2466 | for (size_t i = 0; i < shape.size(); i++) |
| 2467 | { |
| 2468 | totalVals *= shape[i]; |
| 2469 | } |
| 2470 | |
| 2471 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2472 | |
| 2473 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2474 | { |
| 2475 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2476 | { |
| 2477 | vals[idx++] = (*tensor)(i0, i1); |
| 2478 | } |
| 2479 | } |
| 2480 | |
| 2481 | return 0; |
| 2482 | } |
| 2483 | |
| 2484 | template <> |
| 2485 | int TosaReference::Tensor3<double>::getTensorValueDouble(const size_t bufLen, double* vals) const |
| 2486 | { |
| 2487 | uint32_t idx = 0; |
| 2488 | int totalVals = 1; |
| 2489 | |
| 2490 | for (size_t i = 0; i < shape.size(); i++) |
| 2491 | { |
| 2492 | totalVals *= shape[i]; |
| 2493 | } |
| 2494 | |
| 2495 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2496 | |
| 2497 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2498 | { |
| 2499 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2500 | { |
| 2501 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2502 | { |
| 2503 | vals[idx++] = (*tensor)(i0, i1, i2); |
| 2504 | } |
| 2505 | } |
| 2506 | } |
| 2507 | |
| 2508 | return 0; |
| 2509 | } |
| 2510 | |
| 2511 | template <> |
| 2512 | int TosaReference::Tensor4<double>::getTensorValueDouble(const size_t bufLen, double* vals) const |
| 2513 | { |
| 2514 | uint32_t idx = 0; |
| 2515 | int totalVals = 1; |
| 2516 | |
| 2517 | for (size_t i = 0; i < shape.size(); i++) |
| 2518 | { |
| 2519 | totalVals *= shape[i]; |
| 2520 | } |
| 2521 | |
| 2522 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2523 | |
| 2524 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2525 | { |
| 2526 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2527 | { |
| 2528 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2529 | { |
| 2530 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2531 | { |
| 2532 | vals[idx++] = (*tensor)(i0, i1, i2, i3); |
| 2533 | } |
| 2534 | } |
| 2535 | } |
| 2536 | } |
| 2537 | |
| 2538 | return 0; |
| 2539 | } |
| 2540 | |
| 2541 | template <> |
| 2542 | int TosaReference::Tensor5<double>::getTensorValueDouble(const size_t bufLen, double* vals) const |
| 2543 | { |
| 2544 | uint32_t idx = 0; |
| 2545 | int totalVals = 1; |
| 2546 | |
| 2547 | for (size_t i = 0; i < shape.size(); i++) |
| 2548 | { |
| 2549 | totalVals *= shape[i]; |
| 2550 | } |
| 2551 | |
| 2552 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2553 | |
| 2554 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2555 | { |
| 2556 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2557 | { |
| 2558 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2559 | { |
| 2560 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2561 | { |
| 2562 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 2563 | { |
| 2564 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4); |
| 2565 | } |
| 2566 | } |
| 2567 | } |
| 2568 | } |
| 2569 | } |
| 2570 | |
| 2571 | return 0; |
| 2572 | } |
| 2573 | |
| 2574 | template <> |
| 2575 | int TosaReference::Tensor6<double>::getTensorValueDouble(const size_t bufLen, double* vals) const |
| 2576 | { |
| 2577 | uint32_t idx = 0; |
| 2578 | int totalVals = 1; |
| 2579 | |
| 2580 | for (size_t i = 0; i < shape.size(); i++) |
| 2581 | { |
| 2582 | totalVals *= shape[i]; |
| 2583 | } |
| 2584 | |
| 2585 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2586 | |
| 2587 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2588 | { |
| 2589 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2590 | { |
| 2591 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2592 | { |
| 2593 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2594 | { |
| 2595 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 2596 | { |
| 2597 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 2598 | { |
| 2599 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4, i5); |
| 2600 | } |
| 2601 | } |
| 2602 | } |
| 2603 | } |
| 2604 | } |
| 2605 | } |
| 2606 | return 0; |
| 2607 | } |
| 2608 | |
| 2609 | template <class T> |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 2610 | int TosaReference::TensorTemplate<T>::getTensorValueFloat(const size_t bufLen, float* vals) const |
| 2611 | { |
| 2612 | FATAL_ERROR("TensorTemplate<T>::getTensorValueFloat should not be called. " |
| 2613 | "Implement template specialization version."); |
| 2614 | return 0; |
| 2615 | } |
| 2616 | |
| 2617 | template <> |
| 2618 | int TosaReference::Tensor0<float>::getTensorValueFloat(const size_t bufLen, float* vals) const |
| 2619 | { |
| 2620 | int totalVals = 1; |
| 2621 | |
| 2622 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2623 | |
| 2624 | vals[0] = (*tensor)(0); |
| 2625 | |
| 2626 | return 0; |
| 2627 | } |
| 2628 | |
| 2629 | template <> |
| 2630 | int TosaReference::Tensor1<float>::getTensorValueFloat(const size_t bufLen, float* vals) const |
| 2631 | { |
| 2632 | uint32_t idx = 0; |
| 2633 | int totalVals = 1; |
| 2634 | |
| 2635 | for (size_t i = 0; i < shape.size(); i++) |
| 2636 | { |
| 2637 | totalVals *= shape[i]; |
| 2638 | } |
| 2639 | |
| 2640 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2641 | |
| 2642 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2643 | { |
| 2644 | vals[idx++] = (*tensor)(i0); |
| 2645 | } |
| 2646 | |
| 2647 | return 0; |
| 2648 | } |
| 2649 | |
| 2650 | template <> |
| 2651 | int TosaReference::Tensor2<float>::getTensorValueFloat(const size_t bufLen, float* vals) const |
| 2652 | { |
| 2653 | uint32_t idx = 0; |
| 2654 | int totalVals = 1; |
| 2655 | |
| 2656 | for (size_t i = 0; i < shape.size(); i++) |
| 2657 | { |
| 2658 | totalVals *= shape[i]; |
| 2659 | } |
| 2660 | |
| 2661 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2662 | |
| 2663 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2664 | { |
| 2665 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2666 | { |
| 2667 | vals[idx++] = (*tensor)(i0, i1); |
| 2668 | } |
| 2669 | } |
| 2670 | |
| 2671 | return 0; |
| 2672 | } |
| 2673 | |
| 2674 | template <> |
| 2675 | int TosaReference::Tensor3<float>::getTensorValueFloat(const size_t bufLen, float* vals) const |
| 2676 | { |
| 2677 | uint32_t idx = 0; |
| 2678 | int totalVals = 1; |
| 2679 | |
| 2680 | for (size_t i = 0; i < shape.size(); i++) |
| 2681 | { |
| 2682 | totalVals *= shape[i]; |
| 2683 | } |
| 2684 | |
| 2685 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2686 | |
| 2687 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2688 | { |
| 2689 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2690 | { |
| 2691 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2692 | { |
| 2693 | vals[idx++] = (*tensor)(i0, i1, i2); |
| 2694 | } |
| 2695 | } |
| 2696 | } |
| 2697 | |
| 2698 | return 0; |
| 2699 | } |
| 2700 | |
| 2701 | template <> |
| 2702 | int TosaReference::Tensor4<float>::getTensorValueFloat(const size_t bufLen, float* vals) const |
| 2703 | { |
| 2704 | uint32_t idx = 0; |
| 2705 | int totalVals = 1; |
| 2706 | |
| 2707 | for (size_t i = 0; i < shape.size(); i++) |
| 2708 | { |
| 2709 | totalVals *= shape[i]; |
| 2710 | } |
| 2711 | |
| 2712 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2713 | |
| 2714 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2715 | { |
| 2716 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2717 | { |
| 2718 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2719 | { |
| 2720 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2721 | { |
| 2722 | vals[idx++] = (*tensor)(i0, i1, i2, i3); |
| 2723 | } |
| 2724 | } |
| 2725 | } |
| 2726 | } |
| 2727 | |
| 2728 | return 0; |
| 2729 | } |
| 2730 | |
| 2731 | template <> |
| 2732 | int TosaReference::Tensor5<float>::getTensorValueFloat(const size_t bufLen, float* vals) const |
| 2733 | { |
| 2734 | uint32_t idx = 0; |
| 2735 | int totalVals = 1; |
| 2736 | |
| 2737 | for (size_t i = 0; i < shape.size(); i++) |
| 2738 | { |
| 2739 | totalVals *= shape[i]; |
| 2740 | } |
| 2741 | |
| 2742 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2743 | |
| 2744 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2745 | { |
| 2746 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2747 | { |
| 2748 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2749 | { |
| 2750 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2751 | { |
| 2752 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 2753 | { |
| 2754 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4); |
| 2755 | } |
| 2756 | } |
| 2757 | } |
| 2758 | } |
| 2759 | } |
| 2760 | |
| 2761 | return 0; |
| 2762 | } |
| 2763 | |
| 2764 | template <> |
| 2765 | int TosaReference::Tensor6<float>::getTensorValueFloat(const size_t bufLen, float* vals) const |
| 2766 | { |
| 2767 | uint32_t idx = 0; |
| 2768 | int totalVals = 1; |
| 2769 | |
| 2770 | for (size_t i = 0; i < shape.size(); i++) |
| 2771 | { |
| 2772 | totalVals *= shape[i]; |
| 2773 | } |
| 2774 | |
| 2775 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2776 | |
| 2777 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2778 | { |
| 2779 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2780 | { |
| 2781 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2782 | { |
| 2783 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2784 | { |
| 2785 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 2786 | { |
| 2787 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 2788 | { |
| 2789 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4, i5); |
| 2790 | } |
| 2791 | } |
| 2792 | } |
| 2793 | } |
| 2794 | } |
| 2795 | } |
| 2796 | return 0; |
| 2797 | } |
| 2798 | |
| 2799 | template <class T> |
Jerry Ge | c529169 | 2024-01-02 22:29:08 +0000 | [diff] [blame] | 2800 | int TosaReference::TensorTemplate<T>::getTensorValueUInt8(const size_t bufLen, uint8_t* vals) const |
| 2801 | { |
| 2802 | std::cout << "T is: " << typeid(T).name() << std::endl; |
| 2803 | FATAL_ERROR("TensorTemplate<T>::getTensorValueUInt8 should not be called. " |
| 2804 | "Implement template specialization version."); |
| 2805 | return 0; |
| 2806 | } |
| 2807 | |
| 2808 | template <> |
| 2809 | int TosaReference::Tensor0<int32_t>::getTensorValueUInt8(const size_t bufLen, uint8_t* vals) const |
| 2810 | { |
| 2811 | int totalVals = 1; |
| 2812 | |
| 2813 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2814 | |
| 2815 | vals[0] = (*tensor)(0); |
| 2816 | |
| 2817 | return 0; |
| 2818 | } |
| 2819 | |
| 2820 | template <> |
| 2821 | int TosaReference::Tensor1<int32_t>::getTensorValueUInt8(const size_t bufLen, uint8_t* vals) const |
