Revert "[aoti] clear precomputed symbol replacements before cpp wrapp…

…er compilation (#122882)"

This reverts commit 384de46.

Reverted #122882 on behalf of https://github.com/jithunnair-amd due to broke ROCm CI ([comment](#122882 (comment)))

test/inductor/test_aot_inductor.py

@@ -1137,70 +1137,6 @@ def forward(self, x, y):
                     exactly=True,
                 ).run(src_code)
 
-    def test_reuse_kernel_dynamic(self):
-        class Model(torch.nn.Module):
-            def __init__(self, device):
-                super().__init__()
-                self.cst = torch.randn(48, device=device, dtype=torch.float)
-                self.weights = torch.randn(6, 48, 48, device=device, dtype=torch.float)
-                self.cst_1 = torch.randn(48, device=device, dtype=torch.float)
-                self.weights_1 = torch.randn(
-                    6, 48, 48, device=device, dtype=torch.float
-                )
-
-            def forward(self, x, y, z):
-                dim0 = x.size(1)
-                add_0 = z + z
-                expand_2 = add_0.expand(-1, -1, 48)
-                # [s0, 6, 48]
-                mul_3 = add_0 * expand_2
-                # [6, s0, 48]
-                permute_4 = torch.permute(mul_3, (1, 0, 2))
-                # [6, s0, 48]
-                bmm_5 = torch.bmm(permute_4, self.weights)
-                add_6 = bmm_5 + self.cst
-                reshape_7 = torch.reshape(add_6, [6, dim0 * 6, 8])
-                # [6*s0, 6, 8]
-                permute_8 = torch.permute(reshape_7, (1, 0, 2))
-                mul_9 = permute_8 * 0.123
-                reshape_10 = torch.reshape(y, [8, dim0 * 6, 4])
-                # [6*s0, 8, 4]
-                permute_11 = torch.permute(reshape_10, (1, 0, 2))
-                bmm_12 = torch.bmm(mul_9, permute_11)
-
-                add_0_1 = z + z
-                expand_2_1 = add_0_1.expand(-1, -1, 48)
-                # [s0, 6, 48]
-                mul_3_1 = add_0_1 * expand_2_1
-                # [6, s0, 48]
-                permute_4_1 = torch.permute(mul_3_1, (1, 0, 2))
-                # [6, s0, 48]
-                bmm_5_1 = torch.bmm(permute_4_1, self.weights_1)
-                add_6_1 = bmm_5_1 + self.cst_1
-                reshape_7_1 = torch.reshape(add_6_1, [6, dim0 * 6, 8])
-                # [6*s0, 6, 8]
-                permute_8_1 = torch.permute(reshape_7_1, (1, 0, 2))
-                mul_9_1 = permute_8_1 * 0.123
-                reshape_10_1 = torch.reshape(y, [8, dim0 * 6, 4])
-                # [6*s0, 8, 4]
-                permute_11_1 = torch.permute(reshape_10_1, (1, 0, 2))
-                bmm_12_1 = torch.bmm(mul_9_1, permute_11_1)
-                return bmm_12 + bmm_12_1
-
-        x = torch.randn(6, 2, 48, device=self.device, dtype=torch.float)
-        y = torch.randn(48, 2, 4, device=self.device, dtype=torch.float)
-        z = torch.randn(2, 6, 1, device=self.device, dtype=torch.float)
-        dim0 = Dim("dim0", min=1, max=2048)
-        dynamic_shapes = {
-            "x": {1: dim0},
-            "y": {1: dim0},
-            "z": {0: dim0},
-        }
-
-        example_inputs = (x, y, z)
-        m = Model(self.device).to(dtype=torch.float)
-        self.check_model(m, example_inputs, dynamic_shapes=dynamic_shapes)
-
     def test_fake_tensor_device_validation(self):
         if self.device != "cuda":
             raise unittest.SkipTest("requires CUDA")
@@ -2463,7 +2399,6 @@ def fail_non_abi_compatible_cuda(is_skip=False):
             "test_repeat_interleave": fail_minimal_arrayref_interface(is_skip=True),
             "test_return_constant": fail_minimal_arrayref_interface(is_skip=True),
             "test_reuse_kernel": fail_minimal_arrayref_interface(is_skip=True),
-            "test_reuse_kernel_dynamic": fail_minimal_arrayref_interface(is_skip=True),
             "test_simple": fail_minimal_arrayref_interface(is_skip=True),
             "test_small_constant": fail_minimal_arrayref_interface(is_skip=True),
             "test_with_no_triton_profiler": fail_minimal_arrayref_interface(

torch/_inductor/graph.py

@@ -1273,8 +1273,6 @@ def materialize(x):
             self.cpp_wrapper = True
             self.removed_buffers.clear()
             self.inplaced_to_remove.clear()
-            V.graph.sizevars.precomputed_replacements.clear()
-            V.graph.sizevars.inv_precomputed_replacements.clear()
             return self.codegen()
         else:
             # cpu