| # RUN: %PYTHON %s 2>&1 | FileCheck %s |
| |
| import ctypes |
| import sys |
| from mlir.ir import * |
| from mlir.dialects import builtin |
| from mlir.dialects import linalg |
| from mlir.dialects import std |
| from mlir.passmanager import * |
| from mlir.execution_engine import * |
| |
| |
| # Log everything to stderr and flush so that we have a unified stream to match |
| # errors/info emitted by MLIR to stderr. |
| def log(*args): |
| print(*args, file=sys.stderr) |
| sys.stderr.flush() |
| |
| |
| matmul_boiler = """ |
| func @main() -> f32 attributes {llvm.emit_c_interface} { |
| %v0 = arith.constant 0.0 : f32 |
| %v1 = arith.constant 1.0 : f32 |
| %v2 = arith.constant 2.0 : f32 |
| |
| %A = memref.alloc() : memref<4x16xf32> |
| %B = memref.alloc() : memref<16x8xf32> |
| %C = memref.alloc() : memref<4x8xf32> |
| linalg.fill(%v1, %A) : f32, memref<4x16xf32> |
| linalg.fill(%v2, %B) : f32, memref<16x8xf32> |
| linalg.fill(%v0, %C) : f32, memref<4x8xf32> |
| |
| call @matmul_on_buffers(%A, %B, %C) : |
| (memref<4x16xf32>, memref<16x8xf32>, memref<4x8xf32>) -> () |
| |
| %c0 = arith.constant 0 : index |
| %0 = memref.load %C[%c0, %c0] : memref<4x8xf32> |
| |
| // TODO: FFI-based solution to allow testing and printing with python code. |
| return %0 : f32 |
| } |
| """ |
| |
| fill_boiler = """ |
| func @main() -> i32 attributes {llvm.emit_c_interface} { |
| %O = memref.alloc() : memref<4x16xi32> |
| %min = arith.constant -1000.0 : f64 |
| %max = arith.constant 1000.0 : f64 |
| %seed = arith.constant 42 : i32 |
| |
| call @fill_on_buffers(%min, %max, %seed, %O) : |
| (f64, f64, i32, memref<4x16xi32>) -> () |
| |
| %c0 = arith.constant 0 : index |
| %0 = memref.load %O[%c0, %c0] : memref<4x16xi32> |
| |
| // TODO: FFI-based solution to allow testing and printing with python code. |
| return %0 : i32 |
| } |
| """ |
| |
| conv_boiler = """ |
| func @main() -> i32 attributes {llvm.emit_c_interface} { |
| %v0 = arith.constant 0 : i32 |
| %v1 = arith.constant 1.0 : f64 |
| %v2 = arith.constant 2.0 : f64 |
| |
| %input = memref.alloc() : memref<1x4x16x1xf64> |
| %filter = memref.alloc() : memref<2x2x1xf64> |
| %output = memref.alloc() : memref<1x2x4x1xi32> |
| linalg.fill(%v1, %input) : f64, memref<1x4x16x1xf64> |
| linalg.fill(%v2, %filter) : f64, memref<2x2x1xf64> |
| linalg.fill(%v0, %output) : i32, memref<1x2x4x1xi32> |
| |
| call @conv_on_buffers(%input, %filter, %output) : |
| (memref<1x4x16x1xf64>, memref<2x2x1xf64>, memref<1x2x4x1xi32>) -> () |
| |
| %c0 = arith.constant 0 : index |
| %0 = memref.load %output[%c0, %c0, %c0, %c0] : memref<1x2x4x1xi32> |
| |
| // TODO: FFI-based solution to allow testing and printing with python code. |
| return %0 : i32 |
| } |
| """ |
| |
| pooling_boiler = """ |
| func @main() -> i32 attributes {llvm.emit_c_interface} { |
| %v0 = arith.constant 0 : i32 |
| %v42 = arith.constant 42.0 : f64 |
| %v77 = arith.constant 77.0 : f64 |
| %v-13 = arith.constant -13.0 : f64 |
| %v1 = arith.constant 1.0 : f64 |
| |
| %input = memref.alloc() : memref<1x4x16x1xf64> |
| %shape = memref.alloc() : memref<2x2xf64> |
| %output = memref.alloc() : memref<1x2x4x1xi32> |
| linalg.fill(%v1, %input) : f64, memref<1x4x16x1xf64> |
| linalg.fill(%v1, %shape) : f64, memref<2x2xf64> |
| linalg.fill(%v0, %output) : i32, memref<1x2x4x1xi32> |
| |
| %c0 = arith.constant 0 : index |
| %c1 = arith.constant 1 : index |
| %c2 = arith.constant 2 : index |
| memref.store %v42, %input[%c0, %c0, %c0, %c0] : memref<1x4x16x1xf64> |
| memref.store %v77, %input[%c0, %c0, %c1, %c0] : memref<1x4x16x1xf64> |
| memref.store %v-13, %input[%c0, %c0, %c2, %c0] : memref<1x4x16x1xf64> |
| |
| call @pooling_on_buffers(%input, %shape, %output) : |
| (memref<1x4x16x1xf64>, memref<2x2xf64>, memref<1x2x4x1xi32>) -> () |
| |
| %0 = memref.load %output[%c0, %c0, %c0, %c0] : memref<1x2x4x1xi32> |
| |
| // TODO: FFI-based solution to allow testing and printing with python code. |
| return %0 : i32 |
| } |
| """ |
| |
| |
| def transform(module, boilerplate): |