| 2822 | { |
| 2823 | uint32_t idx = 0; |
| 2824 | int totalVals = 1; |
| 2825 | |
| 2826 | for (size_t i = 0; i < shape.size(); i++) |
| 2827 | { |
| 2828 | totalVals *= shape[i]; |
| 2829 | } |
| 2830 | |
| 2831 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2832 | |
| 2833 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2834 | { |
| 2835 | vals[idx++] = (*tensor)(i0); |
| 2836 | } |
| 2837 | |
| 2838 | return 0; |
| 2839 | } |
| 2840 | |
| 2841 | template <> |
| 2842 | int TosaReference::Tensor2<int32_t>::getTensorValueUInt8(const size_t bufLen, uint8_t* vals) const |
| 2843 | { |
| 2844 | uint32_t idx = 0; |
| 2845 | int totalVals = 1; |
| 2846 | |
| 2847 | for (size_t i = 0; i < shape.size(); i++) |
| 2848 | { |
| 2849 | totalVals *= shape[i]; |
| 2850 | } |
| 2851 | |
| 2852 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2853 | |
| 2854 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2855 | { |
| 2856 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2857 | { |
| 2858 | vals[idx++] = (*tensor)(i0, i1); |
| 2859 | } |
| 2860 | } |
| 2861 | |
| 2862 | return 0; |
| 2863 | } |
| 2864 | |
| 2865 | template <> |
| 2866 | int TosaReference::Tensor3<int32_t>::getTensorValueUInt8(const size_t bufLen, uint8_t* vals) const |
| 2867 | { |
| 2868 | uint32_t idx = 0; |
| 2869 | int totalVals = 1; |
| 2870 | |
| 2871 | for (size_t i = 0; i < shape.size(); i++) |
| 2872 | { |
| 2873 | totalVals *= shape[i]; |
| 2874 | } |
| 2875 | |
| 2876 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2877 | |
| 2878 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2879 | { |
| 2880 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2881 | { |
| 2882 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2883 | { |
| 2884 | vals[idx++] = (*tensor)(i0, i1, i2); |
| 2885 | } |
| 2886 | } |
| 2887 | } |
| 2888 | |
| 2889 | return 0; |
| 2890 | } |
| 2891 | |
| 2892 | template <> |
| 2893 | int TosaReference::Tensor4<int32_t>::getTensorValueUInt8(const size_t bufLen, uint8_t* vals) const |
| 2894 | { |
| 2895 | uint32_t idx = 0; |
| 2896 | int totalVals = 1; |
| 2897 | |
| 2898 | for (size_t i = 0; i < shape.size(); i++) |
| 2899 | { |
| 2900 | totalVals *= shape[i]; |
| 2901 | } |
| 2902 | |
| 2903 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2904 | |
| 2905 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2906 | { |
| 2907 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2908 | { |
| 2909 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2910 | { |
| 2911 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2912 | { |
| 2913 | vals[idx++] = (*tensor)(i0, i1, i2, i3); |
| 2914 | } |
| 2915 | } |
| 2916 | } |
| 2917 | } |
| 2918 | |
| 2919 | return 0; |
| 2920 | } |
| 2921 | |
| 2922 | template <> |
| 2923 | int TosaReference::Tensor5<int32_t>::getTensorValueUInt8(const size_t bufLen, uint8_t* vals) const |
| 2924 | { |
| 2925 | uint32_t idx = 0; |
| 2926 | int totalVals = 1; |
| 2927 | |
| 2928 | for (size_t i = 0; i < shape.size(); i++) |
| 2929 | { |
| 2930 | totalVals *= shape[i]; |
| 2931 | } |
| 2932 | |
| 2933 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2934 | |
| 2935 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2936 | { |
| 2937 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2938 | { |
| 2939 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2940 | { |
| 2941 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2942 | { |
| 2943 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 2944 | { |
| 2945 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4); |
| 2946 | } |
| 2947 | } |
| 2948 | } |
| 2949 | } |
| 2950 | } |
| 2951 | |
| 2952 | return 0; |
| 2953 | } |
| 2954 | |
| 2955 | template <> |
| 2956 | int TosaReference::Tensor6<int32_t>::getTensorValueUInt8(const size_t bufLen, uint8_t* vals) const |
| 2957 | { |
| 2958 | uint32_t idx = 0; |
| 2959 | int totalVals = 1; |
| 2960 | |
| 2961 | for (size_t i = 0; i < shape.size(); i++) |
| 2962 | { |
| 2963 | totalVals *= shape[i]; |
| 2964 | } |
| 2965 | |
| 2966 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 2967 | |
| 2968 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 2969 | { |
| 2970 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 2971 | { |
| 2972 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 2973 | { |
| 2974 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 2975 | { |
| 2976 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 2977 | { |
| 2978 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 2979 | { |
| 2980 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4, i5); |
| 2981 | } |
| 2982 | } |
| 2983 | } |
| 2984 | } |
| 2985 | } |
| 2986 | } |
| 2987 | return 0; |
| 2988 | } |
| 2989 | |
| 2990 | template <class T> |
| 2991 | int TosaReference::TensorTemplate<T>::getTensorValueInt8(const size_t bufLen, int8_t* vals) const |
| 2992 | { |
| 2993 | std::cout << "T is: " << typeid(T).name() << std::endl; |
| 2994 | FATAL_ERROR("TensorTemplate<T>::getTensorValueInt8 should not be called. " |
| 2995 | "Implement template specialization version."); |
| 2996 | return 0; |
| 2997 | } |
| 2998 | |
| 2999 | template <> |
| 3000 | int TosaReference::Tensor0<int32_t>::getTensorValueInt8(const size_t bufLen, int8_t* vals) const |
| 3001 | { |
| 3002 | int totalVals = 1; |
| 3003 | |
| 3004 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3005 | |
| 3006 | vals[0] = (*tensor)(0); |
| 3007 | |
| 3008 | return 0; |
| 3009 | } |
| 3010 | |
| 3011 | template <> |
| 3012 | int TosaReference::Tensor1<int32_t>::getTensorValueInt8(const size_t bufLen, int8_t* vals) const |
| 3013 | { |
| 3014 | uint32_t idx = 0; |
| 3015 | int totalVals = 1; |
| 3016 | |
| 3017 | for (size_t i = 0; i < shape.size(); i++) |
| 3018 | { |
| 3019 | totalVals *= shape[i]; |
| 3020 | } |
| 3021 | |
| 3022 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3023 | |
| 3024 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3025 | { |
| 3026 | vals[idx++] = (*tensor)(i0); |
| 3027 | } |
| 3028 | |
| 3029 | return 0; |
| 3030 | } |
| 3031 | |
| 3032 | template <> |
| 3033 | int TosaReference::Tensor2<int32_t>::getTensorValueInt8(const size_t bufLen, int8_t* vals) const |
| 3034 | { |
| 3035 | uint32_t idx = 0; |
| 3036 | int totalVals = 1; |
| 3037 | |
| 3038 | for (size_t i = 0; i < shape.size(); i++) |
| 3039 | { |
| 3040 | totalVals *= shape[i]; |
| 3041 | } |
| 3042 | |
| 3043 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3044 | |
| 3045 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3046 | { |
| 3047 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3048 | { |
| 3049 | vals[idx++] = (*tensor)(i0, i1); |
| 3050 | } |
| 3051 | } |
| 3052 | |
| 3053 | return 0; |
| 3054 | } |
| 3055 | |
| 3056 | template <> |
| 3057 | int TosaReference::Tensor3<int32_t>::getTensorValueInt8(const size_t bufLen, int8_t* vals) const |
| 3058 | { |
| 3059 | uint32_t idx = 0; |
| 3060 | int totalVals = 1; |
| 3061 | |
| 3062 | for (size_t i = 0; i < shape.size(); i++) |
| 3063 | { |
| 3064 | totalVals *= shape[i]; |
| 3065 | } |
| 3066 | |
| 3067 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3068 | |
| 3069 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3070 | { |
| 3071 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3072 | { |
| 3073 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3074 | { |
| 3075 | vals[idx++] = (*tensor)(i0, i1, i2); |
| 3076 | } |
| 3077 | } |
| 3078 | } |
| 3079 | |
| 3080 | return 0; |
| 3081 | } |
| 3082 | |
| 3083 | template <> |
| 3084 | int TosaReference::Tensor4<int32_t>::getTensorValueInt8(const size_t bufLen, int8_t* vals) const |
| 3085 | { |
| 3086 | uint32_t idx = 0; |
| 3087 | int totalVals = 1; |
| 3088 | |
| 3089 | for (size_t i = 0; i < shape.size(); i++) |
| 3090 | { |
| 3091 | totalVals *= shape[i]; |
| 3092 | } |
| 3093 | |
| 3094 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3095 | |
| 3096 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3097 | { |
| 3098 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3099 | { |
| 3100 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3101 | { |
| 3102 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3103 | { |
| 3104 | vals[idx++] = (*tensor)(i0, i1, i2, i3); |
| 3105 | } |
| 3106 | } |
| 3107 | } |
| 3108 | } |
| 3109 | |
| 3110 | return 0; |
| 3111 | } |
| 3112 | |
| 3113 | template <> |
| 3114 | int TosaReference::Tensor5<int32_t>::getTensorValueInt8(const size_t bufLen, int8_t* vals) const |
| 3115 | { |
| 3116 | uint32_t idx = 0; |
| 3117 | int totalVals = 1; |
| 3118 | |
| 3119 | for (size_t i = 0; i < shape.size(); i++) |
| 3120 | { |
| 3121 | totalVals *= shape[i]; |
| 3122 | } |
| 3123 | |
| 3124 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3125 | |
| 3126 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3127 | { |
| 3128 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3129 | { |
| 3130 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3131 | { |
| 3132 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3133 | { |
| 3134 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 3135 | { |
| 3136 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4); |
| 3137 | } |
| 3138 | } |
| 3139 | } |
| 3140 | } |
| 3141 | } |
| 3142 | |
| 3143 | return 0; |
| 3144 | } |
| 3145 | |
| 3146 | template <> |
| 3147 | int TosaReference::Tensor6<int32_t>::getTensorValueInt8(const size_t bufLen, int8_t* vals) const |
| 3148 | { |
| 3149 | uint32_t idx = 0; |
| 3150 | int totalVals = 1; |
| 3151 | |
| 3152 | for (size_t i = 0; i < shape.size(); i++) |
| 3153 | { |
| 3154 | totalVals *= shape[i]; |
| 3155 | } |
| 3156 | |
| 3157 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3158 | |
| 3159 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3160 | { |
| 3161 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3162 | { |
| 3163 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3164 | { |
| 3165 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3166 | { |
| 3167 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 3168 | { |
| 3169 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 3170 | { |
| 3171 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4, i5); |
| 3172 | } |
| 3173 | } |
| 3174 | } |
| 3175 | } |
| 3176 | } |
| 3177 | } |
| 3178 | return 0; |
| 3179 | } |
| 3180 | |
| 3181 | template <class T> |
Georgios Pinitas | e905977 | 2023-12-06 18:52:30 +0000 | [diff] [blame] | 3182 | int TosaReference::TensorTemplate<T>::getTensorValueInt16(const size_t bufLen, int16_t* vals) const |
