minor bug + better defaults in test()

cli.py

@@ -223,7 +223,7 @@ def train(*, dataset='mnist', folder='mnist', resume=False, model='convae', walk
             nb_updates += 1
 
 
-def test(*, dataset='mnist', folder='out', model_path=None, nb_iter=100, nb_generate=100, tsne=False):
+def test(*, dataset='mnist', folder='out', model_path=None, nb_iter=25, nb_generate=100, nb_active=160, tsne=False):
     if not os.path.exists(folder):
         os.makedirs(folder, exist_ok=True)
     dataset = load_dataset(dataset, split='train')
@@ -235,6 +235,7 @@ def test(*, dataset='mnist', folder='out', model_path=None, nb_iter=100, nb_gene
         model_path = os.path.join(folder, "model.th")
     ae = torch.load(model_path, map_location="cpu")
     ae = ae.to(device)
+    ae.nb_active = nb_active # for fc_sparse.th only
     def enc(X):
         batch_size = 64
         h_list = []
@@ -267,12 +268,12 @@ def test(*, dataset='mnist', folder='out', model_path=None, nb_iter=100, nb_gene
     np.savez('{}/generated.npz'.format(folder), X=g.numpy())
     g_subset = g[:, 0:100]
     gr = grid_of_images_default(g_subset.reshape((g_subset.shape[0]*g_subset.shape[1], h, w, 1)).numpy(), shape=(g_subset.shape[0], g_subset.shape[1])) 
-    imsave('{}/gen_full_iters.png'.format(folder), gr)
+    imsave('{}/gen_full_iters.png'.format(folder), (gr*255).astype("uint8") )
 
     g = g[-1] # last iter
     print(g.shape)
     gr = grid_of_images_default(g.numpy())
-    imsave('{}/gen_full.png'.format(folder), gr)
+    imsave('{}/gen_full.png'.format(folder), (gr*255).astype("uint8") )
 
     if tsne:
         from sklearn.manifold import TSNE
@@ -300,13 +301,13 @@ def test(*, dataset='mnist', folder='out', model_path=None, nb_iter=100, nb_gene
         print('fit tsne...')
         ah = sne.fit_transform(ah)
         print('grid embedding...')
-        
+        assert nb_generate >= 450 
         asmall = np.concatenate((a[0:450], a[nb:nb + 450]), axis=0)
         ahsmall = np.concatenate((ah[0:450], ah[nb:nb + 450]), axis=0)
         rows = grid_embedding(ahsmall)
         asmall = asmall[rows]
         gr = grid_of_images_default(asmall)
-        imsave('{}/sne_grid.png'.format(folder), gr)
+        imsave('{}/sne_grid.png'.format(folder), (gr*255).astype("uint8") )
 
         fig = plt.figure(figsize=(10, 10))
         plot_dataset(ah, labels)

viz.py

@@ -116,8 +116,8 @@ def grid_of_images(M, border=0, bordercolor=[0.0, 0.0, 0.0], shape=None, normali
     height, width, color = M[0].shape
     assert color == 3, 'Nb of color channels are {}'.format(color)
     if shape is None:
-        n0 = np.int(np.ceil(np.sqrt(numimages)))
-        n1 = np.int(np.ceil(np.sqrt(numimages)))
+        n0 = np.int32(np.ceil(np.sqrt(numimages)))
+        n1 = np.int32(np.ceil(np.sqrt(numimages)))
     else:
         n0 = shape[0]
         n1 = shape[1]