# RUN: %PYTHON %s 2>&1 | FileCheck %s import ctypes import sys from mlir.ir import * from mlir.dialects import builtin from mlir.dialects import func from mlir.dialects import linalg from mlir.passmanager import * from mlir.execution_engine import * from mlir.dialects.linalg.opdsl.lang 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() elemwise_boiler = """ func.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 %lhs = memref.alloc() : memref %rhs = memref.alloc() : memref<4x8xf32> %O0 = memref.alloc() : memref<4x8xf32> %O1 = memref.alloc() : memref<4x8xf32> linalg.fill ins(%v1 : f32) outs(%lhs : memref) linalg.fill ins(%v2 : f32) outs(%rhs : memref<4x8xf32>) linalg.fill ins(%v0 : f32) outs(%O0 : memref<4x8xf32>) linalg.fill ins(%v0 : f32) outs(%O1 : memref<4x8xf32>) call @elemwise_exp_add_on_buffers(%lhs, %rhs, %O0) : (memref, memref<4x8xf32>, memref<4x8xf32>) -> () call @elemwise_log_mul_on_buffers(%lhs, %rhs, %O1) : (memref, memref<4x8xf32>, memref<4x8xf32>) -> () %c0 = arith.constant 0 : index %res0 = memref.load %O0[%c0, %c0] : memref<4x8xf32> %res1 = memref.load %O1[%c0, %c0] : memref<4x8xf32> %0 = arith.addf %res0, %res1 : f32 // TODO: FFI-based solution to allow testing and printing with python code. return %0 : f32 } """ matmul_boiler = """ func.func @main() -> f32 attributes {llvm.emit_c_interface} { %v0 = arith.constant 0.0 : f32 %v1 = arith.constant -1 : i8 %v2 = arith.constant 2.0 : f32 %A = memref.alloc() : memref<4x16xi8> %B = memref.alloc() : memref<16x8xf32> %C0 = memref.alloc() : memref<4x8xf32> %C1 = memref.alloc() : memref<4x8xf32> linalg.fill ins(%v1 : i8) outs(%A : memref<4x16xi8>) linalg.fill ins(%v2 : f32) outs(%B : memref<16x8xf32>) linalg.fill ins(%v0 : f32) outs(%C0 : memref<4x8xf32>) linalg.fill ins(%v0 : f32) outs(%C1 : memref<4x8xf32>) call @matmul_signed_on_buffers(%A, %B, %C0) : (memref<4x16xi8>, memref<16x8xf32>, memref<4x8xf32>) -> () call @matmul_unsigned_on_buffers(%A, %B, %C1) : (memref<4x16xi8>, memref<16x8xf32>, memref<4x8xf32>) -> () %c0 = arith.constant 0 : index %res0 = memref.load %C0[%c0, %c0] : memref<4x8xf32> %res1 = memref.load %C1[%c0, %c0] : memref<4x8xf32> %0 = arith.addf %res0, %res1 : f32 // TODO: FFI-based solution to allow testing and printing with python code. return %0 : f32 } """ fill_boiler = """ func.func @main() -> i32 attributes {llvm.emit_c_interface} { %O0 = memref.alloc() : memref %O1 = memref.alloc() : memref<16xi32> %O2 = memref.alloc() : memref<4x16xi32> %val0 = arith.constant 1.0 : f32 %val1 = arith.constant 2.0 : f32 %val2 = arith.constant 3.0 : f32 call @fill_0d_on_buffers(%val0, %O0) : (f32, memref) -> () call @fill_1d_on_buffers(%val1, %O1) : (f32, memref<16xi32>) -> () call @fill_2d_on_buffers(%val2, %O2) : (f32, memref<4x16xi32>) -> () %c0 = arith.constant 0 : index %res0 = memref.load %O0[] : memref %c8 = arith.constant 8 : index %res1 = memref.load %O1[%c8] : memref<16xi32> %c2 = arith.constant 2 : index %res2 = memref.load %O2[%c2, %c8] : memref<4x16xi32> %0 = arith.addi %res0, %res1 : i32 %1 = arith.addi %0, %res2 : i32 // TODO: FFI-based solution to allow testing and printing with python code. return %1 : i32 } """ fill_rng_boiler = """ func.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_rng_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.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 ins(%v1 : f64) outs(%input : memref<1x4x16x1xf64>) linalg.fill ins(%v2 : f64) outs(%filter : memref<2x2x1xf64>) linalg.fill ins(%v0 : i32) outs(%output : 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.