| 3183 | { |
| 3184 | FATAL_ERROR("TensorTemplate<T>::getTensorValueInt32 should not be called. " |
| 3185 | "Implement template specialization version."); |
| 3186 | return 0; |
| 3187 | } |
| 3188 | |
| 3189 | template <> |
| 3190 | int TosaReference::Tensor0<int32_t>::getTensorValueInt16(const size_t bufLen, int16_t* vals) const |
| 3191 | { |
| 3192 | int totalVals = 1; |
| 3193 | |
| 3194 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3195 | |
| 3196 | vals[0] = (*tensor)(0); |
| 3197 | |
| 3198 | return 0; |
| 3199 | } |
| 3200 | |
| 3201 | template <> |
| 3202 | int TosaReference::Tensor1<int32_t>::getTensorValueInt16(const size_t bufLen, int16_t* vals) const |
| 3203 | { |
| 3204 | uint32_t idx = 0; |
| 3205 | int totalVals = 1; |
| 3206 | |
| 3207 | for (size_t i = 0; i < shape.size(); i++) |
| 3208 | { |
| 3209 | totalVals *= shape[i]; |
| 3210 | } |
| 3211 | |
| 3212 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3213 | |
| 3214 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3215 | { |
| 3216 | vals[idx++] = (*tensor)(i0); |
| 3217 | } |
| 3218 | |
| 3219 | return 0; |
| 3220 | } |
| 3221 | |
| 3222 | template <> |
| 3223 | int TosaReference::Tensor2<int32_t>::getTensorValueInt16(const size_t bufLen, int16_t* vals) const |
| 3224 | { |
| 3225 | uint32_t idx = 0; |
| 3226 | int totalVals = 1; |
| 3227 | |
| 3228 | for (size_t i = 0; i < shape.size(); i++) |
| 3229 | { |
| 3230 | totalVals *= shape[i]; |
| 3231 | } |
| 3232 | |
| 3233 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3234 | |
| 3235 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3236 | { |
| 3237 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3238 | { |
| 3239 | vals[idx++] = (*tensor)(i0, i1); |
| 3240 | } |
| 3241 | } |
| 3242 | |
| 3243 | return 0; |
| 3244 | } |
| 3245 | |
| 3246 | template <> |
| 3247 | int TosaReference::Tensor3<int32_t>::getTensorValueInt16(const size_t bufLen, int16_t* vals) const |
| 3248 | { |
| 3249 | uint32_t idx = 0; |
| 3250 | int totalVals = 1; |
| 3251 | |
| 3252 | for (size_t i = 0; i < shape.size(); i++) |
| 3253 | { |
| 3254 | totalVals *= shape[i]; |
| 3255 | } |
| 3256 | |
| 3257 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3258 | |
| 3259 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3260 | { |
| 3261 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3262 | { |
| 3263 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3264 | { |
| 3265 | vals[idx++] = (*tensor)(i0, i1, i2); |
| 3266 | } |
| 3267 | } |
| 3268 | } |
| 3269 | |
| 3270 | return 0; |
| 3271 | } |
| 3272 | |
| 3273 | template <> |
| 3274 | int TosaReference::Tensor4<int32_t>::getTensorValueInt16(const size_t bufLen, int16_t* vals) const |
| 3275 | { |
| 3276 | uint32_t idx = 0; |
| 3277 | int totalVals = 1; |
| 3278 | |
| 3279 | for (size_t i = 0; i < shape.size(); i++) |
| 3280 | { |
| 3281 | totalVals *= shape[i]; |
| 3282 | } |
| 3283 | |
| 3284 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3285 | |
| 3286 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3287 | { |
| 3288 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3289 | { |
| 3290 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3291 | { |
| 3292 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3293 | { |
| 3294 | vals[idx++] = (*tensor)(i0, i1, i2, i3); |
| 3295 | } |
| 3296 | } |
| 3297 | } |
| 3298 | } |
| 3299 | |
| 3300 | return 0; |
| 3301 | } |
| 3302 | |
| 3303 | template <> |
| 3304 | int TosaReference::Tensor5<int32_t>::getTensorValueInt16(const size_t bufLen, int16_t* vals) const |
| 3305 | { |
| 3306 | uint32_t idx = 0; |
| 3307 | int totalVals = 1; |
| 3308 | |
| 3309 | for (size_t i = 0; i < shape.size(); i++) |
| 3310 | { |
| 3311 | totalVals *= shape[i]; |
| 3312 | } |
| 3313 | |
| 3314 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3315 | |
| 3316 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3317 | { |
| 3318 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3319 | { |
| 3320 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3321 | { |
| 3322 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3323 | { |
| 3324 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 3325 | { |
| 3326 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4); |
| 3327 | } |
| 3328 | } |
| 3329 | } |
| 3330 | } |
| 3331 | } |
| 3332 | |
| 3333 | return 0; |
| 3334 | } |
| 3335 | |
| 3336 | template <> |
| 3337 | int TosaReference::Tensor6<int32_t>::getTensorValueInt16(const size_t bufLen, int16_t* vals) const |
| 3338 | { |
| 3339 | uint32_t idx = 0; |
| 3340 | int totalVals = 1; |
| 3341 | |
| 3342 | for (size_t i = 0; i < shape.size(); i++) |
| 3343 | { |
| 3344 | totalVals *= shape[i]; |
| 3345 | } |
| 3346 | |
| 3347 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3348 | |
| 3349 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3350 | { |
| 3351 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3352 | { |
| 3353 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3354 | { |
| 3355 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3356 | { |
| 3357 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 3358 | { |
| 3359 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 3360 | { |
| 3361 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4, i5); |
| 3362 | } |
| 3363 | } |
| 3364 | } |
| 3365 | } |
| 3366 | } |
| 3367 | } |
| 3368 | return 0; |
| 3369 | } |
| 3370 | |
| 3371 | template <class T> |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 3372 | int TosaReference::TensorTemplate<T>::getTensorValueInt32(const size_t bufLen, int32_t* vals) const |
| 3373 | { |
| 3374 | FATAL_ERROR("TensorTemplate<T>::getTensorValueInt32 should not be called. " |
| 3375 | "Implement template specialization version."); |
| 3376 | return 0; |
| 3377 | } |
| 3378 | |
| 3379 | template <> |
| 3380 | int TosaReference::Tensor0<int32_t>::getTensorValueInt32(const size_t bufLen, int32_t* vals) const |
| 3381 | { |
| 3382 | int totalVals = 1; |
| 3383 | |
| 3384 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3385 | |
| 3386 | vals[0] = (*tensor)(0); |
| 3387 | |
| 3388 | return 0; |
| 3389 | } |
| 3390 | |
| 3391 | template <> |
| 3392 | int TosaReference::Tensor1<int32_t>::getTensorValueInt32(const size_t bufLen, int32_t* vals) const |
| 3393 | { |
| 3394 | uint32_t idx = 0; |
| 3395 | int totalVals = 1; |
| 3396 | |
| 3397 | for (size_t i = 0; i < shape.size(); i++) |
| 3398 | { |
| 3399 | totalVals *= shape[i]; |
| 3400 | } |
| 3401 | |
| 3402 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3403 | |
| 3404 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3405 | { |
| 3406 | vals[idx++] = (*tensor)(i0); |
| 3407 | } |
| 3408 | |
| 3409 | return 0; |
| 3410 | } |
| 3411 | |
| 3412 | template <> |
| 3413 | int TosaReference::Tensor2<int32_t>::getTensorValueInt32(const size_t bufLen, int32_t* vals) const |
| 3414 | { |
| 3415 | uint32_t idx = 0; |
| 3416 | int totalVals = 1; |
| 3417 | |
| 3418 | for (size_t i = 0; i < shape.size(); i++) |
| 3419 | { |
| 3420 | totalVals *= shape[i]; |
| 3421 | } |
| 3422 | |
| 3423 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3424 | |
| 3425 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3426 | { |
| 3427 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3428 | { |
| 3429 | vals[idx++] = (*tensor)(i0, i1); |
| 3430 | } |
| 3431 | } |
| 3432 | |
| 3433 | return 0; |
| 3434 | } |
| 3435 | |
| 3436 | template <> |
| 3437 | int TosaReference::Tensor3<int32_t>::getTensorValueInt32(const size_t bufLen, int32_t* vals) const |
| 3438 | { |
| 3439 | uint32_t idx = 0; |
| 3440 | int totalVals = 1; |
| 3441 | |
| 3442 | for (size_t i = 0; i < shape.size(); i++) |
| 3443 | { |
| 3444 | totalVals *= shape[i]; |
| 3445 | } |
| 3446 | |
| 3447 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3448 | |
| 3449 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3450 | { |
| 3451 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3452 | { |
| 3453 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3454 | { |
| 3455 | vals[idx++] = (*tensor)(i0, i1, i2); |
| 3456 | } |
| 3457 | } |
| 3458 | } |
| 3459 | |
| 3460 | return 0; |
| 3461 | } |
| 3462 | |
| 3463 | template <> |
| 3464 | int TosaReference::Tensor4<int32_t>::getTensorValueInt32(const size_t bufLen, int32_t* vals) const |
| 3465 | { |
| 3466 | uint32_t idx = 0; |
| 3467 | int totalVals = 1; |
| 3468 | |
| 3469 | for (size_t i = 0; i < shape.size(); i++) |
| 3470 | { |
| 3471 | totalVals *= shape[i]; |
| 3472 | } |
| 3473 | |
| 3474 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3475 | |
| 3476 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3477 | { |
| 3478 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3479 | { |
| 3480 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3481 | { |
| 3482 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3483 | { |
| 3484 | vals[idx++] = (*tensor)(i0, i1, i2, i3); |
| 3485 | } |
| 3486 | } |
| 3487 | } |
| 3488 | } |
| 3489 | |
| 3490 | return 0; |
| 3491 | } |
| 3492 | |
| 3493 | template <> |
| 3494 | int TosaReference::Tensor5<int32_t>::getTensorValueInt32(const size_t bufLen, int32_t* vals) const |
| 3495 | { |
| 3496 | uint32_t idx = 0; |
| 3497 | int totalVals = 1; |
| 3498 | |
| 3499 | for (size_t i = 0; i < shape.size(); i++) |
| 3500 | { |
| 3501 | totalVals *= shape[i]; |
| 3502 | } |
| 3503 | |
| 3504 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3505 | |
| 3506 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3507 | { |
| 3508 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3509 | { |
| 3510 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3511 | { |
| 3512 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3513 | { |
| 3514 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 3515 | { |
| 3516 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4); |
| 3517 | } |
| 3518 | } |
| 3519 | } |
| 3520 | } |
| 3521 | } |
| 3522 | |
| 3523 | return 0; |
| 3524 | } |
| 3525 | |
| 3526 | template <> |
| 3527 | int TosaReference::Tensor6<int32_t>::getTensorValueInt32(const size_t bufLen, int32_t* vals) const |
| 3528 | { |
| 3529 | uint32_t idx = 0; |
| 3530 | int totalVals = 1; |
| 3531 | |
| 3532 | for (size_t i = 0; i < shape.size(); i++) |
| 3533 | { |
| 3534 | totalVals *= shape[i]; |
| 3535 | } |
| 3536 | |
| 3537 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3538 | |
| 3539 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3540 | { |
