[FRONTEND][TENSORFLOW] Add Pad and PadV2 support (#1545)

* [FRONTEND][TENSORFLOW] Add Pad and PadV2 support

* Add assettion to _pad, and fix testcase for pad.

nnvm/python/nnvm/frontend/tensorflow.py

@@ -607,6 +607,26 @@ def _LSTMBlockCell():
     return _impl
 
 
+def _pad(name):
+    def _impl(inputs, attr, params):
+        padlist_key = inputs[1].list_output_names()[0]
+        if padlist_key in params:
+            padlist = params.pop(padlist_key).asnumpy()
+        else:
+            raise RuntimeError("Required parameter {} not fount.".format(padlist_key))
+        paddings = tuple([tuple(l) for l in padlist])
+        attr['pad_width'] = paddings
+        attr['pad_value'] = 0
+        new_inputs = [inputs[0]]
+        if name == 'PadV2':
+            constant_values = params.pop(inputs[2].list_output_names()[0]).asnumpy()
+            attr['pad_value'] = constant_values[0]
+        return AttrCvt(
+            op_name='pad',
+            ignores=['Tpaddings'],)(new_inputs, attr)
+    return _impl
+
+
 # compatible operators that do NOT require any conversion.
 _identity_list = []
 
@@ -649,6 +669,8 @@ _convert_map = {
     'GatherV2'                          : _gather_v2(),
     'StridedSlice'                      : _stridedSlice(),
     'LRN'                               : _lrn(),
+    'Pad'                               : _pad('Pad'),
+    'PadV2'                             : _pad('PadV2'),
 }
 
 # _convert_map_rnn defines maps of rnn operator name to

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

@@ -704,6 +704,45 @@ def test_forward_resize_bilinear():
     _test_resize_bilinear((4, 16, 32, 32), [50, 50], False)
     _test_resize_bilinear((6, 32, 64, 64), [20, 20], True)
 
+#######################################################################
+# Pad
+# ---
+def _test_pad(input_shape, paddings, mode, **kwargs):
+    """ One iteration of pad operation with given shape"""
+
+    x = np.arange(np.prod(input_shape), dtype=np.float32).reshape(input_shape)
+
+    with tf.Graph().as_default():
+        in_data = constant_op.constant(x, shape=input_shape, dtype='float32')
+        pad_values = constant_op.constant(paddings)
+        pad = tf.pad(in_data, paddings=pad_values, mode=mode, **kwargs)
+
+        if mode == 'CONSTANT':
+            if 'constant_values' in kwargs:
+                out_node = 'PadV2'
+                out_name = 'PadV2:0'
+            else:
+                out_node = 'Pad'
+                out_name = 'Pad:0'
+
+        with tf.Session() as sess:
+            graph_def = tf.graph_util.convert_variables_to_constants(
+                sess,
+                sess.graph.as_graph_def(add_shapes=True),
+                [out_node],
+                )
+
+            tf_output = run_tf_graph(sess, x, 'Const:0', out_name)
+            tvm_output = run_tvm_graph(graph_def, x.astype('float32'),
+                                       "Const", tf_output.shape, 'float32')
+            np.testing.assert_allclose(tf_output, tvm_output)
+            sess.close()
+
+def test_forward_pad():
+    """ Pad """
+    _test_pad((2, 3), [[1,1], [2,2]], mode="CONSTANT")
+    _test_pad((2, 3), [[1,1], [2,2]], mode="CONSTANT", constant_values=1.0)
+
 
 #######################################################################
 # Inception V3
@@ -936,6 +975,7 @@ if __name__ == '__main__':
     test_forward_mobilenet()
     test_forward_variable()
     test_forward_resize_bilinear()
+    test_forward_pad()    
     test_forward_lstm()
     test_forward_stridedslice()
     test_forward_gather()