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Remove verified legacy Loop paths after rename

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  1. loop_ifm_freshkv_7b_20260920-213933/step_26703/README.md +0 -50
  2. loop_ifm_freshkv_7b_20260920-213933/step_26703/config.json +0 -1431
  3. loop_ifm_freshkv_7b_20260920-213933/step_26703/launch_config.env +0 -12
  4. loop_ifm_freshkv_7b_20260920-213933/step_26703/manifest.json +0 -25
  5. loop_ifm_freshkv_7b_20260920-213933/step_26703/model.safetensors +0 -3
  6. loop_ifm_freshkv_7b_20260920-213933/step_26703/training_recipe.json +0 -163
  7. loop_ifm_sharekv_7b_20260920-153012/step_12000/README.md +0 -50
  8. loop_ifm_sharekv_7b_20260920-153012/step_12000/config.json +0 -1414
  9. loop_ifm_sharekv_7b_20260920-153012/step_12000/launch_config.env +0 -12
  10. loop_ifm_sharekv_7b_20260920-153012/step_12000/manifest.json +0 -25
  11. loop_ifm_sharekv_7b_20260920-153012/step_12000/model.safetensors +0 -3
  12. loop_ifm_sharekv_7b_20260920-153012/step_12000/training_recipe.json +0 -163
  13. loop_ifm_sharekv_7b_20260920-153012/step_16000/README.md +0 -50
  14. loop_ifm_sharekv_7b_20260920-153012/step_16000/config.json +0 -1414
  15. loop_ifm_sharekv_7b_20260920-153012/step_16000/launch_config.env +0 -12
  16. loop_ifm_sharekv_7b_20260920-153012/step_16000/manifest.json +0 -25
  17. loop_ifm_sharekv_7b_20260920-153012/step_16000/model.safetensors +0 -3
  18. loop_ifm_sharekv_7b_20260920-153012/step_16000/training_recipe.json +0 -163
  19. loop_ifm_sharekv_7b_20260920-153012/step_20000/README.md +0 -50
  20. loop_ifm_sharekv_7b_20260920-153012/step_20000/config.json +0 -1414
  21. loop_ifm_sharekv_7b_20260920-153012/step_20000/launch_config.env +0 -12
  22. loop_ifm_sharekv_7b_20260920-153012/step_20000/manifest.json +0 -25
  23. loop_ifm_sharekv_7b_20260920-153012/step_20000/model.safetensors +0 -3
  24. loop_ifm_sharekv_7b_20260920-153012/step_20000/training_recipe.json +0 -163
  25. loop_ifm_sharekv_7b_20260920-153012/step_24000/README.md +0 -50
  26. loop_ifm_sharekv_7b_20260920-153012/step_24000/config.json +0 -1414
  27. loop_ifm_sharekv_7b_20260920-153012/step_24000/launch_config.env +0 -12
  28. loop_ifm_sharekv_7b_20260920-153012/step_24000/manifest.json +0 -25
  29. loop_ifm_sharekv_7b_20260920-153012/step_24000/model.safetensors +0 -3
  30. loop_ifm_sharekv_7b_20260920-153012/step_24000/training_recipe.json +0 -163
  31. loop_ifm_sharekv_7b_20260920-153012/step_26703/README.md +0 -50
  32. loop_ifm_sharekv_7b_20260920-153012/step_26703/config.json +0 -1431
  33. loop_ifm_sharekv_7b_20260920-153012/step_26703/launch_config.env +0 -12
  34. loop_ifm_sharekv_7b_20260920-153012/step_26703/manifest.json +0 -25
  35. loop_ifm_sharekv_7b_20260920-153012/step_26703/model.safetensors +0 -3
  36. loop_ifm_sharekv_7b_20260920-153012/step_26703/training_recipe.json +0 -163
  37. loop_ifm_sharekv_7b_20260920-153012/step_4000/README.md +0 -50
  38. loop_ifm_sharekv_7b_20260920-153012/step_4000/config.json +0 -1414
  39. loop_ifm_sharekv_7b_20260920-153012/step_4000/launch_config.env +0 -12
  40. loop_ifm_sharekv_7b_20260920-153012/step_4000/manifest.json +0 -25
  41. loop_ifm_sharekv_7b_20260920-153012/step_4000/model.safetensors +0 -3
  42. loop_ifm_sharekv_7b_20260920-153012/step_4000/training_recipe.json +0 -163
  43. loop_ifm_sharekv_7b_20260920-153012/step_8000/README.md +0 -50
  44. loop_ifm_sharekv_7b_20260920-153012/step_8000/config.json +0 -1414
  45. loop_ifm_sharekv_7b_20260920-153012/step_8000/launch_config.env +0 -12
  46. loop_ifm_sharekv_7b_20260920-153012/step_8000/manifest.json +0 -25
  47. loop_ifm_sharekv_7b_20260920-153012/step_8000/model.safetensors +0 -3
  48. loop_ifm_sharekv_7b_20260920-153012/step_8000/training_recipe.json +0 -163
  49. paper2604_loop2_476m_7b_online_FBW0_K3_adapter_norm/step_12000/README.md +0 -50
  50. paper2604_loop2_476m_7b_online_FBW0_K3_adapter_norm/step_12000/config.json +0 -1379
loop_ifm_freshkv_7b_20260920-213933/step_26703/README.md DELETED
@@ -1,50 +0,0 @@
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- # loop_ifm_freshkv_7b_20260920-213933 / step_26703
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-
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- Native fresh-KV full-bandwidth loop K3/L2 with IFM diagonal raw-embedding writes and a terminal adapter, 655,369,088 parameters. Checkpoint step 26703, consumed 7,000,031,232 input tokens. The full run finished at 26,703 steps with exit 0. Final validation metrics are recorded from this run in config.json.
4
-
5
- Training snapshot source exactly matches https://github.com/FFishy-git/loopTF-workspace/tree/414cc438e67f921df1fcd218dcd738b88c83c2e1 (repository access may be required). The training revision is recorded in config.json; the saved code.diff is empty. Megatron-LM revision ed6ac270bacb6a4258e1c5b4a911bcf0fd3e4d9b; use the project's training dependencies. Export verification used Python 3.13.11 and torch 2.14.0+cu132.
6
-
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- Native safetensors weights only, not a Transformers AutoModel package or full training-resume bundle. Tensor names and mixed dtypes are preserved. Null Megatron extra-state entries are recorded explicitly in config.json. Optimizer/scheduler/RNG/dataloader state is excluded. The JSON model arguments are the effective saved settings; they override the base launch snapshot. K3 denotes three feedback passes, each with two shared-stack depth loops and terminal refiners. IFM injects raw token embeddings before both depth loops with shared projection/gating parameters. Loop2 recomputes fresh KV. Preserve all IFM tensors and settings when loading; a non-IFM model is incompatible.