| 3541 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3542 | { |
| 3543 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3544 | { |
| 3545 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3546 | { |
| 3547 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 3548 | { |
| 3549 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 3550 | { |
| 3551 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4, i5); |
| 3552 | } |
| 3553 | } |
| 3554 | } |
| 3555 | } |
| 3556 | } |
| 3557 | } |
| 3558 | return 0; |
| 3559 | } |
| 3560 | |
| 3561 | template <class T> |
| 3562 | int TosaReference::TensorTemplate<T>::getTensorValueInt64(const size_t bufLen, int64_t* vals) const |
| 3563 | { |
| 3564 | FATAL_ERROR("TensorTemplate<T>::getTensorValueInt64 should not be called. " |
| 3565 | "Implement template specialization version."); |
| 3566 | return 0; |
| 3567 | } |
| 3568 | |
| 3569 | template <> |
| 3570 | int TosaReference::Tensor0<int64_t>::getTensorValueInt64(const size_t bufLen, int64_t* vals) const |
| 3571 | { |
| 3572 | int totalVals = 1; |
| 3573 | |
| 3574 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3575 | |
| 3576 | vals[0] = (*tensor)(0); |
| 3577 | |
| 3578 | return 0; |
| 3579 | } |
| 3580 | |
| 3581 | template <> |
| 3582 | int TosaReference::Tensor1<int64_t>::getTensorValueInt64(const size_t bufLen, int64_t* vals) const |
| 3583 | { |
| 3584 | uint32_t idx = 0; |
| 3585 | int totalVals = 1; |
| 3586 | |
| 3587 | for (size_t i = 0; i < shape.size(); i++) |
| 3588 | { |
| 3589 | totalVals *= shape[i]; |
| 3590 | } |
| 3591 | |
| 3592 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3593 | |
| 3594 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3595 | { |
| 3596 | vals[idx++] = (*tensor)(i0); |
| 3597 | } |
| 3598 | |
| 3599 | return 0; |
| 3600 | } |
| 3601 | |
| 3602 | template <> |
| 3603 | int TosaReference::Tensor2<int64_t>::getTensorValueInt64(const size_t bufLen, int64_t* vals) const |
| 3604 | { |
| 3605 | uint32_t idx = 0; |
| 3606 | int totalVals = 1; |
| 3607 | |
| 3608 | for (size_t i = 0; i < shape.size(); i++) |
| 3609 | { |
| 3610 | totalVals *= shape[i]; |
| 3611 | } |
| 3612 | |
| 3613 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3614 | |
| 3615 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3616 | { |
| 3617 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3618 | { |
| 3619 | vals[idx++] = (*tensor)(i0, i1); |
| 3620 | } |
| 3621 | } |
| 3622 | |
| 3623 | return 0; |
| 3624 | } |
| 3625 | |
| 3626 | template <> |
| 3627 | int TosaReference::Tensor3<int64_t>::getTensorValueInt64(const size_t bufLen, int64_t* vals) const |
| 3628 | { |
| 3629 | uint32_t idx = 0; |
| 3630 | int totalVals = 1; |
| 3631 | |
| 3632 | for (size_t i = 0; i < shape.size(); i++) |
| 3633 | { |
| 3634 | totalVals *= shape[i]; |
| 3635 | } |
| 3636 | |
| 3637 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3638 | |
| 3639 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3640 | { |
| 3641 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3642 | { |
| 3643 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3644 | { |
| 3645 | vals[idx++] = (*tensor)(i0, i1, i2); |
| 3646 | } |
| 3647 | } |
| 3648 | } |
| 3649 | |
| 3650 | return 0; |
| 3651 | } |
| 3652 | |
| 3653 | template <> |
| 3654 | int TosaReference::Tensor4<int64_t>::getTensorValueInt64(const size_t bufLen, int64_t* vals) const |
| 3655 | { |
| 3656 | uint32_t idx = 0; |
| 3657 | int totalVals = 1; |
| 3658 | |
| 3659 | for (size_t i = 0; i < shape.size(); i++) |
| 3660 | { |
| 3661 | totalVals *= shape[i]; |
| 3662 | } |
| 3663 | |
| 3664 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3665 | |
| 3666 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3667 | { |
| 3668 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3669 | { |
| 3670 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3671 | { |
| 3672 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3673 | { |
| 3674 | vals[idx++] = (*tensor)(i0, i1, i2, i3); |
| 3675 | } |
| 3676 | } |
| 3677 | } |
| 3678 | } |
| 3679 | |
| 3680 | return 0; |
| 3681 | } |
| 3682 | |
| 3683 | template <> |
| 3684 | int TosaReference::Tensor5<int64_t>::getTensorValueInt64(const size_t bufLen, int64_t* vals) const |
| 3685 | { |
| 3686 | uint32_t idx = 0; |
| 3687 | int totalVals = 1; |
| 3688 | |
| 3689 | for (size_t i = 0; i < shape.size(); i++) |
| 3690 | { |
| 3691 | totalVals *= shape[i]; |
| 3692 | } |
| 3693 | |
| 3694 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3695 | |
| 3696 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3697 | { |
| 3698 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3699 | { |
| 3700 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3701 | { |
| 3702 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3703 | { |
| 3704 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 3705 | { |
| 3706 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4); |
| 3707 | } |
| 3708 | } |
| 3709 | } |
| 3710 | } |
| 3711 | } |
| 3712 | |
| 3713 | return 0; |
| 3714 | } |
| 3715 | |
| 3716 | template <> |
| 3717 | int TosaReference::Tensor6<int64_t>::getTensorValueInt64(const size_t bufLen, int64_t* vals) const |
| 3718 | { |
| 3719 | uint32_t idx = 0; |
| 3720 | int totalVals = 1; |
| 3721 | |
| 3722 | for (size_t i = 0; i < shape.size(); i++) |
| 3723 | { |
| 3724 | totalVals *= shape[i]; |
| 3725 | } |
| 3726 | |
| 3727 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3728 | |
| 3729 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3730 | { |
| 3731 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3732 | { |
| 3733 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3734 | { |
| 3735 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3736 | { |
| 3737 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 3738 | { |
| 3739 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 3740 | { |
| 3741 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4, i5); |
| 3742 | } |
| 3743 | } |
| 3744 | } |
| 3745 | } |
| 3746 | } |
| 3747 | } |
| 3748 | return 0; |
| 3749 | } |
| 3750 | |
| 3751 | template <class T> |
| 3752 | int TosaReference::TensorTemplate<T>::getTensorValueBool(const size_t bufLen, bool* vals) const |
| 3753 | { |
| 3754 | FATAL_ERROR("TensorTemplate<T>::getTensorValueBool should not be called. " |
| 3755 | "Implement template specialization version."); |
| 3756 | return 0; |
| 3757 | } |
| 3758 | |
| 3759 | template <> |
| 3760 | int TosaReference::Tensor0<bool>::getTensorValueBool(const size_t bufLen, bool* vals) const |
| 3761 | { |
| 3762 | int totalVals = 1; |
| 3763 | |
| 3764 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3765 | |
| 3766 | vals[0] = (*tensor)(0); |
| 3767 | |
| 3768 | return 0; |
| 3769 | } |
| 3770 | |
| 3771 | template <> |
| 3772 | int TosaReference::Tensor1<bool>::getTensorValueBool(const size_t bufLen, bool* vals) const |
| 3773 | { |
| 3774 | uint32_t idx = 0; |
| 3775 | int totalVals = 1; |
| 3776 | |
| 3777 | for (size_t i = 0; i < shape.size(); i++) |
| 3778 | { |
| 3779 | totalVals *= shape[i]; |
| 3780 | } |
| 3781 | |
| 3782 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3783 | |
| 3784 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3785 | { |
| 3786 | vals[idx++] = (*tensor)(i0); |
| 3787 | } |
| 3788 | |
| 3789 | return 0; |
| 3790 | } |
| 3791 | |
| 3792 | template <> |
| 3793 | int TosaReference::Tensor2<bool>::getTensorValueBool(const size_t bufLen, bool* vals) const |
| 3794 | { |
| 3795 | uint32_t idx = 0; |
| 3796 | int totalVals = 1; |
| 3797 | |
| 3798 | for (size_t i = 0; i < shape.size(); i++) |
| 3799 | { |
| 3800 | totalVals *= shape[i]; |
| 3801 | } |
| 3802 | |
| 3803 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3804 | |
| 3805 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3806 | { |
| 3807 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3808 | { |
| 3809 | vals[idx++] = (*tensor)(i0, i1); |
| 3810 | } |
| 3811 | } |
| 3812 | |
| 3813 | return 0; |
| 3814 | } |
| 3815 | |
| 3816 | template <> |
| 3817 | int TosaReference::Tensor3<bool>::getTensorValueBool(const size_t bufLen, bool* vals) const |
| 3818 | { |
| 3819 | uint32_t idx = 0; |
| 3820 | int totalVals = 1; |
| 3821 | |
| 3822 | for (size_t i = 0; i < shape.size(); i++) |
| 3823 | { |
| 3824 | totalVals *= shape[i]; |
| 3825 | } |
| 3826 | |
| 3827 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3828 | |
| 3829 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3830 | { |
| 3831 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3832 | { |
| 3833 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3834 | { |
| 3835 | vals[idx++] = (*tensor)(i0, i1, i2); |
| 3836 | } |
| 3837 | } |
| 3838 | } |
| 3839 | |
| 3840 | return 0; |
| 3841 | } |
| 3842 | |
| 3843 | template <> |
| 3844 | int TosaReference::Tensor4<bool>::getTensorValueBool(const size_t bufLen, bool* vals) const |
| 3845 | { |
| 3846 | uint32_t idx = 0; |
| 3847 | int totalVals = 1; |
| 3848 | |
| 3849 | for (size_t i = 0; i < shape.size(); i++) |
| 3850 | { |
| 3851 | totalVals *= shape[i]; |
| 3852 | } |
| 3853 | |
| 3854 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3855 | |
| 3856 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3857 | { |
| 3858 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3859 | { |
| 3860 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3861 | { |
| 3862 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3863 | { |
| 3864 | vals[idx++] = (*tensor)(i0, i1, i2, i3); |
| 3865 | } |
| 3866 | } |
| 3867 | } |
| 3868 | } |
| 3869 | |
| 3870 | return 0; |
| 3871 | } |
| 3872 | |
| 3873 | template <> |
| 3874 | int TosaReference::Tensor5<bool>::getTensorValueBool(const size_t bufLen, bool* vals) const |
| 3875 | { |
| 3876 | uint32_t idx = 0; |
| 3877 | int totalVals = 1; |
| 3878 | |
| 3879 | for (size_t i = 0; i < shape.size(); i++) |
| 3880 | { |
| 3881 | totalVals *= shape[i]; |
| 3882 | } |
| 3883 | |
| 3884 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3885 | |
| 3886 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3887 | { |
| 3888 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3889 | { |
| 3890 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3891 | { |
| 3892 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3893 | { |
| 3894 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 3895 | { |
| 3896 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4); |
| 3897 | } |
| 3898 | } |
| 3899 | } |
| 3900 | } |
| 3901 | } |
| 3902 | |
| 3903 | return 0; |
| 3904 | } |
| 3905 | |
