forked from mindspore-Ecosystem/mindspore
237 lines
7.9 KiB
Python
237 lines
7.9 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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import numpy as np
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import mindspore as ms
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import mindspore.nn as nn
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from mindspore import context, Tensor, Parameter, ParameterTuple, MapTensor
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from mindspore.experimental import MapParameter
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from mindspore.common.initializer import initializer
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from mindspore.ops import composite as C
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def test_basic_operations():
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"""
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Feature: MapParameter
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Description: Test MapParameter basic operations.
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Expectation: MapParameter works as expected.
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"""
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m = MapParameter(key_dtype=ms.int32, value_dtype=ms.float32, value_shape=(2), default_value='zeros', name='my_map')
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assert m.name == 'my_map'
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assert m.requires_grad
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t = m.get(Tensor([1, 2, 3], dtype=ms.int32))
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assert t.dtype == ms.float32
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assert t.shape == (3, 2)
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assert np.allclose(t.asnumpy(), 0)
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t = m.get(Tensor([1, 2, 3], dtype=ms.int32))
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assert t.dtype == ms.float32
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assert t.shape == (3, 2)
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assert np.allclose(t.asnumpy(), 0)
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t = m[Tensor([1, 2, 3], dtype=ms.int32)]
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assert t.dtype == ms.float32
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assert t.shape == (3, 2)
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assert np.allclose(t.asnumpy(), 0)
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m.put(Tensor([1, 2, 3], dtype=ms.int32), Tensor([[1, 1], [2, 2], [3, 3]], dtype=ms.float32))
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m[Tensor([1, 2, 3], dtype=ms.int32)] = Tensor([[11, 11], [22, 22], [33, 33]], dtype=ms.float32)
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m.erase(Tensor([1, 2, 3], dtype=ms.int32))
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data = m.get_data()
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assert data is None
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print(m)
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def test_simple_graph_compile():
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"""
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Feature: MapParameter
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Description: Test IR graph compiled with MapParameter.
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Expectation: IR graph with MapParameter created without exceptions.
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"""
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class MyNet(nn.Cell):
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def __init__(self):
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nn.Cell.__init__(self)
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self.p = Parameter(initializer('ones', (2, 3), ms.float32))
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self.m = MapParameter(key_dtype=ms.int32, value_dtype=ms.float32, value_shape=(3,))
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self.key = Tensor([1, 2], dtype=ms.int32)
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def construct(self, x):
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self.m.put(self.key, x)
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value1 = self.m.get(self.key)
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value2 = self.m[self.key]
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self.m[self.key] = value2
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self.m.erase(self.key)
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keys = self.m.get_keys()
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values = self.m.get_values()
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keys_values = self.m.get_data()
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print(keys_values)
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self.m.put(keys, values)
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return self.p + value1 + value2
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context.set_context(mode=context.GRAPH_MODE)
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net = MyNet()
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t = initializer('ones', (2, 3), ms.float32)
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t = t.init_data()
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out = net(t)
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print(out)
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assert out.shape == (2, 3)
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def test_export_update_api():
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"""
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Feature: MapParameter
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Description: Test export update api for MapParameter.
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Expectation: Export update api works as expected.
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"""
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m = MapParameter(key_dtype=ms.int32, value_dtype=ms.float32, value_shape=(3,))
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data = m.export(full=True)
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m.update(data)
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def test_map_parameter_clone():
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"""
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Feature: MapParameter
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Description: Test MapParameter clone() method.
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Expectation: MapParameter cloned as expected.
