[TFLITE]DepthToSpace and SpaceToDepth support (apache#5041)

* [TFLITE]DepthToSpace and SpaceToDepth op parser support

* DepthToSpace and SpaceToDepth testcases

* Review comments fixed

python/tvm/relay/frontend/tflite.py

@@ -70,6 +70,7 @@ def __init__(self, model, subgraph, exp_tab):
             'CONCATENATION': self.convert_concatenation,
             'CONV_2D': self.convert_conv2d,
             'COS': self.convert_cos,
+            'DEPTH_TO_SPACE': self.convert_depth_to_space,
             'DEPTHWISE_CONV_2D': self.convert_depthwise_conv2d,
             'DETECTION_POSTPROCESS': self.convert_detection_postprocess,
             'DIV': self.convert_div,
@@ -116,6 +117,7 @@ def __init__(self, model, subgraph, exp_tab):
             'SLICE': self.convert_slice,
             'SOFTMAX': self.convert_softmax,
             'SPACE_TO_BATCH_ND': self.convert_space_to_batch_nd,
+            'SPACE_TO_DEPTH': self.convert_space_to_depth,
             'SPLIT': self.convert_split,
             'SQRT': self.convert_sqrt,
             'SQUARE': self.convert_square,
@@ -1896,6 +1898,56 @@ def convert_space_to_batch_nd(self, op):
 
         return reshaped_permuted_reshaped_padded
 
+    def convert_depth_to_space(self, op):
+        """Convert TFLite DEPTH_TO_SPACE"""
+        try:
+            from tflite.BuiltinOptions import BuiltinOptions
+            from tflite.Operator import Operator
+            from tflite.DepthToSpaceOptions import DepthToSpaceOptions
+        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.DepthToSpaceOptions
+        op_options = op.BuiltinOptions()
+        depth_to_space_options = DepthToSpaceOptions()
+        depth_to_space_options.Init(op_options.Bytes, op_options.Pos)
+        block_size = depth_to_space_options.BlockSize()
+        out = _op.nn.depth_to_space(in_expr, block_size, layout='NHWC')
+
+        return out
+
+    def convert_space_to_depth(self, op):
+        """Convert TFLite SPACE_TO_DEPTH"""
+        try:
+            from tflite.BuiltinOptions import BuiltinOptions
+            from tflite.Operator import Operator
+            from tflite.SpaceToDepthOptions import SpaceToDepthOptions
+        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.SpaceToDepthOptions
+        op_options = op.BuiltinOptions()
+        space_to_depth_options = SpaceToDepthOptions()
+        space_to_depth_options.Init(op_options.Bytes, op_options.Pos)
+        block_size = space_to_depth_options.BlockSize()
+        out = _op.nn.space_to_depth(in_expr, block_size, layout='NHWC')
+
+        return out
+
     def convert_prelu(self, op):
         """Convert TFLite PReLU"""
         try:

tests/python/frontend/tflite/test_forward.py

@@ -1448,6 +1448,40 @@ def test_forward_prelu():
     _test_prelu(np.random.uniform(-5, 5, size=(1, 32, 32, 3)).astype("float32"), np.full((3,), 0.2, dtype="float32"))
     _test_prelu(np.random.uniform(-5, 5, size=(1, 32, 32, 3)).astype("float32"), np.full((1, 1, 3), 0.2, dtype="float32"))
 
+#######################################################################
+# DepthToSpace
+# ------------
+
+def _test_depthtospace(data, block_size):
+    """ One iteration of depth_to_space operation with given data and block size """
+
+    with tf.Graph().as_default():
+        in_data = array_ops.placeholder(shape=data.shape, dtype=data.dtype)
+        out = array_ops.depth_to_space(in_data, block_size)
+        compare_tflite_with_tvm(data, 'Placeholder:0', [in_data], [out])
+
+def test_forward_depthtospace():
+    # DEPTH_TO_SPACE comes with TFLite >= 1.15.0 fbs schema
+    if package_version.parse(tf.VERSION) >= package_version.parse('1.15.0'):
+        _test_depthtospace(np.random.normal(size=[1, 32, 32, 4]).astype("float32"), 2)
+        _test_depthtospace(np.random.normal(size=[1, 16, 8, 32]).astype("float32"), 4)
+
+#######################################################################
+# SpaceToDepth
+# ------------
+
+def _test_spacetodepth(data, block_size):
+    """ One iteration of space_to_depth operation with given data and block size """
+
+    with tf.Graph().as_default():
+        in_data = array_ops.placeholder(shape=data.shape, dtype=data.dtype)
+        out = array_ops.space_to_depth(in_data, block_size)
+        compare_tflite_with_tvm(data, 'Placeholder:0', [in_data], [out])
+
+def test_forward_spacetodepth():
+    _test_spacetodepth(np.random.normal(size=[1, 32, 32, 4]).astype("float32"), 2)
+    _test_spacetodepth(np.random.normal(size=[1, 16, 8, 32]).astype("float32"), 4)
+
 #######################################################################
 # Fully Connected
 # ---------------
@@ -1741,6 +1775,8 @@ def test_forward_mediapipe_hand_landmark():
     test_all_resize()
     test_forward_squeeze()
     test_forward_slice()
+    test_forward_depthtospace()
+    test_forward_spacetodepth()
 
     # NN
     test_forward_convolution()