Files

jgrusewski 12fdd18223 refactor: remove entire CPU training path — 5,307 lines of dead code

Deleted:
- DQN::compute_loss_internal (280 lines) — old Candle forward+loss
- DQN::train_step (55 lines) — old Candle training step
- DQN::compute_gradients (47 lines) — old gradient accumulation
- ComputeLossResult struct — only used by deleted functions
- RegimeConditionalDQN::train_step (65 lines) — old dispatch
- RegimeConditionalDQN::train_step_gpu_regime (100 lines) — old GPU path
- RegimeConditionalDQN::compute_gradients_gpu (130 lines) — old regime gradients
- RegimeConditionalDQN::compute_gradients (92 lines) — old dispatch
- DQNAgentType::train_step dispatch — dead
- DQNAgentType::compute_gradients dispatch — dead
- GpuDqnTrainer::upload_batch (71 lines) — old CPU→GPU upload
- train_step.rs (500 lines) — entire module including ensure_fused_ctx
- dqn_benchmark.rs — used old train_step
- examples.rs — used old train_step
- validation/adapters.rs (289 lines) — used old train_step
- dqn/trainable_adapter.rs — used old train_step
- gpu_smoketest.rs — tested old train_step
- Gradient accumulation path in training_loop.rs (144 lines)
- IQN d_h_s2().clone() → raw pointer (zero alloc)
- Causal intervention format! string alloc removed
- Dead HER relabel functions (320 lines)

Kept:
- ensure_fused_ctx logic inlined into training_loop.rs
- set_noise_sigma_scale re-added to RegimeConditionalDQN

Fixed:
- GpuReplayBuffer max_batch_size wired from batch_size parameter
  (was hardcoded 1024, blocking batch_size=8192)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-02 09:06:23 +02:00

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name, description

name	description
sparc-post-deployment-monitoring-mode	📈 Deployment Monitor - You observe the system post-launch, collecting performance, logs, and user feedback. You flag reg...

📈 Deployment Monitor

Role Definition

You observe the system post-launch, collecting performance, logs, and user feedback. You flag regressions or unexpected behaviors.

Custom Instructions

Configure metrics, logs, uptime checks, and alerts. Recommend improvements if thresholds are violated. Use new_task to escalate refactors or hotfixes. Summarize monitoring status and findings with attempt_completion.

Available Tools

read: File reading and viewing
edit: File modification and creation
browser: Web browsing capabilities
mcp: Model Context Protocol tools
command: Command execution

Usage

Option 1: Using MCP Tools (Preferred in Claude Code)

mcp__claude-flow__sparc_mode {
  mode: "post-deployment-monitoring-mode",
  task_description: "monitor production metrics",
  options: {
    namespace: "post-deployment-monitoring-mode",
    non_interactive: false
  }
}

Option 2: Using NPX CLI (Fallback when MCP not available)

# Use when running from terminal or MCP tools unavailable
npx claude-flow sparc run post-deployment-monitoring-mode "monitor production metrics"

# For alpha features
npx claude-flow@alpha sparc run post-deployment-monitoring-mode "monitor production metrics"

# With namespace
npx claude-flow sparc run post-deployment-monitoring-mode "your task" --namespace post-deployment-monitoring-mode

# Non-interactive mode
npx claude-flow sparc run post-deployment-monitoring-mode "your task" --non-interactive

Option 3: Local Installation

# If claude-flow is installed locally
./claude-flow sparc run post-deployment-monitoring-mode "monitor production metrics"

Memory Integration

Using MCP Tools (Preferred)

// Store mode-specific context
mcp__claude-flow__memory_usage {
  action: "store",
  key: "post-deployment-monitoring-mode_context",
  value: "important decisions",
  namespace: "post-deployment-monitoring-mode"
}

// Query previous work
mcp__claude-flow__memory_search {
  pattern: "post-deployment-monitoring-mode",
  namespace: "post-deployment-monitoring-mode",
  limit: 5
}

Using NPX CLI (Fallback)

# Store mode-specific context
npx claude-flow memory store "post-deployment-monitoring-mode_context" "important decisions" --namespace post-deployment-monitoring-mode

# Query previous work
npx claude-flow memory query "post-deployment-monitoring-mode" --limit 5

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