test_operator_desc.py

#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from __future__ import print_function

import unittest

import paddle.fluid.core as core
import paddle.compat as cpt

from paddle.fluid.framework import Program, default_startup_program

main_program = default_startup_program()


class TestOperator(unittest.TestCase):

    def test_error_type(self):
        block = main_program._create_block()
        try:
            block.append_op()
            self.assertFail()
        except ValueError as v_err:
            self.assertEqual(
                cpt.get_exception_message(v_err),
                "`type` to initialized an Operator can not be None.")
        try:
            block.append_op(type="no_such_op")
            self.assertFail()
        except ValueError as a_err:
            self.assertEqual(
                cpt.get_exception_message(a_err),
                "Operator \"no_such_op\" has not been registered.")

    def test_op_desc_creation(self):
        program = Program()
        block = program.current_block()
        mul_x = block.create_var(dtype="float32",
                                 shape=[5, 10],
                                 lod_level=0,
                                 name="mul.x")
        mul_y = block.create_var(dtype="float32",
                                 shape=[10, 8],
                                 lod_level=0,
                                 name="mul.y")
        mul_out = block.create_var(dtype="float32",
                                   shape=[5, 8],
                                   lod_level=0,
                                   name="mul.out")
        mul_op = block.append_op(type="mul",
                                 inputs={
                                     "X": [mul_x],
                                     "Y": mul_y
                                 },
                                 outputs={"Out": [mul_out]},
                                 attrs={"x_num_col_dims": 1})

        self.assertNotEqual(str(mul_op), "")
        self.assertEqual(mul_op.type, "mul")
        self.assertEqual(mul_op.input_names, ["X", "Y"])
        self.assertEqual(mul_op.input("X"), ["mul.x"])
        self.assertEqual(mul_op.input("Y"), ["mul.y"])
        self.assertEqual(mul_op.output_names, ["Out"])
        self.assertEqual(mul_op.output("Out"), ["mul.out"])
        self.assertEqual(
            set(mul_op.attr_names),
            set([
                "x_num_col_dims", "y_num_col_dims", "op_role", "op_role_var",
                "use_mkldnn", "scale_x", "scale_y", "scale_out",
                "force_fp32_output", "op_namescope", "op_callstack",
                "op_device", "with_quant_attr"
            ]))
        self.assertEqual(mul_op.has_attr("x_num_col_dims"), True)
        self.assertEqual(mul_op.attr_type("x_num_col_dims"), core.AttrType.INT)
        self.assertEqual(mul_op.attr("x_num_col_dims"), 1)
        self.assertEqual(mul_op.has_attr("y_num_col_dims"), True)
        self.assertEqual(mul_op.attr_type("y_num_col_dims"), core.AttrType.INT)
        self.assertEqual(mul_op.attr("y_num_col_dims"), 1)
        self.assertEqual(mul_op.idx, 0)
        self.assertEqual(mul_out.op, mul_op)
        mul_op.desc.remove_input("X")
        self.assertEqual(mul_op.input_names, ["Y"])

    def test_mult_input(self):
        program = Program()
        block = program.current_block()
        sum_x1 = block.create_var(dtype="int",
                                  shape=[3, 4],
                                  lod_level=0,
                                  name="sum.x1")
        sum_x2 = block.create_var(dtype="int",
                                  shape=[3, 4],
                                  lod_level=0,
                                  name="sum.x2")
        sum_x3 = block.create_var(dtype="int",
                                  shape=[3, 4],
                                  lod_level=0,
                                  name="sum.x3")
        sum_out = block.create_var(dtype="int",
                                   shape=[3, 4],
                                   lod_level=0,
                                   name="sum.out")
        sum_op = block.append_op(type="sum",
                                 inputs={"X": [sum_x1, sum_x2, sum_x3]},
                                 outputs={"Out": sum_out})
        self.assertEqual(sum_op.type, "sum")
        self.assertEqual(sum_op.input_names, ["X"])
        self.assertEqual(sum_op.input("X"), ["sum.x1", "sum.x2", "sum.x3"])
        self.assertEqual(sum_op.output_names, ["Out"])
        self.assertEqual(sum_op.output("Out"), ["sum.out"])
        self.assertEqual(sum_op.idx, 0)
        self.assertEqual(sum_out.op, sum_op)


if __name__ == '__main__':
    unittest.main()