Shape inference for tile and gather (keras-team#5635)

* Added tile shape inference

* Added shape inference for gather

* Added test for gather

* Fixed test_gather

* PEP8 fix

* Fixed gather test

keras/backend/theano_backend.py

@@ -388,8 +388,11 @@ def gather(reference, indices):
 
     Return: a tensor of same type as reference.
     """
-    # TODO: `keras_shape` inference.
-    return reference[indices]
+    y = reference[indices]
+    if hasattr(reference, '_keras_shape') and hasattr(indices, '_keras_shape'):
+        l = indices._keras_shape[0]
+        y._keras_shape = (l,) + reference._keras_shape[1:]
+    return y
 
 
 # ELEMENT-WISE OPERATIONS
@@ -778,8 +781,18 @@ def arange(start, stop=None, step=1, dtype='int32'):
 
 
 def tile(x, n):
-    # TODO: `keras_shape` inference.
-    return T.tile(x, n)
+    y = T.tile(x, n)
+    if hasattr(x, '_keras_shape'):
+        xshape = np.asarray(x._keras_shape)
+        n = np.asarray(n)
+        diff = len(xshape) - len(n)
+        if diff > 0:
+            n = np.append([1] * diff, n)
+        else:
+            xshape = np.append([1] * -diff, xshape)
+        y._keras_shape = tuple(xshape * n)
+
+    return y
 
 
 def flatten(x):

tests/keras/backend/backend_test.py

@@ -167,6 +167,24 @@ def test_tile(self):
         if hasattr(th_z, '_keras_shape'):
             assert th_z._keras_shape == th_rep.shape
 
+    def test_gather(self):
+        shape = (10, 2, 3)
+        ref = np.arange(np.prod(shape)).reshape(shape)
+        ref_th = KTH.variable(ref)
+        ref_tf = KTF.variable(ref)
+
+        inds = [1, 3, 7, 9]
+        inds_th = KTH.variable(inds, dtype='int32')
+        inds_tf = KTF.variable(inds, dtype='int32')
+        th_z = KTH.gather(ref_th, inds_th)
+        th_result = KTH.eval(th_z)
+        tf_result = KTF.eval(KTF.gather(ref_tf, inds_tf))
+
+        assert_allclose(tf_result, th_result, atol=1e-05)
+
+        if hasattr(th_z, '_keras_shape'):
+            assert th_z._keras_shape == th_result.shape
+
     def test_value_manipulation(self):
         val = np.random.random((4, 2))
         xth = KTH.variable(val)