| 3906 | template <> |
| 3907 | int TosaReference::Tensor6<bool>::getTensorValueBool(const size_t bufLen, bool* vals) const |
| 3908 | { |
| 3909 | uint32_t idx = 0; |
| 3910 | int totalVals = 1; |
| 3911 | |
| 3912 | for (size_t i = 0; i < shape.size(); i++) |
| 3913 | { |
| 3914 | totalVals *= shape[i]; |
| 3915 | } |
| 3916 | |
| 3917 | ASSERT_MSG((size_t)totalVals == bufLen, "Output buffer and tensor size do not match"); |
| 3918 | |
| 3919 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 3920 | { |
| 3921 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 3922 | { |
| 3923 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 3924 | { |
| 3925 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 3926 | { |
| 3927 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 3928 | { |
| 3929 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 3930 | { |
| 3931 | vals[idx++] = (*tensor)(i0, i1, i2, i3, i4, i5); |
| 3932 | } |
| 3933 | } |
| 3934 | } |
| 3935 | } |
| 3936 | } |
| 3937 | } |
| 3938 | return 0; |
| 3939 | } |
| 3940 | |
Eric Kunze | 9a36755 | 2023-07-11 13:27:36 -0700 | [diff] [blame] | 3941 | #define TOSAREF_ZERORANK_TENSOR_ALLOCATE(dtype) \ |
| 3942 | template <> \ |
| 3943 | int TosaReference::Tensor0<dtype>::allocate() \ |
| 3944 | { \ |
| 3945 | ASSERT_MSG(tensor == nullptr, "Error: double allocate Eigen tensor"); \ |
| 3946 | tensor = new ETensor0<dtype>(); \ |
| 3947 | \ |
| 3948 | if (tensor) \ |
| 3949 | return 0; \ |
| 3950 | else \ |
| 3951 | return 1; \ |
| 3952 | } |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 3953 | |
Eric Kunze | 9a36755 | 2023-07-11 13:27:36 -0700 | [diff] [blame] | 3954 | #define TOSAREF_TENSOR_ALLOCATE(rank, dtype) \ |
| 3955 | template <> \ |
| 3956 | int TosaReference::Tensor##rank<dtype>::allocate() \ |
| 3957 | { \ |
| 3958 | ASSERT_MSG(tensor == nullptr, "Error: double allocate Eigen tensor"); \ |
| 3959 | std::array<Eigen::DenseIndex, rank> arrshape; \ |
| 3960 | std::copy_n(shape.begin(), rank, arrshape.begin()); \ |
| 3961 | tensor = new ETensor##rank<dtype>(arrshape); \ |
| 3962 | \ |
| 3963 | if (tensor) \ |
| 3964 | return 0; \ |
| 3965 | else \ |
| 3966 | return 1; \ |
| 3967 | } |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 3968 | |
Eric Kunze | 9a36755 | 2023-07-11 13:27:36 -0700 | [diff] [blame] | 3969 | TOSAREF_ZERORANK_TENSOR_ALLOCATE(double) |
| 3970 | TOSAREF_TENSOR_ALLOCATE(1, double) |
| 3971 | TOSAREF_TENSOR_ALLOCATE(2, double) |
| 3972 | TOSAREF_TENSOR_ALLOCATE(3, double) |
| 3973 | TOSAREF_TENSOR_ALLOCATE(4, double) |
| 3974 | TOSAREF_TENSOR_ALLOCATE(5, double) |
| 3975 | TOSAREF_TENSOR_ALLOCATE(6, double) |
| 3976 | TOSAREF_ZERORANK_TENSOR_ALLOCATE(float) |
| 3977 | TOSAREF_TENSOR_ALLOCATE(1, float) |
| 3978 | TOSAREF_TENSOR_ALLOCATE(2, float) |
| 3979 | TOSAREF_TENSOR_ALLOCATE(3, float) |
| 3980 | TOSAREF_TENSOR_ALLOCATE(4, float) |
| 3981 | TOSAREF_TENSOR_ALLOCATE(5, float) |
| 3982 | TOSAREF_TENSOR_ALLOCATE(6, float) |
| 3983 | TOSAREF_ZERORANK_TENSOR_ALLOCATE(int32_t) |
| 3984 | TOSAREF_TENSOR_ALLOCATE(1, int32_t) |
| 3985 | TOSAREF_TENSOR_ALLOCATE(2, int32_t) |
| 3986 | TOSAREF_TENSOR_ALLOCATE(3, int32_t) |
| 3987 | TOSAREF_TENSOR_ALLOCATE(4, int32_t) |
| 3988 | TOSAREF_TENSOR_ALLOCATE(5, int32_t) |
| 3989 | TOSAREF_TENSOR_ALLOCATE(6, int32_t) |
| 3990 | TOSAREF_ZERORANK_TENSOR_ALLOCATE(int64_t) |
| 3991 | TOSAREF_TENSOR_ALLOCATE(1, int64_t) |
| 3992 | TOSAREF_TENSOR_ALLOCATE(2, int64_t) |
| 3993 | TOSAREF_TENSOR_ALLOCATE(3, int64_t) |
| 3994 | TOSAREF_TENSOR_ALLOCATE(4, int64_t) |
| 3995 | TOSAREF_TENSOR_ALLOCATE(5, int64_t) |
| 3996 | TOSAREF_TENSOR_ALLOCATE(6, int64_t) |
| 3997 | TOSAREF_ZERORANK_TENSOR_ALLOCATE(bool) |
| 3998 | TOSAREF_TENSOR_ALLOCATE(1, bool) |
| 3999 | TOSAREF_TENSOR_ALLOCATE(2, bool) |
| 4000 | TOSAREF_TENSOR_ALLOCATE(3, bool) |
| 4001 | TOSAREF_TENSOR_ALLOCATE(4, bool) |
| 4002 | TOSAREF_TENSOR_ALLOCATE(5, bool) |
| 4003 | TOSAREF_TENSOR_ALLOCATE(6, bool) |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4004 | |
| 4005 | template <> |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 4006 | int TosaReference::Tensor0<double>::dumpTensor(FILE* out) const |
| 4007 | { |
| 4008 | char fp_fmt[32]; |
| 4009 | snprintf(fp_fmt, sizeof(fp_fmt), "[ %%%sf ]\n", g_func_config.fp_format.c_str()); |
| 4010 | |
| 4011 | if (tensor == nullptr) |
| 4012 | { |
| 4013 | fprintf(out, "<Not allocated>\n"); |
| 4014 | return 0; |
| 4015 | } |
| 4016 | |
| 4017 | fprintf(out, fp_fmt, (*tensor)(0)); |
| 4018 | |
| 4019 | return 0; |
| 4020 | } |
| 4021 | |
| 4022 | template <> |
| 4023 | int TosaReference::Tensor1<double>::dumpTensor(FILE* out) const |
| 4024 | { |
| 4025 | char fp_fmt[32]; |
| 4026 | snprintf(fp_fmt, sizeof(fp_fmt), " %%%sf ", g_func_config.fp_format.c_str()); |
| 4027 | |
| 4028 | if (tensor == nullptr) |
| 4029 | { |
| 4030 | fprintf(out, "<Not allocated>\n"); |
| 4031 | return 0; |
| 4032 | } |
| 4033 | |
| 4034 | fprintf(out, "["); |
| 4035 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4036 | { |
| 4037 | fprintf(out, fp_fmt, (*tensor)(i0)); |
| 4038 | } |
| 4039 | fprintf(out, "]\n"); |
| 4040 | |
| 4041 | return 0; |
| 4042 | } |
| 4043 | |
| 4044 | template <> |
| 4045 | int TosaReference::Tensor2<double>::dumpTensor(FILE* out) const |
| 4046 | { |
| 4047 | char fp_fmt[32]; |
| 4048 | snprintf(fp_fmt, sizeof(fp_fmt), " %%%sf ", g_func_config.fp_format.c_str()); |
| 4049 | |
| 4050 | if (tensor == nullptr) |
| 4051 | { |
| 4052 | fprintf(out, "<Not allocated>\n"); |
| 4053 | return 0; |
| 4054 | } |
| 4055 | |
| 4056 | fprintf(out, "["); |
| 4057 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4058 | { |
| 4059 | fprintf(out, "["); |
| 4060 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4061 | { |
| 4062 | fprintf(out, fp_fmt, (*tensor)(i0, i1)); |
| 4063 | } |
| 4064 | fprintf(out, "]\n"); |
| 4065 | } |
| 4066 | fprintf(out, "]\n"); |
| 4067 | |
| 4068 | return 0; |
| 4069 | } |
| 4070 | |
| 4071 | template <> |
| 4072 | int TosaReference::Tensor3<double>::dumpTensor(FILE* out) const |
| 4073 | { |
| 4074 | char fp_fmt[32]; |
| 4075 | snprintf(fp_fmt, sizeof(fp_fmt), " %%%sf ", g_func_config.fp_format.c_str()); |
| 4076 | |
| 4077 | if (tensor == nullptr) |
| 4078 | { |
| 4079 | fprintf(out, "<Not allocated>\n"); |
| 4080 | return 0; |
| 4081 | } |
| 4082 | |
| 4083 | fprintf(out, "["); |
| 4084 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4085 | { |
| 4086 | fprintf(out, "["); |
| 4087 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4088 | { |
| 4089 | fprintf(out, "["); |
| 4090 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4091 | { |
| 4092 | fprintf(out, fp_fmt, (*tensor)(i0, i1, i2)); |
| 4093 | } |
| 4094 | fprintf(out, "]\n"); |
| 4095 | } |
| 4096 | fprintf(out, "]\n"); |
| 4097 | } |
| 4098 | fprintf(out, "]\n"); |
| 4099 | |
| 4100 | return 0; |
| 4101 | } |
| 4102 | |
| 4103 | template <> |
| 4104 | int TosaReference::Tensor4<double>::dumpTensor(FILE* out) const |
| 4105 | { |
| 4106 | char fp_fmt[32]; |
| 4107 | snprintf(fp_fmt, sizeof(fp_fmt), " %%%sf ", g_func_config.fp_format.c_str()); |
| 4108 | |
| 4109 | if (tensor == nullptr) |
| 4110 | { |
| 4111 | fprintf(out, "<Not allocated>\n"); |
| 4112 | return 0; |
| 4113 | } |
| 4114 | |
| 4115 | fprintf(out, "["); |
| 4116 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4117 | { |
| 4118 | fprintf(out, "["); |
| 4119 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4120 | { |
| 4121 | fprintf(out, "["); |
| 4122 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4123 | { |
| 4124 | fprintf(out, "["); |
| 4125 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 4126 | { |
| 4127 | fprintf(out, fp_fmt, (*tensor)(i0, i1, i2, i3)); |
| 4128 | } |
| 4129 | fprintf(out, "]\n"); |
| 4130 | } |
| 4131 | fprintf(out, "]\n"); |
| 4132 | } |
| 4133 | fprintf(out, "]\n"); |
| 4134 | } |
| 4135 | fprintf(out, "]\n"); |
| 4136 | |
| 4137 | return 0; |
| 4138 | } |
| 4139 | |
| 4140 | template <> |
| 4141 | int TosaReference::Tensor5<double>::dumpTensor(FILE* out) const |
| 4142 | { |
| 4143 | char fp_fmt[32]; |
| 4144 | snprintf(fp_fmt, sizeof(fp_fmt), " %%%sf ", g_func_config.fp_format.c_str()); |
| 4145 | |
| 4146 | if (tensor == nullptr) |
| 4147 | { |
| 4148 | fprintf(out, "<Not allocated>\n"); |
| 4149 | return 0; |
| 4150 | } |
| 4151 | |
| 4152 | fprintf(out, "["); |
| 4153 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4154 | { |
| 4155 | fprintf(out, "["); |
| 4156 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4157 | { |
| 4158 | fprintf(out, "["); |
| 4159 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4160 | { |
| 4161 | fprintf(out, "["); |
| 4162 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 4163 | { |
| 4164 | fprintf(out, "["); |
| 4165 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 4166 | { |
| 4167 | fprintf(out, fp_fmt, (*tensor)(i0, i1, i2, i3, i4)); |
| 4168 | } |
| 4169 | fprintf(out, "]\n"); |
| 4170 | } |
| 4171 | fprintf(out, "]\n"); |
| 4172 | } |
| 4173 | fprintf(out, "]\n"); |
| 4174 | } |
| 4175 | fprintf(out, "]\n"); |
| 4176 | } |
| 4177 | fprintf(out, "]\n"); |
| 4178 | |
| 4179 | return 0; |
| 4180 | } |
| 4181 | |
| 4182 | template <> |
| 4183 | int TosaReference::Tensor6<double>::dumpTensor(FILE* out) const |
| 4184 | { |
| 4185 | char fp_fmt[32]; |
| 4186 | snprintf(fp_fmt, sizeof(fp_fmt), " %%%sf ", g_func_config.fp_format.c_str()); |
| 4187 | |
| 4188 | if (tensor == nullptr) |
| 4189 | { |
| 4190 | fprintf(out, "<Not allocated>\n"); |
| 4191 | return 0; |
| 4192 | } |
| 4193 | |
| 4194 | fprintf(out, "["); |
| 4195 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4196 | { |
| 4197 | fprintf(out, "["); |
| 4198 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4199 | { |
| 4200 | fprintf(out, "["); |
| 4201 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4202 | { |
| 4203 | fprintf(out, "["); |
| 4204 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 4205 | { |
| 4206 | fprintf(out, "["); |
| 4207 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 4208 | { |
| 4209 | fprintf(out, "["); |
| 4210 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 4211 | { |
| 4212 | fprintf(out, fp_fmt, (*tensor)(i0, i1, i2, i3, i4, i5)); |
| 4213 | } |
| 4214 | fprintf(out, "]\n"); |
| 4215 | } |
| 4216 | fprintf(out, "]\n"); |
| 4217 | } |
| 4218 | fprintf(out, "]\n"); |
| 4219 | } |
| 4220 | fprintf(out, "]\n"); |
| 4221 | } |
| 4222 | fprintf(out, "]\n"); |
| 4223 | } |
| 4224 | fprintf(out, "]\n"); |
| 4225 | |
| 4226 | return 0; |