8
-
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- ## Native CPU loading
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-
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- ```python
12
- import json, torch, importlib, tempfile
13
- from argparse import Namespace
14
- from megatron.core import parallel_state
15
- from megatron.core.process_groups_config import ProcessGroupCollection
16
- from full_bandwidth_loop_tf.megatron.config import build_model_config
17
- from full_bandwidth_loop_tf.megatron.builder import LoopedFullBandwidthMegatronBuilder
18
- from safetensors.torch import load_file
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-
20
- def decode(x):
21
- if isinstance(x, dict):
22
- if "__torch_dtype__" in x: return getattr(torch, x["__torch_dtype__"])
23
- if "__dataclass__" in x:
24
- module, cls, values = x["__dataclass__"]
25
- return getattr(importlib.import_module(module), cls)(**decode(values))
26
- if "__enum__" in x:
27
- module, cls, member = x["__enum__"]
28
- return getattr(importlib.import_module(module), cls)[member]
29
- return {k: decode(v) for k, v in x.items()}
30
- if isinstance(x, list): return [decode(v) for v in x]
31
- return x
32
-
33
- c = json.load(open("config.json"))
34
- a = Namespace(**decode(c["model_arguments"]))
35
- a.use_cpu_initialization = True
36
- a.perform_initialization = False
37
- cfg = build_model_config(a)
38
- # Standalone CPU loading; use your existing groups in an initialized runtime.
39
- with tempfile.TemporaryDirectory() as tmp:
40
- torch.distributed.init_process_group("gloo", init_method="file://" + tmp + "/rdzv", rank=0, world_size=1)
41
- parallel_state.initialize_model_parallel()
42
- with torch.device("meta"):
43
- model = LoopedFullBandwidthMegatronBuilder(cfg).build_model(ProcessGroupCollection.use_mpu_process_groups())
44
- state = load_file("model.safetensors") | c["non_tensor_state"]
45
- model.load_state_dict(state, strict=True, assign=True)
46
- model.eval()
47
- torch.distributed.destroy_process_group()
48
- ```
49
-
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- All exported tensor values/shapes/dtypes/names are exactly equal to the source, all finite, and strict native loading passed. manifest.json hashes every payload file except itself.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
loop_ifm_freshkv_7b_20260920-213933/step_26703/config.json DELETED
@@ -1,1431 +0,0 @@
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- {
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- "checkpoint_format": "safetensors_native_megatron_state_dict",
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- "architecture": "full_bandwidth_loop",
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- "backbone_profile": "paper2604_vanilla",
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- "run_name": "loop_ifm_freshkv_7b_20260920-213933",
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- "iteration": 26703,
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- "checkpoint_version": 3.0,
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- "training_code_revision": "414cc438e67f921df1fcd218dcd738b88c83c2e1",
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- "training_base_revision": "414cc438e67f921df1fcd218dcd738b88c83c2e1",
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- "source_provenance": "Training used training_code_revision with an empty saved code.diff.",
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- "backbone_source_revision": "122366472a31e57982a2877eeee10bb115477713",
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- "parameter_counts": {
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- "total": 655369088,
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- "trainable": 655369088
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- },
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- "model_arguments": {
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- "tensor_model_parallel_size": 1,
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- "tensor_parallel_num_weight_shards": 1,
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- "pipeline_model_parallel_comm_backend": null,
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- "pipeline_model_parallel_size": 1,
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- "sequence_parallel": false,
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- "context_parallel_size": 1,
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- "hierarchical_context_parallel_sizes": null,
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- "expert_model_parallel_size": 1,
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- "expert_tensor_parallel_size": 1,
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- "expert_tensor_parallel_num_weight_shards": 1,
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- "perform_initialization": true,
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- "use_cpu_initialization": null,
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- "fp16": false,
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- "bf16": true,
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- "deterministic_mode": false,
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- "tp_comm_overlap": false,
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- "tp_comm_bulk_wgrad": true,
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- "tp_comm_bulk_dgrad": true,
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- "tp_comm_overlap_ag": true,
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- "tp_comm_overlap_rs": true,
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- "tp_comm_overlap_rs_dgrad": false,
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- "tp_comm_split_ag": true,
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- "tp_comm_split_rs": true,
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- "cross_entropy_loss_fusion": false,
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- "cross_entropy_fusion_impl": "native",
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- "tp_comm_bootstrap_backend": "nccl",
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- "overlap_moe_expert_parallel_comm": false,
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- "delay_wgrad_compute": false,
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- "overlap_dispatch_backward_with_experts_wgrad": false,
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- "ep_overlap_early_attn_memory_release": false,
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- "use_ring_exchange_p2p": false,
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- "defer_embedding_wgrad_compute": false,
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- "wgrad_deferral_limit": 0,
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- "overlap_p2p_comm_warmup_flush": false,
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- "microbatch_group_size_per_vp_stage": null,
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- "mtp_standalone": false,
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- "cpu_offloading_num_layers": 0,
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- "cpu_offloading_retain_pinned_cpu_buffers": false,
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- "num_layers": 20,
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- "mtp_num_layers": null,
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- "mtp_loss_scaling_factor": 0.1,
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- "mtp_use_repeated_layer": false,
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- "mtp_detach_heads": false,
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- "mtp_hsm": false,
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- "mtp_hybrid_override_pattern": null,
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- "account_for_embedding_in_pipeline_split": false,
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- "account_for_loss_in_pipeline_split": false,
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- "hidden_size": 1408,
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- "num_attention_heads": 11,
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- "attention_backend": {
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- "__enum__": [
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- "megatron.core.transformer.enums",
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- "AttnBackend",
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- "auto"
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- ]
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- },
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- "softmax_type": "vanilla",
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- "num_query_groups": 11,
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- "kv_channels": 128,
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- "hidden_dropout": 0.0,
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- "fp32_residual_connection": false,
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- "apply_residual_connection_post_layernorm": false,
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- "qk_clip_alpha": 0.5,
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- "qk_clip_threshold": 100,
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- "attention_output_gate": false,
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- "fp8_recipe": "delayed",
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- "fp8_quantizer_factory": null,
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- "fp8_margin": 0,
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- "fp8_interval": 1,
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- "fp8_amax_history_len": 1,
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- "fp8_amax_compute_algo": "most_recent",
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- "fp8_wgrad": true,
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- "fp8_output_proj": false,
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- "first_last_layers_bf16": false,
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- "num_layers_at_start_in_bf16": 1,
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- "num_layers_at_end_in_bf16": 1,
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- "use_kitchen_attention": false,
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- "kitchen_attention_backend": "sdpa",
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- "fp4": null,
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- "fp4_recipe": "nvfp4",
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- "fp4_quantizer_factory": null,
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- "high_priority_a2a_comm_stream": false,
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- "moe_shared_expert_intermediate_size": null,
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- "moe_shared_expert_gate": false,
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- "moe_shared_expert_overlap": false,
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- "use_grouped_gemm_for_shared_expert": false,
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- "moe_shared_expert_glu_interleave_size": null,
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- "moe_router_topk": 2,
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- "moe_enable_routing_replay": false,
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- "moe_router_padding_for_fp8": false,
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- "moe_router_num_groups": null,
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- "moe_router_group_topk": null,
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- "moe_router_pre_softmax": false,
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- "moe_router_topk_scaling_factor": null,
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- "moe_router_score_function": "softmax",
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- "moe_grouped_gemm": false,
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- "moe_use_grouped_tensor": false,
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- "moe_single_grouped_weight": false,
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- "enable_cuda_graph": false,
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- "cuda_graph_warmup_steps": 3,
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- "external_cuda_graph": false,
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- "cuda_graph_impl": "none",
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- "inference_cuda_graph_scope": {
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- "__enum__": [
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- "megatron.core.transformer.enums",
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- "InferenceCudaGraphScope",
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- "none"
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- ]
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- },
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- "enable_mhc_connections": false,
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- "mhc_sinkhorn_iterations": 20,
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- "mhc_init_gating_factor": 0.01,
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- "use_fused_mhc": false,
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- "mhc_fused_backend": "auto",
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- "clone_scatter_output_in_embedding": true,
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- "config_logger_dir": "",
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- "flash_decode": false,
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- "batch_invariant_mode": false,
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- "batch_invariant_backend": "te_native",
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- "batch_invariant_collective": "ordered",
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- "use_te_activation_func": false,
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- "symmetric_ar_type": null,
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- "nccl_all_reduce_for_prefill": false,
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- "inference_disable_triton_nvls_kernels": false,
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- "inference_grouped_gemm_backend": "vllm",
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- "inference_moe_disable_fused_quant_kernels": false,
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- "is_hybrid_model": false,
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- # loop_ifm_sharekv_7b_20260920-153012 / step_12000
2
-
3
- Native shared-KV full-bandwidth loop K3/L2 with IFM diagonal raw-embedding writes and a terminal adapter, 655,369,088 parameters. Checkpoint step 12000, consumed 3,145,728,000 input tokens. The full run finished at 26,703 steps with exit 0. Earlier checkpoints are intermediate weights; no final evaluation metric is asserted here.
