Johan Alfven | 014bc28 | 2024-01-25 12:32:13 +0100 | [diff] [blame] | 1 | # SPDX-FileCopyrightText: Copyright 2020-2024 Arm Limited and/or its affiliates <open-source-office@arm.com> |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 2 | # |
| 3 | # SPDX-License-Identifier: Apache-2.0 |
| 4 | # |
| 5 | # Licensed under the Apache License, Version 2.0 (the License); you may |
| 6 | # not use this file except in compliance with the License. |
| 7 | # You may obtain a copy of the License at |
| 8 | # |
| 9 | # www.apache.org/licenses/LICENSE-2.0 |
| 10 | # |
| 11 | # Unless required by applicable law or agreed to in writing, software |
| 12 | # distributed under the License is distributed on an AS IS BASIS, WITHOUT |
| 13 | # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| 14 | # See the License for the specific language governing permissions and |
| 15 | # limitations under the License. |
Rickard Bolin | bc6ee58 | 2022-11-04 08:24:29 +0000 | [diff] [blame] | 16 | # |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 17 | # Description: |
| 18 | # Neural network graph classes and enums. |
| 19 | # Pass - A packed pass containing one or more Operations. |
| 20 | # CascadedPass - A scheduled pass containing one or more Passes, as well as a scheduling strategy and block |
| 21 | # configurations. |
| 22 | # Subgraph - Holds a neural network subgraph, pointing at Tensors, Operations, Passes, and CascadedPasses. |
| 23 | # Graph - A full neural network graph with one or more Subgraphs. |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 24 | import enum |
patrik.gustavsson | eeb8515 | 2020-12-21 17:10:40 +0000 | [diff] [blame] | 25 | from typing import List |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 26 | |
Louis Verhaard | aee5d75 | 2020-09-30 09:01:52 +0200 | [diff] [blame] | 27 | from .operation import Op |
patrik.gustavsson | eeb8515 | 2020-12-21 17:10:40 +0000 | [diff] [blame] | 28 | from .shape4d import Shape4D |
Louis Verhaard | aee5d75 | 2020-09-30 09:01:52 +0200 | [diff] [blame] | 29 | |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 30 | |
| 31 | class PassPlacement(enum.Enum): |
| 32 | Unknown = 0 |
| 33 | Cpu = 1 |
| 34 | Npu = 2 |
| 35 | MemoryOnly = 3 |
| 36 | StartupInit = 4 |
| 37 | |
| 38 | |
| 39 | class TensorAllocator(enum.Enum): |
| 40 | LinearAlloc = 1 |
| 41 | Greedy = 2 |
Louis Verhaard | d700252 | 2021-01-20 17:23:54 +0100 | [diff] [blame] | 42 | HillClimb = 3 |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 43 | |
| 44 | def __str__(self): |
| 45 | return self.name |
| 46 | |
| 47 | |
Patrik Gustavsson | 8f1f9aa | 2021-06-28 07:41:58 +0200 | [diff] [blame] | 48 | class NetworkType(enum.Enum): |
| 49 | TFLite = 1 |
| 50 | TOSA = 2 |
| 51 | |
| 52 | |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 53 | class Pass: |
| 54 | def __init__(self, name, placement, is_element_wise, npu_block_type): |
| 55 | self.inputs = [] |
| 56 | self.intermediates = [] |
| 57 | self.outputs = [] |
| 58 | self.ops = [] |
| 59 | self.primary_op = None |
| 60 | self.ifm_tensor = None |
| 61 | self.ifm2_tensor = None |
| 62 | self.ofm_tensor = None |
| 63 | self.weight_tensor = None |
| 64 | self.scale_tensor = None |
Fredrik Svedberg | a0c3624 | 2020-06-03 15:43:31 +0200 | [diff] [blame] | 65 | self.lut_tensor = None |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 66 | self.name = name |
| 67 | self.cascade = None |
| 68 | self.placement = placement |
patrik.gustavsson | eeb8515 | 2020-12-21 17:10:40 +0000 | [diff] [blame] | 69 | self.ifm_shapes: List[Shape4D] = [] |
| 70 | self.ofm_shapes: List[Shape4D] = [] |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 71 | |
