Fit callbacks

fastFM/als.py

@@ -69,7 +69,7 @@ def __init__(self, n_iter=100, init_stdev=0.1, rank=8, random_state=123,
         self.solver = "cd"
         self.iter_count = 0
 
-    def fit(self, X, y, n_more_iter=0):
+    def fit(self, X, y, n_more_iter=0, callback = None):
         """ Fit model with specified loss.
 
         Parameters
@@ -97,7 +97,7 @@ def fit(self, X, y, n_more_iter=0):
 
         settings_dict = _settings_factory(self)
         ffm2.ffm_fit(self.w0_, self.w_, self.V_, X, y, self.rank,
-                     settings_dict)
+                     settings_dict, callback)
 
         self.iter_count += self.n_iter
         return self

fastFM/cpp_ffm.pxd

@@ -30,4 +30,10 @@ cdef extern from "../fastFM-core2/fastFM/fastfm.h" namespace "fastfm":
 
     cdef void fit(Settings* s, Model* m, Data* d)
 
+    # NEW CALLBACK DEVELOPMENTS #########################################
+    ctypedef void (*fit_callback_t)(int iter, void* python_func)
+    cdef void fit_with_callback(Settings* s, Model* m, Data*,
+                                fit_callback_t callback, void* python_callback_func)
+
+    ######################################################################
     cdef void predict(Model* m, Data* d)

fastFM/ffm2.pyx

@@ -77,11 +77,25 @@ def ffm_predict(np.ndarray[np.float64_t, ndim = 1] w_0,
 
     return y
 
+# The main piece of the glue between Python, Cython and C++
+# In essence it wraps the python function so it can be used in C++ space.
+# Convert the python function from a pointer back into a python object and invoke
+# with other parameters. (For now just one, `current_iter`)
+cdef void fit_callback_wrapper(int current_iter, void* python_function):
+    f = (<object>python_function)
+
+    if f is not None:
+        f(current_iter)
+
+from typing import Callable, NoReturn
 
 def ffm_fit(np.ndarray[np.float64_t, ndim = 1] w_0,
         np.ndarray[np.float64_t, ndim = 1] w,
         np.ndarray[np.float64_t, ndim = 2] V,
-                X, np.ndarray[np.float64_t, ndim = 1] y, int rank, dict settings):
+                X, np.ndarray[np.float64_t, ndim = 1] y,
+                int rank, dict settings,
+                # callback is a python object
+                callback : Callable[int, NoReturn]):
     assert isinstance(settings, dict)
     assert X.shape[0] == len(y) # test shapes
 
@@ -96,6 +110,10 @@ def ffm_fit(np.ndarray[np.float64_t, ndim = 1] w_0,
 
     cpp_ffm.fit(s, m, d)
 
+    # Proof of concept `dummy fit` with a callback.
+    # we must cast the python object into void* so it can be passed to C++
+    cpp_ffm.fit_with_callback(s, m, d, fit_callback_wrapper, (<void*> callback))
+
     del d
     del m
     del s