forked from mindspore-Ecosystem/mindspore
91 lines
2.4 KiB
Python
91 lines
2.4 KiB
Python
# Copyright 2020 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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'''Remove after MindData merge to MindSpore '''
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import numpy as np
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from mindspore import Tensor
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class MindData:
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""" Stub for MindData """
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def __init__(self, size=1, batch_size=None, repeat_count=1,
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np_types=None, output_shapes=None, input_indexs=()):
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self._size = size
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self._batch_size = batch_size
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self._repeat_count = repeat_count
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self._np_types = np_types
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self._output_shapes = output_shapes
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self._input_indexs = input_indexs
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self._iter_num = 0
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def get_dataset_size(self):
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return self._size
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def get_repeat_count(self):
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return self._repeat_count
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def get_batch_size(self):
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return self._batch_size
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def output_types(self):
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return self._np_types
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def output_shapes(self):
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return self._output_shapes
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@property
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def input_indexs(self):
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return self._input_indexs
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def device_que(self, send_epoch_end=True):
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self.queue_name = '6ba41974-209e-11ea-88b0-a24efeb2c736'
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self.send_epoch_end = send_epoch_end
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return self
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def create_tuple_iterator(self, num_epochs=-1):
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return self.__iter__()
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def send(self, num_epochs=-1):
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pass
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def stop_send(self):
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pass
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def continue_send(self):
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pass
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def __len__(self):
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return self._size
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def __iter__(self):
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return self
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def __next__(self):
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if self._size < self._iter_num:
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raise StopIteration
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self._iter_num += 1
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next_value = []
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for shape, typ in zip(self._output_shapes, self._np_types):
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next_value.append(Tensor(np.ndarray(shape, typ)))
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return tuple(next_value)
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def next(self):
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return self.__next__()
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def reset(self):
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self._iter_num = 0
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