| 72 | # TODO: rename is_element_wise because it is not the same as an ElementWise operator. It is used by the tensor |
| 73 | # allocation and requires that the OFM and IFM has the exact same address. Essentially complete overlap. |
| 74 | self.is_element_wise = is_element_wise |
| 75 | self.npu_block_type = npu_block_type |
| 76 | self.block_config = None # will be filled in by scheduler |
| 77 | self.shared_buffer = None # will be filled in by scheduler |
Tim Hall | d8339a7 | 2021-05-27 18:49:40 +0100 | [diff] [blame] | 78 | self.scheduling_info = None # will be filled in by scheduler |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 79 | |
| 80 | self.predecessors = [] |
| 81 | self.successors = [] |
| 82 | |
| 83 | def __str__(self): |
| 84 | return "<nng.Pass '%s', %s, ops=%s>" % (self.name, self.placement, [op.type for op in self.ops]) |
| 85 | |
| 86 | __repr__ = __str__ |
| 87 | |
| 88 | def get_primary_op_ifm_weights(self): |
| 89 | if not self.primary_op: |
| 90 | return None, None |
| 91 | return self.primary_op.get_ifm_ifm2_weights_ofm()[::2] |
| 92 | |
| 93 | def get_primary_op_ifm_ifm2_weights_ofm(self): |
| 94 | if not self.primary_op: |
| 95 | return None, None, None, None |
| 96 | return self.primary_op.get_ifm_ifm2_weights_ofm() |
| 97 | |
| 98 | def get_primary_op_ifm_weights_biases_ofm(self): |
| 99 | if not self.primary_op: |
| 100 | return None, None, None, None |
| 101 | return self.primary_op.get_ifm_weights_biases_ofm() |
| 102 | |
Fredrik Svedberg | a0c3624 | 2020-06-03 15:43:31 +0200 | [diff] [blame] | 103 | def get_primary_op_lut(self): |
| 104 | if not self.primary_op: |
| 105 | return None |
| 106 | return self.primary_op.activation_lut |
| 107 | |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 108 | |
| 109 | class SchedulingStrategy(enum.Enum): |
| 110 | Unknown = -1 |
| 111 | IfmStream = 0 |
| 112 | WeightStream = 1 |
| 113 | |
| 114 | |
| 115 | class SchedulerRewrite(enum.Enum): |
| 116 | Nop = 0 |
| 117 | ChangeTensorSubPurpose = 1 |
| 118 | |
| 119 | |
| 120 | class CascadedPass: |
| 121 | def __init__(self, name, strat, inputs, intermediates, outputs, passes, placement, is_element_wise): |
| 122 | self.name = name |
| 123 | self.strategy = strat |
| 124 | self.inputs = inputs |
| 125 | self.intermediates = intermediates |
| 126 | self.outputs = outputs |
| 127 | self.passes = passes |
| 128 | self.placement = placement |
| 129 | self.is_element_wise = is_element_wise |
| 130 | |
| 131 | self.predecessors = [] |
| 132 | self.successors = [] |
Tim Hall | d8339a7 | 2021-05-27 18:49:40 +0100 | [diff] [blame] | 133 | self.sram_used = 0 |
Jonas Ohlsson | 845e232 | 2022-03-01 12:39:55 +0100 | [diff] [blame] | 134 | self.time = 0 |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 135 | |
| 136 | def __str__(self): |
| 137 | return "<nng.CascadedPass strategy=%s x %s '%s', passes=%s, block_configs=%s>" % ( |
| 138 | self.strategy, |
| 139 | len(self.passes), |
| 140 | self.name, |
| 141 | [ps.name for ps in self.passes], |
| 142 | [ps.block_config for ps in self.passes], |
| 143 | ) |
| 144 | |
| 145 | __repr__ = __str__ |
| 146 | |
| 147 | |
| 148 | class Subgraph: |
| 149 | def __init__(self, name="<unnamed>", placement=PassPlacement.Cpu): |
| 150 | self.output_tensors = [] |
| 151 | self.input_tensors = [] |
Johan Alfven | 9070f0f | 2023-02-07 13:01:03 +0100 | [diff] [blame] | 152 | # Preserve the original input order |
| 153 | self.original_inputs = [] |
| 154 | # Attach virtual outputs to resource variables op |
| 155 | # in order to be able to traverse the graph correctly |
