重命名 pt2tf 为 pt2pb

pt2pb/onnx-tensorflow/onnx_tf/handlers/backend/equal.py

@@ -0,0 +1,41 @@
+import tensorflow as tf
+
+from onnx_tf.handlers.backend_handler import BackendHandler
+from onnx_tf.handlers.handler import onnx_op
+from onnx_tf.handlers.handler import tf_func
+from onnx_tf.handlers.handler import partial_support
+from onnx_tf.handlers.handler import ps_description
+from .control_flow_mixin import ComparisonMixin
+
+
+@onnx_op("Equal")
+@tf_func(tf.equal)
+@partial_support(True)
+@ps_description("Equal inputs in uint16/uint32/uint64 " +
+                "are not supported in Tensorflow.")
+class Equal(ComparisonMixin, BackendHandler):
+
+  @classmethod
+  def args_check(cls, node, **kwargs):
+    supported_dtype = [
+        tf.bfloat16, tf.half, tf.float32, tf.float64, tf.uint8,
+        tf.int8, tf.int16, tf.int32, tf.int64, tf.complex64,
+        tf.quint8, tf.qint8, tf.qint32, tf.string, tf.bool, 
+        tf.complex128
+    ]
+    x = kwargs["tensor_dict"][node.inputs[0]]
+    if x.dtype not in supported_dtype:
+      exception.OP_UNSUPPORTED_EXCEPT(
+          "Equal inputs in " + str(x.dtype) + " which", "Tensorflow")
+
+  @classmethod
+  def version_1(cls, node, **kwargs):
+    return cls.limited_broadcast(node, **kwargs)
+
+  @classmethod
+  def version_7(cls, node, **kwargs):
+    return [cls.make_tensor_from_onnx_node(node, **kwargs)]
+
+  @classmethod
+  def version_11(cls, node, **kwargs):
+    return [cls.make_tensor_from_onnx_node(node, **kwargs)]