4
-
5
- Training snapshot source exactly matches https://github.com/FFishy-git/loopTF-workspace/tree/414cc438e67f921df1fcd218dcd738b88c83c2e1 (repository access may be required). The training revision is recorded in config.json; the saved code.diff is empty. Megatron-LM revision ed6ac270bacb6a4258e1c5b4a911bcf0fd3e4d9b; use the project's training dependencies. Export verification used Python 3.13.11 and torch 2.14.0+cu132.
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-
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- Native safetensors weights only, not a Transformers AutoModel package or full training-resume bundle. Tensor names and mixed dtypes are preserved. Null Megatron extra-state entries are recorded explicitly in config.json. Optimizer/scheduler/RNG/dataloader state is excluded. The JSON model arguments are the effective saved settings; they override the base launch snapshot. K3 denotes three feedback passes, each with two shared-stack depth loops and terminal refiners. IFM injects raw token embeddings before both depth loops with shared projection/gating parameters. Loop2 reuses connected first-loop KV. Preserve all IFM tensors and settings when loading; a non-IFM model is incompatible.
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-
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- ## Native CPU loading
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-
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- ```python
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- import json, torch, importlib, tempfile
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- from argparse import Namespace
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- from megatron.core import parallel_state
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- from megatron.core.process_groups_config import ProcessGroupCollection
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- from full_bandwidth_loop_tf.megatron.config import build_model_config
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- from full_bandwidth_loop_tf.megatron.builder import LoopedFullBandwidthMegatronBuilder
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- from safetensors.torch import load_file
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-
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- def decode(x):
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- if isinstance(x, dict):
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- if "__torch_dtype__" in x: return getattr(torch, x["__torch_dtype__"])
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- if "__dataclass__" in x:
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- module, cls, values = x["__dataclass__"]
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- return getattr(importlib.import_module(module), cls)(**decode(values))
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- if "__enum__" in x:
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- module, cls, member = x["__enum__"]
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- return getattr(importlib.import_module(module), cls)[member]
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- return {k: decode(v) for k, v in x.items()}
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- if isinstance(x, list): return [decode(v) for v in x]
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- return x
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-
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- c = json.load(open("config.json"))
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- a = Namespace(**decode(c["model_arguments"]))
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- a.use_cpu_initialization = True
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- a.perform_initialization = False
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- cfg = build_model_config(a)
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- # Standalone CPU loading; use your existing groups in an initialized runtime.
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- with tempfile.TemporaryDirectory() as tmp:
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- torch.distributed.init_process_group("gloo", init_method="file://" + tmp + "/rdzv", rank=0, world_size=1)
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- parallel_state.initialize_model_parallel()
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- with torch.device("meta"):
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- model = LoopedFullBandwidthMegatronBuilder(cfg).build_model(ProcessGroupCollection.use_mpu_process_groups())
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- state = load_file("model.safetensors") | c["non_tensor_state"]
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- model.load_state_dict(state, strict=True, assign=True)
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- model.eval()
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- torch.distributed.destroy_process_group()
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- ```
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-
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- All exported tensor values/shapes/dtypes/names are exactly equal to the source, all finite, and strict native loading passed. manifest.json hashes every payload file except itself.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- # loop_ifm_sharekv_7b_20260920-153012 / step_16000
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-
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- Native shared-KV full-bandwidth loop K3/L2 with IFM diagonal raw-embedding writes and a terminal adapter, 655,369,088 parameters. Checkpoint step 16000, consumed 4,194,304,000 input tokens. The full run finished at 26,703 steps with exit 0. Earlier checkpoints are intermediate weights; no final evaluation metric is asserted here.
4
-
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- Training snapshot source exactly matches https://github.com/FFishy-git/loopTF-workspace/tree/414cc438e67f921df1fcd218dcd738b88c83c2e1 (repository access may be required). The training revision is recorded in config.json; the saved code.diff is empty. Megatron-LM revision ed6ac270bacb6a4258e1c5b4a911bcf0fd3e4d9b; use the project's training dependencies. Export verification used Python 3.13.11 and torch 2.14.0+cu132.
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-
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- Native safetensors weights only, not a Transformers AutoModel package or full training-resume bundle. Tensor names and mixed dtypes are preserved. Null Megatron extra-state entries are recorded explicitly in config.json. Optimizer/scheduler/RNG/dataloader state is excluded. The JSON model arguments are the effective saved settings; they override the base launch snapshot. K3 denotes three feedback passes, each with two shared-stack depth loops and terminal refiners. IFM injects raw token embeddings before both depth loops with shared projection/gating parameters. Loop2 reuses connected first-loop KV. Preserve all IFM tensors and settings when loading; a non-IFM model is incompatible.