| 156 | self.virtual_outputs = [] |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 157 | self.passes = [] |
| 158 | self.cascaded_passes = [] |
| 159 | self.name = name |
| 160 | self.high_level_command_stream = [] |
| 161 | self.placement = placement |
| 162 | self.command_stream_tensor = None |
| 163 | self.flash_tensor = None |
Louis Verhaard | 0b9c9a3 | 2020-09-15 14:05:38 +0200 | [diff] [blame] | 164 | # Scratch information locally used in the scheduler |
Tim Hall | d8339a7 | 2021-05-27 18:49:40 +0100 | [diff] [blame] | 165 | self.schedule = None |
| 166 | self.sched_ops = [] |
| 167 | |
erik.andersson@arm.com | ad45f79 | 2021-02-03 10:20:16 +0100 | [diff] [blame] | 168 | self.generated_stream_id = None |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 169 | |
| 170 | self.memory_used = {} |
Patrik Gustavsson | eca2e95 | 2020-05-27 09:15:11 +0200 | [diff] [blame] | 171 | self.memory_used_per_type = {} |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 172 | |
| 173 | def __str__(self): |
| 174 | return "<nng.Subgraph '%s', n_passes=%d, n_cascaded_passes=%d>" % ( |
| 175 | self.name, |
| 176 | len(self.passes), |
| 177 | len(self.cascaded_passes), |
| 178 | ) |
| 179 | |
| 180 | __repr__ = __str__ |
| 181 | |
| 182 | def update_consumers(self): |
| 183 | visit_op_set = set() |
| 184 | visit_tensor_set = set() |
Johan Alfven | abed3c2 | 2024-04-04 10:08:05 +0200 | [diff] [blame] | 185 | sg_passes_op_set = set() |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 186 | self.input_tensors = [] |
| 187 | |
Johan Alfven | abed3c2 | 2024-04-04 10:08:05 +0200 | [diff] [blame] | 188 | for ps in self.passes: |
| 189 | for op in ps.ops: |
| 190 | sg_passes_op_set.add(op) |
| 191 | |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 192 | print_visit = False |
| 193 | |
| 194 | def visit_op(op): |
Johan Alfven | abed3c2 | 2024-04-04 10:08:05 +0200 | [diff] [blame] | 195 | if op in visit_op_set or (sg_passes_op_set and op not in sg_passes_op_set): |
| 196 | # Op already visited or op is not part of a pass in this subgraph |
| 197 | # Typcial case when op is not part of this subgraph but is visited anyway are concat ops |
| 198 | # that are split up into different subgraphs (several avgpool). Since they share the same |
| 199 | # output the avgpool that do not belong to this subgraph will be traversed which |
| 200 | # should be avoided. |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 201 | return |
| 202 | |
| 203 | visit_op_set.add(op) |
| 204 | for inp in op.inputs: |
Jacob Bohlin | 67e0d8f | 2020-08-20 10:53:02 +0200 | [diff] [blame] | 205 | if not inp: |
| 206 | continue |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 207 | if print_visit: |
| 208 | print(inp, "adding consumer", op) |
| 209 | visit_tensor(inp) |
| 210 | inp.consumer_list.append(op) |
| 211 | |
Michael McGeagh | f3e3ad7 | 2020-12-02 12:39:03 +0000 | [diff] [blame] | 212 | if op.type in (Op.Placeholder, Op.SubgraphInput): |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 213 | assert len(op.outputs) == 1 |
Fredrik Svedberg | 33c01e6 | 2023-02-13 11:32:12 +0100 | [diff] [blame] | 214 | if not op.outputs[0].is_variable: |
| 215 | self.input_tensors.append(op.outputs[0]) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 216 | |
| 217 | for out in op.outputs: |
| 218 | if out not in visit_tensor_set: |
| 219 | out.consumer_list = [] # reset unvisited output, just in case |
| 220 | |
| 221 | def visit_tensor(tens): |
| 222 | if tens in visit_tensor_set: |
| 223 | return |
| 224 | visit_tensor_set.add(tens) |
| 225 | tens.consumer_list = [] |
| 226 | for op in tens.ops: |
