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README.md ADDED
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+ ---
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+ library_name: ml-agents
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+ tags:
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+ - SoccerTwos
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+ - deep-reinforcement-learning
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+ - reinforcement-learning
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+ - ML-Agents-SoccerTwos
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+ ---
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+
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+ # **poca** Agent playing **SoccerTwos**
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+ This is a trained model of a **poca** agent playing **SoccerTwos**
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+ using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
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+
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+ ## Usage (with ML-Agents)
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+ The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
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+
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+ We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
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+ - A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
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+ browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
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+ - A *longer tutorial* to understand how works ML-Agents:
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+ https://huggingface.co/learn/deep-rl-course/unit5/introduction
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+
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+ ### Resume the training
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+ ```bash
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+ mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
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+ ```
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+
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+ ### Watch your Agent play
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+ You can watch your agent **playing directly in your browser**
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+
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+ 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
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+ 2. Step 1: Find your model_id: gael1130/poca-SoccerTwos
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+ 3. Step 2: Select your *.nn /*.onnx file
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+ 4. Click on Watch the agent play 👀
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+
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+ default_settings: null
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+ behaviors:
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+ SoccerTwos:
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+ trainer_type: poca
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+ hyperparameters:
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+ batch_size: 1024
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+ buffer_size: 50000
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+ learning_rate: 0.0003
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+ beta: 0.01
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+ epsilon: 0.3
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+ lambd: 0.9
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+ num_epoch: 3
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+ learning_rate_schedule: linear
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+ beta_schedule: linear
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+ epsilon_schedule: linear
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+ checkpoint_interval: 500000
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+ network_settings:
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+ normalize: true
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+ hidden_units: 256
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+ num_layers: 3
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+ vis_encode_type: simple
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+ memory: null
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+ goal_conditioning_type: hyper
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+ deterministic: false
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+ reward_signals:
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+ extrinsic:
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+ gamma: 0.995
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+ strength: 1.0
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+ network_settings:
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+ normalize: false
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+ hidden_units: 128
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+ num_layers: 2
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+ vis_encode_type: simple
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+ memory: null
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+ goal_conditioning_type: hyper
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+ deterministic: false
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+ init_path: null
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+ keep_checkpoints: 10
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+ even_checkpoints: false
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+ max_steps: 50000000
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+ time_horizon: 1000
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+ summary_freq: 5000
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+ threaded: false
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+ self_play:
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+ save_steps: 10000
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+ team_change: 100000
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+ swap_steps: 1000
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+ window: 20
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+ play_against_latest_model_ratio: 0.75
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+ initial_elo: 1200.0
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+ behavioral_cloning: null
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+ env_settings:
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+ env_path: ./training-envs-executables/SoccerTwos.exe
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+ env_args: null
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+ base_port: 5005
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+ num_envs: 1
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+ num_areas: 1
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+ timeout_wait: 60
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+ seed: -1
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+ restarts_rate_limit_n: 1
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+ engine_settings:
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+ width: 84
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+ height: 84
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+ capture_frame_rate: 60
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+ no_graphics: true
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+ no_graphics_monitor: false
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+ environment_parameters: null
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+ checkpoint_settings:
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+ run_id: SoccerTwos3
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+ initialize_from: null
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+ load_model: false
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+ resume: false
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+ force: false
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+ train_model: false
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+ inference: false
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+ results_dir: results
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+ torch_settings:
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+ device: null
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+ debug: false
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+ TOO LONG
202
+ TOO LONG
203
+ TOO LONG
204
+ TOO LONG
205
+ TOO LONG
206
+ TOO LONG
207
+ TOO LONG
208
+ TOO LONG
209
+ TOO LONG
210
+ TOO LONG
211
+ TOO LONG
212
+ TOO LONG
213
+ TOO LONG
214
+ TOO LONG
215
+ TOO LONG
216
+ TOO LONG
217
+ TOO LONG
218
+ TOO LONG
219
+ TOO LONG
220
+ TOO LONG
221
+ TOO LONG
222
+ TOO LONG
223
+ TOO LONG
224
+ TOO LONG
225
+ TOO LONG
226
+ TOO LONG
227
+ TOO LONG
228
+ TOO LONG
229
+ TOO LONG
230
+ TOO LONG
231
+ TOO LONG
232
+ TOO LONG
233
+ TOO LONG
234
+ TOO LONG
235
+ TOO LONG
236
+ GRPC Exception: Status(StatusCode=Unknown, Detail="Exception calling application: [WinError 109] Le canal de communication a été fermé"). Disconnecting from trainer.
237
+ Setting up 8 worker threads for Enlighten.
238
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241
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242
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244
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245
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247
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248
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249
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250
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251
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252
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254
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255
+ Peak Allocated Bytes 68.0 KB
256
+ Overflow Count 4
257
+ [ALLOC_TEMP_Background Job.Worker 8]
258
+ Initial Block Size 32.0 KB
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+ Current Block Size 32.0 KB
260
+ Peak Allocated Bytes 54 B
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263
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264
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265
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266
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267
+ [ALLOC_TEMP_Job.Worker 0]
268
+ Initial Block Size 256.0 KB
269
+ Current Block Size 256.0 KB
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+ Peak Allocated Bytes 0 B
271
+ Overflow Count 0
272
+ [ALLOC_TEMP_Background Job.Worker 10]
273
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274
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275
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277
+ [ALLOC_TEMP_Background Job.Worker 9]
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280
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+ [ALLOC_TEMP_Job.Worker 5]
283
+ Initial Block Size 256.0 KB
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+ [ALLOC_TEMP_Background Job.Worker 14]
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+ Current Block Size 32.0 KB
295
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+ [ALLOC_TEMP_Job.Worker 4]
298
+ Initial Block Size 256.0 KB
299
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+ [ALLOC_TEMP_Job.Worker 14]
303
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+ [ALLOC_TEMP_Job.Worker 3]
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+ [ALLOC_TEMP_EnlightenWorker] x 8
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+ Initial Block Size 64.0 KB
324
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328
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329
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330
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+ [ALLOC_TEMP_Background Job.Worker 1]
333
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334
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335
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336
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+ [ALLOC_TEMP_Background Job.Worker 2]
338
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339
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340
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341
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342
+ [ALLOC_TEMP_Background Job.Worker 7]
343
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344
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345
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+ [ALLOC_TEMP_AssetGarbageCollectorHelper] x 15
348
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349
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350
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351
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353
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354
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355
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359
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360
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365
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+ [ALLOC_TEMP_Job.Worker 8]
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369
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376
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+ [ALLOC_TEMP_Job.Worker 1]
378
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379
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380
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381
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+ [ALLOC_TEMP_Job.Worker 2]
383
+ Initial Block Size 256.0 KB
384
+ Current Block Size 256.0 KB
385
+ Peak Allocated Bytes 0.8 KB
386
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387
+ [ALLOC_TEMP_Background Job.Worker 3]
388
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389
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390
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391
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+ [ALLOC_TEMP_Background Job.Worker 11]
393
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394
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395
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399
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409
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418
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419
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+ [ALLOC_TEMP_BatchDeleteObjects]
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+ [ALLOC_DEFAULT] Dual Thread Allocator
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+ Large Block size 4.0 MB
431
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434
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435
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436
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438
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440
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444
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