small refactoring and kicked the visualizer again

bridge.pyx

@@ -47,6 +47,12 @@ cdef public void serve():
     srv.serve()
 
 
+cdef public void server_update(float *emb):
+    embeddings = np.asarray(<float[:getvocsize(),:getemb()]>emb)
+    low_dim = nn.calc_TSNE(embeddings)
+    srv.emb_map = dict(zip(nn.inv_vocab, low_dim))
+
+
 cdef public size_t getwin():
     return nn.WIN
 
@@ -67,6 +73,10 @@ cdef public float gettarget():
     return nn.CFG['target']
 
 
+cdef public size_t getvocsize():
+    return len(nn.vocab)
+
+
 cdef public int get_tokens(WordList* wl, const char *filename):
     fnu = filename.decode('utf-8')
     if fnu not in tokenizers:
@@ -101,8 +111,8 @@ cdef public void _dbg_print(object o):
     eprint(o)
 
 
-cdef public void _dbg_print_cbow_batch(float* batch, size_t bs):
-    X_np, y_np = cbow_batch(batch, bs)
+cdef public void _dbg_print_cbow_batch(float* batch):
+    X_np, y_np = cbow_batch(batch)
     eprint(X_np)
     eprint(y_np)
 
@@ -124,10 +134,8 @@ cdef public void set_net_weights(object net, WeightList* wl):
     net.set_weights(wrap_weight_list(wl))
 
 
-cdef public void step_net(
-    object net, float* batch, size_t bs
-):
-    X_train, y_train = cbow_batch(batch, bs)
+cdef public void step_net(object net, float* batch):
+    X_train, y_train = cbow_batch(batch)
     net.train_on_batch(X_train, y_train)
 
 
@@ -183,8 +191,9 @@ cdef public void combo_weights(
             wf += alpha * ww
 
 
-cdef tuple cbow_batch(float* batch, size_t bs):
-    win = nn.WIN
+cdef tuple cbow_batch(float* batch):
+    win = getwin()
+    bs = getbs()
     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))