| 4227 | } |
| 4228 | |
| 4229 | template <> |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4230 | int TosaReference::Tensor0<float>::dumpTensor(FILE* out) const |
| 4231 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4232 | char fp_fmt[32]; |
| 4233 | snprintf(fp_fmt, sizeof(fp_fmt), "[ %%%sf ]\n", g_func_config.fp_format.c_str()); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4234 | |
| 4235 | if (tensor == nullptr) |
| 4236 | { |
| 4237 | fprintf(out, "<Not allocated>\n"); |
| 4238 | return 0; |
| 4239 | } |
| 4240 | |
| 4241 | fprintf(out, fp_fmt, (*tensor)(0)); |
| 4242 | |
| 4243 | return 0; |
| 4244 | } |
| 4245 | |
| 4246 | template <> |
| 4247 | int TosaReference::Tensor1<float>::dumpTensor(FILE* out) const |
| 4248 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4249 | char fp_fmt[32]; |
| 4250 | snprintf(fp_fmt, sizeof(fp_fmt), " %%%sf ", g_func_config.fp_format.c_str()); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4251 | |
| 4252 | if (tensor == nullptr) |
| 4253 | { |
| 4254 | fprintf(out, "<Not allocated>\n"); |
| 4255 | return 0; |
| 4256 | } |
| 4257 | |
| 4258 | fprintf(out, "["); |
| 4259 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4260 | { |
| 4261 | fprintf(out, fp_fmt, (*tensor)(i0)); |
| 4262 | } |
| 4263 | fprintf(out, "]\n"); |
| 4264 | |
| 4265 | return 0; |
| 4266 | } |
| 4267 | |
| 4268 | template <> |
| 4269 | int TosaReference::Tensor2<float>::dumpTensor(FILE* out) const |
| 4270 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4271 | char fp_fmt[32]; |
| 4272 | snprintf(fp_fmt, sizeof(fp_fmt), " %%%sf ", g_func_config.fp_format.c_str()); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4273 | |
| 4274 | if (tensor == nullptr) |
| 4275 | { |
| 4276 | fprintf(out, "<Not allocated>\n"); |
| 4277 | return 0; |
| 4278 | } |
| 4279 | |
| 4280 | fprintf(out, "["); |
| 4281 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4282 | { |
| 4283 | fprintf(out, "["); |
| 4284 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4285 | { |
| 4286 | fprintf(out, fp_fmt, (*tensor)(i0, i1)); |
| 4287 | } |
| 4288 | fprintf(out, "]\n"); |
| 4289 | } |
| 4290 | fprintf(out, "]\n"); |
| 4291 | |
| 4292 | return 0; |
| 4293 | } |
| 4294 | |
| 4295 | template <> |
| 4296 | int TosaReference::Tensor3<float>::dumpTensor(FILE* out) const |
| 4297 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4298 | char fp_fmt[32]; |
| 4299 | snprintf(fp_fmt, sizeof(fp_fmt), " %%%sf ", g_func_config.fp_format.c_str()); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4300 | |
| 4301 | if (tensor == nullptr) |
| 4302 | { |
| 4303 | fprintf(out, "<Not allocated>\n"); |
| 4304 | return 0; |
| 4305 | } |
| 4306 | |
| 4307 | fprintf(out, "["); |
| 4308 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4309 | { |
| 4310 | fprintf(out, "["); |
| 4311 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4312 | { |
| 4313 | fprintf(out, "["); |
| 4314 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4315 | { |
| 4316 | fprintf(out, fp_fmt, (*tensor)(i0, i1, i2)); |
| 4317 | } |
| 4318 | fprintf(out, "]\n"); |
| 4319 | } |
| 4320 | fprintf(out, "]\n"); |
| 4321 | } |
| 4322 | fprintf(out, "]\n"); |
| 4323 | |
| 4324 | return 0; |
| 4325 | } |
| 4326 | |
| 4327 | template <> |
| 4328 | int TosaReference::Tensor4<float>::dumpTensor(FILE* out) const |
| 4329 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4330 | char fp_fmt[32]; |
| 4331 | snprintf(fp_fmt, sizeof(fp_fmt), " %%%sf ", g_func_config.fp_format.c_str()); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4332 | |
| 4333 | if (tensor == nullptr) |
| 4334 | { |
| 4335 | fprintf(out, "<Not allocated>\n"); |
| 4336 | return 0; |
| 4337 | } |
| 4338 | |
| 4339 | fprintf(out, "["); |
| 4340 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4341 | { |
| 4342 | fprintf(out, "["); |
| 4343 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4344 | { |
| 4345 | fprintf(out, "["); |
| 4346 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4347 | { |
| 4348 | fprintf(out, "["); |
| 4349 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 4350 | { |
| 4351 | fprintf(out, fp_fmt, (*tensor)(i0, i1, i2, i3)); |
| 4352 | } |
| 4353 | fprintf(out, "]\n"); |
| 4354 | } |
| 4355 | fprintf(out, "]\n"); |
| 4356 | } |
| 4357 | fprintf(out, "]\n"); |
| 4358 | } |
| 4359 | fprintf(out, "]\n"); |
| 4360 | |
| 4361 | return 0; |
| 4362 | } |
| 4363 | |
| 4364 | template <> |
| 4365 | int TosaReference::Tensor5<float>::dumpTensor(FILE* out) const |
| 4366 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4367 | char fp_fmt[32]; |
| 4368 | snprintf(fp_fmt, sizeof(fp_fmt), " %%%sf ", g_func_config.fp_format.c_str()); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4369 | |
| 4370 | if (tensor == nullptr) |
| 4371 | { |
| 4372 | fprintf(out, "<Not allocated>\n"); |
| 4373 | return 0; |
| 4374 | } |
| 4375 | |
| 4376 | fprintf(out, "["); |
| 4377 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4378 | { |
| 4379 | fprintf(out, "["); |
| 4380 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4381 | { |
| 4382 | fprintf(out, "["); |
| 4383 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4384 | { |
| 4385 | fprintf(out, "["); |
| 4386 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 4387 | { |
| 4388 | fprintf(out, "["); |
| 4389 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 4390 | { |
| 4391 | fprintf(out, fp_fmt, (*tensor)(i0, i1, i2, i3, i4)); |
| 4392 | } |
| 4393 | fprintf(out, "]\n"); |
| 4394 | } |
| 4395 | fprintf(out, "]\n"); |
| 4396 | } |
| 4397 | fprintf(out, "]\n"); |
| 4398 | } |
| 4399 | fprintf(out, "]\n"); |
| 4400 | } |
| 4401 | fprintf(out, "]\n"); |
| 4402 | |
| 4403 | return 0; |
| 4404 | } |
| 4405 | |
| 4406 | template <> |
| 4407 | int TosaReference::Tensor6<float>::dumpTensor(FILE* out) const |
| 4408 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4409 | char fp_fmt[32]; |
| 4410 | snprintf(fp_fmt, sizeof(fp_fmt), " %%%sf ", g_func_config.fp_format.c_str()); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4411 | |
| 4412 | if (tensor == nullptr) |
| 4413 | { |
| 4414 | fprintf(out, "<Not allocated>\n"); |
| 4415 | return 0; |
| 4416 | } |
| 4417 | |
| 4418 | fprintf(out, "["); |
| 4419 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4420 | { |
| 4421 | fprintf(out, "["); |
| 4422 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4423 | { |
| 4424 | fprintf(out, "["); |
| 4425 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4426 | { |
| 4427 | fprintf(out, "["); |
| 4428 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 4429 | { |
| 4430 | fprintf(out, "["); |
| 4431 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 4432 | { |
| 4433 | fprintf(out, "["); |
| 4434 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 4435 | { |
| 4436 | fprintf(out, fp_fmt, (*tensor)(i0, i1, i2, i3, i4, i5)); |
| 4437 | } |
| 4438 | fprintf(out, "]\n"); |
| 4439 | } |
| 4440 | fprintf(out, "]\n"); |
| 4441 | } |
| 4442 | fprintf(out, "]\n"); |
| 4443 | } |
| 4444 | fprintf(out, "]\n"); |
| 4445 | } |
| 4446 | fprintf(out, "]\n"); |
| 4447 | } |
| 4448 | fprintf(out, "]\n"); |
| 4449 | |
| 4450 | return 0; |
| 4451 | } |
| 4452 | |
| 4453 | template <> |
| 4454 | int TosaReference::Tensor0<int64_t>::dumpTensor(FILE* out) const |
| 4455 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4456 | char i64_fmt[32]; |
| 4457 | snprintf(i64_fmt, sizeof(i64_fmt), "[ %%ld ]\n"); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4458 | |
| 4459 | if (tensor == nullptr) |
| 4460 | { |
| 4461 | fprintf(out, "<Not allocated>\n"); |
| 4462 | return 0; |
| 4463 | } |
| 4464 | |
| 4465 | fprintf(out, i64_fmt, (*tensor)(0)); |
| 4466 | |
| 4467 | return 0; |
| 4468 | } |
| 4469 | |
| 4470 | template <> |
| 4471 | int TosaReference::Tensor1<int64_t>::dumpTensor(FILE* out) const |
| 4472 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4473 | char i64_fmt[32]; |
| 4474 | snprintf(i64_fmt, sizeof(i64_fmt), " %%ld "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4475 | |
| 4476 | if (tensor == nullptr) |
| 4477 | { |
| 4478 | fprintf(out, "<Not allocated>\n"); |
| 4479 | return 0; |
| 4480 | } |
| 4481 | |
| 4482 | fprintf(out, "["); |
| 4483 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4484 | { |
| 4485 | fprintf(out, i64_fmt, (*tensor)(i0)); |
| 4486 | } |
| 4487 | fprintf(out, "]\n"); |
| 4488 | |
| 4489 | return 0; |
| 4490 | } |
| 4491 | |
| 4492 | template <> |
| 4493 | int TosaReference::Tensor2<int64_t>::dumpTensor(FILE* out) const |
| 4494 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4495 | char i64_fmt[32]; |
| 4496 | snprintf(i64_fmt, sizeof(i64_fmt), " %%ld "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4497 | |
| 4498 | if (tensor == nullptr) |
| 4499 | { |
| 4500 | fprintf(out, "<Not allocated>\n"); |
| 4501 | return 0; |
| 4502 | } |
| 4503 | |
| 4504 | fprintf(out, "["); |
| 4505 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4506 | { |
| 4507 | fprintf(out, "["); |
| 4508 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4509 | { |
| 4510 | fprintf(out, i64_fmt, (*tensor)(i0, i1)); |
| 4511 | } |
| 4512 | fprintf(out, "]\n"); |
| 4513 | } |
| 4514 | fprintf(out, "]\n"); |
| 4515 | |
| 4516 | return 0; |
| 4517 | } |
| 4518 | |
| 4519 | template <> |
| 4520 | int TosaReference::Tensor3<int64_t>::dumpTensor(FILE* out) const |
| 4521 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4522 | char i64_fmt[32]; |
| 4523 | snprintf(i64_fmt, sizeof(i64_fmt), " %%ld "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4524 | |
| 4525 | if (tensor == nullptr) |
| 4526 | { |
| 4527 | fprintf(out, "<Not allocated>\n"); |
| 4528 | return 0; |
| 4529 | } |
| 4530 | |
| 4531 | fprintf(out, "["); |
| 4532 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4533 | { |
| 4534 | fprintf(out, "["); |
| 4535 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4536 | { |
| 4537 | fprintf(out, "["); |
| 4538 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4539 | { |
| 4540 | fprintf(out, i64_fmt, (*tensor)(i0, i1, i2)); |
| 4541 | } |
| 4542 | fprintf(out, "]\n"); |
| 4543 | } |
| 4544 | fprintf(out, "]\n"); |
| 4545 | } |
| 4546 | fprintf(out, "]\n"); |
| 4547 | |
| 4548 | return 0; |
| 4549 | } |
| 4550 | |
| 4551 | template <> |
| 4552 | int TosaReference::Tensor4<int64_t>::dumpTensor(FILE* out) const |
| 4553 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4554 | char i64_fmt[32]; |
| 4555 | snprintf(i64_fmt, sizeof(i64_fmt), " %%ld "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4556 | |
