forked from huawei/mindspore2022
278 lines
7.4 KiB
Python
278 lines
7.4 KiB
Python
# Copyright 2021 Huawei Technologies Co., Ltd
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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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# ============================================================================
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""" test graph fallback """
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import pytest
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import numpy as np
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import mindspore.nn as nn
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from mindspore import Tensor, ms_function, context
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context.set_context(mode=context.GRAPH_MODE)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_np_print_1():
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"""
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Feature: JIT Fallback
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Description: Support print.
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Expectation: No exception.
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"""
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@ms_function
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def np_print():
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x = np.array([1, 2, 3, 4, 5])
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print("x: ", x)
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return Tensor(x)
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assert np.all(np_print().asnumpy() == np.array([1, 2, 3, 4, 5]))
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_np_print_2():
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"""
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Feature: JIT Fallback
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Description: Support print.
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Expectation: No exception.
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"""
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class PrintNet(nn.Cell):
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def construct(self):
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x = np.array([1, 2, 3, 4, 5])
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print("x: ", x)
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return Tensor(x)
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net = PrintNet()
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res = net()
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print("res: ", res)
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assert (res.asnumpy() == [1, 2, 3, 4, 5]).all()
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_tensor_print_1():
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"""
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Feature: JIT Fallback
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Description: Support print.
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Expectation: No exception.
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"""
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@ms_function
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def np_print():
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x = np.array([1, 2, 3, 4, 5])
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print("Tensor(x): ", Tensor(x))
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return Tensor(x)
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assert np.all(np_print().asnumpy() == np.array([1, 2, 3, 4, 5]))
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_print_cnode_1():
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"""
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Feature: JIT Fallback
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Description: Support print.
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Expectation: No exception.
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"""
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@ms_function
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def print_func(x, y):
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res_sum = x + y
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print("res_sum: ", res_sum)
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return res_sum
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x = Tensor(np.array([1, 2, 3, 4, 5]))
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y = Tensor(np.array([1, 2, 3, 4, 5]))
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res = print_func(x, y)
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print("res: ", res)
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assert (res.asnumpy() == [2, 4, 6, 8, 10]).all()
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_print_cnode_2():
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"""
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Feature: JIT Fallback
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Description: Support print.
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Expectation: No exception.
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"""
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@ms_function
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def print_func():
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x = Tensor(np.array([1, 2, 3, 4, 5]))
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y = Tensor(np.array([1, 2, 3, 4, 5]))
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res_sum = x + y
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print("res_sum: ", res_sum)
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return res_sum
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res = print_func()
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print("res: ", res)
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assert (res.asnumpy() == [2, 4, 6, 8, 10]).all()
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_print_cnode_3():
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"""
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Feature: JIT Fallback
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Description: Support print.
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Expectation: No exception.
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"""
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@ms_function
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def print_func():
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x = np.array([1, 2, 3, 4, 5])
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y = np.array([1, 2, 3, 4, 5])
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res_sum = x + y
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print("res_sum: ", res_sum)
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return Tensor(res_sum)
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res = print_func()
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print("res: ", res)
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assert (res.asnumpy() == [2, 4, 6, 8, 10]).all()
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_print_validate_tuple():
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"""
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Feature: JIT Fallback
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Description: Support print.
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Expectation: No exception.
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"""
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@ms_function
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def print_func():
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x = Tensor(np.array([1, 2, 3, 4, 5]))
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y = Tensor(np.array([1, 2, 3, 4, 5]))
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tensor_sum = x + y
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print("tensor_sum: ", tensor_sum)
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np_x = np.array([1, 2, 3, 4, 5])
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np_y = np.array([1, 2, 3, 4, 5])
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np_sum = np_x + np_y
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print("np_sum: ", np_sum)
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return tensor_sum, np_sum
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with pytest.raises(RuntimeError) as err:
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res1, res2 = print_func()
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print("res1: ", res1)
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print("res2: ", res2)
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assert "Should not use Python object in runtime" in str(err.value)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_print_validate():
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"""
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Feature: JIT Fallback
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Description: Support print.
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Expectation: No exception.
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"""
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@ms_function
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def print_func():
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np_x = np.array([1, 2, 3, 4, 5])
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np_y = np.array([1, 2, 3, 4, 5])
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np_sum = np_x + np_y
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print("np_sum: ", np_sum)
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return np_sum
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with pytest.raises(RuntimeError) as err:
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res = print_func()
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print("res: ", res)
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assert "Should not use Python object in runtime" in str(err.value)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_print_format_np():
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"""
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Feature: JIT Fallback
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Description: Support print.
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Expectation: No exception.
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"""
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@ms_function
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def print_func():
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np_x = np.array([1, 2, 3, 4, 5])
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np_y = np.array([1, 2, 3, 4, 5])
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np_sum = np_x + np_y
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print("np_sum: {}".format(np_sum))
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return Tensor(np_sum)
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res = print_func()
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print("res: ", res)
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assert (res.asnumpy() == [2, 4, 6, 8, 10]).all()
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_print_format_tensor():
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"""
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Feature: JIT Fallback
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Description: Support print.
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Expectation: No exception.
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"""
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@ms_function
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def print_func():
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x = Tensor(np.array([1, 2, 3, 4, 5]))
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y = Tensor(np.array([1, 2, 3, 4, 5]))
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tensor_sum = x + y
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print("tensor_sum: {}".format(tensor_sum))
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return tensor_sum
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res = print_func()
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print("res: ", res)
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assert (res.asnumpy() == [2, 4, 6, 8, 10]).all()
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_print_string_format():
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"""
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Feature: JIT Fallback
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Description: Support print(string % var).
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Expectation: No exception.
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"""
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@ms_function
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def print_func():
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print("I'm %s. I'm %d years old." % ('MindSpore', 3))
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return 0
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res = print_func()
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print("res: ", res)
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