| 227 | visit_op(op) |
| 228 | |
| 229 | for ps in self.passes: |
| 230 | for tens in ps.outputs + ps.inputs: |
Jacob Bohlin | 67e0d8f | 2020-08-20 10:53:02 +0200 | [diff] [blame] | 231 | if not tens: |
| 232 | continue |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 233 | tens.consumer_list = [] # reset unvisited tensors to start with |
| 234 | |
| 235 | for tens in self.output_tensors: |
| 236 | visit_tensor(tens) |
| 237 | tens.consumer_list.append(None) # special op to indicate that the graph consumes the result |
| 238 | |
| 239 | print_visit = True |
| 240 | for ps in self.passes: |
| 241 | for op in ps.ops: |
| 242 | visit_op(op) |
| 243 | for tens in ps.inputs: |
| 244 | visit_tensor(tens) |
| 245 | |
| 246 | def build_pass_links(self): |
| 247 | for idx, ps in enumerate(self.passes): |
| 248 | ps.time = 2 * idx |
| 249 | ps.predecessors = [] |
| 250 | ps.successors = [] |
| 251 | |
| 252 | for ps in self.passes: |
| 253 | for tens in ps.inputs: |
| 254 | for op in tens.ops: |
| 255 | pred_pass = op.scheduled_pass |
Johan Alfven | f9194e1 | 2024-04-22 15:17:33 +0200 | [diff] [blame^] | 256 | # Pass with split concat ops may end up with a dependency to |
| 257 | # itself since output from concat is produced by several avg pool ops. |
| 258 | # Hence pred_pass can be equal to ps. |
| 259 | assert pred_pass == ps or pred_pass.time < ps.time |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 260 | if ps not in pred_pass.successors: |
| 261 | pred_pass.successors.append(ps) |
| 262 | |
| 263 | if pred_pass not in ps.predecessors: |
| 264 | ps.predecessors.append(pred_pass) |
| 265 | |
| 266 | assert tens in pred_pass.outputs |
| 267 | |
| 268 | def build_pass_dag_predecessors(self): |
| 269 | for ps in self.passes: |
| 270 | ps.dag_predecessors = [] |
| 271 | |
| 272 | class State(enum.Enum): |
| 273 | NotVisited = 0 |
| 274 | BeingVisited = 1 |
| 275 | Visited = 2 |
| 276 | |
| 277 | pass_visit_dict = {} |
| 278 | |
| 279 | def visit_pass(ps): |
| 280 | state = pass_visit_dict.get(ps, State.NotVisited) |
| 281 | if state == State.Visited: |
| 282 | return True |
| 283 | elif state == State.BeingVisited: |
| 284 | return False # this is a loop, need to remove this link |
| 285 | elif state == State.NotVisited: |
| 286 | pass_visit_dict[ps] = State.BeingVisited |
| 287 | |
| 288 | ps.dag_predecessors = [] |
| 289 | for pred in ps.predecessors: |
| 290 | if visit_pass(pred): |
| 291 | ps.dag_predecessors.append(pred) |
| 292 | |
| 293 | pass_visit_dict[ps] = State.Visited |
| 294 | return True |
| 295 | |
| 296 | for ps in self.passes: |
| 297 | if not ps.successors: |
| 298 | visit_pass(ps) |
| 299 | |
| 300 | def build_cascaded_pass_links(self): |
| 301 | for cps in self.cascaded_passes: |
| 302 | cps.predecessors = [] |
| 303 | cps.successors = [] |
| 304 | |
| 305 | for cps in self.cascaded_passes: |
| 306 | for tens in cps.inputs: |
| 307 | for op in tens.ops: |
| 308 | pred_cpass = op.scheduled_pass.cascade |
| 309 | if cps not in pred_cpass.successors: |
| 310 | pred_cpass.successors.append(cps) |
| 311 | |
| 312 | if pred_cpass not in cps.predecessors: |
| 313 | cps.predecessors.append(pred_cpass) |
| 314 | |
| 315 | assert tens in pred_cpass.outputs |
| 316 | |
| 317 | def refresh_after_modification(self): |
Rickard Bolin | 26c8e84 | 2023-05-11 10:53:42 +0000 | [diff] [blame] | 318 | try: |
| 319 | self.update_consumers() |
| 320 | except RecursionError as e: |
| 321 | raise RecursionError( |
| 322 | "Compilation failed due to exceeding the default maximum recursion depth.\n" |
| 323 | 'Try increasing the maximum recursion depth with the "--recursion-limit" option.' |
