refine (#69765)

wanghuancoder · web-flow · commit bcb9a712402a · 2024-11-27T16:26:49.000+08:00
diff --git a/paddle/fluid/primitive/decomp_rule/decomp_vjp/details.h b/paddle/fluid/primitive/decomp_rule/decomp_vjp/details.h
@@ -1711,14 +1711,14 @@ void tile_grad(const Tensor& x,
     if (has_dynamic_shape(x.shape()) || has_dynamic_shape(out_grad.shape())) {
       std::vector<Tensor> out_grad_shape_vec;
       for (int64_t i = 0; i < out_grad.dims().size(); ++i) {
-        auto out_grad_shape_slice = get_slice<T>(shape<T>(out_grad_tmp), i);
+        auto out_grad_shape_slice = get_slice<T>(shape64<T>(out_grad_tmp), i);
         out_grad_shape_vec.push_back(out_grad_shape_slice);
       }
       if (repeat_times_data.size() != 0) {
         while (true) {
           std::vector<Tensor> expand_shape_vec;
           for (int64_t i = 0; i < out_grad_tmp.dims().size(); ++i) {
-            auto expand_shape = get_slice<T>(shape<T>(out_grad_tmp), i);
+            auto expand_shape = get_slice<T>(shape64<T>(out_grad_tmp), i);
             expand_shape_vec.push_back(expand_shape);
           }
           int num_reduce = 0;
@@ -1754,7 +1754,7 @@ void tile_grad(const Tensor& x,
           }
         }
       }
-      x_grad_tmp = backend::reshape<T>(out_grad_tmp, shape<T>(x));
+      x_grad_tmp = backend::reshape<T>(out_grad_tmp, shape64<T>(x));
     } else {
       std::vector<int64_t> out_grad_shape(out_grad.shape());
 

Original file line number	Diff line number	Diff line change
`@@ -1711,14 +1711,14 @@ void tile_grad(const Tensor& x,`
`1711`	`1711`	`if (has_dynamic_shape(x.shape()) \|\| has_dynamic_shape(out_grad.shape())) {`
`1712`	`1712`	`std::vector<Tensor> out_grad_shape_vec;`
`1713`	`1713`	`for (int64_t i = 0; i < out_grad.dims().size(); ++i) {`
`1714`		`- auto out_grad_shape_slice = get_slice<T>(shape<T>(out_grad_tmp), i);`
	`1714`	`+ auto out_grad_shape_slice = get_slice<T>(shape64<T>(out_grad_tmp), i);`
`1715`	`1715`	`out_grad_shape_vec.push_back(out_grad_shape_slice);`
`1716`	`1716`	`}`
`1717`	`1717`	`if (repeat_times_data.size() != 0) {`
`1718`	`1718`	`while (true) {`
`1719`	`1719`	`std::vector<Tensor> expand_shape_vec;`
`1720`	`1720`	`for (int64_t i = 0; i < out_grad_tmp.dims().size(); ++i) {`
`1721`		`- auto expand_shape = get_slice<T>(shape<T>(out_grad_tmp), i);`
	`1721`	`+ auto expand_shape = get_slice<T>(shape64<T>(out_grad_tmp), i);`
`1722`	`1722`	`expand_shape_vec.push_back(expand_shape);`
`1723`	`1723`	`}`
`1724`	`1724`	`int num_reduce = 0;`
`@@ -1754,7 +1754,7 @@ void tile_grad(const Tensor& x,`
`1754`	`1754`	`}`
`1755`	`1755`	`}`
`1756`	`1756`	`}`
`1757`		`- x_grad_tmp = backend::reshape<T>(out_grad_tmp, shape<T>(x));`
	`1757`	`+ x_grad_tmp = backend::reshape<T>(out_grad_tmp, shape64<T>(x));`
`1758`	`1758`	`} else {`
`1759`	`1759`	`std::vector<int64_t> out_grad_shape(out_grad.shape());`
`1760`	`1760`