remove op_test_util.py

python/paddle/v2/framework/tests/op_test_util.py

-import numpy
-import paddle.v2.framework.core as core
-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)
-                if isinstance(place, core.GPUPlace) and not op.support_gpu():
-                    return
-
-                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]
-                    print "actual: %s" % actual
-                    print "expect: %s" % expect
-                    self.assertTrue(
-                        numpy.allclose(
-                            actual, expect, atol=1e-05),
-                        "output name: " + out_name + " has diff")
-
-        obj.test_all = test_all
-        return obj