mindspore/tests/ut/python/nn/test_map_parameter.py

129 lines
4.6 KiB
Python

# 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
# limitations under the License.
# ============================================================================
import numpy as np
import mindspore as ms
import mindspore.nn as nn
from mindspore import context, Tensor, Parameter, ParameterTuple
from mindspore.experimental import MapParameter
from mindspore.common.initializer import initializer
def test_basic_operations():
"""
Feature: MapParameter
Description: Test MapParameter basic operations.
Expectation: MapParameter works as expected.
"""
m = MapParameter(key_dtype=ms.int32, value_dtype=ms.float32, value_shape=(2), default_value='zeros', name='my_map')
assert m.name == 'my_map'
assert m.requires_grad
t = m.get(Tensor([1, 2, 3], dtype=ms.int32))
assert t.dtype == ms.float32
assert t.shape == (3, 2)
assert np.allclose(t.asnumpy(), 0)
t = m.get(Tensor([1, 2, 3], dtype=ms.int32), 0)
assert t.dtype == ms.float32
assert t.shape == (3, 2)
assert np.allclose(t.asnumpy(), 0)
t = m[Tensor([1, 2, 3], dtype=ms.int32)]
assert t.dtype == ms.float32
assert t.shape == (3, 2)
assert np.allclose(t.asnumpy(), 0)
m.put(Tensor([1, 2, 3], dtype=ms.int32), Tensor([[1, 1], [2, 2], [3, 3]], dtype=ms.float32))
m[Tensor([1, 2, 3], dtype=ms.int32)] = Tensor([[11, 11], [22, 22], [33, 33]], dtype=ms.float32)
m.erase(Tensor([1, 2, 3], dtype=ms.int32))
print(m)
def test_simple_graph_compile():
"""
Feature: MapParameter
Description: Test IR graph compiled with MapParameter.
Expectation: IR graph with MapParameter created without exceptions.
"""
class MyNet(nn.Cell):
def __init__(self):
nn.Cell.__init__(self)
self.p = Parameter(initializer('ones', (2, 3), ms.float32))
self.m = MapParameter(key_dtype=ms.int32, value_dtype=ms.float32, value_shape=(3,))
self.key = Tensor([1, 2], dtype=ms.int32)
def construct(self, x):
self.m.put(self.key, x)
value1 = self.m.get(self.key, 0.1)
value2 = self.m.get(self.key, 'zeros')
value3 = self.m.get(self.key)
value4 = self.m[self.key]
self.m[self.key] = value4
self.m.erase(self.key)
return self.p + value1 + value2 + value3 + value4
context.set_context(mode=context.GRAPH_MODE)
net = MyNet()
t = initializer('ones', (2, 3), ms.float32)
t = t.init_data()
out = net(t)
print(out)
assert out.shape == (2, 3)
def test_export_update_api():
"""
Feature: MapParameter
Description: Test export update api for MapParameter.
Expectation: Export update api works as expected.
"""
m = MapParameter(key_dtype=ms.int32, value_dtype=ms.float32, value_shape=(3,))
data = m.export(full=True)
m.update(data)
def test_map_parameter_clone():
"""
Feature: MapParameter
Description: Test MapParameter clone() method.
Expectation: MapParameter cloned as expected.
"""
m = MapParameter(key_dtype=ms.int32, value_dtype=ms.float32, value_shape=(3,), name="map")
p = Parameter(Tensor(1), name="param")
params = ParameterTuple([m, p])
cloned_params = params.clone(prefix="cloned", init='zeros')
cloned_map = cloned_params[0]
assert isinstance(cloned_map, MapParameter)
assert cloned_map.name == 'cloned.map'
assert cloned_map.key_dtype == m.key_dtype
assert cloned_map.value_dtype == m.value_dtype
assert cloned_map.value_shape == m.value_shape
assert cloned_map.default_value == 'zeros'
old_map_tensor = m._map_tensor # pylint: disable=W0212
new_map_tensor = cloned_map._map_tensor # pylint: disable=W0212
assert new_map_tensor != old_map_tensor
assert new_map_tensor.key_dtype == old_map_tensor.key_dtype
assert new_map_tensor.value_dtype == old_map_tensor.value_dtype
assert new_map_tensor.value_shape == old_map_tensor.value_shape
clone_same = cloned_map.clone(init='same')
assert clone_same.key_dtype == m.key_dtype
assert clone_same.value_dtype == m.value_dtype
assert clone_same.value_shape == m.value_shape
assert clone_same.default_value == 'zeros'