def elementwise_binary(alpha,
A,
desc_A,
mode_A,
gamma,
C,
desc_C,
mode_C,
out=None,
op_AC=cutensor.OP_ADD,
compute_dtype=None):
"""Element-wise tensor operation for two input tensors
This function performs a element-wise tensor operation of the form:
D_{Pi^C(i_0,i_1,...,i_n)} =
op_AC(alpha * uop_A(A_{Pi^A(i_0,i_1,...,i_n)}),
gamma * uop_C(C_{Pi^C(i_0,i_1,...,i_n)}))
See elementwise_trinary() for details.
Examples:
See examples/cutensor/elementwise_binary.py
"""
if A.dtype != C.dtype:
raise ValueError('dtype mismatch: {} != {}'.format(A.dtype, C.dtype))
if not (A.flags.c_contiguous and C.flags.c_contiguous):
raise ValueError('The inputs should be contiguous arrays.')
if out is None:
out = cupy.ndarray(C.shape, dtype=C.dtype)
elif C.dtype != out.dtype:
raise ValueError('dtype mismatch: {} != {}'.format(C.dtype, out.dtype))
elif C.shape != out.shape:
raise ValueError('shape mismatch: {} != {}'.format(C.shape, out.shape))
elif not out.flags.c_contiguous:
raise ValueError('`out` should be a contiguous array.')
if A.ndim != len(mode_A):
raise ValueError('ndim mismatch: {} != {}'.format(A.ndim, len(mode_A)))
if C.ndim != len(mode_C):
raise ValueError('ndim mismatch: {} != {}'.format(C.ndim, len(mode_C)))
mode_A = _convert_mode(mode_A)
mode_C = _convert_mode(mode_C)
if compute_dtype is None:
compute_dtype = A.dtype
alpha = numpy.array(alpha, compute_dtype)
gamma = numpy.array(gamma, compute_dtype)
handle = get_handle()
cuda_dtype = get_cuda_dtype(compute_dtype)
cutensor.elementwiseBinary(handle, alpha.ctypes.data, A.data.ptr, desc_A,
mode_A.ctypes.data, gamma.ctypes.data,
C.data.ptr, desc_C, mode_C.ctypes.data,
out.data.ptr, desc_C, mode_C.ctypes.data, op_AC,
cuda_dtype)
return out
def elementwise_binary(alpha,
A,
desc_A,
mode_A,
gamma,
C,
desc_C,
mode_C,
out=None,
op_AC=cutensor.OP_ADD,
compute_dtype=None):
"""Element-wise tensor operation for two input tensors
This function performs a element-wise tensor operation of the form:
D_{Pi^C(i_0,i_1,...,i_n)} =
op_AC(alpha * uop_A(A_{Pi^A(i_0,i_1,...,i_n)}),
gamma * uop_C(C_{Pi^C(i_0,i_1,...,i_n)}))
See elementwise_trinary() for details.
Examples:
See examples/cutensor/elementwise_binary.py
"""
assert A.dtype == C.dtype
assert A.ndim == len(mode_A)
assert C.ndim == len(mode_C)
mode_A = _convert_mode(mode_A)
mode_C = _convert_mode(mode_C)
if out is None:
out = cupy.ndarray(C.shape, dtype=C.dtype)
else:
assert C.dtype == out.dtype
assert C.ndim == out.ndim
for i in range(C.ndim):
assert C.shape[i] == out.shape[i]
if compute_dtype is None:
compute_dtype = A.dtype
alpha = numpy.array(alpha, compute_dtype)
gamma = numpy.array(gamma, compute_dtype)
handle = get_handle()
cuda_dtype = get_cuda_dtype(compute_dtype)
cutensor.elementwiseBinary(handle, alpha.ctypes.data, A.data.ptr, desc_A,
mode_A.ctypes.data, gamma.ctypes.data,
C.data.ptr, desc_C, mode_C.ctypes.data,
out.data.ptr, desc_C, mode_C.ctypes.data, op_AC,
cuda_dtype)
return out