split_v was removed already (tf#6405)

examples/SpatialTransformer/mnist-addition.py

@@ -65,7 +65,7 @@ class Model(ModelDesc):
         transform2 = tf.concat_v2([padded2[:, :, :, 0], padded2[:, :, :, 1]], 1)
         stacked = tf.concat_v2([img_orig, transform1, transform2], 2, 'viz')
         tf.summary.image('visualize',
-                         tf.expand_dims(stacked, -1), max_images=30)
+                         tf.expand_dims(stacked, -1), max_outputs=30)
 
         sampled = tf.concat_v2([sampled1, sampled2], 3, 'sampled_concat')
         logits = (LinearWrap(sampled)

tensorpack/models/conv2d.py

@@ -54,8 +54,8 @@ def Conv2D(x, out_channel, kernel_shape,
         conv = tf.nn.conv2d(x, W, stride, padding)
     else:
         # TODO rename to split later
-        inputs = tf.split_v(x, split, 3)
-        kernels = tf.split_v(W, split, 3)
+        inputs = tf.split(x, split, 3)
+        kernels = tf.split(W, split, 3)
         outputs = [tf.nn.conv2d(i, k, stride, padding)
                    for i, k in zip(inputs, kernels)]
         conv = tf.concat_v2(outputs, 3)

tensorpack/models/image_sample.py

@@ -74,14 +74,14 @@ def ImageSample(inputs, borderMode='repeat'):
     diff = mapping - lcoor
     neg_diff = 1.0 - diff  # bxh2xw2x2
 
-    lcoory, lcoorx = tf.split_v(lcoor, 2, 3)
-    ucoory, ucoorx = tf.split_v(ucoor, 2, 3)
+    lcoory, lcoorx = tf.split(lcoor, 2, 3)
+    ucoory, ucoorx = tf.split(ucoor, 2, 3)
 
     lyux = tf.concat_v2([lcoory, ucoorx], 3)
     uylx = tf.concat_v2([ucoory, lcoorx], 3)
 
-    diffy, diffx = tf.split_v(diff, 2, 3)
-    neg_diffy, neg_diffx = tf.split_v(neg_diff, 2, 3)
+    diffy, diffx = tf.split(diff, 2, 3)
+    neg_diffy, neg_diffx = tf.split(neg_diff, 2, 3)
 
     # prod = tf.reduce_prod(diff, 3, keep_dims=True)
     # diff = tf.Print(diff, [tf.is_finite(tf.reduce_sum(diff)), tf.shape(prod),