mindspore/tests/ut/python/python_builtin/test_max_min.py

# Copyright 2022 Huawei Technologies Co., Ltd
#
# 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
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# ============================================================================
""" test graph fallback buildin python function max and min"""
import operator
import pytest
import numpy as np
from mindspore import ms_function, context, Tensor

context.set_context(mode=context.GRAPH_MODE)


def test_fallback_max_with_one_input_list():
    """
    Feature: JIT Fallback
    Description: Test max() in graph mode with one input list.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        x = max([1, 2, 3])
        return x
    out = foo()
    assert out == 3


def test_fallback_max_with_one_input_list_2():
    """
    Feature: JIT Fallback
    Description: Test max() in graph mode with one input list.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        x = max([(1, 2), (1, 3), (3, 4)])
        return x
    out = foo()
    assert operator.eq(out, (3, 4))


def test_fallback_max_with_one_input_tuple():
    """
    Feature: JIT Fallback
    Description: Test max() in graph mode with one input tuple.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        x = max((1, 2, 3))
        return x
    out = foo()
    assert out == 3


def test_fallback_max_with_one_input_tuple_2():
    """
    Feature: JIT Fallback
    Description: Test max() in graph mode with one input tuple.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        x = max((1, 2), (1, 3), (3, 4))
        return x
    out = foo()
    assert operator.eq(out, (3, 4))


def test_fallback_max_with_one_input_dict():
    """
    Feature: JIT Fallback
    Description: Test max() in graph mode with one input dict.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        x = max({'a': 1, 'b': 2, 'c': 3})
        return x
    out = foo()
    assert out == 'c'


def test_fallback_max_with_one_input_numpy_array():
    """
    Feature: JIT Fallback
    Description: Test max() in graph mode with one input numpy array.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        x = max(np.array([1, 2, 3]))
        return Tensor(x)
    out = foo()
    assert out == 3


def test_fallback_max_with_one_input_tensor():
    """
    Feature: JIT Fallback
    Description: Test max() in graph mode with one input tensor.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        x = max(Tensor([1, 2, 3]))
        return x
    out = foo()
    assert out == 3


def test_fallback_max_with_two_inputs_list():
    """
    Feature: JIT Fallback
    Description: Test max() in graph mode with two inputs list.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        x = max([1, 2, 3], [4, 5])
        return x
    out = foo()
    assert operator.eq(out, (4, 5))


def test_fallback_min_with_two_inputs_list():
    """
    Feature: JIT Fallback
    Description: Test min() in graph mode with two inputs list.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        x = min([1, 2, 3], [4, 5])
        return x
    out = foo()
    assert operator.eq(out, (1, 2, 3))


def test_builtin_function_max_min_with_string():
    """
    Feature: Support the type of the input of built-in function min is string.
    Description: Support the type of the input of built-in function min is string.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        return max("1, 2, 3, 4"), min("1, 2, 3, 4")

    out_max, out_min = foo()
    assert out_max == '4'
    assert out_min == ' '


def test_builtin_function_max_min_with_tuple():
    """
    Feature: Support the type of the input of built-in function min is tuple.
    Description: Support the type of the input of built-in function min is tuple.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        x = [('a', 1), ('A', 1), ('a', 2)]
        return max(x), min(x)

    out_max, out_min = foo()
    assert out_max == ('a', 2)
    assert out_min == ('A', 1)


def test_fallback_max_with_one_input_numpy_array_multidimensional():
    """
    Feature: JIT Fallback
    Description: Test max() in graph mode with one input numpy array.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        x = max(np.array([[1, 2, 3], [1, 2, 3]]))
        return Tensor(x)
    with pytest.raises(ValueError, match="The truth value of an array with more than one element is ambiguous."):
        out = foo()
        assert out == 3


def test_builtin_function_max_min_with_multiple_strings():
    """
    Feature: Support the type of the input of built-in function min is string.
    Description: Support the type of the input of built-in function min is string.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        return max("1, 2, 3, 4", "2, 1, 0"), min("1, 2, 3, 4", "2, 1, 0")

    out_max, out_min = foo()
    assert out_max == '2, 1, 0'
    assert out_min == '1, 2, 3, 4'


def test_fallback_max_min_with_multiple_num():
    """
    Feature: JIT Fallback
    Description: Test max() in graph mode with multiple numbers.
    Expectation: No exception.
    """
    @ms_function
    def foo():
        x1 = max(1, 4, 0, 10)
        x2 = max(3.0, 4.9, 4.8)
        x3 = max(x1, x2)
        return x1, x2, x3
    out = foo()
    assert out[0] == 10
    assert abs(out[1] - 4.9) <= 0.0000001
    assert out[2] == 10