Revert "[DICP]add ge/logical_or/repeat/tril for ascendgraph" (#659)

dicp/dicp/vendor/AscendGraph/ascend_op.py

@@ -909,21 +909,6 @@ def __init__(self):
         super().__init__("PadV3")
 
 
-class LogicalOr(Operator):
-    def __init__(self):
-        super().__init__("LogicalOr")
-
-
-class Tril(Operator):
-    def __init__(self):
-        super().__init__("Tril")
-
-
-class Tile(Operator):
-    def __init__(self):
-        super().__init__("Tile")
-
-
 def ret_triple(a, b, c) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
     return a, b, c
 

dicp/dicp/vendor/AscendGraph/codegen/ascend.py

@@ -1531,24 +1531,3 @@ def GatherElements(name, x, index, dim):
         op.set_input("index", index)
         op.set_attr_int("dim", dim)
         return op.to_node()
-
-    @staticmethod
-    def Tril(name, x, diagonal=0):
-        op = OP(name, "Tril")
-        op.set_input("x", x)
-        op.set_attr_int("diagonal", diagonal)
-        return op.to_node()
-
-    @staticmethod
-    def Tile(name, x, repeats):
-        op = OP(name, "Tile")
-        op.set_input("x", x)
-        op.set_input("multiples", repeats)
-        return op.to_node()
-
-    @staticmethod
-    def LogicalOr(name, x, y):
-        op = OP(name, "LogicalOr")
-        op.set_input("x1", x)
-        op.set_input("x2", y)
-        return op.to_node()

dicp/dicp/vendor/AscendGraph/conversion.py

@@ -1268,25 +1268,3 @@ def NativeDropoutBackward(self, grad_output, mask, scale):
         p = 1. - scale
         prob_op = self.get_const_proxy(float(p), dtype)
         return self.get_proxy(ascend_op.DropOutDoMaskV3, (grad_output, mask, prob_op))
-
-    @register_conversion(torch.ops.aten.tril.default)
-    def Tril(self, x, diagonal=0):
-        return self.get_proxy(ascend_op.Tril, (x, diagonal))
-
-    @register_conversion(torch.ops.aten.repeat.default)
-    def Repeat(self, x, repeats):
-        if not isinstance(repeats, torch.fx.proxy.Proxy):
-            assert isinstance(repeats, list)
-            repeats = self.get_const_proxy(repeats, torch.int32)
-        return self.get_proxy(ascend_op.Tile, (x, repeats))
-
-    @register_conversion([torch.ops.aten.ge.Scalar, torch.ops.aten.ge.Tensor])
-    def Ge(self, x, y):
-        if not isinstance(y, torch.fx.proxy.Proxy):
-            dtype = x.node.meta['val'].dtype
-            y = self.get_const_proxy(y, dtype)
-        return self.get_proxy(ascend_op.GreaterEqual, (x, y))
-
-    @register_conversion(torch.ops.aten.logical_or.default)
-    def LogicalOr(self, x, y):
-        return self.get_proxy(ascend_op.LogicalOr, (x, y))

dicp/test/ascend_scripts/ops/static.ini

@@ -27,13 +27,11 @@ python_files =
                test_full_like.py
             ;    test_full.py
                test_gather.py
-               test_ge.py
                test_getitem.py
                test_index.py
                test_le.py
             ;    test_lift_fresh_copy.py
             ;    test_log.py
-               test_logical_or.py
                test_lt.py
                test_masked_fill.py
             ;    test_max_pool2d_with_indices.py
@@ -49,7 +47,6 @@ python_files =
             ;    test_permute.py
                test_pow.py
                test_relu.py
-               test_repeat.py
                test_rsqrt.py
                test_scatter.py
                test_select.py
@@ -60,7 +57,6 @@ python_files =
                test_sub.py
                test_sum.py
             ;    test_transpose.py
-               test_tril.py
                test_unsqueeze.py
                test_view_as_complex.py
                test_view_as_real.py