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"""
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m = MapParameter(key_dtype=ms.int32, value_dtype=ms.float32, value_shape=(3,), name="map")
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p = Parameter(Tensor(1), name="param")
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params = ParameterTuple([m, p])
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cloned_params = params.clone(prefix="cloned", init='zeros')
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cloned_map = cloned_params[0]
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assert isinstance(cloned_map, MapParameter)
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assert cloned_map.name == 'cloned.map'
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assert cloned_map.key_dtype == m.key_dtype
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assert cloned_map.value_dtype == m.value_dtype
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assert cloned_map.value_shape == m.value_shape
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assert cloned_map.default_value == 'zeros'
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old_map_tensor = m._map_tensor # pylint: disable=W0212
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new_map_tensor = cloned_map._map_tensor # pylint: disable=W0212
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assert new_map_tensor != old_map_tensor
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assert new_map_tensor.key_dtype == old_map_tensor.key_dtype
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assert new_map_tensor.value_dtype == old_map_tensor.value_dtype
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assert new_map_tensor.value_shape == old_map_tensor.value_shape
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clone_same = cloned_map.clone(init='same')
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assert clone_same.key_dtype == m.key_dtype
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assert clone_same.value_dtype == m.value_dtype
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assert clone_same.value_shape == m.value_shape
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assert clone_same.default_value == 'zeros'
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def test_grad_net():
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"""
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Feature: MapParameter
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Description: Test grad graph compiled with MapParameter.
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Expectation: Grad graph for MapParameter created without exceptions.
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"""
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class MyNet(nn.Cell):
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def __init__(self):
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nn.Cell.__init__(self)
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self.m = MapParameter(key_dtype=ms.int32, value_dtype=ms.float32, value_shape=(3,))
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self.key = Tensor([1, 2], dtype=ms.int32)
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def construct(self, x):
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a = self.m.get(self.key)
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self.m.erase(self.key)
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return x * a
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class GradNet(nn.Cell):
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def __init__(self, network):
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super(GradNet, self).__init__()
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self.grad_by_list = C.GradOperation(get_by_list=True)
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self.network = network
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self.weights = ParameterTuple(network.trainable_params())
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def construct(self, *inputs):
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gout = self.grad_by_list(self.network, self.weights)(*inputs)
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return gout
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context.set_context(mode=context.GRAPH_MODE)
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net = MyNet()
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grad = GradNet(net)
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t = initializer('ones', (2, 3), ms.float32)
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t = t.init_data()
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grad(t)
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def test_map_tensor():
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"""
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Feature: MapTensor
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Description: Test new MapTensor in construct.
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Expectation: New MapTensor in construct without exceptions.
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"""
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class MapTensorNet(nn.Cell):
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def __init__(self):
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super().__init__()
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self.default_value = 'zeros'
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self.map_param = MapParameter(key_dtype=ms.int32, value_dtype=ms.float32, value_shape=(3,))
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def construct(self):
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keys = self.map_param.get_keys()
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values = self.map_param.get_values()
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new_map_tensor = MapTensor(keys, values, self.default_value)
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new_data = new_map_tensor.get_data()
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return new_map_tensor, new_data
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context.set_context(mode=context.GRAPH_MODE)
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net = MapTensorNet()
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out = net()
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print("out:", out)
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def test_map_tensor_with_keys_values():
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"""
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Feature: MapTensor
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Description: Test new MapTensor in construct.
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Expectation: New MapTensor in construct without exceptions.
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"""
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class MapTensorNet(nn.Cell):
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def __init__(self):
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super().__init__()
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self.default_value = 'zeros'
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def construct(self):
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keys = Tensor([1, 2], dtype=ms.int32)
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values = Tensor([[1, 2], [1, 2]], dtype=ms.float32)
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return MapTensor(keys, values, self.default_value)
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context.set_context(mode=context.GRAPH_MODE)
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net = MapTensorNet()
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out = net()
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print("out:", out)
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def test_map_tensor_get_data_api():
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"""
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Feature: MapTensor
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Description: Test get_data api for MapTensor.
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Expectation: get_data api works as expected.
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"""
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keys = Tensor([1, 2], dtype=ms.int32)
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values = Tensor([[1, 2], [1, 2]], dtype=ms.float32)
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map_tensor = MapTensor(keys, values, 'zeros')
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get_keys = map_tensor.get_keys()
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print("get_keys:", get_keys)
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get_values = map_tensor.get_values()
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print("get_values:", get_values)
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[the_keys, the_values] = map_tensor.get_data()
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print("the_keys:", the_keys)
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print("the_values:", the_values)
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