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The fast and furious way
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Let us assume that you know what you are doing. And also let us assume that you notices how extremely slow the "correct" way of communication between Python and C++ is. Well the following section is for you...
Questions to David Rotermund
On the Python side
# If it is a torch tensor then make a "view" to its numpy core
np_input: np.ndarray = input.contiguous().detach().numpy()
# We need to make sure that the numpy ndarray is C_CONTIGUOUS.
# If not then use numpy.ascontiguousarray() to make it so
assert np_input.flags["C_CONTIGUOUS"] is True
# Input is a 4d ndarray. And I will make sure that this is really the case
assert np_input.ndim == 4
# Now I extract the pointer to the data memory of the ndarray
np_input_pointer, _ = np_input.__array_interface__["data"]
# Also I need the shape information for the C++ program.
np_input_dim_0: int = np_input.shape[0]
np_input_dim_1: int = np_input.shape[1]
np_input_dim_2: int = np_input.shape[2]
np_input_dim_3: int = np_input.shape[3]
On the C++ side
Your C++ method needs to accept these arguments
int64_t np_input_pointer_addr,
int64_t np_input_dim_0,
int64_t np_input_dim_1,
int64_t np_input_dim_2,
int64_t np_input_dim_3,
Inside your C++ method you convert the address into a pointer. BE WARNED: Make absolutely sure that the dtype of the np.ndarray is correctly reflected in the pointer type
dtype=np.float32 --> float dtype=np.float64 --> double dtype=np.uint64 --> uint64
If you fuck this up then this will end in tears!
float *np_input_pointer = (float *)np_input_pointer_addr;
// Input
assert((np_input_pointer != nullptr));
assert((np_input_dim_0 > 0));
assert((np_input_dim_1 > 0));
assert((np_input_dim_2 > 0));
assert((np_input_dim_3 > 0));
Don't forget that C Contiguous is just a complicated way of saying Row-major order memory layout Row- and column-major order.
M[a,b,c,d] = M[\eta_a \cdot a + \eta_b \cdot b + \eta_c \cdot c + d]with
\eta_c = n_d\eta_b = \eta_c \cdot n_c\eta_a = \eta_b \cdot n_b