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Premchandyadav369
Complete 16-phase scientific hardening, strict checkpoint audit, empirical benchmarks, and documentation
7aefd9e | # Phase Zero — Complete Repository Inventory | |
| ## 1. Root-Level Source, Configuration, and Export Files | |
| | Path | Type | Size (Bytes) | Role & Status | | |
| | :--- | :--- | :--- | :--- | | |
| | `README.md` | Documentation | ~56 KB | Primary repository documentation & Hugging Face Hub landing page | | |
| | `MODEL_CARD.md` | Documentation | ~18 KB | Standalone model card with architecture, evidence, and limitations | | |
| | `config.json` | Configuration | 834 B | Hugging Face `QTensorFormerConfig` JSON descriptor | | |
| | `configuration_qtensorformer.py` | Source (Family 4) | 11,708 B | Hugging Face `PretrainedConfig` (`QTensorFormerConfig`) | | |
| | `modeling_qtensorformer.py` | Source (Family 4) | 36,326 B | Hugging Face `PreTrainedModel` (`QTensorFormerForCausalLM`) | | |
| | `qtensorformer_vision.py` | Source | 10,842 B | Experimental multimodal vision-language extension (`QTensorFormerForConditionalGeneration`) | | |
| | `qtensorformer_to_gguf.py` | Deployment Tool | 12,150 B | Pure-Python GGUF v3 binary serializer & Ollama `Modelfile` generator (`strict=True` enforced) | | |
| | `export_onnx.py` | Deployment Tool | 4,120 B | ONNX graph exporter and structural checker for `TTLinear` | | |
| | `q_tensor_former.py` | Legacy Prototype (Family 1) | 26,462 B | Historical single-file v1 prototype (`CFG`, `QTensorFormer`) | | |
| | `q_tensor_former_v2.py` | Legacy Prototype (Family 2) | 43,441 B | Historical single-file v2 prototype (`Config`, `QTensorFormer`) | | |
| | `qtensorformer_small.pt` | Legacy Checkpoint | 5,432,305 B | Historical external TensorLy container checkpoint (incompatible under `strict=True`) | | |
| | `demo.py` | Script | ~12 KB | Interactive demonstration script | | |
| | `app.py` | UI Script | ~14 KB | Gradio telemetry & interactive dashboard | | |
| | `requirements.txt` | Packaging | 145 B | Core Python dependencies | | |
| | `pyproject.toml` / `setup.py` | Packaging | ~2 KB | Package build metadata | | |
| --- | |
| ## 2. Core Research Package (`src/` — Family 3) | |
| | Path | Classes / Functions | Status | | |
| | :--- | :--- | :--- | | |
| | `src/__init__.py` | Package exports | Active | | |
| | `src/config.py` | `ModelConfig`, `TrainingConfig`, `BudgetConfig`, `ExperimentConfig`, `validate_model_config` | Active, Canonical Research Config | | |
| | `src/models.py` | `QTensorFormer`, `DenseBaseline`, `PositionalEncoding`, `create_model` | Active, Canonical Research Model | | |
| | `src/blocks.py` | `HybridBlock` | Active | | |
| | `src/attention.py` | `MultiHeadAttention` (SDPA, GQA/MQA, RoPE, optional QKSAM fidelity kernel) | Active | | |
| | `src/tensor_layers.py` | `TTLinear`, `TTFeedForward`, `factorize_dim` | Active | | |
| | `src/information_state.py` | `TokenInformationState` (8D normalized information vector $z_t$ + LOFO ablation) | Active | | |
| | `src/resource_allocator.py` | `MarginalValueModel`, `InformationValueAllocator`, `PIDDualSubgradientController`, `ConstrainedDecisionEngine`, `AllocationBudget` | Active | | |
| | `src/kv_cache.py` | `AdaptiveKVCache`, `HierarchicalAdaptiveKVCache`, `QuantizedKVTensor`, `KVPrecision` | Active | | |
| | `src/quantum_backend.py` | `QuantumBackend`, `ClassicalSurrogateUnitary`, `BackendType`, `compute_meyer_wallach_entanglement`, `compute_quantum_expressibility` | Active | | |
| | `src/quantum_layers.py` | `QuantumAngleEmbedding`, `EntanglementMonitor`, `ClassicalQuantumFallback` | Active | | |
| | `src/router.py` | `QuantumRouter` | Active (fixed deterministic `__init__` layer registration) | | |
| | `src/scheduler.py` | `RankScheduler`, `BudgetAwareScheduler` | Active | | |
| | `src/hardware_cost_model.py` | `HardwareCostModel`, `HardwareRooflineAnalyzer`, `KernelBreakdownProfiler` | Active | | |
