Alias tracking fails for basic views like reshape and diagonal causing silent data staleness upon base tensor mutation

### bug描述 Describe the Bug Description: When compiling models in static mode, view tensors are not correctly synchronized if their original base tensor is modified in-place. In Eager execution, modifying a base tensor automatically updates its active views, whether they are shape-changing views, subset views, or offset views. However, in static mode, this alias relationship is broken. The view tensor retains a stale, pre-mutation snapshot of the data, which leads to a critical silent value mismatch. Minimal Reproducer: ```python import os import paddle def kernel_contiguous_views(x): # 1. Shape-changing View v_resh = paddle.reshape(x, [4]) # 2. Subset View v_slic = x[1, :] # 3. Offset View v_diag = paddle.diagonal(x) # CORE MUTATION: Mutate the base tensor in-place x[1, 1] = 99.0 return paddle.sum(v_resh), paddle.sum(v_slic), paddle.sum(v_diag) # Initialize data: [[0.0, 1.0], [2.0, 3.0]] x_init = paddle.arange(4, dtype="float32").reshape([2, 2]) # Eager Execution e_resh, e_slic, e_diag = kernel_contiguous_views(x_init.clone()) # Static PIR Execution static_fn = paddle.jit.to_static(kernel_contiguous_views, full_graph=True) s_resh, s_slic, s_diag = static_fn(x_init.clone()) print("=== Basic View Alias Tracking Failure ===") print(f"[reshape] Eager Sum: {e_resh.item():.1f} | Static Sum: {s_resh.item():.1f}") print(f"[slice] Eager Sum: {e_slic.item():.1f} | Static Sum: {s_slic.item():.1f}") print(f"[diagonal] Eager Sum: {e_diag.item():.1f} | Static Sum: {s_diag.item():.1f}") ```` Output: ``` === Basic View Alias Tracking Failure === [reshape] Eager Sum: 102.0 | Static Sum: 6.0 [slice] Eager Sum: 101.0 | Static Sum: 5.0 [diagonal] Eager Sum: 99.0 | Static Sum: 3.0 ``` ### 其他补充信息 Additional Supplementary Information `Paddle Version: 3.3.0`