import paddle.v2.framework.core as core import unittest import numpy from paddle.v2.framework.op import Operator class OpTestMeta(type): """ Operator Test ClassMeta. It injects `test_all` method into user's OperatorTest class, to make Python unittest module run that method. The `test_all` read what value is stored in `self`. It use self's values to create and run a operator, and check whether that op is OK or not. See `test_add_two_op` for example usage. """ def __new__(cls, name, bases, attrs): obj = super(OpTestMeta, cls).__new__(cls, name, bases, attrs) def test_all(self): scope = core.Scope() kwargs = dict() places = [core.CPUPlace()] if core.is_compile_gpu(): places.append(core.GPUPlace(0)) for place in places: for in_name in Operator.get_op_input_names(self.type): if hasattr(self, "inputs") and in_name in self.inputs kwargs[in_name] = in_name var = scope.new_var(in_name).get_tensor() arr = self.inputs[in_name] var.set_dims(arr.shape) var.set(arr, place) else: kwargs[in_name] = "@EMPTY@" for out_name in Operator.get_op_output_names(self.type): if not hasattr(self, "outputs"): raise ValueError( "The test op must set self.outputs dict.") if out_name not in self.outputs: raise ValueError("The %s is not in self.outputs dict." % (out_name)) kwargs[out_name] = out_name scope.new_var(out_name).get_tensor() for attr_name in Operator.get_op_attr_names(self.type): if hasattr(self, "attrs") and attr_name in self.attrs: kwargs[attr_name] = self.attrs[attr_name] op = Operator(self.type, **kwargs) op.infer_shape(scope) ctx = core.DeviceContext.create(place) op.run(scope, ctx) for out_name in Operator.get_op_output_names(self.type): actual = numpy.array(scope.find_var(out_name).get_tensor()) expect = self.outputs[out_name] numpy.isclose(actual, expect) obj.test_all = test_all return obj