| | `src/phase_aware_profiler.py` | `PhaseAwareProfiler`, `PhaseProfileResult` | Active | | |
| | `src/counterfactual_learning.py` | `CounterfactualDatasetGenerator`, `PolicyBenchmarkEvaluator` | Active | | |
| | `src/baseline_comparator.py` | `BaselineComparator` | Active | | |
| | `src/baselines.py` | `StandardTransformer`, `DistilledTransformer`, `PrunedTransformer` | Active | | |
| | `src/hf_model.py` | Re-exports `QTensorFormerConfig` and `QTensorFormerForCausalLM` | Active | | |
| | `src/validator.py` | `ScientificClaimValidator` | Active | | |
| --- | |
| ## 3. Custom Kernel & Acceleration Modules (`kernels/`) | |
| | Path | Classes / Functions | Status | | |
| | :--- | :--- | :--- | | |
| | `kernels/tt_kernels.py` | `FusedTTContraction`, `DynamicINT4Quantizer`, `HAS_TRITON` | Active (PyTorch fallback on CPU; Triton JIT when CUDA + Triton available) | | |
| --- | |
| ## 4. Verification & Test Suite (`tests/`) | |
| | Test File | Scope | Status | | |
| | :--- | :--- | :--- | | |
| | `tests/test_advanced_features.py` | GQA, Early Exit, Roofline, Kernel Breakdown, Marginal Value | Passing | | |
| | `tests/test_baseline_comparator.py` | Multi-baseline evaluation & Pareto domination | Passing | | |
| | `tests/test_frontier_v10.py` | GGUF v3 binary spec, Vision-Language forward, Triton/PyTorch fallback, ONNX export | Passing | | |
| | `tests/test_hf_integration.py` | `AutoConfig`, `AutoModelForCausalLM`, `.generate()`, `save_pretrained`/`from_pretrained` | Passing | | |
| | `tests/test_information_state.py` | 8D `TokenInformationState` bounds, normalization, ablation | Passing | | |
| | `tests/test_kv_cache.py` | `AdaptiveKVCache` FP16/INT8/INT4 quantization, sink retention, eviction | Passing | | |
| | `tests/test_model.py` | Model forward/backward shapes and presets | Passing | | |
| | `tests/test_nested_tt.py` | Nested TT core slicing and rank consistency | Passing | | |
| | `tests/test_quantum_backend.py` | `QuantumBackend`, `ClassicalSurrogateUnitary`, Meyer-Wallach, Expressibility | Passing | | |
| | `tests/test_quantum_layers.py` | Quantum embeddings & classical fallback (3 PennyLane-specific tests skipped when `pennylane` absent) | Passing / Skipped | | |
| | `tests/test_research_hardening.py` | Counterfactual learning, hierarchical KV, phase-aware profiler | Passing | | |
| | `tests/test_resource_allocator.py` | `InformationValueAllocator`, hysteresis, PID dual controller | Passing | | |
| | `tests/test_scientific_guardrails.py` | `strict=True` checkpoint enforcement, GGUF strict check, config validation, router init | Passing | | |
| | `tests/test_tensor_layers.py` | `TTLinear` & `TTFeedForward` shapes, reconstruction, compression | Passing | | |
| | `tests/test_v4.py` | End-to-end integration tests | Passing | | |
| --- | |
| ## 5. Benchmark Scripts, Raw Results, and Forensic Reports | |
| - **Scripts (`scripts/`):** | |
| - `scripts/run_scientific_benchmark.py` — End-to-end reproducible benchmark suite (`RUN-20261013-QTF-HARDENING`) | |
| - `scripts/scientific_integrity_checker.py` — Automated scientific integrity & evidence-label auditor | |
| - `scripts/smoke_test.py` — Fast deterministic one-command smoke test | |
| - `scripts/generate_figures.py` & `scripts/run_experiments.py` — Historical figure and experiment generators | |
| - **Empirical Results (`results/`):** | |
| - `results/metadata/run_metadata.json` | |
| - `results/raw/checkpoint_integrity.json` | |
| - `results/raw/cold_start_and_edge.json` | |
| - `results/raw/tt_compression_audit.json` | |
| - `results/raw/controller_audit.json` | |
| - `results/raw/kv_cache_audit.json` | |
| - `results/raw/quantum_pathway_audit.json` | |
| - `results/processed/benchmark_summary.json` | |
| - `results/processed/benchmark_summary.csv` | |
| - **Reports (`reports/`):** | |
| - Full 22-document forensic, architectural, checkpoint, benchmark, edge/cold-start, energy, novelty, and release-readiness report suite. | |