Support bitwise ops (#2192)

* 10787 support bitwise ops
* 10787 add bitwise tests
* ANTIALIAS has been removed in Pillow 10 (2023-07-01).
Use LANCZOS instead.

Signed-off-by: Salvetti, Francesco <[email protected]>
Signed-off-by: Jay Zhang <[email protected]>
Co-authored-by: Jay Zhang <[email protected]>

Author: f-salvetti

support_status.md

@@ -32,6 +32,9 @@
 | BiasAdd | 1 ~ 17 |
 | BiasAddV1 | 1 ~ 17 |
 | Bincount | 11 ~ 17 |
+| BitwiseAnd | 18 |
+| BitwiseOr | 18 |
+| BitwiseXor | 18 |
 | BroadcastTo | 8 ~ 17 |
 | CTCGreedyDecoder | 11 ~ 17 |
 | Cast | 1 ~ 17 |
@@ -93,6 +96,7 @@
 | Identity | 1 ~ 17 |
 | IdentityN | 1 ~ 17 |
 | If | 1 ~ 17 |
+| Invert | 18 |
 | InvertPermutation | 11 ~ 17 |
 | IsFinite | 10 ~ 17 |
 | IsInf | 10 ~ 17 |

tests/run_pretrained_models.py

@@ -58,7 +58,7 @@ def get_img(shape, path, dtype, should_scale=True):
     resize_to = shape[1:3]
     path = os.path.join(os.path.dirname(os.path.abspath(__file__)), path)
     img = PIL.Image.open(path)
-    img = img.resize(resize_to, PIL.Image.ANTIALIAS)
+    img = img.resize(resize_to, PIL.Image.LANCZOS)
     img_np = np.array(img).astype(dtype)
     img_np = np.stack([img_np] * shape[0], axis=0).reshape(shape)
     if should_scale:

tests/test_backend.py

@@ -4896,6 +4896,41 @@ def func(x):
             return tf.identity(x_, name=_TFOUTPUT)
         self._run_test_case(func, [_OUTPUT], {_INPUT: x_val})
 
+    @check_opset_min_version(18, "BitwiseAnd")
+    def test_bitwise_and(self):
+        x_val = np.array([21, 4, 1], dtype=np.int32)
+        y_val = np.array([45, 69, 3], dtype=np.int32)
+        def func(x, y):
+            x_ = tf.bitwise.bitwise_and(x, y)
+            return tf.identity(x_, name=_TFOUTPUT)
+        self._run_test_case(func, [_OUTPUT], {_INPUT: x_val, _INPUT1: y_val})
+
+    @check_opset_min_version(18, "BitwiseOr")
+    def test_bitwise_or(self):
+        x_val = np.array([21, 4, 87], dtype=np.int32)
+        y_val = np.array([45, 69, 173], dtype=np.int32)
+        def func(x, y):
+            x_ = tf.bitwise.bitwise_or(x, y)
+            return tf.identity(x_, name=_TFOUTPUT)
+        self._run_test_case(func, [_OUTPUT], {_INPUT: x_val, _INPUT1: y_val})
+
+    @check_opset_min_version(18, "BitwiseXor")
+    def test_bitwise_xor(self):
+        x_val = np.array([21, 4, 87], dtype=np.int32)
+        y_val = np.array([45, 69, 173], dtype=np.int32)
+        def func(x, y):
+            x_ = tf.bitwise.bitwise_xor(x, y)
+            return tf.identity(x_, name=_TFOUTPUT)
+        self._run_test_case(func, [_OUTPUT], {_INPUT: x_val, _INPUT1: y_val})
+
+    @check_opset_min_version(18, "BitwiseNot")
+    def test_bitwise_not(self):
+        x_val = np.array([21, 4, 1], dtype=np.int32)
+        def func(x):
+            x_ = tf.bitwise.invert(x)
+            return tf.identity(x_, name=_TFOUTPUT)
+        self._run_test_case(func, [_OUTPUT], {_INPUT: x_val})
+
     @check_tf_min_version("1.14", "tensor_scatter_nd_update needs tf 1.14")
     @check_opset_min_version(11, "ScatterND")
     def test_tensor_scatter_update(self):

tf2onnx/onnx_opset/math.py

@@ -792,7 +792,6 @@ def version_11(cls, ctx, node, **kwargs):
 
 @tf_op(["LeftShift", "RightShift"])
 class BitShift:
-
     @classmethod
     def version_11(cls, ctx, node, **kwargs):
         dir_map = {"LeftShift": "LEFT", "RightShift": "RIGHT"}
@@ -818,6 +817,16 @@ def version_11(cls, ctx, node, **kwargs):
             ctx.copy_dtype(node.input[0], node.output[0])
 
 
+@tf_op("BitwiseAnd")
+@tf_op("BitwiseOr")
+@tf_op("BitwiseXor")
+@tf_op("Invert", onnx_op="BitwiseNot")
+class BitwiseOps:
+    @classmethod
+    def version_18(cls, ctx, node, **kwargs):
+        pass
+
+
 @tf_op("SquaredDistance", onnx_op="MeanSquaredDistance")
 class SquaredDistance:
     @classmethod