| 4557 | if (tensor == nullptr) |
| 4558 | { |
| 4559 | fprintf(out, "<Not allocated>\n"); |
| 4560 | return 0; |
| 4561 | } |
| 4562 | |
| 4563 | fprintf(out, "["); |
| 4564 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4565 | { |
| 4566 | fprintf(out, "["); |
| 4567 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4568 | { |
| 4569 | fprintf(out, "["); |
| 4570 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4571 | { |
| 4572 | fprintf(out, "["); |
| 4573 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 4574 | { |
| 4575 | fprintf(out, i64_fmt, (*tensor)(i0, i1, i2, i3)); |
| 4576 | } |
| 4577 | fprintf(out, "]\n"); |
| 4578 | } |
| 4579 | fprintf(out, "]\n"); |
| 4580 | } |
| 4581 | fprintf(out, "]\n"); |
| 4582 | } |
| 4583 | fprintf(out, "]\n"); |
| 4584 | |
| 4585 | return 0; |
| 4586 | } |
| 4587 | |
| 4588 | template <> |
| 4589 | int TosaReference::Tensor5<int64_t>::dumpTensor(FILE* out) const |
| 4590 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4591 | char i64_fmt[32]; |
| 4592 | snprintf(i64_fmt, sizeof(i64_fmt), " %%ld "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4593 | |
| 4594 | if (tensor == nullptr) |
| 4595 | { |
| 4596 | fprintf(out, "<Not allocated>\n"); |
| 4597 | return 0; |
| 4598 | } |
| 4599 | |
| 4600 | fprintf(out, "["); |
| 4601 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4602 | { |
| 4603 | fprintf(out, "["); |
| 4604 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4605 | { |
| 4606 | fprintf(out, "["); |
| 4607 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4608 | { |
| 4609 | fprintf(out, "["); |
| 4610 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 4611 | { |
| 4612 | fprintf(out, "["); |
| 4613 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 4614 | { |
| 4615 | fprintf(out, i64_fmt, (*tensor)(i0, i1, i2, i3, i4)); |
| 4616 | } |
| 4617 | fprintf(out, "]\n"); |
| 4618 | } |
| 4619 | fprintf(out, "]\n"); |
| 4620 | } |
| 4621 | fprintf(out, "]\n"); |
| 4622 | } |
| 4623 | fprintf(out, "]\n"); |
| 4624 | } |
| 4625 | fprintf(out, "]\n"); |
| 4626 | |
| 4627 | return 0; |
| 4628 | } |
| 4629 | |
| 4630 | template <> |
| 4631 | int TosaReference::Tensor6<int64_t>::dumpTensor(FILE* out) const |
| 4632 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4633 | char i64_fmt[32]; |
| 4634 | snprintf(i64_fmt, sizeof(i64_fmt), " %%ld "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4635 | |
| 4636 | if (tensor == nullptr) |
| 4637 | { |
| 4638 | fprintf(out, "<Not allocated>\n"); |
| 4639 | return 0; |
| 4640 | } |
| 4641 | |
| 4642 | fprintf(out, "["); |
| 4643 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4644 | { |
| 4645 | fprintf(out, "["); |
| 4646 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4647 | { |
| 4648 | fprintf(out, "["); |
| 4649 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4650 | { |
| 4651 | fprintf(out, "["); |
| 4652 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 4653 | { |
| 4654 | fprintf(out, "["); |
| 4655 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 4656 | { |
| 4657 | fprintf(out, "["); |
| 4658 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 4659 | { |
| 4660 | fprintf(out, i64_fmt, (*tensor)(i0, i1, i2, i3, i4, i5)); |
| 4661 | } |
| 4662 | fprintf(out, "]\n"); |
| 4663 | } |
| 4664 | fprintf(out, "]\n"); |
| 4665 | } |
| 4666 | fprintf(out, "]\n"); |
| 4667 | } |
| 4668 | fprintf(out, "]\n"); |
| 4669 | } |
| 4670 | fprintf(out, "]\n"); |
| 4671 | } |
| 4672 | fprintf(out, "]\n"); |
| 4673 | |
| 4674 | return 0; |
| 4675 | } |
| 4676 | |
| 4677 | template <> |
| 4678 | int TosaReference::Tensor0<int32_t>::dumpTensor(FILE* out) const |
| 4679 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4680 | char i32_fmt[32]; |
| 4681 | snprintf(i32_fmt, sizeof(i32_fmt), "[ %%d ]\n"); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4682 | |
| 4683 | if (tensor == nullptr) |
| 4684 | { |
| 4685 | fprintf(out, "<Not allocated>\n"); |
| 4686 | return 0; |
| 4687 | } |
| 4688 | |
| 4689 | fprintf(out, i32_fmt, (*tensor)(0)); |
| 4690 | |
| 4691 | return 0; |
| 4692 | } |
| 4693 | |
| 4694 | template <> |
| 4695 | int TosaReference::Tensor1<int32_t>::dumpTensor(FILE* out) const |
| 4696 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4697 | char i32_fmt[32]; |
| 4698 | snprintf(i32_fmt, sizeof(i32_fmt), " %%d "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4699 | |
| 4700 | if (tensor == nullptr) |
| 4701 | { |
| 4702 | fprintf(out, "<Not allocated>\n"); |
| 4703 | return 0; |
| 4704 | } |
| 4705 | |
| 4706 | fprintf(out, "["); |
| 4707 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4708 | { |
| 4709 | fprintf(out, i32_fmt, (*tensor)(i0)); |
| 4710 | } |
| 4711 | fprintf(out, "]\n"); |
| 4712 | |
| 4713 | return 0; |
| 4714 | } |
| 4715 | |
| 4716 | template <> |
| 4717 | int TosaReference::Tensor2<int32_t>::dumpTensor(FILE* out) const |
| 4718 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4719 | char i32_fmt[32]; |
| 4720 | snprintf(i32_fmt, sizeof(i32_fmt), " %%d "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4721 | |
| 4722 | if (tensor == nullptr) |
| 4723 | { |
| 4724 | fprintf(out, "<Not allocated>\n"); |
| 4725 | return 0; |
| 4726 | } |
| 4727 | |
| 4728 | if (tensor == nullptr) |
| 4729 | { |
| 4730 | fprintf(out, "<Not allocated>\n"); |
| 4731 | return 0; |
| 4732 | } |
| 4733 | |
| 4734 | fprintf(out, "["); |
| 4735 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4736 | { |
| 4737 | fprintf(out, "["); |
| 4738 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4739 | { |
| 4740 | fprintf(out, i32_fmt, (*tensor)(i0, i1)); |
| 4741 | } |
| 4742 | fprintf(out, "]\n"); |
| 4743 | } |
| 4744 | fprintf(out, "]\n"); |
| 4745 | |
| 4746 | return 0; |
| 4747 | } |
| 4748 | |
| 4749 | template <> |
| 4750 | int TosaReference::Tensor3<int32_t>::dumpTensor(FILE* out) const |
| 4751 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4752 | char i32_fmt[32]; |
| 4753 | snprintf(i32_fmt, sizeof(i32_fmt), " %%d "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4754 | |
| 4755 | if (tensor == nullptr) |
| 4756 | { |
| 4757 | fprintf(out, "<Not allocated>\n"); |
| 4758 | return 0; |
| 4759 | } |
| 4760 | |
| 4761 | if (tensor == nullptr) |
| 4762 | { |
| 4763 | fprintf(out, "<Not allocated>\n"); |
| 4764 | return 0; |
| 4765 | } |
| 4766 | |
| 4767 | fprintf(out, "["); |
| 4768 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4769 | { |
| 4770 | fprintf(out, "["); |
| 4771 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4772 | { |
| 4773 | fprintf(out, "["); |
| 4774 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4775 | { |
| 4776 | fprintf(out, i32_fmt, (*tensor)(i0, i1, i2)); |
| 4777 | } |
| 4778 | fprintf(out, "]\n"); |
| 4779 | } |
| 4780 | fprintf(out, "]\n"); |
| 4781 | } |
| 4782 | fprintf(out, "]\n"); |
| 4783 | |
| 4784 | return 0; |
| 4785 | } |
| 4786 | |
| 4787 | template <> |
| 4788 | int TosaReference::Tensor4<int32_t>::dumpTensor(FILE* out) const |
| 4789 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4790 | char i32_fmt[32]; |
| 4791 | snprintf(i32_fmt, sizeof(i32_fmt), " %%d "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4792 | |
| 4793 | if (tensor == nullptr) |
| 4794 | { |
| 4795 | fprintf(out, "<Not allocated>\n"); |
| 4796 | return 0; |
| 4797 | } |
| 4798 | |
| 4799 | fprintf(out, "["); |
| 4800 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4801 | { |
| 4802 | fprintf(out, "["); |
| 4803 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4804 | { |
| 4805 | fprintf(out, "["); |
| 4806 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4807 | { |
| 4808 | fprintf(out, "["); |
| 4809 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 4810 | { |
| 4811 | fprintf(out, i32_fmt, (*tensor)(i0, i1, i2, i3)); |
| 4812 | } |
| 4813 | fprintf(out, "]\n"); |
| 4814 | } |
| 4815 | fprintf(out, "]\n"); |
| 4816 | } |
| 4817 | fprintf(out, "]\n"); |
| 4818 | } |
| 4819 | fprintf(out, "]\n"); |
| 4820 | |
| 4821 | return 0; |
| 4822 | } |
| 4823 | |
| 4824 | template <> |
| 4825 | int TosaReference::Tensor5<int32_t>::dumpTensor(FILE* out) const |
| 4826 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4827 | char i32_fmt[32]; |
| 4828 | snprintf(i32_fmt, sizeof(i32_fmt), " %%d "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4829 | |
| 4830 | if (tensor == nullptr) |
| 4831 | { |
| 4832 | fprintf(out, "<Not allocated>\n"); |
| 4833 | return 0; |
| 4834 | } |
| 4835 | |
| 4836 | fprintf(out, "["); |
| 4837 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4838 | { |
| 4839 | fprintf(out, "["); |
| 4840 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4841 | { |
| 4842 | fprintf(out, "["); |
| 4843 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4844 | { |
| 4845 | fprintf(out, "["); |
| 4846 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 4847 | { |
| 4848 | fprintf(out, "["); |
| 4849 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 4850 | { |
| 4851 | fprintf(out, i32_fmt, (*tensor)(i0, i1, i2, i3, i4)); |
| 4852 | } |
| 4853 | fprintf(out, "]\n"); |
| 4854 | } |
| 4855 | fprintf(out, "]\n"); |
| 4856 | } |
| 4857 | fprintf(out, "]\n"); |
| 4858 | } |
| 4859 | fprintf(out, "]\n"); |
| 4860 | } |
| 4861 | fprintf(out, "]\n"); |
| 4862 | |
| 4863 | return 0; |
| 4864 | } |
| 4865 | |
| 4866 | template <> |
| 4867 | int TosaReference::Tensor6<int32_t>::dumpTensor(FILE* out) const |
| 4868 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4869 | char i32_fmt[32]; |
| 4870 | snprintf(i32_fmt, sizeof(i32_fmt), " %%d "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4871 | |
| 4872 | if (tensor == nullptr) |
| 4873 | { |
| 4874 | fprintf(out, "<Not allocated>\n"); |
| 4875 | return 0; |
| 4876 | } |
| 4877 | |
| 4878 | fprintf(out, "["); |
| 4879 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4880 | { |
| 4881 | fprintf(out, "["); |
| 4882 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4883 | { |
| 4884 | fprintf(out, "["); |
| 4885 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4886 | { |
| 4887 | fprintf(out, "["); |
| 4888 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 4889 | { |
| 4890 | fprintf(out, "["); |
| 4891 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 4892 | { |
| 4893 | fprintf(out, "["); |
| 4894 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 4895 | { |
| 4896 | fprintf(out, i32_fmt, (*tensor)(i0, i1, i2, i3, i4, i5)); |
| 4897 | } |
| 4898 | fprintf(out, "]\n"); |
| 4899 | } |
