# RUN: %PYTHON %s | FileCheck %s --dump-input=fail # Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. # See https://llvm.org/LICENSE.txt for license information. # SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception import os os.environ["NUMPY_EXPERIMENTAL_ARRAY_FUNCTION"] = "1" from npcomp.types import * from npcomp.exporter import * from npcomp.tracing.mlir_trace import * def simple_mul(a: np.ndarray, b: np.ndarray) -> np.ndarray: return a * b + a + b # TODO: Implement subclassing and deriving constraints by run exp = Exporter() exp.simple_mul = simple_mul exp.simple_mul.sig.args["a"] += Shape(1, 4) exp.simple_mul.sig.args["a"] += DynamicDim(0) exp.simple_mul.sig.args["a"] += DType(np.float32) exp.simple_mul.sig.args["b"] += Shape(1) exp.simple_mul.sig.args["b"] += DType(np.float32) exp.simple_mul.sig.result += Shape(1, 4) exp.simple_mul.sig.result += DynamicDim(0) exp.simple_mul.sig.result += DType(np.float32) mb = ModuleBuilder() mb.trace(exp.simple_mul) # CHECK: func @simple_mul(%arg0: tensor, %arg1: tensor<1xf32>) -> tensor { # CHECK: %0 = numpy.builtin_ufunc_call<"numpy.multiply"> (%arg0, %arg1) : (tensor, tensor<1xf32>) -> tensor<*x!basicpy.UnknownType> # CHECK: %1 = numpy.builtin_ufunc_call<"numpy.add"> (%0, %arg0) : (tensor<*x!basicpy.UnknownType>, tensor) -> tensor<*x!basicpy.UnknownType> # CHECK: %2 = numpy.builtin_ufunc_call<"numpy.add"> (%1, %arg1) : (tensor<*x!basicpy.UnknownType>, tensor<1xf32>) -> tensor<*x!basicpy.UnknownType> # CHECK: %3 = numpy.narrow %2 : (tensor<*x!basicpy.UnknownType>) -> tensor # CHECK: return %3 : tensor # CHECK: } print(mb.module.to_asm())