| 324 | ) from e |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 325 | |
| 326 | def prune_startup_init_pass(self): |
| 327 | assert len(self.passes) >= 1 |
| 328 | ps = self.passes[0] |
| 329 | assert ps.placement == PassPlacement.StartupInit |
| 330 | |
| 331 | ps.outputs = [out_tens for out_tens in ps.outputs if len(out_tens.consumers()) > 0] |
| 332 | ps.ops = [op for op in ps.ops if op.outputs[0] in ps.outputs] |
| 333 | |
Johan Alfven | 014bc28 | 2024-01-25 12:32:13 +0100 | [diff] [blame] | 334 | # get_all_ops is used when traversing the original graph |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 335 | def get_all_ops(self): |
| 336 | all_ops = [] |
| 337 | visit_op_set = set() |
| 338 | visit_tensor_set = set() |
| 339 | |
| 340 | def visit_op(op): |
| 341 | if op in visit_op_set: |
| 342 | return |
| 343 | visit_op_set.add(op) |
| 344 | for inp in op.inputs: |
| 345 | visit_tensor(inp) |
| 346 | |
| 347 | all_ops.append(op) |
| 348 | |
| 349 | def visit_tensor(tens): |
Andreas Nevalainen | e1cc3de | 2020-09-08 15:31:02 +0200 | [diff] [blame] | 350 | if tens is None or tens in visit_tensor_set: |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 351 | return |
| 352 | visit_tensor_set.add(tens) |
| 353 | for op in tens.ops: |
| 354 | visit_op(op) |
| 355 | |
| 356 | for tens in self.output_tensors: |
| 357 | visit_tensor(tens) |
| 358 | |
| 359 | return all_ops |
| 360 | |
Johan Alfven | 014bc28 | 2024-01-25 12:32:13 +0100 | [diff] [blame] | 361 | # get_all_ops_from_passes is used by stats writer to calculate the number of |
| 362 | # CPU and NPU ops |
| 363 | # Due to a side effect get_all_ops might not be traversing the full graph |
| 364 | # after extract_npu_subgraph have been called and should not be used by stats writer. |
| 365 | # The reason is that the main graph might have NPU nodes with no visible outputs |
| 366 | # and therefore the nodes will be missed. |
| 367 | def get_all_ops_from_passes(self): |
| 368 | all_ops = [] |
| 369 | for idx, ps in enumerate(self.passes): |
| 370 | for op in ps.ops: |
| 371 | all_ops.append(op) |
| 372 | |
| 373 | return all_ops |
| 374 | |
Tim Hall | cd03504 | 2023-08-08 14:10:17 +0100 | [diff] [blame] | 375 | def print_operators(self, ignore_placeholder_const=True, show_attributes=True): |
| 376 | print(f"Operators of Subgraph {self.name}") |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 377 | |
Tim Hall | cd03504 | 2023-08-08 14:10:17 +0100 | [diff] [blame] | 378 | ignore_ops = (Op.Const, Op.Identity, Op.Placeholder) if ignore_placeholder_const else () |
| 379 | all_ops = [op for op in self.get_all_ops() if op.type not in ignore_ops] |
| 380 | |
| 381 | if len(all_ops) > 0: |
| 382 | max_op_type_len = max([len(op.type.name) for op in all_ops]) |
| 383 | |
| 384 | for idx, op in enumerate(all_ops): |
| 385 | attrs_str = f" - {op.attrs}" if show_attributes else "" |
| 386 | print(f"{idx:3}: {op.type:{max_op_type_len}}{attrs_str} - {op.name}") |
| 387 | |
| 388 | else: |
| 389 | print("No Operators") |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 390 | |
Fredrik Svedberg | c875aa6 | 2021-05-06 09:53:31 +0200 | [diff] [blame] | 391 | def print_graph(self, label=None): |
| 392 | if label: |
| 393 | print(f"\n[ {label} ]") |
Michael McGeagh | 775e396 | 2020-07-28 11:44:22 +0100 | [diff] [blame] | 394 | print("print_graph()", self.name) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 395 | all_ops = self.get_all_ops() |
| 396 | for idx, op in enumerate(all_ops): |
| 397 | print(idx, op.type, op.name) |
| 398 | |
| 399 | def print_graph_with_tensors(self): |
