Set runtime_include_dir in Paddle.__init__.py (#37886)

Paddle don't have to set runtime_include_dir during run CINN.

paddle/fluid/pybind/pybind.cc

@@ -207,6 +207,14 @@ bool IsCompiledWithMKLDNN() {
 #endif
 }
 
+bool IsCompiledWithCINN() {
+#ifndef PADDLE_WITH_CINN
+  return false;
+#else
+  return true;
+#endif
+}
+
 bool IsCompiledWithHETERPS() {
 #ifndef PADDLE_WITH_HETERPS
   return false;
@@ -2191,6 +2199,7 @@ All parameter, weight, gradient are variables in Paddle.
   m.def("is_compiled_with_npu", IsCompiledWithNPU);
   m.def("is_compiled_with_xpu", IsCompiledWithXPU);
   m.def("is_compiled_with_mkldnn", IsCompiledWithMKLDNN);
+  m.def("is_compiled_with_cinn", IsCompiledWithCINN);
   m.def("_is_compiled_with_heterps", IsCompiledWithHETERPS);
   m.def("supports_bfloat16", SupportsBfloat16);
   m.def("supports_bfloat16_fast_performance", SupportsBfloat16FastPerformance);

python/paddle/__init__.py

@@ -282,6 +282,7 @@ from .tensor.stat import median  # noqa: F401
 from .device import get_cudnn_version  # noqa: F401
 from .device import set_device  # noqa: F401
 from .device import get_device  # noqa: F401
+from .fluid.framework import is_compiled_with_cinn  # noqa: F401
 from .fluid.framework import is_compiled_with_cuda  # noqa: F401
 from .fluid.framework import is_compiled_with_rocm  # noqa: F401
 from .fluid.framework import disable_signal_handler  # noqa: F401
@@ -310,6 +311,16 @@ import paddle.text  # noqa: F401
 import paddle.vision  # noqa: F401
 
 from .tensor.random import check_shape  # noqa: F401
+
+# CINN has to set a flag to include a lib
+if is_compiled_with_cinn():
+    import os
+    package_dir = os.path.dirname(os.path.abspath(__file__))
+    runtime_include_dir = os.path.join(package_dir, "libs")
+    cuh_file = os.path.join(runtime_include_dir, "cinn_cuda_runtime_source.cuh")
+    if os.path.exists(cuh_file):
+        os.environ['runtime_include_dir'] = runtime_include_dir
+
 disable_static()
 
 __all__ = [  # noqa

python/paddle/device/__init__.py

@@ -18,6 +18,7 @@ import os
 from paddle.fluid import core
 from paddle.fluid import framework
 from paddle.fluid.dygraph.parallel import ParallelEnv
+from paddle.fluid.framework import is_compiled_with_cinn  # noqa: F401
 from paddle.fluid.framework import is_compiled_with_cuda  # noqa: F401
 from paddle.fluid.framework import is_compiled_with_rocm  # noqa: F401
 from . import cuda
@@ -28,6 +29,7 @@ __all__ = [  # noqa
     'get_device',
     'XPUPlace',
     'is_compiled_with_xpu',
+    'is_compiled_with_cinn',
     'is_compiled_with_cuda',
     'is_compiled_with_rocm',
     'is_compiled_with_npu'

python/paddle/fluid/framework.py

@@ -54,6 +54,7 @@ __all__ = [
     'xpu_places',
     'cuda_pinned_places',
     'in_dygraph_mode',
+    'is_compiled_with_cinn',
     'is_compiled_with_cuda',
     'is_compiled_with_rocm',
     'is_compiled_with_xpu',
@@ -477,6 +478,21 @@ def disable_signal_handler():
     core.disable_signal_handler()
 
 
+def is_compiled_with_cinn():
+    """
+    Whether this whl package can be used to run the model on CINN.
+
+    Returns (bool): `True` if CINN is currently available, otherwise `False`.
+
+    Examples:
+        .. code-block:: python
+
+            import paddle
+            support_cinn = paddle.device.is_compiled_with_cinn()
+    """
+    return core.is_compiled_with_cinn()
+
+
 def is_compiled_with_cuda():
     """
     Whether this whl package can be used to run the model on GPU.

python/setup.py.in

@@ -470,7 +470,9 @@ if '${WITH_LITE}' == 'ON':
 
 if '${WITH_CINN}' == 'ON':
     shutil.copy('${CINN_LIB_LOCATION}/${CINN_LIB_NAME}', libs_path)
+    shutil.copy('${CINN_INCLUDE_DIR}/cinn/runtime/cuda/cinn_cuda_runtime_source.cuh', libs_path)
     package_data['paddle.libs']+=['libcinnapi.so']
+    package_data['paddle.libs']+=['cinn_cuda_runtime_source.cuh']
 
 if '${WITH_PSLIB}' == 'ON':
     shutil.copy('${PSLIB_LIB}', libs_path)