| import mlir.conversions |
| import mlir.all_passes_registration |
| import mlir.transforms |
| |
| # TODO: Allow cloning functions from one module to another. |
| # Atm we have to resort to string concatenation. |
| mod = Module.parse( |
| str(module.operation.regions[0].blocks[0].operations[0].operation) + |
| boilerplate) |
| pm = PassManager.parse( |
| "builtin.func(convert-linalg-to-loops, lower-affine, " + |
| "convert-scf-to-std, arith-expand, std-expand), convert-vector-to-llvm," + |
| "convert-memref-to-llvm, convert-std-to-llvm," + |
| "reconcile-unrealized-casts") |
| pm.run(mod) |
| return mod |
| |
| |
| def test_matmul_builtin(): |
| with Context() as ctx, Location.unknown(): |
| module = Module.create() |
| f32 = F32Type.get() |
| with InsertionPoint(module.body): |
| |
| @builtin.FuncOp.from_py_func( |
| MemRefType.get((4, 16), f32), MemRefType.get((16, 8), f32), |
| MemRefType.get((4, 8), f32)) |
| def matmul_on_buffers(lhs, rhs, out): |
| linalg.matmul(lhs, rhs, outs=[out]) |
| |
| execution_engine = ExecutionEngine(transform(module, matmul_boiler)) |
| |
| # TODO: FFI-based solution to allow testing and printing with python code. |
| # Prepare arguments: one result f32. |
| # Arguments must be passed as pointers. |
| c_float_p = ctypes.c_float * 1 |
| res = c_float_p(-1.) |
| execution_engine.invoke("main", res) |
| |
| log("RESULT: ", res[0]) |
| # CHECK: RESULT: 32.0 |
| |
| |
| test_matmul_builtin() |
| |
| |
| def test_matmul_generic(): |
| with Context() as ctx, Location.unknown(): |
| module = Module.create() |
| f32 = F32Type.get() |
| with InsertionPoint(module.body): |
| |
| @builtin.FuncOp.from_py_func( |
| MemRefType.get((4, 16), f32), MemRefType.get((16, 8), f32), |
| MemRefType.get((4, 8), f32)) |
| def matmul_on_buffers(lhs, rhs, out): |
| linalg.matmul(lhs, rhs, outs=[out], emit_generic=True) |
| |
| execution_engine = ExecutionEngine(transform(module, matmul_boiler)) |
| |
| # TODO: FFI-based solution to allow testing and printing with python code. |
| # Prepare arguments: one result f32. |
| # Arguments must be passed as pointers. |
| c_float_p = ctypes.c_float * 1 |
| res = c_float_p(-1.) |
| execution_engine.invoke("main", res) |
| |
| log("RESULT: ", res[0]) |
| # CHECK: RESULT: 32.0 |
| |
| |
| test_matmul_generic() |
| |
| |
| def test_fill_builtin(): |
| with Context() as ctx, Location.unknown(): |
| module = Module.create() |
| f64 = F64Type.get() |
| i32 = IntegerType.get_signless(32) |
| with InsertionPoint(module.body): |
| |
| @builtin.FuncOp.from_py_func(f64, f64, i32, MemRefType.get((4, 16), i32)) |
| def fill_on_buffers(min, max, seed, out): |
| linalg.fill_rng_2d(min, max, seed, outs=[out]) |
| |
| execution_engine = ExecutionEngine(transform(module, fill_boiler)) |
| |
| # TODO: FFI-based solution to allow testing and printing with python code. |
| # Prepare arguments: one result i32. |
| # Arguments must be passed as pointers. |
| c_int_p = ctypes.c_int * 1 |
| res = c_int_p(-1) |
| execution_engine.invoke("main", res) |
| |
| log("RESULT: ", res[0]) |
| # CHECK: RESULT: -480 |
| |
| |
| test_fill_builtin() |
| |
| |
| def test_fill_generic(): |
| with Context() as ctx, Location.unknown(): |
| module = Module.create() |
| f64 = F64Type.get() |
| i32 = IntegerType.get_signless(32) |
| with InsertionPoint(module.body): |
| |
| @builtin.FuncOp.from_py_func(f64, f64, i32, MemRefType.get((4, 16), i32)) |
| def fill_on_buffers(min, max, seed, out): |
| linalg.fill_rng_2d(min, max, seed, outs=[out], emit_generic=True) |
| |
| execution_engine = ExecutionEngine(transform(module, fill_boiler)) |
| |
| # TODO: FFI-based solution to allow testing and printing with python code. |
| # Prepare arguments: one result i32. |
| # Arguments must be passed as pointers. |
| c_int_p = ctypes.c_int * 1 |
| res = c_int_p(-1) |
| execution_engine.invoke("main", res) |
| |
| log("RESULT: ", res[0]) |
| # CHECK: RESULT: -480 |
| |
| |
| test_fill_generic() |
| |
| |