Michael McGeagh | 775e396 | 2020-07-28 11:44:22 +0100 | [diff] [blame] | 400 | print("print_graph_with_tensors()", self.name) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 401 | all_ops = self.get_all_ops() |
| 402 | for idx, op in enumerate(all_ops): |
| 403 | print(idx, op.type, op.name) |
| 404 | for idx, tens in enumerate(op.inputs): |
Fredrik Svedberg | b3d941e | 2021-10-13 14:06:03 +0200 | [diff] [blame] | 405 | if tens: |
| 406 | print( |
| 407 | f" Input {idx:02d}" |
| 408 | f" {tens.purpose.name:>20} {tens.mem_area.name:>20} {tens.mem_type.name:>20} {tens}" |
| 409 | ) |
| 410 | else: |
| 411 | print(f" Input {idx:02d} {'-':>20} {'-':>20} {'-':>20} {tens}") |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 412 | for idx, tens in enumerate(op.outputs): |
Patrik Gustavsson | eca2e95 | 2020-05-27 09:15:11 +0200 | [diff] [blame] | 413 | print( |
Fredrik Svedberg | b3d941e | 2021-10-13 14:06:03 +0200 | [diff] [blame] | 414 | f" Output {idx:02d}" |
| 415 | f" {tens.purpose.name:>20} {tens.mem_area.name:>20} {tens.mem_type.name:>20} {tens}" |
Patrik Gustavsson | eca2e95 | 2020-05-27 09:15:11 +0200 | [diff] [blame] | 416 | ) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 417 | print() |
| 418 | |
| 419 | def print_graph_with_tensor_quantization(self): |
Michael McGeagh | 775e396 | 2020-07-28 11:44:22 +0100 | [diff] [blame] | 420 | print("print_graph_with_tensor_quantization()", self.name) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 421 | all_ops = self.get_all_ops() |
| 422 | for idx, op in enumerate(all_ops): |
| 423 | print(idx, op.type, op.name) |
| 424 | for idx, tens in enumerate(op.inputs): |
Fredrik Svedberg | b3d941e | 2021-10-13 14:06:03 +0200 | [diff] [blame] | 425 | if tens: |
| 426 | q = tens.quantization |
| 427 | if q is None: |
| 428 | print(f" Input {idx:02d} {tens.dtype!s:>10} NO QUANTIZATION INFO {tens.name}") |
| 429 | else: |
| 430 | print( |
| 431 | f" Input {idx:02d} {tens.dtype!s:>10}" |
| 432 | f" min={q.min} max={q.max} scale={q.scale_f32!s} zero_point={q.zero_point} {tens.name}" |
| 433 | ) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 434 | else: |
Fredrik Svedberg | b3d941e | 2021-10-13 14:06:03 +0200 | [diff] [blame] | 435 | print(f" Input {idx:02d} {'-':>10} {tens}") |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 436 | for idx, tens in enumerate(op.outputs): |
| 437 | q = tens.quantization |
| 438 | if q is None: |
Fredrik Svedberg | b3d941e | 2021-10-13 14:06:03 +0200 | [diff] [blame] | 439 | print(f" Output {idx:02d} {tens.dtype!s:>10} NO QUANTIZATION INFO {tens.name}") |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 440 | else: |
| 441 | print( |
Fredrik Svedberg | b3d941e | 2021-10-13 14:06:03 +0200 | [diff] [blame] | 442 | f" Output {idx:02d} {tens.dtype!s:>10}" |
| 443 | f" min={q.min} max={q.max} scale={q.scale_f32!s} zero_point={q.zero_point} {tens.name}" |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 444 | ) |
| 445 | print() |
| 446 | |
| 447 | def print_passes(self): |
Michael McGeagh | 775e396 | 2020-07-28 11:44:22 +0100 | [diff] [blame] | 448 | print("print_passes()", self.name) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 449 | for idx, ps in enumerate(self.passes): |
| 450 | print("%03d %s" % (idx * 2, ps)) |
| 451 | |
| 452 | def print_passes_with_tensors(self): |
Michael McGeagh | 775e396 | 2020-07-28 11:44:22 +0100 | [diff] [blame] | 453 | print("print_passes_with_tensors()", self.name) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 454 | for idx, ps in enumerate(self.passes): |
| 455 | print("%3d %s" % (idx * 2, ps)) |
