def to_chainerx(array):
"""Converts an array or arrays to ChainerX.
Destination ChainerX devices are chosen according to the types of input
arrays.
"""
return _backend._convert_arrays(array, _array_to_chainerx)
def to_gpu(array, device=None, stream=None):
"""Copies the given CPU array to the specified device.
Args:
array (*array*, None, list or tuple):
Array or arrays to be sent to GPU.
device: CUDA device specifier. If ``None`` or :data:`cuda.DummyDevice`,
the arrays will be copied to the current CUDA device.
stream (~cupy.cuda.Stream): *(deprecated since v3.0.0)*
CUDA stream. If not ``None``, the copy runs asynchronously.
Returns:
cupy.ndarray, list or tuple: Array or arrays on GPU.
If some of the arrays are already on GPU, then this function just
returns those arrays without performing any copy.
If input arrays include `None`, it is returned as `None` as is.
"""
if stream is not None:
warnings.warn(
'The stream option is deprecated in chainer.backends.cuda.to_gpu. '
'Please remove it.', DeprecationWarning)
check_cuda_available()
if device is DummyDevice:
device = cuda.Device()
else:
device = _get_device_or_current(device)
return _backend._convert_arrays(
array, lambda arr: _array_to_gpu(arr, device, stream))
def to_gpu(array, device=None, stream=None):
"""Copies the given CPU array to the specified device.
Args:
array (*array*, None, list or tuple):
Array or arrays to be sent to GPU.
device: CUDA device specifier. If ``None`` or :data:`cuda.DummyDevice`,
the arrays will be copied to the current CUDA device.
stream (~cupy.cuda.Stream): *(deprecated since v3.0.0)*
CUDA stream. If not ``None``, the copy runs asynchronously.
Returns:
cupy.ndarray, list or tuple: Array or arrays on GPU.
If some of the arrays are already on GPU, then this function just
returns those arrays without performing any copy.
If input arrays include `None`, it is returned as `None` as is.
"""
if stream is not None:
warnings.warn(
'The stream option is deprecated in chainer.backends.cuda.to_gpu. '
'Please remove it.', DeprecationWarning)
check_cuda_available()
if device is DummyDevice:
device = cuda.Device()
else:
device = _get_device_or_current(device)
return _backend._convert_arrays(
array, lambda arr: _array_to_gpu(arr, device, stream))
def to_chx(array):
"""Converts an array or arrays to ChainerX.
Destination ChainerX devices are chosen according to the types of input
arrays.
"""
return _backend._convert_arrays(array, _array_to_chainerx)
def to_cpu(array, stream=None):
"""Copies the given GPU array to host CPU.
Args:
array (*array*, None, list or tuple):
Array or arrays to be sent to CPU.
stream (cupy.cuda.Stream): CUDA stream.
Returns:
numpy.ndarray, list or tuple: Array on CPU.
If some of the arrays are already on CPU, then this function just
returns those arrays without performing any copy.
If input arrays include `None`, it is returned as `None` as is.
"""
return _backend._convert_arrays(
array, lambda arr: _array_to_cpu(arr, stream))
def to_cpu(array, stream=None):
"""Copies the given GPU array to host CPU.
Args:
array (*array*, None, list or tuple):
Array or arrays to be sent to CPU.
stream (cupy.cuda.Stream): CUDA stream.
Returns:
numpy.ndarray, list or tuple: Array on CPU.
If some of the arrays are already on CPU, then this function just
returns those arrays without performing any copy.
If input arrays include `None`, it is returned as `None` as is.
"""
return _backend._convert_arrays(
array, lambda arr: _array_to_cpu(arr, stream))
def from_chainerx(array):
"""Converts an array or arrays from ChainerX to NumPy or CuPy ones.
Destination array types are chosen such that no copies occur.
"""
return _backend._convert_arrays(array, _array_from_chainerx)
def from_chx(array):
"""Converts an array or arrays from ChainerX to NumPy or CuPy ones.
Destination array types are chosen such that no copies occur.
"""
return _backend._convert_arrays(array, _array_from_chainerx)
def _to_cpu(array):
"""Converts an array or arrays to NumPy."""
return _backend._convert_arrays(array, _array_to_cpu)
def _to_cpu(array):
"""Converts an array or arrays to NumPy."""
return _backend._convert_arrays(array, _array_to_cpu)