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-
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- ## Native CPU loading
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-
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- ```python
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- import json, torch, importlib, tempfile
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- from argparse import Namespace
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- from megatron.core import parallel_state
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- from megatron.core.process_groups_config import ProcessGroupCollection
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- from full_bandwidth_loop_tf.megatron.config import build_model_config
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- from full_bandwidth_loop_tf.megatron.builder import LoopedFullBandwidthMegatronBuilder
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- from safetensors.torch import load_file
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-
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- def decode(x):
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- if isinstance(x, dict):
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- if "__torch_dtype__" in x: return getattr(torch, x["__torch_dtype__"])
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- return x
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-
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- c = json.load(open("config.json"))
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- a = Namespace(**decode(c["model_arguments"]))
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- a.use_cpu_initialization = True
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- a.perform_initialization = False
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- cfg = build_model_config(a)
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- # Standalone CPU loading; use your existing groups in an initialized runtime.
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- with tempfile.TemporaryDirectory() as tmp:
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- torch.distributed.init_process_group("gloo", init_method="file://" + tmp + "/rdzv", rank=0, world_size=1)
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- parallel_state.initialize_model_parallel()
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- with torch.device("meta"):
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- model.load_state_dict(state, strict=True, assign=True)
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- model.eval()
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- torch.distributed.destroy_process_group()
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- ```
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-
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- All exported tensor values/shapes/dtypes/names are exactly equal to the source, all finite, and strict native loading passed. manifest.json hashes every payload file except itself.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- # IFM raw-token input injection before every depth loop; fresh 16-GPU arm.
2
- source "$(dirname "${BASH_SOURCE[0]}")/476M_7b_FBW0_K3_L2_ADAPTER_SHARE_KV.env"
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- LOOP_ADAPTER_CHECKPOINT_REFINER=false
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- SAVE_RETAIN_INTERVAL=4000
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- RUN_NAME=paper2604_loop2_476m_7b_fbw_k3_adapter_ifm_sharekv
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- WANDB_RUN_GROUP=loop2_adapter_ifm_476m_7b_FBW_K3
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- WANDB_TAGS=product,loop,loop2,paper2604,476m,7b,fullbandwidth,K3,lookahead_refiner,ifm_diagonal,sharekv
 
 
 
 
 
 
 
 
 
 
 
 
 
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- },
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- "tokenizer_fidelity_note": "Released preprint/current code uses 32001 active tokens, padded to 32064; paper table reports 32008. Follow executable release; do not invent seven tokens.",
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- "execution_architecture": "full_bandwidth_loop",
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- }
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- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
loop_ifm_sharekv_7b_20260920-153012/step_20000/README.md DELETED
@@ -1,50 +0,0 @@
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- # loop_ifm_sharekv_7b_20260920-153012 / step_20000
2
-
3
- Native shared-KV full-bandwidth loop K3/L2 with IFM diagonal raw-embedding writes and a terminal adapter, 655,369,088 parameters. Checkpoint step 20000, consumed 5,242,880,000 input tokens. The full run finished at 26,703 steps with exit 0. Earlier checkpoints are intermediate weights; no final evaluation metric is asserted here.
4
-
5
- Training snapshot source exactly matches https://github.com/FFishy-git/loopTF-workspace/tree/414cc438e67f921df1fcd218dcd738b88c83c2e1 (repository access may be required). The training revision is recorded in config.json; the saved code.diff is empty. Megatron-LM revision ed6ac270bacb6a4258e1c5b4a911bcf0fd3e4d9b; use the project's training dependencies. Export verification used Python 3.13.11 and torch 2.14.0+cu132.
6
-
7
- Native safetensors weights only, not a Transformers AutoModel package or full training-resume bundle. Tensor names and mixed dtypes are preserved. Null Megatron extra-state entries are recorded explicitly in config.json. Optimizer/scheduler/RNG/dataloader state is excluded. The JSON model arguments are the effective saved settings; they override the base launch snapshot. K3 denotes three feedback passes, each with two shared-stack depth loops and terminal refiners. IFM injects raw token embeddings before both depth loops with shared projection/gating parameters. Loop2 reuses connected first-loop KV. Preserve all IFM tensors and settings when loading; a non-IFM model is incompatible.
8
-
9
- ## Native CPU loading
10
-
11
- ```python
12
- import json, torch, importlib, tempfile
13
- from argparse import Namespace
14
- from megatron.core import parallel_state
15
- from megatron.core.process_groups_config import ProcessGroupCollection
16
- from full_bandwidth_loop_tf.megatron.config import build_model_config
17
- from full_bandwidth_loop_tf.megatron.builder import LoopedFullBandwidthMegatronBuilder
18
- from safetensors.torch import load_file
19
-
20
- def decode(x):
21
- if isinstance(x, dict):
22
- if "__torch_dtype__" in x: return getattr(torch, x["__torch_dtype__"])
23
- if "__dataclass__" in x:
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- module, cls, values = x["__dataclass__"]
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- return getattr(importlib.import_module(module), cls)(**decode(values))
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- if "__enum__" in x:
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- module, cls, member = x["__enum__"]
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- return getattr(importlib.import_module(module), cls)[member]
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- return {k: decode(v) for k, v in x.items()}
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- if isinstance(x, list): return [decode(v) for v in x]
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- return x
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-
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- c = json.load(open("config.json"))
34
- a = Namespace(**decode(c["model_arguments"]))
35
- a.use_cpu_initialization = True
36
- a.perform_initialization = False
37
- cfg = build_model_config(a)
38
- # Standalone CPU loading; use your existing groups in an initialized runtime.
39
- with tempfile.TemporaryDirectory() as tmp:
40
- torch.distributed.init_process_group("gloo", init_method="file://" + tmp + "/rdzv", rank=0, world_size=1)
41
- parallel_state.initialize_model_parallel()
42
- with torch.device("meta"):
43
- model = LoopedFullBandwidthMegatronBuilder(cfg).build_model(ProcessGroupCollection.use_mpu_process_groups())
44
- state = load_file("model.safetensors") | c["non_tensor_state"]
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- model.load_state_dict(state, strict=True, assign=True)
46
- model.eval()
47
- torch.distributed.destroy_process_group()
48
- ```
49
-
50
- All exported tensor values/shapes/dtypes/names are exactly equal to the source, all finite, and strict native loading passed. manifest.json hashes every payload file except itself.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
loop_ifm_sharekv_7b_20260920-153012/step_20000/launch_config.env DELETED
@@ -1,12 +0,0 @@
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- # IFM raw-token input injection before every depth loop; fresh 16-GPU arm.
