import paddle.v2.framework.core as core import unittest import numpy import paddle.v2.framework.create_op_creation_methods as creation 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): func = getattr(creation.op_creations, self.type, None) self.assertIsNotNone(func) scope = core.Scope(None) kwargs = dict() for in_name in func.all_input_args: if hasattr(self, in_name): kwargs[in_name] = in_name var = scope.create_var(in_name).get_tensor() arr = getattr(self, in_name) var.set_dims(arr.shape) var.set(arr) else: kwargs[in_name] = "@EMPTY@" for out_name in func.all_output_args: if hasattr(self, out_name): kwargs[out_name] = out_name scope.create_var(out_name).get_tensor() for attr_name in func.all_attr_args: if hasattr(self, attr_name): kwargs[attr_name] = getattr(self, attr_name) op = func(**kwargs) op.infer_shape(scope) ctx = core.DeviceContext.cpu_context() op.run(scope, ctx) for out_name in func.all_output_args: actual = numpy.array(scope.get_var(out_name).get_tensor()) expect = getattr(self, out_name) numpy.testing.assert_almost_equal(actual, expect) obj.test_all = test_all return obj