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 ins(%v1 : f64) outs(%input : memref<1x4x16x1xf64>) linalg.fill ins(%v1 : f64) outs(%shape : memref<2x2xf64>) linalg.fill ins(%v0 : i32) outs(%output : 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, %c1, %c0, %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. ops = module.operation.regions[0].blocks[0].operations mod = Module.parse("\n".join([str(op) for op in ops]) + boilerplate) pm = PassManager.parse( "func.func(convert-linalg-to-loops, lower-affine, " + "convert-math-to-llvm, convert-scf-to-cf, arith-expand, memref-expand), " + "convert-vector-to-llvm, convert-memref-to-llvm, convert-func-to-llvm," + "reconcile-unrealized-casts") pm.run(mod) return mod def test_elemwise_builtin(): with Context() as ctx, Location.unknown(): module = Module.create() f32 = F32Type.get() i8 = IntegerType.get_signless(8) with InsertionPoint(module.body): @func.FuncOp.from_py_func( MemRefType.get((), f32), MemRefType.get((4, 8), f32), MemRefType.get((4, 8), f32)) def elemwise_exp_add_on_buffers(lhs, rhs, out): linalg.elemwise_unary(lhs, outs=[out]) linalg.elemwise_binary(out, rhs, outs=[out]) @func.FuncOp.from_py_func( MemRefType.get((), f32), MemRefType.get((4, 8), f32), MemRefType.get((4, 8), f32)) def elemwise_log_mul_on_buffers(lhs, rhs, out): linalg.elemwise_unary(lhs, outs=[out], fun=UnaryFn.log) linalg.elemwise_binary(out, rhs, outs=[out], fun=BinaryFn.mul) execution_engine = ExecutionEngine(transform(module, elemwise_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]) # elemwise_exp_add_on_buffers: exp(1.0) + 2.0 = 4.71828182846 # elemwise_log_mul_on_buffers: log(1.0) * 2.0 = 0.0 # CHECK: RESULT: 4.71828 test_elemwise_builtin() def test_elemwise_generic(): with Context() as ctx, Location.unknown(): module = Module.create() f32 = F32Type.get() i8 = IntegerType.get_signless(8) with InsertionPoint(module.body): @func.FuncOp.from_py_func( MemRefType.get((), f32), MemRefType.get((4, 8), f32), MemRefType.get((4, 8), f32)) def elemwise_exp_add_on_buffers(lhs, rhs, out): linalg.elemwise_unary(lhs, outs=[out], emit_generic=True) linalg.elemwise_binary(out, rhs, outs=[out], emit_generic=True) @func.FuncOp.from_py_func( MemRefType.get((), f32), MemRefType.get((4, 8), f32), MemRefType.get((4, 8), f32)) def elemwise_log_mul_on_buffers(lhs, rhs, out): linalg.elemwise_unary( lhs, outs=[out], fun=UnaryFn.log, emit_generic=True) linalg.elemwise_binary( out, rhs, outs=[out], fun=BinaryFn.mul, emit_generic=True) execution_engine = ExecutionEngine(transform(module, elemwise_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]) # elemwise_exp_add_on_buffers: exp(1.0) + 2.0 = 4.71828182846 # elemwise_log_mul_on_buffers: log(1.0) * 2.0 = 0.0 # CHECK: RESULT: 4.71828 test_elemwise_generic() def test_matmul_builtin(): with Context() as ctx, Location.unknown(): module = Module.create() f32 = F32Type.get() i8 = IntegerType.get_signless(8) with InsertionPoint(module.body): @func.FuncOp.from_py_func( MemRefType.get((4, 16), i8), MemRefType.get((16, 8), f32), MemRefType.get((4, 8), f32)) def matmul_signed_on_buffers(lhs, rhs, out): linalg.matmul(lhs, rhs, outs=[out]) @func.FuncOp.from_py_func( MemRefType.get((4, 16), i8), MemRefType.get((16, 8), f32), MemRefType.get((4, 8), f32)) def matmul_unsigned_on_buffers(lhs, rhs, out): linalg.matmul(lhs, rhs, outs=[out], cast=TypeFn.cast_unsigned) 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]) # matmul_signed_on_buffers: -1 * 2.0 * 16 = -32 # matmul_unsigned_on_buffers: (2^8-1) * 2.0 * 16 = 8160 # CHECK: RESULT: 8128 test_matmul_builtin() def test_matmul_generic(): with Context() as ctx, Location.unknown(): module = Module.create() f32 = F32Type.get() i8 = IntegerType.get_signless(8) with InsertionPoint(module.body): @func.FuncOp.from_py_func( MemRefType.get((4, 16), i8), MemRefType.get((16, 