forked from mindspore-Ecosystem/mindspore
242 lines
6.7 KiB
Python
242 lines
6.7 KiB
Python
# Copyright 2022 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 joinedstr """
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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, jit, context
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import mindspore.ops as ops
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import mindspore.ops.operations as P
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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_joinedstr_basic_tuple_list_dict():
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"""
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Feature: Support joinedstr.
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Description: Support joinedstr.
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Expectation: No exception.
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"""
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@jit
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def joined_net():
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x = (1, 2, 3, 4, 5)
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y = [1, 2, 3, 4, 5]
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z = {'a': 1, 'b': 2, 'c': 3}
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res_x = f"x: {x}"
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res_y = f"y: {y}"
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res_z = f"z: {z}"
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return res_x, res_y, res_z
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out_x, out_y, out_z = joined_net()
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assert out_x == "x: (1, 2, 3, 4, 5)"
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assert out_y == "y: [1, 2, 3, 4, 5]"
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assert out_z == "z: {'a': 1, 'b': 2, 'c': 3}"
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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_joinedstr_basic_dict_key():
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"""
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Feature: Support joinedstr.
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Description: Support joinedstr.
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Expectation: No exception.
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"""
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@jit
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def joined_net():
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c = (1, 2, 3, 4, 5)
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dict_key = f"c: {c}"
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z = {'a': 1, 'b': 2, dict_key: 3}
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dict_res = z.get(dict_key)
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return dict_res
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out = joined_net()
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assert out == 3
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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_joinedstr_basic_numpy_scalar():
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"""
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Feature: Support joinedstr.
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Description: Support joinedstr.
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Expectation: No exception.
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"""
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@jit
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def joined_net():
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x = np.array([1, 2, 3, 4, 5])
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y = 3
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res = f"x: {x}, y: {y}"
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return res
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out = joined_net()
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assert out == "x: [1 2 3 4 5], y: 3"
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_joinedstr_basic_variable_gpu():
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"""
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Feature: Support joinedstr.
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Description: Support joinedstr.
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Expectation: No exception.
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"""
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@jit
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def joined_net(x, y):
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if (x > 2 * y).all():
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res = f"res: {2 * y}"
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else:
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res = f"res: {x}"
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return res
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with pytest.raises(RuntimeError, match="Invalid value:res:"):
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input_x = Tensor(np.array([1, 2, 3, 4, 5]))
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out = joined_net(input_x, input_x)
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print("out:", out)
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@pytest.mark.level0
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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_joinedstr_basic_variable_ascend():
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"""
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Feature: Support joinedstr.
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Description: Support joinedstr.
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Expectation: No exception.
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"""
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@jit
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def joined_net(x, y):
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if (x > 2 * y).all():
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res = f"res: {2 * y}"
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else:
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res = f"res: {x}"
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return res
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with pytest.raises(RuntimeError, match="Illegal input dtype: String"):
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input_x = Tensor(np.array([1, 2, 3, 4, 5]))
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out = joined_net(input_x, input_x)
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assert out == "x: [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_joinedstr_basic_variable_2():
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"""
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Feature: Support joinedstr.
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Description: Support joinedstr.
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Expectation: No exception.
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"""
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@jit
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def joined_net(x, y):
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if (x > 2 * y).all():
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res = f"{2 * y}"
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else:
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res = f"{x}"
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return res
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input_x = Tensor(np.array([1, 2, 3, 4, 5]))
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out = joined_net(input_x, input_x)
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assert str(out) == "(Tensor(shape=[5], dtype=Int64, value= [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_joinedstr_inner_tensor():
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"""
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Feature: Support joinedstr.
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Description: Support joinedstr.
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Expectation: No exception.
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"""
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@jit
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def joined_net():
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x = (1, 2, 3, 4, 5)
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inner_tensor_1 = Tensor(x)
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res = f"x: {x}, inner_tensor_1: {inner_tensor_1}, inner_tensor_2: {Tensor(2)}"
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return res
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out = joined_net()
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assert str(out) == "x: (1, 2, 3, 4, 5), inner_tensor_1: [1 2 3 4 5], inner_tensor_2: 2"
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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_joinedstr_out_tensor():
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"""
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Feature: Support joinedstr.
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Description: Support joinedstr.
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Expectation: No exception.
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"""
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@jit
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def joined_net(x):
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return f"x: {x}"
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input_x = Tensor([1, 2, 3])
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out = joined_net(input_x)
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assert str(out) == "('x: ', Tensor(shape=[3], dtype=Int64, value= [1, 2, 3]))"
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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_joinedstr_dynamic_shape_scalar():
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"""
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Feature: Support joinedstr.
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Description: dynamic shape is scalar in joined str.
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Expectation: No exception.
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"""
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class Net(nn.Cell):
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def __init__(self):
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super().__init__()
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self.unique = P.Unique()
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self.gather = P.Gather()
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self.axis = 0
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self.shape = ops.TensorShape()
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def construct(self, x, indices):
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unique_indices, _ = self.unique(indices)
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x = self.gather(x, unique_indices, self.axis)
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x_shape = self.shape(x)
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print(f"x.shape:{x_shape}")
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return x_shape
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input_np = Tensor(np.random.randn(5, 4).astype(np.float32))
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indices_np = Tensor(np.random.randint(0, 3, size=3))
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net = Net()
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out = net(input_np, indices_np)
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print("out:", out)
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