2
- source "$(dirname "${BASH_SOURCE[0]}")/476M_7b_FBW0_K3_L2_ADAPTER_SHARE_KV.env"
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- LOOP_INPUT_WRITE=ifm_diagonal
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- DEPTH_SHARE_KV=true
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- MICRO_BATCH_SIZE=8
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- ENABLE_RECOMPUTE=false
8
- LOOP_ADAPTER_CHECKPOINT_REFINER=false
9
- SAVE_RETAIN_INTERVAL=4000
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- RUN_NAME=paper2604_loop2_476m_7b_fbw_k3_adapter_ifm_sharekv
11
- WANDB_RUN_GROUP=loop2_adapter_ifm_476m_7b_FBW_K3
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- WANDB_TAGS=product,loop,loop2,paper2604,476m,7b,fullbandwidth,K3,lookahead_refiner,ifm_diagonal,sharekv
 
 
 
 
 
 
 
 
 
 
 
 
 
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- "matrix_uniform_bound": "sqrt(3/fan_in)",
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- },
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- },
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- "tokenizer_fidelity_note": "Released preprint/current code uses 32001 active tokens, padded to 32064; paper table reports 32008. Follow executable release; do not invent seven tokens.",
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- "execution_architecture": "full_bandwidth_loop",
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- "objective": "latent_feedback_causal_lm",
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- "loop_final_adapter": "lookahead_refiner",
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- "state_input": "second-loop hidden states after norm_recur and norm_final",
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- "bank_layers": [
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- 0,
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- 10,
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- 19
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- "bank_source": "first depth loop, fresh on each feedback pass",
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- "weight_sharing": "one adapter shared across feedback passes"
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- },
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- "block_application_multiplier_per_pass": 2.15,
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- "block_application_multiplier": 6.449999999999999
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- }
163
- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
loop_ifm_sharekv_7b_20260920-153012/step_24000/README.md DELETED
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1
- # loop_ifm_sharekv_7b_20260920-153012 / step_24000
2
-
3
- Native shared-KV full-bandwidth loop K3/L2 with IFM diagonal raw-embedding writes and a terminal adapter, 655,369,088 parameters. Checkpoint step 24000, consumed 6,291,456,000 input tokens. The full run finished at 26,703 steps with exit 0. Earlier checkpoints are intermediate weights; no final evaluation metric is asserted here.
4
-
5
- Training snapshot source exactly matches https://github.com/FFishy-git/loopTF-workspace/tree/414cc438e67f921df1fcd218dcd738b88c83c2e1 (repository access may be required). The training revision is recorded in config.json; the saved code.diff is empty. Megatron-LM revision ed6ac270bacb6a4258e1c5b4a911bcf0fd3e4d9b; use the project's training dependencies. Export verification used Python 3.13.11 and torch 2.14.0+cu132.
6
-
7
- Native safetensors weights only, not a Transformers AutoModel package or full training-resume bundle. Tensor names and mixed dtypes are preserved. Null Megatron extra-state entries are recorded explicitly in config.json. Optimizer/scheduler/RNG/dataloader state is excluded. The JSON model arguments are the effective saved settings; they override the base launch snapshot. K3 denotes three feedback passes, each with two shared-stack depth loops and terminal refiners. IFM injects raw token embeddings before both depth loops with shared projection/gating parameters. Loop2 reuses connected first-loop KV. Preserve all IFM tensors and settings when loading; a non-IFM model is incompatible.
8
-
9
- ## Native CPU loading
10
-
11
- ```python
12
- import json, torch, importlib, tempfile
13
- from argparse import Namespace
14
- from megatron.core import parallel_state
15
- from megatron.core.process_groups_config import ProcessGroupCollection
16
- from full_bandwidth_loop_tf.megatron.config import build_model_config
17
- from full_bandwidth_loop_tf.megatron.builder import LoopedFullBandwidthMegatronBuilder
18
- from safetensors.torch import load_file
19
-
20
- def decode(x):
21
- if isinstance(x, dict):
22
- if "__torch_dtype__" in x: return getattr(torch, x["__torch_dtype__"])
23
- if "__dataclass__" in x:
24
- module, cls, values = x["__dataclass__"]
25
- return getattr(importlib.import_module(module), cls)(**decode(values))
26
- if "__enum__" in x:
27
- module, cls, member = x["__enum__"]
28
- return getattr(importlib.import_module(module), cls)[member]
29
- return {k: decode(v) for k, v in x.items()}
30
- if isinstance(x, list): return [decode(v) for v in x]
31
- return x
32
-
33
- c = json.load(open("config.json"))
34
- a = Namespace(**decode(c["model_arguments"]))
35
- a.use_cpu_initialization = True
36
- a.perform_initialization = False
37
- cfg = build_model_config(a)
38
- # Standalone CPU loading; use your existing groups in an initialized runtime.
39
- with tempfile.TemporaryDirectory() as tmp:
40
- torch.distributed.init_process_group("gloo", init_method="file://" + tmp + "/rdzv", rank=0, world_size=1)
41
- parallel_state.initialize_model_parallel()
42
- with torch.device("meta"):
43
- model = LoopedFullBandwidthMegatronBuilder(cfg).build_model(ProcessGroupCollection.use_mpu_process_groups())
44
- state = load_file("model.safetensors") | c["non_tensor_state"]
45
- model.load_state_dict(state, strict=True, assign=True)
46
- model.eval()
47
- torch.distributed.destroy_process_group()
48
- ```
49
-
50
- All exported tensor values/shapes/dtypes/names are exactly equal to the source, all finite, and strict native loading passed. manifest.json hashes every payload file except itself.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- },
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- "pipeline_model_parallel_comm_backend": null,
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- "hierarchical_context_parallel_sizes": null,
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- "fp16": false,
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- "tp_comm_bulk_wgrad": true,
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- "tp_comm_bulk_dgrad": true,
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- "tp_comm_overlap_ag": true,
36
- "tp_comm_overlap_rs": true,
37
- "tp_comm_overlap_rs_dgrad": false,
38
- "tp_comm_split_ag": true,
39
- "tp_comm_split_rs": true,
40
- "cross_entropy_loss_fusion": false,
41
- "cross_entropy_fusion_impl": "native",
42
- "tp_comm_bootstrap_backend": "nccl",
43
- "overlap_moe_expert_parallel_comm": false,
44
- "delay_wgrad_compute": false,
45
- "overlap_dispatch_backward_with_experts_wgrad": false,
46
- "ep_overlap_early_attn_memory_release": false,
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- "use_ring_exchange_p2p": false,
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- "defer_embedding_wgrad_compute": false,
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- "wgrad_deferral_limit": 0,
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- "overlap_p2p_comm_warmup_flush": false,
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- "microbatch_group_size_per_vp_stage": null,
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- "mtp_standalone": false,
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- "cpu_offloading_num_layers": 0,
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- "cpu_offloading_retain_pinned_cpu_buffers": false,
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- "hidden_size": 1408,
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- "attention_backend": {
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- "__enum__": [
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- "megatron.core.transformer.enums",
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- "AttnBackend",
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- "auto"
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- ]
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- "flash_attention_version": null,
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- "softmax_type": "vanilla",
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- "num_query_groups": 11,
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- "ffn_hidden_size": 5632,
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- "kv_channels": 128,
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- "hidden_dropout": 0.0,
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- "attention_dropout": 0.0,
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- "fp32_residual_connection": false,
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- "apply_residual_connection_post_layernorm": false,
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- "layernorm_epsilon": 1e-06,
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- "layernorm_zero_centered_gamma": false,
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- "add_bias_linear": false,
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- "loading": "Construct matching native Megatron model from model_arguments, restore non_tensor_state, load_state_dict(strict=True, assign=True). See README."
