[Relay][Frontend][TFlite] Add parses support for UNPACK tflite operat…

…or (apache#4447)

* use SPLIT & SQUEEZE = UNPACK as implemented in tensorflow parser
  Relay doesn't support UNPACK
* tflite 1.13: UNPACK doesn't work as exepcted -> copies the values from
  1st unpacked tensor to the other unpacks
* tflite 1.13: doesn't accept negative axis

python/tvm/relay/frontend/tflite.py

@@ -86,6 +86,7 @@ def __init__(self, model, subgraph, exp_tab):
             'FULLY_CONNECTED': self.convert_fully_connected,
             'PAD': self.convert_pad,
             'PACK': self.convert_pack,
+            'UNPACK': self.convert_unpack,
             'LOGISTIC': self.convert_logistic,
             'TANH':self.convert_tanh,
             'RELU':self.convert_relu,
@@ -1239,6 +1240,50 @@ def convert_pack(self, op):
         out = _op.concatenate(in_exprs_reshaped, pack_axis)
         return out
 
+    def convert_unpack(self, op):
+        """Convert TFLite unpack"""
+        try:
+            from tflite.BuiltinOptions import BuiltinOptions
+            from tflite.Operator import Operator
+            from tflite.UnpackOptions import UnpackOptions
+        except ImportError:
+            raise ImportError("The tflite package must be installed")
+
+        assert isinstance(op, Operator)
+        input_tensors = self.get_input_tensors(op)
+        assert len(input_tensors) == 1, "input tensors length should be 1"
+        input_tensor = input_tensors[0]
+        in_expr = self.get_expr(input_tensor.tensor_idx)
+        assert op.BuiltinOptionsType() == BuiltinOptions.UnpackOptions
+        op_options = op.BuiltinOptions()
+        unpack_options = UnpackOptions()
+        unpack_options.Init(op_options.Bytes, op_options.Pos)
+        num_unpacks = unpack_options.Num()
+        unpack_axis = unpack_options.Axis()
+
+        # Relay doesn't support 'unpack' operator so we use 'split' & 'squeeze' instead.
+        # We have to do 'squeeze' along the split axis but Relay expects
+        # squeeze_axis to be either None or List.
+        squeeze_axis = None if unpack_axis == 0 else [unpack_axis]
+
+        # Relay doesn't like TupleWrapper of 1 element so we isolate the case of unpacking
+        # a tensor by an axis with len(axis) == 1. For reference see convert_split().
+        # Such unpacking will result in the same tensor so we omit 'split' and only squeeze
+        # along the axis of dim == 1.
+        if num_unpacks == 1:
+            squeezed = _op.squeeze(in_expr, axis=squeeze_axis)
+            if isinstance(squeezed, _expr.TupleWrapper):
+                squeezed = squeezed[0]
+        else:
+            splitted = _op.split(in_expr,
+                                 indices_or_sections=num_unpacks,
+                                 axis=unpack_axis)
+            squeezed = _expr.TupleWrapper(
+                _expr.Tuple([_op.squeeze(split_item, axis=squeeze_axis) \
+                             for split_item in splitted]), len(splitted))
+
+        return squeezed
+
     def convert_batch_to_space_nd(self, op):
         """batch_to_space_nd implementation."""
         try:

tests/python/frontend/tflite/test_forward.py

@@ -970,6 +970,27 @@ def test_forward_pack():
          np.arange(6).reshape((2, 1, 1, 3))], 1)
 
 
+#######################################################################
+# Unpack
+# ------
+
+def _test_unpack(data, axis, num_unpacks):
+    """ One iteration of UNPACK """
+    with tf.Graph().as_default():
+        in_data = array_ops.placeholder(shape=data.shape, dtype=data.dtype)
+        out = gen_array_ops.unpack(in_data, num=num_unpacks, axis=axis, name='unpack')
+        out_names = ['out_' + str(n) + ':0' for n in range(num_unpacks)]
+        compare_tflite_with_tvm([data], 'Placeholder:0',  [in_data], out, out_names=out_names)
+
+def test_forward_unpack():
+    """ UNPACK """
+    _test_unpack(np.array(np.random.uniform(0, 5, (3, 1)), dtype=np.int32), axis=1, num_unpacks=1)
+    _test_unpack(np.array(np.random.uniform(0, 5, (3, 4)), dtype=np.float32), axis=0, num_unpacks=3)
+    # tflite 1.13 doesn't accept negative axis
+    if package_version.parse(tf.VERSION) >= package_version.parse('1.14.0'):
+        _test_unpack(np.array(np.random.uniform(0, 5, (3, 6)), dtype=np.int32), axis=-2, num_unpacks=3)
+        _test_unpack(np.array(np.random.uniform(0, 5, (2, 3, 4)), dtype=np.int32), axis=-3, num_unpacks=2)
+
 #######################################################################
 # Logistic
 # --------
@@ -1280,6 +1301,7 @@ def test_forward_mediapipe_hand_landmark():
     test_forward_concatenation()
     test_forward_pad()
     test_forward_pack()
+    test_forward_unpack()
     test_forward_reshape()
     test_all_resize()
     test_forward_squeeze()