wehub-resource-sync
110 lines
4.1 KiB
Python
110 lines
4.1 KiB
Python
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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from paddle.base import core
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from paddle.base.framework import Program, default_startup_program
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main_program = default_startup_program()
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class TestOperator(unittest.TestCase):
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def test_error_type(self):
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block = main_program._create_block()
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try:
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block.append_op()
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self.assertFail()
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except ValueError as v_err:
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self.assertEqual(
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str(v_err), "`type` to initialized an Operator can not be None."
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)
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try:
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block.append_op(type="no_such_op")
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self.assertFail()
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except ValueError as a_err:
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self.assertEqual(
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str(a_err), 'Operator "no_such_op" has not been registered.'
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)
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def test_op_desc_creation(self):
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program = Program()
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block = program.current_block()
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mul_x = block.create_var(dtype="float32", shape=[5, 10], name="mul.x")
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mul_y = block.create_var(dtype="float32", shape=[10, 8], name="mul.y")
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mul_out = block.create_var(
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dtype="float32", shape=[5, 8], name="mul.out"
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)
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mul_op = block.append_op(
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type="mul",
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inputs={"X": [mul_x], "Y": mul_y},
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outputs={"Out": [mul_out]},
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attrs={"x_num_col_dims": 1},
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)
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self.assertNotEqual(str(mul_op), "")
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self.assertEqual(mul_op.type, "mul")
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self.assertEqual(mul_op.input_names, ["X", "Y"])
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self.assertEqual(mul_op.input("X"), ["mul.x"])
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self.assertEqual(mul_op.input("Y"), ["mul.y"])
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self.assertEqual(mul_op.output_names, ["Out"])
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self.assertEqual(mul_op.output("Out"), ["mul.out"])
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self.assertEqual(
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set(mul_op.attr_names),
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{
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"x_num_col_dims",
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"y_num_col_dims",
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"op_role",
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"op_role_var",
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"op_namescope",
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"op_callstack",
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"op_device",
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"with_quant_attr",
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},
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)
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self.assertEqual(mul_op.has_attr("x_num_col_dims"), True)
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self.assertEqual(mul_op.attr_type("x_num_col_dims"), core.AttrType.INT)
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self.assertEqual(mul_op.attr("x_num_col_dims"), 1)
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self.assertEqual(mul_op.has_attr("y_num_col_dims"), True)
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self.assertEqual(mul_op.attr_type("y_num_col_dims"), core.AttrType.INT)
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self.assertEqual(mul_op.attr("y_num_col_dims"), 1)
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self.assertEqual(mul_op.idx, 0)
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self.assertEqual(mul_out.op, mul_op)
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mul_op.desc.remove_input("X")
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self.assertEqual(mul_op.input_names, ["Y"])
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def test_mult_input(self):
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program = Program()
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block = program.current_block()
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sum_x1 = block.create_var(dtype="int", shape=[3, 4], name="sum.x1")
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sum_x2 = block.create_var(dtype="int", shape=[3, 4], name="sum.x2")
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sum_x3 = block.create_var(dtype="int", shape=[3, 4], name="sum.x3")
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sum_out = block.create_var(dtype="int", shape=[3, 4], name="sum.out")
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sum_op = block.append_op(
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type="sum",
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inputs={"X": [sum_x1, sum_x2, sum_x3]},
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outputs={"Out": sum_out},
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)
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self.assertEqual(sum_op.type, "sum")
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self.assertEqual(sum_op.input_names, ["X"])
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self.assertEqual(sum_op.input("X"), ["sum.x1", "sum.x2", "sum.x3"])
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self.assertEqual(sum_op.output_names, ["Out"])
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self.assertEqual(sum_op.output("Out"), ["sum.out"])
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self.assertEqual(sum_op.idx, 0)
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self.assertEqual(sum_out.op, sum_op)
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if __name__ == '__main__':
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unittest.main()
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