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- # 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.
-
- import unittest
-
- from paddle.base import core
- from paddle.base.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(
- str(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(
- str(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),
- {
- "x_num_col_dims",
- "y_num_col_dims",
- "op_role",
- "op_role_var",
- "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()
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