1414
- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
loop_ifm_sharekv_7b_20260920-153012/step_24000/launch_config.env DELETED
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- source "$(dirname "${BASH_SOURCE[0]}")/476M_7b_FBW0_K3_L2_ADAPTER_SHARE_KV.env"
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- DEPTH_SHARE_KV=true
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- LOOP_ADAPTER_CHECKPOINT_REFINER=false
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- SAVE_RETAIN_INTERVAL=4000
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- RUN_NAME=paper2604_loop2_476m_7b_fbw_k3_adapter_ifm_sharekv
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- WANDB_RUN_GROUP=loop2_adapter_ifm_476m_7b_FBW_K3
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- WANDB_TAGS=product,loop,loop2,paper2604,476m,7b,fullbandwidth,K3,lookahead_refiner,ifm_diagonal,sharekv
 
 
 
 
 
 
 
 
 
 
 
 
 
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- "tokenizer_fidelity_note": "Released preprint/current code uses 32001 active tokens, padded to 32064; paper table reports 32008. Follow executable release; do not invent seven tokens.",
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- "loop_final_adapter": "lookahead_refiner",
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- "state_input": "second-loop hidden states after norm_recur and norm_final",
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- "bank_layers": [
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- 0,
154
- 10,
155
- 19
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- ],
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- "bank_source": "first depth loop, fresh on each feedback pass",
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- "weight_sharing": "one adapter shared across feedback passes"
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- },
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- "block_application_multiplier_per_pass": 2.15,
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- "block_application_multiplier": 6.449999999999999
162
- }
163
- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
loop_ifm_sharekv_7b_20260920-153012/step_26703/README.md DELETED
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1
- # loop_ifm_sharekv_7b_20260920-153012 / step_26703
2
-
3
- Native shared-KV full-bandwidth loop K3/L2 with IFM diagonal raw-embedding writes and a terminal adapter, 655,369,088 parameters. Checkpoint step 26703, consumed 7,000,031,232 input tokens. The full run finished at 26,703 steps with exit 0. Earlier checkpoints are intermediate weights; no final evaluation metric is asserted here.
4
-
5
- Training snapshot source exactly matches https://github.com/FFishy-git/loopTF-workspace/tree/414cc438e67f921df1fcd218dcd738b88c83c2e1 (repository access may be required). The training revision is recorded in config.json; the saved code.diff is empty. Megatron-LM revision ed6ac270bacb6a4258e1c5b4a911bcf0fd3e4d9b; use the project's training dependencies. Export verification used Python 3.13.11 and torch 2.14.0+cu132.
6
-
7
- Native safetensors weights only, not a Transformers AutoModel package or full training-resume bundle. Tensor names and mixed dtypes are preserved. Null Megatron extra-state entries are recorded explicitly in config.json. Optimizer/scheduler/RNG/dataloader state is excluded. The JSON model arguments are the effective saved settings; they override the base launch snapshot. K3 denotes three feedback passes, each with two shared-stack depth loops and terminal refiners. IFM injects raw token embeddings before both depth loops with shared projection/gating parameters. Loop2 reuses connected first-loop KV. Preserve all IFM tensors and settings when loading; a non-IFM model is incompatible.
8
-
9
- ## Native CPU loading
10
-
11
- ```python
12
- import json, torch, importlib, tempfile
13
- from argparse import Namespace
14
- from megatron.core import parallel_state
15
- from megatron.core.process_groups_config import ProcessGroupCollection
16
- from full_bandwidth_loop_tf.megatron.config import build_model_config
17
- from full_bandwidth_loop_tf.megatron.builder import LoopedFullBandwidthMegatronBuilder
18
- from safetensors.torch import load_file
19
-
20
- def decode(x):
21
- if isinstance(x, dict):
22
- if "__torch_dtype__" in x: return getattr(torch, x["__torch_dtype__"])
23
- if "__dataclass__" in x:
24
- module, cls, values = x["__dataclass__"]
25
- return getattr(importlib.import_module(module), cls)(**decode(values))
26
- if "__enum__" in x:
27
- module, cls, member = x["__enum__"]
28
- return getattr(importlib.import_module(module), cls)[member]
29
- return {k: decode(v) for k, v in x.items()}
30
- if isinstance(x, list): return [decode(v) for v in x]
31
- return x
32
-
33
- c = json.load(open("config.json"))
34
- a = Namespace(**decode(c["model_arguments"]))
35
- a.use_cpu_initialization = True
36
- a.perform_initialization = False
37
- cfg = build_model_config(a)
38
- # Standalone CPU loading; use your existing groups in an initialized runtime.
39
- with tempfile.TemporaryDirectory() as tmp:
40
- torch.distributed.init_process_group("gloo", init_method="file://" + tmp + "/rdzv", rank=0, world_size=1)
41
- parallel_state.initialize_model_parallel()
42
- with torch.device("meta"):
43
- model = LoopedFullBandwidthMegatronBuilder(cfg).build_model(ProcessGroupCollection.use_mpu_process_groups())
44
- state = load_file("model.safetensors") | c["non_tensor_state"]
45
- model.load_state_dict(state, strict=True, assign=True)
46
- model.eval()
47
- torch.distributed.destroy_process_group()
48
- ```
49
-
50
- All exported tensor values/shapes/dtypes/names are exactly equal to the source, all finite, and strict native loading passed. manifest.json hashes every payload file except itself.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- },
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- "tensor_parallel_num_weight_shards": 1,
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- "pipeline_model_parallel_comm_backend": null,
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- "hierarchical_context_parallel_sizes": null,
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- "fp16": false,
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- "tp_comm_bulk_wgrad": true,
34
- "tp_comm_bulk_dgrad": true,
35
- "tp_comm_overlap_ag": true,
36
- "tp_comm_overlap_rs": true,
37
- "tp_comm_overlap_rs_dgrad": false,
38
- "tp_comm_split_ag": true,
39
- "tp_comm_split_rs": true,
40
- "cross_entropy_loss_fusion": false,
41
- "cross_entropy_fusion_impl": "native",
42
- "tp_comm_bootstrap_backend": "nccl",
43
- "overlap_moe_expert_parallel_comm": false,
44
- "delay_wgrad_compute": false,
45
- "overlap_dispatch_backward_with_experts_wgrad": false,
46
- "ep_overlap_early_attn_memory_release": false,
47
- "use_ring_exchange_p2p": false,
48
- "defer_embedding_wgrad_compute": false,
49
- "wgrad_deferral_limit": 0,
50
- "overlap_p2p_comm_warmup_flush": false,
51
- "microbatch_group_size_per_vp_stage": null,
52
- "mtp_standalone": false,
53
- "cpu_offloading_num_layers": 0,
54
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- "bank_layers": [
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- 0,
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- "bank_source": "first depth loop, fresh on each feedback pass",
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- "weight_sharing": "one adapter shared across feedback passes"
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- },
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- "block_application_multiplier_per_pass": 2.15,
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- "block_application_multiplier": 6.449999999999999
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- }
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- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
loop_ifm_sharekv_7b_20260920-153012/step_4000/README.md DELETED
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1
- # loop_ifm_sharekv_7b_20260920-153012 / step_4000
2
-
3
- Native shared-KV full-bandwidth loop K3/L2 with IFM diagonal raw-embedding writes and a terminal adapter, 655,369,088 parameters. Checkpoint step 4000, consumed 1,048,576,000 input tokens. The full run finished at 26,703 steps with exit 0. Earlier checkpoints are intermediate weights; no final evaluation metric is asserted here.
