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: