test_trunc_op.py 3.0 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111
#!/usr/bin/env python3

# Copyright (c) 2023 CINN 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 numpy as np
from op_test import OpTest, OpTestTool
from op_test_helper import TestCaseHelper
import paddle
import cinn
from cinn.frontend import *
from cinn.common import *


@OpTestTool.skip_if(not is_compiled_with_cuda(),
                    "x86 test will be skipped due to timeout.")
class TestTruncOp(OpTest):
    def setUp(self):
        print(f"\nRunning {self.__class__.__name__}: {self.case}")
        self.prepare_inputs()

    def prepare_inputs(self):
        self.x_np = self.random(
            shape=self.case["x_shape"],
            dtype=self.case["x_dtype"],
            low=-1000.0,
            high=1000.0)

    def build_paddle_program(self, target):
        x = paddle.to_tensor(self.x_np, stop_gradient=True)
        out = paddle.trunc(x)
        self.paddle_outputs = [out]

    def build_cinn_program(self, target):
        builder = NetBuilder("unary_elementwise_test")
        x = builder.create_input(
            self.nptype2cinntype(self.case["x_dtype"]), self.case["x_shape"],
            "x")
        out = builder.trunc(x)
        prog = builder.build()
        res = self.get_cinn_output(prog, target, [x], [self.x_np], [out])

        self.cinn_outputs = [res[0]]

    def test_check_results(self):
        self.check_outputs_and_grads()


class TestTruncOpShape(TestCaseHelper):
    def init_attrs(self):
        self.class_name = "TestTruncOpShape"
        self.cls = TestTruncOp
        self.inputs = [{
            "x_shape": [1],
        }, {
            "x_shape": [1024],
        }, {
            "x_shape": [1, 2048],
        }, {
            "x_shape": [1, 1, 1],
        }, {
            "x_shape": [32, 64],
        }, {
            "x_shape": [16, 8, 4, 2],
        }, {
            "x_shape": [16, 8, 4, 2, 1],
        }]
        self.dtypes = [{
            "x_dtype": "float32",
        }]
        self.attrs = []


class TestTruncOpDtype(TestCaseHelper):
    def init_attrs(self):
        self.class_name = "TestTruncOpDtype"
        self.cls = TestTruncOp
        self.inputs = [{
            "x_shape": [32, 64],
        }]
        self.dtypes = [
            {
                "x_dtype": "int32",
            },
            {
                "x_dtype": "int64",
            },
            {
                "x_dtype": "float32",
            },
            {
                "x_dtype": "float64",
            },
        ]
        self.attrs = []


if __name__ == "__main__":
    TestTruncOpShape().run()
    TestTruncOpDtype().run()