mindspore/tests/dataset_mock.py

107 lines
2.8 KiB
Python

# Copyright 2020-2023 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.
# ============================================================================
'''Remove after MindData merge to MindSpore '''
import numpy as np
from mindspore import Tensor
class MindData:
""" Stub for MindData """
def __init__(self, size=1, batch_size=None, repeat_count=1,
np_types=None, output_shapes=None, input_indexs=()):
self._size = size
self._batch_size = batch_size
self._repeat_count = repeat_count
self._np_types = np_types
self._output_shapes = output_shapes
self._input_indexs = input_indexs
self._iter_num = 0
self._global_step = 0
def get_dataset_size(self):
return self._size
def get_repeat_count(self):
return self._repeat_count
def get_batch_size(self):
return self._batch_size
def output_types(self):
return self._np_types
def output_shapes(self):
return self._output_shapes
@property
def input_indexs(self):
return self._input_indexs
def device_que(self, send_epoch_end=True, create_data_info_queue=False, queue_name=""):
self.queue_name = '6ba41974-209e-11ea-88b0-a24efeb2c736'
self.send_epoch_end = send_epoch_end
return self
def create_tuple_iterator(self, num_epochs=-1, do_copy=True):
return self.__iter__()
def send(self, num_epochs=-1):
pass
def stop_send(self):
pass
def release(self):
pass
def continue_send(self):
pass
def get_data_info(self):
pass
def get_mbuf_queue_size(self):
pass
def get_send_info(self):
pass
def __len__(self):
return self._size
def __iter__(self):
return self
def __next__(self):
if self._size < self._iter_num:
raise StopIteration
self._iter_num += 1
next_value = []
for shape, typ in zip(self._output_shapes, self._np_types):
next_value.append(Tensor(np.ndarray(shape, typ)))
return tuple(next_value)
def next(self):
return self.__next__()
def reset(self):
self._iter_num = 0
def get_init_step(self):
return self._global_step