[Language][Reshape] Improve variable handling and ensure correctness during Layout Reshape (#1248)

* fix

* Refactor tensor reshaping in fp8_lighting_indexer.py

- Replaced the allocation of `s_reshaped` with a reshape operation to improve clarity and performance.
- Updated the logic in the computation of `s_reshaped` to utilize the reshaped tensor, enhancing the overall functionality of the attention mechanism.

* Refactor analyzer usage in Layout and Fragment reshaping

- Consolidated analyzer logic in the `Reshape` methods of `LayoutNode` and `FragmentNode` to utilize a fallback analyzer, improving code clarity and preventing potential null dereference issues.
- Updated variable binding and simplification calls to use the selected analyzer consistently, enhancing robustness in shape validation and index computation.

examples/deepseek_v32/fp8_lighting_indexer.py

@@ -127,7 +127,7 @@ def mqa_attn_return_logits(
             index_k_shared = T.alloc_shared([block_N, index_dim], dtype)
             index_k_scale_fragment = T.alloc_fragment([block_N], accum_dtype)
             s = T.alloc_fragment([block_N, block_Q * heads], accum_dtype)
-            s_reshaped = T.alloc_fragment([block_N, block_Q, heads], accum_dtype)
+            s_reshaped = T.reshape(s, (block_N, block_Q, heads))
             logits = T.alloc_fragment([block_N, block_Q], accum_dtype)
             weights = T.alloc_fragment([block_Q, heads], accum_dtype)
 
@@ -165,7 +165,7 @@ def mqa_attn_return_logits(
 
                 for bn_i, bq_i, h_i in T.Parallel(block_N, block_Q, heads):
                     s_reshaped[bn_i, bq_i,
-                               h_i] = (T.max(s[bn_i, bq_i * heads + h_i], 0) *
+                               h_i] = (T.max(s_reshaped[bn_i, bq_i, h_i], 0) *
                                        weights[bq_i, h_i]) * index_k_scale_fragment[bn_i]
 
                 T.reduce_sum(s_reshaped, logits, dim=-1, clear=True)

src/layout/layout.cc

@@ -313,20 +313,21 @@ Layout LayoutNode::Reshape(const Array<PrimExpr> &shape,
     shape_product *= dim;
   }
 
-  if (analyzer) {
-    ICHECK(analyzer->CanProveEqual(input_shape_product, shape_product))
+  // Use provided analyzer if present, otherwise a local fallback to avoid
+  // potential null dereference paths flagged by static analysis.
+  arith::Analyzer fallback_analyzer;
+  arith::Analyzer *az = analyzer ? analyzer : &fallback_analyzer;
+  ICHECK(az->CanProveEqual(input_shape_product, shape_product))
       << "InputShape() = " << InputShape() << " shape = " << shape;
-  } else {
-    arith::Analyzer local_analyzer;
-    ICHECK(local_analyzer.CanProveEqual(input_shape_product, shape_product))
-        << "InputShape() = " << InputShape() << " shape = " << shape;
-  }
 
   // Step 2. Create new forward indices by reshaping
   // For each dimension in the new shape, we create a placeholder variable
   Array<Var> new_vars;
+  new_vars.reserve(shape.size());
   for (size_t i = 0; i < shape.size(); ++i) {
-    new_vars.push_back(InputPlaceholder(i));
+    auto var = Var(std::string("n_") + std::to_string(i), shape[i].dtype());
+    az->Bind(var, Range(0, shape[i]));
+    new_vars.push_back(var);
   }
   // Step 3. Compute the flat index from new shape indices
   // flat_index = k0 * (s1 * s2 * ...) + k1 * (s2 * s3 * ...) + ... + kn
@@ -362,7 +363,11 @@ Layout LayoutNode::Reshape(const Array<PrimExpr> &shape,
       substituted =
           Substitute(substituted, {{InputPlaceholder(i), original_indices[i]}});
     }
-    new_forward_index.push_back(substituted);
+    new_forward_index.push_back(az->Simplify(substituted));
+  }
+  for (size_t i = 0; i < new_vars.size(); ++i) {
+    new_forward_index =
+        Substitute(new_forward_index, {{new_vars[i], InputPlaceholder(i)}});
   }
   return Layout(shape, new_forward_index);
 }
@@ -382,21 +387,25 @@ Layout FragmentNode::Reshape(const Array<PrimExpr> &shape,
   for (const auto &d : shape)
     shape_prod *= d;
 
