stop refactoring and get some stuff huggin' done

bridge.pyx

@@ -11,8 +11,6 @@ import flask
 
 
 tokenizers = {}
-X_test = None
-y_test = None
 
 
 cdef extern from "numpy/arrayobject.h":
@@ -49,6 +47,30 @@ cdef public void serve():
     nn.app.run(port=8448)
 
 
+cdef public size_t getwin():
+    return nn.WIN
+
+
+cdef public size_t getemb():
+    return nn.EMB
+
+
+cdef public size_t getbs():
+    return nn.CFG['bs']
+
+
+cdef public size_t getbpe():
+    return nn.CFG['bpe']
+
+
+cdef public float gettarget():
+    return nn.CFG['target']
+
+
+cdef public float getflpc():
+    return nn.CFG['flpc']
+
+
 cdef public int get_tokens(WordList* wl, const char *filename):
     fnu = filename.decode('utf-8')
     if fnu not in tokenizers:
@@ -82,10 +104,8 @@ cdef public void _dbg_print(object o):
     eprint(o)
 
 
-cdef public void _dbg_print_cbow_batch(
-    object net, float* batch, size_t bs
-):
-    X_np, y_np = cbow_batch(net, batch, bs)
+cdef public void _dbg_print_cbow_batch(float* batch, size_t bs):
+    X_np, y_np = cbow_batch(batch, bs)
     eprint(X_np)
     eprint(y_np)
 
@@ -95,9 +115,9 @@ cdef public void randidx(int* idx, size_t l, size_t how_much):
     memcpy(idx, PyArray_DATA(i_np), how_much * sizeof(int))
 
 
-cdef public object create_network(int win, int embed):
+cdef public object create_network():
     try:
-        net = nn.create_cbow_network(win, embed)
+        net = nn.create_cbow_network()
         eprint(net)
         return net
     except Exception as e:
@@ -111,7 +131,7 @@ cdef public void set_net_weights(object net, WeightList* wl):
 cdef public void step_net(
     object net, float* batch, size_t bs
 ):
-    X_train, y_train = cbow_batch(net, batch, bs)
+    X_train, y_train = cbow_batch(batch, bs)
     net.train_on_batch(X_train, y_train)
 
 
@@ -120,10 +140,7 @@ cdef public size_t out_size(object net):
 
 
 cdef public float eval_net(object net):
-    try:
-        return net.evaluate(X_test, y_test, verbose=False)
-    except Exception as e:
-        eprint(e)
+    return nn.eval_network(net)
 
 
 cdef public void init_weightlist_like(WeightList* wl, object net):
@@ -162,14 +179,8 @@ cdef public void combo_weights(
             wf += alpha * ww
 
 
-cdef public void create_test_dataset(size_t win):
-    _create_test_dataset(win)
-
-
-cdef tuple cbow_batch(
-    object net, float* batch, size_t bs
-):
-    win = net.input_shape[1] // 2
+cdef tuple cbow_batch(float* batch, size_t bs):
+    win = nn.WIN
     batch_np = np.asarray(<float[:bs,:2*win+1]>batch)
     X_np = batch_np[:, [*range(win), *range(win+1, win+win+1)]]
     y_np = nn.onehot(batch_np[:, win], nc=len(nn.vocab))
@@ -177,6 +188,7 @@ cdef tuple cbow_batch(
 
 
 cdef list wrap_weight_list(WeightList* wl):
+    """Thinly wraps a WeightList struct into a NumPy array."""
     weights = []
     for i in range(wl.n_weights):
         w_shape = <long[:wl.weights[i].dims]>wl.weights[i].shape
@@ -220,9 +232,3 @@ def ensure_contiguous(a):
 
 def eprint(*args, **kwargs):
     return print(*args, flush=True, **kwargs)
-
-
-def _create_test_dataset(win):
-    global X_test, y_test
-    if X_test is None or y_test is None:
-        X_test, y_test = nn.create_test_dataset(win)