8), f32), MemRefType.get((4, 8), f32)) def matmul_signed_on_buffers(lhs, rhs, out): linalg.matmul(lhs, rhs, outs=[out], emit_generic=True) @func.FuncOp.from_py_func( MemRefType.get((4, 16), i8), MemRefType.get((16, 8), f32), MemRefType.get((4, 8), f32)) def matmul_unsigned_on_buffers(lhs, rhs, out): linalg.matmul( lhs, rhs, outs=[out], cast=TypeFn.cast_unsigned, 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]) # matmul_signed_on_buffers = -1 * 2.0 * 16 = -32 # matmul_unsigned_on_buffers = (2^8-1) * 2.0 * 16 = 8160 # CHECK: RESULT: 8128 test_matmul_generic() def test_fill_builtin(): with Context() as ctx, Location.unknown(): module = Module.create() f32 = F32Type.get() i32 = IntegerType.get_signless(32) with InsertionPoint(module.body): @func.FuncOp.from_py_func(f32, MemRefType.get([], i32)) def fill_0d_on_buffers(value, out): linalg.fill(value, outs=[out]) @func.FuncOp.from_py_func(f32, MemRefType.get([16], i32)) def fill_1d_on_buffers(value, out): linalg.fill(value, outs=[out]) @func.FuncOp.from_py_func(f32, MemRefType.get([4, 16], i32)) def fill_2d_on_buffers(value, out): linalg.fill(value, 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: 6 test_fill_builtin() def test_fill_generic(): with Context() as ctx, Location.unknown(): module = Module.create() f32 = F32Type.get() i32 = IntegerType.get_signless(32) with InsertionPoint(module.body): @func.FuncOp.from_py_func(f32, MemRefType.get([], i32)) def fill_0d_on_buffers(value, out): linalg.fill(value, outs=[out], emit_generic=True) @func.FuncOp.from_py_func(f32, MemRefType.get([16], i32)) def fill_1d_on_buffers(value, out): linalg.fill(value, outs=[out], emit_generic=True) @func.FuncOp.from_py_func(f32, MemRefType.get([4, 16], i32)) def fill_2d_on_buffers(value, out): linalg.fill(value, 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: 6 test_fill_generic() def test_fill_rng_builtin(): with Context() as ctx, Location.unknown(): module = Module.create() f64 = F64Type.get() i32 = IntegerType.get_signless(32) with InsertionPoint(module.body): @func.FuncOp.from_py_func(f64, f64, i32, MemRefType.get((4, 16), i32)) def fill_rng_on_buffers(min, max, seed, out): linalg.fill_rng_2d(min, max, seed, outs=[out]) execution_engine = ExecutionEngine(transform(module, fill_rng_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_rng_builtin() def test_fill_rng_generic(): with Context() as ctx, Location.unknown(): module = Module.create() f64 = F64Type.get() i32 = IntegerType.get_signless(32) with InsertionPoint(module.body): @func.FuncOp.from_py_func(f64, f64, i32, MemRefType.get((4, 16), i32)) def fill_rng_on_buffers(min, max, seed, out): linalg.fill_rng_2d(min, max, seed, outs=[out], emit_generic=True) execution_engine = ExecutionEngine(transform(module, fill_rng_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_rng_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): @func.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): @func.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): @func.FuncOp.from_py_func( MemRefType.get((1, 4, 16, 1), f64), MemRefType.get((2, 2), f64), MemRefType.get((1, 2, 4, 1), i32)) # Set the strides and use the default dilations. def pooling_on_buffers(input, shape, output): linalg.pooling_nhwc_min(input, shape, outs=[output], strides=[2, 4]) 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): @func.FuncOp.from_py_func( MemRefType.get((1, 4, 16, 1), f64), MemRefType.get((2, 2), f64), MemRefType.get((1, 2, 4, 1), i32)) # Set the strides and use the default dilations. def pooling_on_buffers(input, shape, output): linalg.pooling_nhwc_min( input, shape, outs=[output], strides=[2, 4], 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()