[Relay][TensorFlow] Add support for SquaredDifference

python/tvm/relay/frontend/tensorflow.py

@@ -469,7 +469,9 @@ def _impl(inputs, attr, params):
 
         # reshape result back to n-dimensional
         if len(orig_shape_x) > 3:
-            final_shape = attr['_output_shapes'][0]
+            final_shape = list(orig_shape_x)
+            final_shape[-2] = orig_shape_x[-1] if adj_x else orig_shape_x[-2]
+            final_shape[-1] = orig_shape_y[-2] if adj_y else orig_shape_y[-1]
             ret = _op.reshape(ret, newshape=final_shape)
 
         return ret
@@ -1227,6 +1229,12 @@ def _impl(inputs, attr, params):
                        extras={'depth' : depth, 'dtype' : dtype})(new_inputs, attr)
     return _impl
 
+def _squared_difference():
+    def _impl(inputs, attr, params):
+        difference = _op.subtract(inputs[0], inputs[1])
+        return _op.multiply(difference, difference)
+    return _impl
+
 # compatible operators that do NOT require any conversion.
 _identity_list = []
 
@@ -1334,6 +1342,7 @@ def _impl(inputs, attr, params):
     'SplitV'                            : _split(True),
     'Sqrt'                              : AttrCvt('sqrt'),
     'Square'                            : _square(),
+    'SquaredDifference'                 : _squared_difference(),
     'Squeeze'                           : _squeeze(),
     'StridedSlice'                      : _stridedSlice(),
     'Sub'                               : _elemwise('subtract'),

tests/python/frontend/tensorflow/test_forward.py

@@ -1852,6 +1852,16 @@ def test_forward_erf():
         tf.math.erf(in1)
         compare_tf_with_tvm(inp_array, 'Placeholder:0', 'Erf:0')
 
+def test_forward_squared_difference():
+    ishape = (1, 3, 10, 14)
+    inp_array_a = np.random.uniform(-5, 5, size=ishape).astype(np.float32)
+    inp_array_b = np.random.uniform(-5, 5, size=ishape).astype(np.float32)
+    with tf.Graph().as_default():
+        in1 = tf.placeholder(shape=inp_array_a.shape, dtype=inp_array_a.dtype, name="in1")
+        in2 = tf.placeholder(shape=inp_array_b.shape, dtype=inp_array_b.dtype, name="in2")
+        out = tf.math.squared_difference(in1, in2)
+        compare_tf_with_tvm([inp_array_a, inp_array_b], [in1.name, in2.name], out.name)
+
 def _test_forward_reverse_v2(in_shape, axis, dtype):
     np_data = np.random.uniform(-10, 10, size=in_shape).astype(dtype)
     tf.reset_default_graph()
@@ -2253,6 +2263,7 @@ def test_forward_one_hot():
     test_forward_bias_add()
     test_forward_zeros_like()
     test_forward_erf()
+    test_forward_squared_difference()
 
     # Reductions
     test_forward_argminmax()