| 4900 | fprintf(out, "]\n"); |
| 4901 | } |
| 4902 | fprintf(out, "]\n"); |
| 4903 | } |
| 4904 | fprintf(out, "]\n"); |
| 4905 | } |
| 4906 | fprintf(out, "]\n"); |
| 4907 | } |
| 4908 | fprintf(out, "]\n"); |
| 4909 | |
| 4910 | return 0; |
| 4911 | } |
| 4912 | |
| 4913 | template <> |
| 4914 | int TosaReference::Tensor0<bool>::dumpTensor(FILE* out) const |
| 4915 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4916 | char bool_fmt[32]; |
| 4917 | snprintf(bool_fmt, sizeof(bool_fmt), "[ %%s ]\n"); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4918 | |
| 4919 | if (tensor == nullptr) |
| 4920 | { |
| 4921 | fprintf(out, "<Not allocated>\n"); |
| 4922 | return 0; |
| 4923 | } |
| 4924 | |
| 4925 | fprintf(out, bool_fmt, bool_to_str((*tensor)(0))); |
| 4926 | |
| 4927 | return 0; |
| 4928 | } |
| 4929 | |
| 4930 | template <> |
| 4931 | int TosaReference::Tensor1<bool>::dumpTensor(FILE* out) const |
| 4932 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4933 | char bool_fmt[32]; |
| 4934 | snprintf(bool_fmt, sizeof(bool_fmt), " %%s "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4935 | |
| 4936 | if (tensor == nullptr) |
| 4937 | { |
| 4938 | fprintf(out, "<Not allocated>\n"); |
| 4939 | return 0; |
| 4940 | } |
| 4941 | |
| 4942 | fprintf(out, "["); |
| 4943 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4944 | { |
| 4945 | fprintf(out, bool_fmt, bool_to_str((*tensor)(i0))); |
| 4946 | } |
| 4947 | fprintf(out, "]\n"); |
| 4948 | |
| 4949 | return 0; |
| 4950 | } |
| 4951 | |
| 4952 | template <> |
| 4953 | int TosaReference::Tensor2<bool>::dumpTensor(FILE* out) const |
| 4954 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4955 | char bool_fmt[32]; |
| 4956 | snprintf(bool_fmt, sizeof(bool_fmt), " %%s "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4957 | |
| 4958 | if (tensor == nullptr) |
| 4959 | { |
| 4960 | fprintf(out, "<Not allocated>\n"); |
| 4961 | return 0; |
| 4962 | } |
| 4963 | |
| 4964 | fprintf(out, "["); |
| 4965 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4966 | { |
| 4967 | fprintf(out, "["); |
| 4968 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4969 | { |
| 4970 | fprintf(out, bool_fmt, bool_to_str((*tensor)(i0, i1))); |
| 4971 | } |
| 4972 | fprintf(out, "]\n"); |
| 4973 | } |
| 4974 | fprintf(out, "]\n"); |
| 4975 | |
| 4976 | return 0; |
| 4977 | } |
| 4978 | |
| 4979 | template <> |
| 4980 | int TosaReference::Tensor3<bool>::dumpTensor(FILE* out) const |
| 4981 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 4982 | char bool_fmt[32]; |
| 4983 | snprintf(bool_fmt, sizeof(bool_fmt), " %%s "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 4984 | |
| 4985 | if (tensor == nullptr) |
| 4986 | { |
| 4987 | fprintf(out, "<Not allocated>\n"); |
| 4988 | return 0; |
| 4989 | } |
| 4990 | |
| 4991 | fprintf(out, "["); |
| 4992 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 4993 | { |
| 4994 | fprintf(out, "["); |
| 4995 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 4996 | { |
| 4997 | fprintf(out, "["); |
| 4998 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 4999 | { |
| 5000 | fprintf(out, bool_fmt, bool_to_str((*tensor)(i0, i1, i2))); |
| 5001 | } |
| 5002 | fprintf(out, "]\n"); |
| 5003 | } |
| 5004 | fprintf(out, "]\n"); |
| 5005 | } |
| 5006 | fprintf(out, "]\n"); |
| 5007 | |
| 5008 | return 0; |
| 5009 | } |
| 5010 | |
| 5011 | template <> |
| 5012 | int TosaReference::Tensor4<bool>::dumpTensor(FILE* out) const |
| 5013 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 5014 | char bool_fmt[32]; |
| 5015 | snprintf(bool_fmt, sizeof(bool_fmt), " %%s "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 5016 | |
| 5017 | if (tensor == nullptr) |
| 5018 | { |
| 5019 | fprintf(out, "<Not allocated>\n"); |
| 5020 | return 0; |
| 5021 | } |
| 5022 | |
| 5023 | fprintf(out, "["); |
| 5024 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 5025 | { |
| 5026 | fprintf(out, "["); |
| 5027 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 5028 | { |
| 5029 | fprintf(out, "["); |
| 5030 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 5031 | { |
| 5032 | fprintf(out, "["); |
| 5033 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 5034 | { |
| 5035 | fprintf(out, bool_fmt, bool_to_str((*tensor)(i0, i1, i2, i3))); |
| 5036 | } |
| 5037 | fprintf(out, "]\n"); |
| 5038 | } |
| 5039 | fprintf(out, "]\n"); |
| 5040 | } |
| 5041 | fprintf(out, "]\n"); |
| 5042 | } |
| 5043 | fprintf(out, "]\n"); |
| 5044 | |
| 5045 | return 0; |
| 5046 | } |
| 5047 | |
| 5048 | template <> |
| 5049 | int TosaReference::Tensor5<bool>::dumpTensor(FILE* out) const |
| 5050 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 5051 | char bool_fmt[32]; |
| 5052 | snprintf(bool_fmt, sizeof(bool_fmt), " %%s "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 5053 | |
| 5054 | if (tensor == nullptr) |
| 5055 | { |
| 5056 | fprintf(out, "<Not allocated>\n"); |
| 5057 | return 0; |
| 5058 | } |
| 5059 | |
| 5060 | fprintf(out, "["); |
| 5061 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 5062 | { |
| 5063 | fprintf(out, "["); |
| 5064 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 5065 | { |
| 5066 | fprintf(out, "["); |
| 5067 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 5068 | { |
| 5069 | fprintf(out, "["); |
| 5070 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 5071 | { |
| 5072 | fprintf(out, "["); |
| 5073 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 5074 | { |
| 5075 | fprintf(out, bool_fmt, bool_to_str((*tensor)(i0, i1, i2, i3, i4))); |
| 5076 | } |
| 5077 | fprintf(out, "]\n"); |
| 5078 | } |
| 5079 | fprintf(out, "]\n"); |
| 5080 | } |
| 5081 | fprintf(out, "]\n"); |
| 5082 | } |
| 5083 | fprintf(out, "]\n"); |
| 5084 | } |
| 5085 | fprintf(out, "]\n"); |
| 5086 | |
| 5087 | return 0; |
| 5088 | } |
| 5089 | |
| 5090 | template <> |
| 5091 | int TosaReference::Tensor6<bool>::dumpTensor(FILE* out) const |
| 5092 | { |
Eric Kunze | 286f834 | 2022-06-22 11:30:23 -0700 | [diff] [blame] | 5093 | char bool_fmt[32]; |
| 5094 | snprintf(bool_fmt, sizeof(bool_fmt), " %%s "); |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 5095 | |
| 5096 | if (tensor == nullptr) |
| 5097 | { |
| 5098 | fprintf(out, "<Not allocated>\n"); |
| 5099 | return 0; |
| 5100 | } |
| 5101 | |
| 5102 | fprintf(out, "["); |
| 5103 | for (int i0 = 0; i0 < shape[0]; i0++) |
| 5104 | { |
| 5105 | fprintf(out, "["); |
| 5106 | for (int i1 = 0; i1 < shape[1]; i1++) |
| 5107 | { |
| 5108 | fprintf(out, "["); |
| 5109 | for (int i2 = 0; i2 < shape[2]; i2++) |
| 5110 | { |
| 5111 | fprintf(out, "["); |
| 5112 | for (int i3 = 0; i3 < shape[3]; i3++) |
| 5113 | { |
| 5114 | fprintf(out, "["); |
| 5115 | for (int i4 = 0; i4 < shape[4]; i4++) |
| 5116 | { |
| 5117 | fprintf(out, "["); |
| 5118 | for (int i5 = 0; i5 < shape[5]; i5++) |
| 5119 | { |
| 5120 | fprintf(out, bool_fmt, bool_to_str((*tensor)(i0, i1, i2, i3, i4, i5))); |
| 5121 | } |
| 5122 | fprintf(out, "]\n"); |
| 5123 | } |
| 5124 | fprintf(out, "]\n"); |
| 5125 | } |
| 5126 | fprintf(out, "]\n"); |
| 5127 | } |
| 5128 | fprintf(out, "]\n"); |
| 5129 | } |
| 5130 | fprintf(out, "]\n"); |
| 5131 | } |
| 5132 | fprintf(out, "]\n"); |
| 5133 | |
| 5134 | return 0; |
| 5135 | } |
| 5136 | |
| 5137 | template <class T> |
| 5138 | int TosaReference::TensorTemplate<T>::dumpTensor(FILE* out) const |
| 5139 | { |
| 5140 | return 0; |
| 5141 | } |
| 5142 | |
| 5143 | // template explicit specialization |
Tai Ly | a4d748b | 2023-03-28 22:06:56 +0000 | [diff] [blame] | 5144 | template class TosaReference::TensorTemplate<Eigen::Tensor<double, 0>>; |
| 5145 | template class TosaReference::TensorTemplate<Eigen::Tensor<double, 1>>; |
| 5146 | template class TosaReference::TensorTemplate<Eigen::Tensor<double, 2>>; |
| 5147 | template class TosaReference::TensorTemplate<Eigen::Tensor<double, 3>>; |
| 5148 | template class TosaReference::TensorTemplate<Eigen::Tensor<double, 4>>; |
| 5149 | template class TosaReference::TensorTemplate<Eigen::Tensor<double, 5>>; |
| 5150 | template class TosaReference::TensorTemplate<Eigen::Tensor<double, 6>>; |
| 5151 | |
Eric Kunze | e5e2676 | 2020-10-13 16:11:07 -0700 | [diff] [blame] | 5152 | template class TosaReference::TensorTemplate<Eigen::Tensor<float, 0>>; |
| 5153 | template class TosaReference::TensorTemplate<Eigen::Tensor<float, 1>>; |
| 5154 | template class TosaReference::TensorTemplate<Eigen::Tensor<float, 2>>; |
| 5155 | template class TosaReference::TensorTemplate<Eigen::Tensor<float, 3>>; |
| 5156 | template class TosaReference::TensorTemplate<Eigen::Tensor<float, 4>>; |
| 5157 | template class TosaReference::TensorTemplate<Eigen::Tensor<float, 5>>; |
| 5158 | template class TosaReference::TensorTemplate<Eigen::Tensor<float, 6>>; |
| 5159 | |
| 5160 | template class TosaReference::TensorTemplate<Eigen::Tensor<int32_t, 0>>; |
| 5161 | template class TosaReference::TensorTemplate<Eigen::Tensor<int32_t, 1>>; |
| 5162 | template class TosaReference::TensorTemplate<Eigen::Tensor<int32_t, 2>>; |
| 5163 | template class TosaReference::TensorTemplate<Eigen::Tensor<int32_t, 3>>; |
| 5164 | template class TosaReference::TensorTemplate<Eigen::Tensor<int32_t, 4>>; |
| 5165 | template class TosaReference::TensorTemplate<Eigen::Tensor<int32_t, 5>>; |
| 5166 | template class TosaReference::TensorTemplate<Eigen::Tensor<int32_t, 6>>; |
| 5167 | |
| 5168 | template class TosaReference::TensorTemplate<Eigen::Tensor<int64_t, 0>>; |
| 5169 | template class TosaReference::TensorTemplate<Eigen::Tensor<int64_t, 1>>; |
| 5170 | template class TosaReference::TensorTemplate<Eigen::Tensor<int64_t, 2>>; |
| 5171 | template class TosaReference::TensorTemplate<Eigen::Tensor<int64_t, 3>>; |
| 5172 | template class TosaReference::TensorTemplate<Eigen::Tensor<int64_t, 4>>; |
| 5173 | template class TosaReference::TensorTemplate<Eigen::Tensor<int64_t, 5>>; |
| 5174 | template class TosaReference::TensorTemplate<Eigen::Tensor<int64_t, 6>>; |
| 5175 | |
| 5176 | template class TosaReference::TensorTemplate<Eigen::Tensor<bool, 0>>; |
| 5177 | template class TosaReference::TensorTemplate<Eigen::Tensor<bool, 1>>; |
| 5178 | template class TosaReference::TensorTemplate<Eigen::Tensor<bool, 2>>; |
| 5179 | template class TosaReference::TensorTemplate<Eigen::Tensor<bool, 3>>; |
| 5180 | template class TosaReference::TensorTemplate<Eigen::Tensor<bool, 4>>; |
| 5181 | template class TosaReference::TensorTemplate<Eigen::Tensor<bool, 5>>; |
| 5182 | template class TosaReference::TensorTemplate<Eigen::Tensor<bool, 6>>; |