# Copyright 2021 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. # ============================================================================ """ test tensor properties in graph mode""" import numpy as np import mindspore.nn as nn import mindspore.common.dtype as mstype from mindspore import Tensor from mindspore import context context.set_context(mode=context.GRAPH_MODE) def test_ndim(): class Net(nn.Cell): def __init__(self): super(Net, self).__init__() self.value = Tensor(np.random.random( (2, 3, 4, 5)), dtype=mstype.float32) def construct(self): return self.value.ndim net = Net() res = net() assert res == 4 def test_nbytes(): class Net(nn.Cell): def __init__(self): super(Net, self).__init__() self.value = Tensor(np.random.random( (2, 3, 4, 5)), dtype=mstype.float32) def construct(self): return self.value.nbytes net = Net() res = net() assert res == 480 def test_size(): class Net(nn.Cell): def __init__(self): super(Net, self).__init__() self.value = Tensor(np.random.random( (2, 3, 4, 5)), dtype=mstype.float32) def construct(self): return self.value.size net = Net() res = net() assert res == 120 def test_strides(): class Net(nn.Cell): def __init__(self): super(Net, self).__init__() self.value = Tensor(np.random.random( (2, 3, 4, 5)), dtype=mstype.float32) def construct(self): return self.value.strides net = Net() res = net() assert res == (240, 80, 20, 4) def test_itemsize(): class Net(nn.Cell): def __init__(self): super(Net, self).__init__() self.value1 = Tensor(np.random.random( (2, 3, 4, 5)), dtype=mstype.float64) self.value2 = Tensor(np.random.random( (2, 3, 4, 5)), dtype=mstype.int32) self.value3 = Tensor(np.random.random( (2, 3, 4, 5)), dtype=mstype.bool_) def construct(self): return (self.value1.itemsize, self.value2.itemsize, self.value3.itemsize) net = Net() res = net() assert res == (8, 4, 1)