2.5 KiB
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
Design corner stone
It is the job of Python (Numpy or PyTorch) to provide the tensors from which we read and in which we write. In the cpp domain, we will use this matrices as the interface to Python. We are not allowed to change the sizes of these tensors. We are only allowed to change the content of the tensors.
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