4
-
5
- Training snapshot source exactly matches https://github.com/FFishy-git/loopTF-workspace/tree/414cc438e67f921df1fcd218dcd738b88c83c2e1 (repository access may be required). The training revision is recorded in config.json; the saved code.diff is empty. Megatron-LM revision ed6ac270bacb6a4258e1c5b4a911bcf0fd3e4d9b; use the project's training dependencies. Export verification used Python 3.13.11 and torch 2.14.0+cu132.
6
-
7
- Native safetensors weights only, not a Transformers AutoModel package or full training-resume bundle. Tensor names and mixed dtypes are preserved. Null Megatron extra-state entries are recorded explicitly in config.json. Optimizer/scheduler/RNG/dataloader state is excluded. The JSON model arguments are the effective saved settings; they override the base launch snapshot. K3 denotes three feedback passes, each with two shared-stack depth loops and terminal refiners. IFM injects raw token embeddings before both depth loops with shared projection/gating parameters. Loop2 reuses connected first-loop KV. Preserve all IFM tensors and settings when loading; a non-IFM model is incompatible.
8
-
9
- ## Native CPU loading
10
-
11
- ```python
12
- import json, torch, importlib, tempfile
13
- from argparse import Namespace
14
- from megatron.core import parallel_state
15
- from megatron.core.process_groups_config import ProcessGroupCollection
16
- from full_bandwidth_loop_tf.megatron.config import build_model_config
17
- from full_bandwidth_loop_tf.megatron.builder import LoopedFullBandwidthMegatronBuilder
18
- from safetensors.torch import load_file
19
-
20
- def decode(x):
21
- if isinstance(x, dict):
22
- if "__torch_dtype__" in x: return getattr(torch, x["__torch_dtype__"])
23
- if "__dataclass__" in x:
24
- module, cls, values = x["__dataclass__"]
25
- return getattr(importlib.import_module(module), cls)(**decode(values))
26
- if "__enum__" in x:
27
- module, cls, member = x["__enum__"]
28
- return getattr(importlib.import_module(module), cls)[member]
29
- return {k: decode(v) for k, v in x.items()}
30
- if isinstance(x, list): return [decode(v) for v in x]
31
- return x
32
-
33
- c = json.load(open("config.json"))
34
- a = Namespace(**decode(c["model_arguments"]))
35
- a.use_cpu_initialization = True
36
- a.perform_initialization = False
37
- cfg = build_model_config(a)
38
- # Standalone CPU loading; use your existing groups in an initialized runtime.
39
- with tempfile.TemporaryDirectory() as tmp:
40
- torch.distributed.init_process_group("gloo", init_method="file://" + tmp + "/rdzv", rank=0, world_size=1)
41
- parallel_state.initialize_model_parallel()
42
- with torch.device("meta"):
43
- model = LoopedFullBandwidthMegatronBuilder(cfg).build_model(ProcessGroupCollection.use_mpu_process_groups())
44
- state = load_file("model.safetensors") | c["non_tensor_state"]
45
- model.load_state_dict(state, strict=True, assign=True)
46
- model.eval()
47
- torch.distributed.destroy_process_group()
48
- ```
49
-
50
- All exported tensor values/shapes/dtypes/names are exactly equal to the source, all finite, and strict native loading passed. manifest.json hashes every payload file except itself.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- {
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- "checkpoint_format": "safetensors_native_megatron_state_dict",
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- "loading": "Construct matching native Megatron model from model_arguments, restore non_tensor_state, load_state_dict(strict=True, assign=True). See README."
1414
- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
loop_ifm_sharekv_7b_20260920-153012/step_4000/launch_config.env DELETED
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- WANDB_RUN_GROUP=loop2_adapter_ifm_476m_7b_FBW_K3
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- WANDB_TAGS=product,loop,loop2,paper2604,476m,7b,fullbandwidth,K3,lookahead_refiner,ifm_diagonal,sharekv
 
 
 
 
 
 
 
 
 
 
 
 
 
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- "matrix_uniform_bound": "sqrt(3/fan_in)",
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- },
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- "loop_adapter_parameters": 83271936
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- },
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- "tokenizer_fidelity_note": "Released preprint/current code uses 32001 active tokens, padded to 32064; paper table reports 32008. Follow executable release; do not invent seven tokens.",
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- "execution_architecture": "full_bandwidth_loop",
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- "objective": "latent_feedback_causal_lm",
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- "feedback_enabled": true,
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- "train_passes": 3,
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- },
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- "logical_layers_per_pass": 40,
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- "shared_layer_weights": true,
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- "depth_share_kv": true,
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- "depth_kv_policy": "first_loop_per_layer_connected",
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- "norm_placement": "embedding once; recur/final after loop 2 before three refiners; no post-refiner norm",
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- "loop_input_write": "ifm_diagonal",
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- "loop_input_write_source": "raw_token_embeddings",
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- "loop_input_write_placement": "before_every_depth_loop_after_initial_norm_emb",
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- "loop_input_write_sharing": "all_depth_loops_and_outer_feedback_passes",
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- "loop_input_write_init": "paper_matrix; a=b_delta=0; alpha=0.5; delta=log(2)",
145
- "loop_final_adapter": "lookahead_refiner",
146
- "loop_adapter": {
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- "ffn_size": 5632,
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- "state_input": "second-loop hidden states after norm_recur and norm_final",
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- "terminal_norms": true,
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- "attention_backend": "sdpa_auto",
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- "checkpoint_refiner": false,
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- "bank_layers": [
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- 0,
154
- 10,
155
- 19
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- ],
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- "bank_source": "first depth loop, fresh on each feedback pass",
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- "weight_sharing": "one adapter shared across feedback passes"
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- },
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- "block_application_multiplier_per_pass": 2.15,
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- "block_application_multiplier": 6.449999999999999
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- }
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- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
loop_ifm_sharekv_7b_20260920-153012/step_8000/README.md DELETED
@@ -1,50 +0,0 @@
1
- # loop_ifm_sharekv_7b_20260920-153012 / step_8000
2
-
3
- Native shared-KV full-bandwidth loop K3/L2 with IFM diagonal raw-embedding writes and a terminal adapter, 655,369,088 parameters. Checkpoint step 8000, consumed 2,097,152,000 input tokens. The full run finished at 26,703 steps with exit 0. Earlier checkpoints are intermediate weights; no final evaluation metric is asserted here.
