Implement tensorflow relational operators and related tests (#1714)

nnvm/python/nnvm/frontend/tensorflow.py

@@ -759,6 +759,15 @@ def _mean():
                        extras={'axis': tuple(axis.asnumpy())})(inputs[0], attr)
     return _impl
 
+def _broadcast(name):
+    def _impl(inputs, attr, params):
+        op_name = _math_name_picker(name)(attr)
+        return AttrCvt(
+            op_name=op_name,
+            ignores=['name', 'Tidx']
+        )(inputs, attr)
+    return _impl
+
 # compatible operators that do NOT require any conversion.
 _identity_list = []
 
@@ -819,6 +828,12 @@ _convert_map = {
     'Transpose'                         : _transpose(),
     'Tanh'                              : AttrCvt('tanh'),
     'Mean'                              : _mean(),
+    'Less'                              : _broadcast('less'),
+    'Greater'                           : _broadcast('greater'),
+    'LessEqual'                         : _broadcast('less_equal'),
+    'GreaterEqual'                      : _broadcast('greater_equal'),
+    'Equal'                             : _broadcast('equal'),
+    'NotEqual'                          : _broadcast('not_equal'),
 }
 
 # _convert_map_rnn defines maps of rnn operator name to

nnvm/tests/python/frontend/tensorflow/test_forward.py

@@ -378,7 +378,7 @@ def test_forward_reduce():
     data = np.random.uniform(size=(8,4,9)).astype('float32')
     _test_reduce(tf.reduce_sum, data=data)
     _test_reduce(tf.reduce_sum, data=data, axis=0)
-    _test_reduce(tf.reduce_sum, data=data, axis=(0,1))    
+    _test_reduce(tf.reduce_sum, data=data, axis=(0,1))
 
 
 #######################################################################
@@ -978,6 +978,28 @@ def test_forward_mean():
     check_mean((10, 8, 16, 32), axis=(2,3))
     check_mean((10, 8, 16, 32), axis=(1,2), keepdims=True)
 
+#######################################################################
+# Relational operators
+# --------------------
+def _test_forward_rel_op(data, func):
+    with tf.Graph().as_default():
+        in1 = tf.placeholder(shape=data[0].shape, dtype=data[0].dtype, name='in1')
+        in2 = tf.placeholder(shape=data[1].shape, dtype=data[1].dtype, name='in2')
+        op = func(in1, in2, name='op')
+        out = tf.cast(op, tf.int32, name='out1')
+        compare_tf_with_tvm([data[0], data[1]], ['in1:0', 'in2:0'], 'out1:0')
+
+def test_forward_rel_ops():
+    t1 = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
+    t2 = np.array([[9, 8, 7], [6, 5, 4], [3, 2, 1]])
+    _test_forward_rel_op([t1, t2], math_ops.less)
+    _test_forward_rel_op([t1, t2], math_ops.greater)
+    _test_forward_rel_op([t1, t2], math_ops.less_equal)
+    _test_forward_rel_op([t1, t2], math_ops.greater_equal)
+    _test_forward_rel_op([t1, t2], math_ops.equal)
+    _test_forward_rel_op([t1, t2], math_ops.not_equal)
+
+
 #######################################################################
 # Main
 # ----
@@ -1030,3 +1052,6 @@ if __name__ == '__main__':
     # Elementwise
     test_forward_ceil()
     test_forward_floor()
+
+    # Relational ops
+    test_forward_rel_ops()