| 456 | for idx, tens in enumerate(ps.inputs): |
| 457 | print( |
| 458 | " Input %2d %-15s %-15s %-15s %s" |
| 459 | % (idx, tens.purpose.name, tens.mem_area.name, tens.format.name, tens.name) |
| 460 | ) |
| 461 | for idx, tens in enumerate(ps.intermediates): |
| 462 | print( |
| 463 | " Intermediate %2d %-15s %-15s %-15s %s" |
| 464 | % (idx, tens.purpose.name, tens.mem_area.name, tens.format.name, tens.name) |
| 465 | ) |
| 466 | for idx, tens in enumerate(ps.outputs): |
| 467 | print( |
| 468 | " Output %2d %-15s %-15s %-15s %s" |
| 469 | % (idx, tens.purpose.name, tens.mem_area.name, tens.format.name, tens.name) |
| 470 | ) |
| 471 | print() |
| 472 | |
| 473 | def print_cascaded_passes(self): |
Michael McGeagh | 775e396 | 2020-07-28 11:44:22 +0100 | [diff] [blame] | 474 | print("print_cascaded_passes()", self.name) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 475 | for idx, ps in enumerate(self.cascaded_passes): |
| 476 | print("%3d %s SRAM used %.1f KB" % (idx * 2, ps, ps.sram_used / 1024)) |
| 477 | |
| 478 | def print_cascaded_passes_with_tensors(self): |
Michael McGeagh | 775e396 | 2020-07-28 11:44:22 +0100 | [diff] [blame] | 479 | print("print_cascaded_passes_with_tensors()", self.name) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 480 | for idx, ps in enumerate(self.cascaded_passes): |
| 481 | print("%3d %s SRAM used %.1f KB" % (idx * 2, ps, ps.sram_used / 1024)) |
| 482 | for idx, tens in enumerate(ps.inputs): |
| 483 | print( |
| 484 | " Input %2d %-15s %-15s %-15s %s" |
| 485 | % (idx, tens.purpose.name, tens.mem_area.name, tens.format.name, tens.name) |
| 486 | ) |
| 487 | for idx, tens in enumerate(ps.intermediates): |
| 488 | print( |
| 489 | " Intermediate %2d %-15s %-15s %-15s %s" |
| 490 | % (idx, tens.purpose.name, tens.mem_area.name, tens.format.name, tens.name) |
| 491 | ) |
| 492 | for idx, tens in enumerate(ps.outputs): |
| 493 | print( |
| 494 | " Output %2d %-15s %-15s %-15s %s" |
| 495 | % (idx, tens.purpose.name, tens.mem_area.name, tens.format.name, tens.name) |
| 496 | ) |
| 497 | print() |
| 498 | |
| 499 | def print_cascaded_passes_with_tensor_sizes(self): |
Michael McGeagh | 775e396 | 2020-07-28 11:44:22 +0100 | [diff] [blame] | 500 | print("print_cascaded_passes_with_tensor_sizes()", self.name) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 501 | for idx, ps in enumerate(self.cascaded_passes): |
| 502 | print("%3d %s SRAM used %.1f KB" % (idx * 2, ps, ps.sram_used / 1024)) |
| 503 | for idx, tens in enumerate(ps.inputs): |
| 504 | print( |
| 505 | " Input %2d %7.1f KB %-24s %-15s %-15s %-20s %s" |
| 506 | % ( |
| 507 | idx, |
| 508 | tens.storage_size() / 1024, |
| 509 | tens.storage_shape, |
| 510 | tens.mem_area.name, |
| 511 | tens.purpose.name, |
| 512 | tens.format.name, |
| 513 | tens.name, |
| 514 | ) |
| 515 | ) |
| 516 | for idx, tens in enumerate(ps.intermediates): |
| 517 | print( |
| 518 | " Intermediate %2d %7.1f KB %-24s %-15s %-15s %-20s %s" |
| 519 | % ( |
| 520 | idx, |
| 521 | tens.storage_size() / 1024, |
| 522 | tens.storage_shape, |
| 523 | tens.mem_area.name, |
| 524 | tens.purpose.name, |
| 525 | tens.format.name, |
| 526 | tens.name, |
| 527 | ) |
| 528 | ) |
| 529 | for idx, tens in enumerate(ps.outputs): |
| 530 | print( |
| 531 | " Output %2d %7.1f KB %-24s %-15s %-15s %-20s %s" |
| 532 | % ( |
| 533 | idx, |
| 534 | tens.storage_size() / 1024, |
| 535 | tens.storage_shape, |
| 536 | tens.mem_area.name, |
| 537 | tens.purpose.name, |
| 538 | tens.format.name, |
| 539 | tens.name, |
| 540 | ) |
| 541 | ) |
| 542 | print() |
| 543 | |
| 544 | def print_high_level_command_stream(self): |
