Set batch_size=0 in config/gpu/h100.toml as sentinel for auto-compute.
The constructor now treats batch_size==0 as "let AutoBatchSizer drive":
it uses the VRAM-computed ceiling capped at 8192, instead of the static
1024 that was wasting >90% of H100's 80GB VRAM bandwidth.
Previously AutoBatchSizer computed the optimal batch (e.g. 2085808) but
the profile's batch_size=1024 always won. Now with batch_size=0 the
sizer's result flows through, enabling full SM occupancy on H100.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Created config/gpu/{default,rtx3050,h100,a100}.toml with all GPU-specific
parameters: batch_size, num_atoms, buffer_size, hidden_dim_base,
replay_buffer_vram_fraction, gpu_n_episodes, gpu_timesteps_per_episode,
cuda_stack_bytes.
GpuProfile::load() auto-detects GPU by device name, falls back to
embedded defaults (include_str!). Override via FOXHUNT_GPU_PROFILE env.
Removed dead code:
- detect_vram_mb(), vram_scaled_hidden_dims(), vram_scaled_base_dim(),
resolve_hidden_dim_base() + 18 tests for these functions
All callers updated: train_baseline_rl, DQNTrainer constructor,
PPO trainer, smoke tests, pipeline tests.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Replace scattered VRAM-based if/else chains with a declarative TOML profile
system. GPU profiles (rtx3050, a100, h100, default) are selected by device
name and embedded at compile time via include_str! for zero-filesystem
fallback in CI/containers, with filesystem and env var overrides.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
