from chainerx.activation import relu # NOQA from chainerx.activation import sigmoid # NOQA from chainerx.manipulation.shape import ravel # NOQA from chainerx.math.misc import clip # NOQA from chainerx.math.misc import square # NOQA from chainerx import random # NOQA _global_context = _core.Context() _core.set_global_default_context(_global_context) # Implements ndarray methods in Python from chainerx import _ndarray _ndarray.populate() # Temporary workaround implementations that fall back to NumPy/CuPy's # respective functions. from chainerx import _fallback_workarounds _fallback_workarounds.populate() # Dynamically inject docstrings from chainerx import _docs _docs.set_docs() from chainerx import _cuda # Share memory pool with CuPy. if bool(int(os.getenv('CHAINERX_CUDA_CUPY_SHARE_ALLOCATOR', '0'))): _cuda.cupy_share_allocator() else:
from chainerx.creation.from_data import fromiter # NOQA from chainerx.creation.from_data import fromstring # NOQA from chainerx.creation.from_data import loadtxt # NOQA from chainerx.manipulation.shape import ravel # NOQA from chainerx.math.misc import clip # NOQA from chainerx import random # NOQA _global_context = _core.Context() _core.set_global_default_context(_global_context) # Implements ndarray methods in Python from chainerx import _ndarray _ndarray.populate() # Temporary workaround implementations that fall back to NumPy/CuPy's # respective functions. from chainerx import _fallback_workarounds _fallback_workarounds.populate() # Dynamically inject docstrings from chainerx import _docs _docs.set_docs() from chainerx import _cuda # Share memory pool with CuPy. if bool(int(os.getenv('CHAINERX_CUDA_CUPY_SHARE_ALLOCATOR', '0'))): _cuda.cupy_share_allocator() else: