Lunderberg commented on a change in pull request #9091:
URL: https://github.com/apache/tvm/pull/9091#discussion_r716977020
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File path: src/tir/transforms/storage_flatten.cc
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@@ -499,6 +1298,40 @@ class StorageFlattener : public StmtExprMutator {
bool create_bound_attributes_{false};
};
+// The specific tensor data layout is not determined before
+// StorageFlatten pass. We use buffer_bind_scope
+// to specify before hand we want to bind a subregion
+// of tensor to a symbolic buffer, which get used in extern.
+//
+// Example:
+//
+// realize A in range [i*4, extent=10) {
+// bind Ab to A in [i*4+1, extent=4) {
+// call_func(Ab.ptr, Ab.shape[0])
+// }
+// }
+//
+// After StorageFlatten
+//
+// alloc A[10]
+// call(A + 1, 4)
+//
+// Buffer is a protocol to declare specific
+// data layout and shape we expect.
+// So this function need to check:
+// - If the bind range is within the realize range
+// - If we can match the requirement of buffer
+// - Remap variables such as Ab.ptr to the actual value.
+//
+// Here are a few possible failure cases:
+// - Buffer is declared to have constant shape,
+// but we try to bind it to a different one.
+// - Buffer is declared to be compact(no strides)
+// but this binded region is a subregion of
+// a matrix(tensor), which means it requires strides.
+//
+// We do support a few relaxed case, such as bindingx
+// region with shape [1, 1, n, m] to buffer with shape [n, m]
Review comment:
Thank you, and updated to have shorter documentation in
BufferBindUnwrapper, while StorageFlatten maintains the full documentation.
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