[Relay] Fix TFlite frontend for unpack, stridedslice (#10333)

We found this while converting an RNN model.

The relay tflite frontend use squeeze at converting unpack, but when the
unpack.axis=0, `None` is passed to relay.squeeze(), which would squeeze
all dimensions with length 1, causing different results from TFLite.

A possible fix might be, assign the unpack.axis as-is to relay.squeeze()

As for stridedslice, when the tflite frontend handles shrink_axis_mask,
the wrapped `begin` should be used, instead of the original one which
can be negative. It can cause errors at
https://github.com/apache/tvm/blob/d65ff6594d4d6db0062537a1d43c0504173b8e5c/include/tvm/topi/detail/strided_slice.h#L140

Related cases are also added to the python test.

python/tvm/relay/frontend/tflite.py

@@ -1667,7 +1667,7 @@ def _transform_mask(stride_dim, ellipsis_mask):
                             if begin[index] < 0
                             else begin[index]
                         )
-                        m_end[final_index] = begin[index] + 1
+                        m_end[final_index] = m_begin[final_index] + 1
                         m_stride[final_index] = 1
                         fshape_indices.append(-2)
                     else:
@@ -2705,9 +2705,9 @@ def convert_unpack(self, op):
         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]
+        # We have to do 'squeeze' along the split axis.
+        # Relay expects squeeze_axis to be List.
+        squeeze_axis = [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().

tests/python/frontend/tflite/test_forward.py

@@ -618,6 +618,9 @@ def test_forward_stridedslice():
         _test_stridedslice(
             (4, 4), [1, 0], [4, 4], [1, 1], "float32", shrink_axis_mask=2, quantized=quantized
         )
+        _test_stridedslice(
+            (3, 4), [-1, 0], [0, 3], [1, 1], "float32", shrink_axis_mask=1, quantized=quantized
+        )
 
 
 #######################################################################
@@ -3186,6 +3189,9 @@ 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)
+    _test_unpack(
+        np.array(np.random.uniform(0, 5, (3, 1, 2)), 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(