【prim】delete Floor divide decomp (#68779)

xiaoguoguo626807 · web-flow · commit 6f24872e5908 · 2024-10-21T13:55:56.000+08:00
* modify assign inplace

* delete floor_divide decomp

* delete floor_divide decomp

* modify prim test

* modify prim test
diff --git a/paddle/fluid/pir/dialect/op_generator/decomp_interface_gen_op_list.py b/paddle/fluid/pir/dialect/op_generator/decomp_interface_gen_op_list.py
@@ -30,7 +30,6 @@
     "elu",
     "embedding",
     "flatten",
-    "floor_divide",
     "full_like",
     "gelu",
     "hardswish",
@@ -83,7 +82,6 @@
     "elu",
     "embedding",
     "flatten",
-    "floor_divide",
     "full_like",
     "gelu",
     "hardswish",
diff --git a/paddle/fluid/primitive/composite/composite.h b/paddle/fluid/primitive/composite/composite.h
@@ -732,14 +732,6 @@ Tensor full_like_decomp(const Tensor& x,
   }
 }
 
-template <typename T>
-Tensor floor_divide_decomp(const Tensor& x, const Tensor& y) {
-  auto x_cast = cast<T>(x, DataType::INT64);
-  auto y_cast = cast<T>(y, DataType::INT64);
-  auto res = x_cast / y_cast;
-  return cast<T>(res, x.dtype());
-}
-
 template <typename T>
 std::tuple<Tensor, Tensor> dropout_decomp(
     const Tensor& x,
diff --git a/test/legacy_test/test_elementwise_floordiv_op.py b/test/legacy_test/test_elementwise_floordiv_op.py
@@ -48,7 +48,7 @@ def setUp(self):
         self.outputs = {'Out': self.out}
 
     def test_check_output(self):
-        self.check_output(check_pir=True, check_prim_pir=True)
+        self.check_output(check_pir=True)
 
     def init_input_output(self):
         self.x = np.random.uniform(0, 10000, [10, 10]).astype(self.dtype)
diff --git a/test/prim/pir_prim/test_prim_sub_graph_dynamic_shape.py b/test/prim/pir_prim/test_prim_sub_graph_dynamic_shape.py
@@ -246,10 +246,6 @@ def softsign_net(x):
     return paddle.nn.functional.softsign(x)
 
 
-def floor_divide_net(x, y):
-    return paddle.floor_divide(x, y)
-
-
 def gelu_net(x):
     return paddle.nn.functional.gelu(x)
 
@@ -1332,28 +1328,6 @@ def setUp(self):
         self.tol = 1e-6
 
 
-class TestPrimFloorDivide(TestPrimTwo):
-    def setUp(self):
-        np.random.seed(2024)
-        paddle.seed(2024)
-        self.shape_x = [300, 2048]
-        self.shape_y = [300, 2048]
-        self.dtype_x = int
-        self.dtype_y = int
-        self.init_x_shape = [None, None]
-        self.init_y_shape = [None, None]
-        self.x = np.random.uniform(
-            low=1.0, high=100.0, size=self.shape_x
-        ).astype(self.dtype_x)
-        self.y = np.random.uniform(
-            low=1.0, high=100.0, size=self.shape_x
-        ).astype(self.dtype_x)
-        self.net = floor_divide_net
-        self.necessary_ops = "pd_op.floor_divide"
-        self.enable_cinn = False
-        self.tol = 1e-6
-
-
 class TestPrimGelu(TestPrimBase):
     def setUp(self):
         np.random.seed(2024)

Original file line number	Diff line number	Diff line change
`@@ -732,14 +732,6 @@ Tensor full_like_decomp(const Tensor& x,`
`732`	`732`	`}`
`733`	`733`	`}`
`734`	`734`
`735`		`-template <typename T>`
`736`		`-Tensor floor_divide_decomp(const Tensor& x, const Tensor& y) {`
`737`		`- auto x_cast = cast<T>(x, DataType::INT64);`
`738`		`- auto y_cast = cast<T>(y, DataType::INT64);`
`739`		`- auto res = x_cast / y_cast;`
`740`		`- return cast<T>(res, x.dtype());`
`741`		`-}`
`742`		`-`
`743`	`735`	`template <typename T>`
`744`	`736`	`std::tuple<Tensor, Tensor> dropout_decomp(`
`745`	`737`	`const Tensor& x,`