4
-
5
- Training snapshot source exactly matches https://github.com/FFishy-git/loopTF-workspace/tree/414cc438e67f921df1fcd218dcd738b88c83c2e1 (repository access may be required). The training revision is recorded in config.json; the saved code.diff is empty. Megatron-LM revision ed6ac270bacb6a4258e1c5b4a911bcf0fd3e4d9b; use the project's training dependencies. Export verification used Python 3.13.11 and torch 2.14.0+cu132.
6
-
7
- Native safetensors weights only, not a Transformers AutoModel package or full training-resume bundle. Tensor names and mixed dtypes are preserved. Null Megatron extra-state entries are recorded explicitly in config.json. Optimizer/scheduler/RNG/dataloader state is excluded. The JSON model arguments are the effective saved settings; they override the base launch snapshot. K3 denotes three feedback passes, each with two shared-stack depth loops and terminal refiners. IFM injects raw token embeddings before both depth loops with shared projection/gating parameters. Loop2 reuses connected first-loop KV. Preserve all IFM tensors and settings when loading; a non-IFM model is incompatible.
8
-
9
- ## Native CPU loading
10
-
11
- ```python
12
- import json, torch, importlib, tempfile
13
- from argparse import Namespace
14
- from megatron.core import parallel_state
15
- from megatron.core.process_groups_config import ProcessGroupCollection
16
- from full_bandwidth_loop_tf.megatron.config import build_model_config
17
- from full_bandwidth_loop_tf.megatron.builder import LoopedFullBandwidthMegatronBuilder
18
- from safetensors.torch import load_file
19
-
20
- def decode(x):
21
- if isinstance(x, dict):
22
- if "__torch_dtype__" in x: return getattr(torch, x["__torch_dtype__"])
23
- if "__dataclass__" in x:
24
- module, cls, values = x["__dataclass__"]
25
- return getattr(importlib.import_module(module), cls)(**decode(values))
26
- if "__enum__" in x:
27
- module, cls, member = x["__enum__"]
28
- return getattr(importlib.import_module(module), cls)[member]
29
- return {k: decode(v) for k, v in x.items()}
30
- if isinstance(x, list): return [decode(v) for v in x]
31
- return x
32
-
33
- c = json.load(open("config.json"))
34
- a = Namespace(**decode(c["model_arguments"]))
35
- a.use_cpu_initialization = True
36
- a.perform_initialization = False
37
- cfg = build_model_config(a)
38
- # Standalone CPU loading; use your existing groups in an initialized runtime.
39
- with tempfile.TemporaryDirectory() as tmp:
40
- torch.distributed.init_process_group("gloo", init_method="file://" + tmp + "/rdzv", rank=0, world_size=1)
41
- parallel_state.initialize_model_parallel()
42
- with torch.device("meta"):
43
- model = LoopedFullBandwidthMegatronBuilder(cfg).build_model(ProcessGroupCollection.use_mpu_process_groups())
44
- state = load_file("model.safetensors") | c["non_tensor_state"]
45
- model.load_state_dict(state, strict=True, assign=True)
46
- model.eval()
47
- torch.distributed.destroy_process_group()
48
- ```
49
-
50
- All exported tensor values/shapes/dtypes/names are exactly equal to the source, all finite, and strict native loading passed. manifest.json hashes every payload file except itself.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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paper2604_loop2_476m_7b_online_FBW0_K3_adapter_norm/step_12000/README.md DELETED
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- # paper2604_loop2_476m_7b_online_FBW0_K3_adapter_norm / step_12000
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-
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- Native full-bandwidth loop K3/L2 normalized-state refiner model, 653,383,808 parameters. Checkpoint step 12000, consumed 3,145,728,000 input tokens. The full run finished at 26,703 steps with exit 0. Earlier checkpoints are intermediate weights; no final evaluation metric is asserted here.
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-
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- Training snapshot source exactly matches https://github.com/FFishy-git/loopTF-workspace/tree/8ce34798f6137fdaa27e6dfccc9323b506142b83 (repository access may be required). The original dirty base revision is recorded separately in config.json. Megatron-LM revision ed6ac270bacb6a4258e1c5b4a911bcf0fd3e4d9b; use the project's training dependencies. Export verification used Python 3.13.11 and torch 2.14.0+cu132.
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-
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- Native safetensors weights only, not a Transformers AutoModel package or full training-resume bundle. Tensor names and mixed dtypes are preserved. Null Megatron extra-state entries are recorded explicitly in config.json. Optimizer/scheduler/RNG/dataloader state is excluded. The JSON model arguments are the effective saved settings; they override the base launch snapshot. K3 denotes three feedback passes, each with two shared-stack depth loops and terminal refiners.
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-
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- ## Native CPU loading
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-
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- ```python
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- import json, torch, importlib, tempfile
13
- from argparse import Namespace
14
- from megatron.core import parallel_state
15
- from megatron.core.process_groups_config import ProcessGroupCollection
16
- from full_bandwidth_loop_tf.megatron.config import build_model_config
17
- from full_bandwidth_loop_tf.megatron.builder import LoopedFullBandwidthMegatronBuilder
18
- from safetensors.torch import load_file
19
-
20
- def decode(x):
21
- if isinstance(x, dict):
22
- if "__torch_dtype__" in x: return getattr(torch, x["__torch_dtype__"])
23
- if "__dataclass__" in x:
24
- module, cls, values = x["__dataclass__"]
25
- return getattr(importlib.import_module(module), cls)(**decode(values))
26
- if "__enum__" in x:
27
- module, cls, member = x["__enum__"]
28
- return getattr(importlib.import_module(module), cls)[member]
29
- return {k: decode(v) for k, v in x.items()}
30
- if isinstance(x, list): return [decode(v) for v in x]
31
- return x
32
-
33
- c = json.load(open("config.json"))
34
- a = Namespace(**decode(c["model_arguments"]))
35
- a.use_cpu_initialization = True
36
- a.perform_initialization = False
37
- cfg = build_model_config(a)
38
- # Standalone CPU loading; use your existing groups in an initialized runtime.
39
- with tempfile.TemporaryDirectory() as tmp:
40
- torch.distributed.init_process_group("gloo", init_method="file://" + tmp + "/rdzv", rank=0, world_size=1)
41
- parallel_state.initialize_model_parallel()
42
- with torch.device("meta"):
43
- model = LoopedFullBandwidthMegatronBuilder(cfg).build_model(ProcessGroupCollection.use_mpu_process_groups())
44
- state = load_file("model.safetensors") | c["non_tensor_state"]
45
- model.load_state_dict(state, strict=True, assign=True)
46
- model.eval()
47
- torch.distributed.destroy_process_group()
48
- ```
49
-
50
- All exported tensor values/shapes/dtypes/names are exactly equal to the source, all finite, and strict native loading passed. manifest.json hashes every payload file except itself.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
paper2604_loop2_476m_7b_online_FBW0_K3_adapter_norm/step_12000/config.json DELETED
@@ -1,1379 +0,0 @@
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- ]
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- "loading": "Construct matching native Megatron model from model_arguments, restore non_tensor_state, load_state_dict(strict=True, assign=True). See README."
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