paddle-style-default-device

name	paddle-style-default-device
description	Implement PaddlePaddle-style lazy GPU default device in C++ core, all languages inherit
source	auto-skill
extracted_at	2026-06-05T14:22:08.096Z

PaddlePaddle-Style Default Device

Problem: PaddlePaddle defaults to GPU when available, CPU otherwise. Insight7 should match this behavior.

Implementation (in src/core/place.cpp):

namespace {
thread_local Place g_default_device = CPUPlace();
thread_local bool g_device_explicitly_set = false;
}

Place get_device() {
  // Lazy: first call checks if GPU is available
  if (!g_device_explicitly_set && g_default_device.kind() == DeviceKind::CPU) {
    if (is_device_available(DeviceKind::GPU)) {
      g_default_device = GPUPlace(0);
    }
  }
  return g_default_device;
}

void set_device(const Place &place) {
  g_default_device = place;
  g_device_explicitly_set = true;  // User's choice is honored
}

Key design:

• g_device_explicitly_set flag ensures set_device(CPUPlace()) is honored
• is_device_available(DeviceKind::GPU) handles ALL backends (cuda/npu/rocm/...)
• No hardcoded backend names

Binding requirements:

• All languages MUST expose set_device and get_device
• Python creation.py MUST call get_device() at call time, NOT at module load time:

  # ❌ WRONG — evaluated once at import
  m.def("zeros", &zeros, py::arg("place") = get_device());
  # ✅ CORRECT — evaluated at each call
  def zeros(shape, dtype, place=None):
      if place is None:
          return _native_zeros(shape, dtype, get_device())
  

• CPU test suites need set_device(CPUPlace()) in setup (conftest.py for Python, setup block for Lua/busted)

Why: PaddlePaddle does this in _current_expected_place_() — checks is_compiled_with_cuda() + get_cuda_device_count(). Insight7's HAL abstraction makes it simpler: one is_device_available() check.