| def test_max_pooling_builtin(): |
| with Context() as ctx, Location.unknown(): |
| module = Module.create() |
| f64 = F64Type.get() |
| i32 = IntegerType.get_signless(32) |
| with InsertionPoint(module.body): |
| |
| @builtin.FuncOp.from_py_func( |
| MemRefType.get((1, 4, 16, 1), f64), MemRefType.get((2, 2), f64), |
| MemRefType.get((1, 2, 4, 1), i32)) |
| def pooling_on_buffers(input, shape, output): |
| linalg.pooling_nhwc_max( |
| input, shape, outs=[output], strides=[2, 4], dilations=[1, 2]) |
| |
| execution_engine = ExecutionEngine(transform(module, pooling_boiler)) |
| |
| # TODO: FFI-based solution to allow testing and printing with python code. |
| # Prepare arguments: one result i32. |
| # Arguments must be passed as pointers. |
| c_int_p = ctypes.c_int * 1 |
| res = c_int_p(-1) |
| execution_engine.invoke("main", res) |
| |
| log("RESULT: ", res[0]) |
| # 77 is not selected due to the dilation 2 in the second dimension. |
| # CHECK: RESULT: 42 |
| |
| |
| test_max_pooling_builtin() |
| |
| |
| def test_max_pooling_generic(): |
| with Context() as ctx, Location.unknown(): |
| module = Module.create() |
| f64 = F64Type.get() |
| i32 = IntegerType.get_signless(32) |
| with InsertionPoint(module.body): |
| |
| @builtin.FuncOp.from_py_func( |
| MemRefType.get((1, 4, 16, 1), f64), MemRefType.get((2, 2), f64), |
| MemRefType.get((1, 2, 4, 1), i32)) |
| def pooling_on_buffers(input, shape, output): |
| linalg.pooling_nhwc_max( |
| input, |
| shape, |
| outs=[output], |
| strides=[2, 4], |
| dilations=[1, 2], |
| emit_generic=True) |
| |
| execution_engine = ExecutionEngine(transform(module, pooling_boiler)) |
| |
| # TODO: FFI-based solution to allow testing and printing with python code. |
| # Prepare arguments: one result i32. |
| # Arguments must be passed as pointers. |
| c_int_p = ctypes.c_int * 1 |
| res = c_int_p(-1) |
| execution_engine.invoke("main", res) |
| |
| log("RESULT: ", res[0]) |
| # 77 is not selected due to the dilation 2 in the second dimension. |
| # CHECK: RESULT: 42 |
| |
| |
| test_max_pooling_generic() |
| |
| |
| def test_min_pooling_builtin(): |
| with Context() as ctx, Location.unknown(): |
| module = Module.create() |
| f64 = F64Type.get() |
| i32 = IntegerType.get_signless(32) |
| with InsertionPoint(module.body): |
| |
| @builtin.FuncOp.from_py_func( |
| MemRefType.get((1, 4, 16, 1), f64), MemRefType.get((2, 2), f64), |
| MemRefType.get((1, 2, 4, 1), i32)) |
| def pooling_on_buffers(input, shape, output): |
| linalg.pooling_nhwc_min( |
| input, shape, outs=[output], strides=[2, 4], dilations=[1, 2]) |
| |
| execution_engine = ExecutionEngine(transform(module, pooling_boiler)) |
| |
| # TODO: FFI-based solution to allow testing and printing with python code. |
| # Prepare arguments: one result i32. |
| # Arguments must be passed as pointers. |
| c_int_p = ctypes.c_int * 1 |
| res = c_int_p(-1) |
| execution_engine.invoke("main", res) |
| |
| log("RESULT: ", res[0]) |
| # CHECK: RESULT: -13 |
| |
| |
| test_min_pooling_builtin() |
| |
| |
| def test_min_pooling_generic(): |
| with Context() as ctx, Location.unknown(): |
| module = Module.create() |
| f64 = F64Type.get() |
| i32 = IntegerType.get_signless(32) |
| with InsertionPoint(module.body): |
| |
| @builtin.FuncOp.from_py_func( |
| MemRefType.get((1, 4, 16, 1), f64), MemRefType.get((2, 2), f64), |
| MemRefType.get((1, 2, 4, 1), i32)) |
| def pooling_on_buffers(input, shape, output): |
| linalg.pooling_nhwc_min( |
| input, |
| shape, |
| outs=[output], |
| strides=[2, 4], |
| dilations=[1, 2], |
| emit_generic=True) |
| |
| execution_engine = ExecutionEngine(transform(module, pooling_boiler)) |
| |
| # TODO: FFI-based solution to allow testing and printing with python code. |
| # Prepare arguments: one result i32. |
| # Arguments must be passed as pointers. |
| c_int_p = ctypes.c_int * 1 |
| res = c_int_p(-1) |
| execution_engine.invoke("main", res) |
| |
| log("RESULT: ", res[0]) |
| # CHECK: RESULT: -13 |
| |
| |
| test_min_pooling_generic() |