-  if (analyzer) {
-    ICHECK(analyzer->CanProveEqual(input_prod, shape_prod))
+  // Use provided analyzer if present, otherwise a local fallback.
+  arith::Analyzer fallback_analyzer;
+  arith::Analyzer *az = analyzer ? analyzer : &fallback_analyzer;
+  ICHECK(az->CanProveEqual(input_prod, shape_prod))
       << "InputShape() = " << InputShape() << " shape = " << shape
       << " input fragment layout is = " << DebugOutput();
-  } else {
-    arith::Analyzer local_analyzer;
-    ICHECK(local_analyzer.CanProveEqual(input_prod, shape_prod))
-        << "InputShape() = " << InputShape() << " shape = " << shape;
-  }
 
   // 2) Build flat index from new-shape indices
   Array<Var> new_vars;
   new_vars.reserve(shape.size());
-  for (size_t i = 0; i < shape.size(); ++i)
-    new_vars.push_back(InputPlaceholder(i));
+  for (size_t i = 0; i < shape.size(); ++i) {
+    // Cannot use InputPlaceholder(i) here, because it would cause name capture
+    // (variable capture) with InputPlaceholder(i) in upper scopes. Therefore,
+    // we must create a fresh variable here to avoid confusion when
+    // substituting.
+    auto var = Var(std::string("n_") + std::to_string(i), shape[i].dtype());
+    az->Bind(var, Range(0, shape[i]));
+    new_vars.push_back(var);
+  }
 
   PrimExpr flat = Integer(0);
   for (size_t i = 0; i < shape.size(); ++i) {
@@ -405,7 +414,6 @@ Layout FragmentNode::Reshape(const Array<PrimExpr> &shape,
       stride = stride * shape[j];
     flat = flat + new_vars[i] * stride;
   }
-
   // 3) Recover original indices from flat index
   Array<PrimExpr> orig_indices;
   PrimExpr remain = flat;
@@ -416,7 +424,6 @@ Layout FragmentNode::Reshape(const Array<PrimExpr> &shape,
     orig_indices.push_back(floordiv(remain, stride));
     remain = floormod(remain, stride);
   }
-
   // 4) Substitute old placeholders with expressions of new indices
   Array<PrimExpr> new_forward_index;
   for (const auto &e : forward_index_) {
@@ -424,15 +431,22 @@ Layout FragmentNode::Reshape(const Array<PrimExpr> &shape,
     for (size_t i = 0; i < InputShape().size(); ++i) {
       cur = Substitute(cur, {{InputPlaceholder(i), orig_indices[i]}});
     }
+    cur = az->Simplify(cur);
     new_forward_index.push_back(cur);
   }
-
   PrimExpr new_forward_thread = forward_thread_;
   for (size_t i = 0; i < InputShape().size(); ++i) {
     new_forward_thread = Substitute(new_forward_thread,
                                     {{InputPlaceholder(i), orig_indices[i]}});
   }
-
+  new_forward_thread = az->Simplify(new_forward_thread);
+  for (size_t i = 0; i < new_vars.size(); ++i) {
+    auto var = new_vars[i];
+    new_forward_index =
+        Substitute(new_forward_index, {{var, InputPlaceholder(i)}});
+    new_forward_thread =
+        Substitute(new_forward_thread, {{var, InputPlaceholder(i)}});
+  }
   Fragment reshaped(shape, new_forward_index, new_forward_thread,
                     ReplicateExtent(), std::nullopt);
   if (thread_range_.defined()) {