Replace np.prod with np.multiply.reduce for improved efficiency in input shape calculation #2
Description
Line 157 in a48dc32
In the line num_inputs = np.prod(input_shape[2:]), it is recommended to use np.multiply.reduce(input_shape[2:]) instead. Although both expressions return the same result, np.prod() is a wrapper function around np.multiply.reduce() and includes additional overhead such as input validation, type coercion, axis handling, and logic for parameters like dtype, keepdims, and initial.
When such functionality is not required, directly using np.multiply.reduce() results in a more efficient and lightweight operation, reducing unnecessary internal function calls and improving runtime performance. Since this usage only involves computing a simple product of shape dimensions, there is no need for the extra abstraction layer provided by np.prod().
Replacing it with:
num_inputs = np.multiply.reduce(input_shape[2:])
would offer the same functionality with a more efficient execution path.