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| // RUN: mlir-opt %s -test-transform-dialect-interpreter="debug-payload-root-tag=payload" -transform-dialect-drop-schedule | |
| module attributes {transform.target_tag="payload"} { | |
| // Batched TOSA matrix multiplication. %A and %B are the inputs, %C is the | |
| // output. | |
| func.func @test_matmul(%A: memref<1x17x19xf32>, %B: memref<1x19x29xf32>, | |
| %C: memref<1x17x29xf32>) { | |
| %A_tensor = bufferization.to_tensor %A restrict : memref<1x17x19xf32> | |
| %B_tensor = bufferization.to_tensor %B restrict : memref<1x19x29xf32> | |
| %0 = tosa.matmul %A_tensor, %B_tensor | |
| : (tensor<1x17x19xf32>, tensor<1x19x29xf32>) -> tensor<1x17x29xf32> | |
| bufferization.materialize_in_destination %0 in restrict writable %C | |
| : (tensor<1x17x29xf32>, memref<1x17x29xf32>) -> () | |
| return | |
| } | |
| } | |
| transform.sequence failures(propagate) { | |
| ^bb0(%module1: !transform.any_op): | |
| // Convert TOSA to Linalg | |
| %func1 = transform.structured.match ops{["func.func"]} in %module1 | |
| : (!transform.any_op) -> !transform.any_op | |
| %func2 = transform.apply_registered_pass "tosa-to-linalg-named" to %func1 | |
| : (!transform.any_op) -> !transform.any_op | |
| // Eliminate empty tensors | |
| transform.bufferization.eliminate_empty_tensors %func2 : !transform.any_op | |
| // Bufferize | |
| // %module2 = transform.bufferization.one_shot_bufferize %module1 | |
| // : (!transform.any_op) -> !transform.any_op | |
| // Canonicalize + CSE | |
| // transform.apply_patterns to %module2 { | |
| // transform.apply_patterns.canonicalization | |
| // } {apply_cse} : !transform.any_op | |
| // Deallocate buffers. That's a no-op in this example because no temporary | |
| // buffers are allocated. | |
| // %module3 = transform.apply_registered_pass | |
| // "buffer-deallocation-pipeline" to %module2 | |
| // : (!transform.any_op) -> !transform.any_op | |
| } |
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