Michael McGeagh | 775e396 | 2020-07-28 11:44:22 +0100 | [diff] [blame] | 545 | print("print_high_level_command_stream()", self.name) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 546 | for idx, cmd in enumerate(self.high_level_command_stream): |
| 547 | print("%3d %s" % (idx, cmd)) |
| 548 | |
| 549 | |
| 550 | class Graph: |
| 551 | def __init__(self, name="<unnamed>", batch_size=1): |
| 552 | self.name = name |
| 553 | self.batch_size = batch_size |
| 554 | self.subgraphs = [] |
Michael McGeagh | 22f74e1 | 2020-08-07 16:21:03 +0100 | [diff] [blame] | 555 | self.metadata = [] |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 556 | self.memory_used = {} |
Diqing Zhong | db5124c | 2021-01-11 12:52:48 +0100 | [diff] [blame] | 557 | self.total_original_weights = 0 |
Fredrik Svedberg | f5c07c4 | 2021-04-23 14:36:42 +0200 | [diff] [blame] | 558 | self.total_npu_encoded_weights = 0 |
Louis Verhaard | 3c07c97 | 2020-05-07 08:12:58 +0200 | [diff] [blame] | 559 | self.weight_cache = None # See CompressedWeightCache |
Jonas Ohlsson | 845e232 | 2022-03-01 12:39:55 +0100 | [diff] [blame] | 560 | self.bandwidths = 0 |
| 561 | self.macs = 0 |
| 562 | self.cycles = 0 |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 563 | |
| 564 | def get_root_subgraph(self): |
| 565 | return self.subgraphs[0] |
| 566 | |
| 567 | def prune_startup_init_pass(self): |
| 568 | for sg in self.subgraphs: |
| 569 | sg.prune_startup_init_pass() |
| 570 | |
| 571 | def update_consumers(self): |
| 572 | for sg in self.subgraphs: |
| 573 | sg.update_consumers() |
| 574 | |
| 575 | def refresh_after_modification(self): |
| 576 | for sg in self.subgraphs: |
| 577 | sg.refresh_after_modification() |
| 578 | |
Tim Hall | cd03504 | 2023-08-08 14:10:17 +0100 | [diff] [blame] | 579 | def print_operators(self, ignore_placeholder_const=True, show_attributes=True): |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 580 | for sg in self.subgraphs: |
Tim Hall | cd03504 | 2023-08-08 14:10:17 +0100 | [diff] [blame] | 581 | sg.print_operators(ignore_placeholder_const, show_attributes) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 582 | |
Fredrik Svedberg | c875aa6 | 2021-05-06 09:53:31 +0200 | [diff] [blame] | 583 | def print_graph(self, label=None): |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 584 | for sg in self.subgraphs: |
Fredrik Svedberg | c875aa6 | 2021-05-06 09:53:31 +0200 | [diff] [blame] | 585 | sg.print_graph(label) |
Tim Hall | 79d07d2 | 2020-04-27 18:20:16 +0100 | [diff] [blame] | 586 | |
| 587 | def print_graph_with_tensors(self): |
| 588 | for sg in self.subgraphs: |
| 589 | sg.print_graph_with_tensors() |
| 590 | |
| 591 | def print_graph_with_tensor_quantization(self): |
| 592 | for sg in self.subgraphs: |
| 593 | sg.print_graph_with_tensor_quantization() |
| 594 | |
| 595 | def print_passes(self): |
| 596 | for sg in self.subgraphs: |
| 597 | sg.print_passes() |
| 598 | |
| 599 | def print_passes_with_tensors(self): |
| 600 | for sg in self.subgraphs: |
| 601 | sg.print_passes_with_tensors() |
| 602 | |
| 603 | def print_cascaded_passes(self): |
| 604 | for sg in self.subgraphs: |
| 605 | sg.print_cascaded_passes() |
| 606 | |
| 607 | def print_cascaded_passes_with_tensors(self): |
| 608 | for sg in self.subgraphs: |
| 609 | sg.print_cascaded_passes_with_tensors() |
| 610 | |
| 611 | def print_cascaded_passes_with_tensor_sizes(self): |
| 612 | for sg in self.subgraphs: |
| 613 | sg.print_cascaded_passes_with_tensor_sizes() |
| 614 | |
| 615 | def print_high_level_command_stream(self): |
| 616 | for sg in self.subgraphs: |
| 617 | sg.print_high_level_command_stream() |