Delete the last remaining set_dynamic_columns interface part
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@ -334,9 +334,6 @@ class Dataset:
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self.saved_output_shapes = None
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self.estimated_output_shapes = None
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self.runtime_context = None
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self.dynamic_setting = [False, None]
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self.saved_min_shapes = None
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self.saved_max_shapes = None
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self._col_names = None
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self.dataset_size = None
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self._batch_size = None
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@ -1644,23 +1641,6 @@ class Dataset:
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return self.dataset_size
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@staticmethod
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def __check_dynamic_column_name(dynamic_columns, dataset_columns):
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for column in dynamic_columns:
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if column not in dataset_columns:
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raise RuntimeError("dynamic column [" + column + "] does not match any column in dataset: " +
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str(dataset_columns))
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@staticmethod
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def __check_dynamic_column_shape(data, col, dynamic_columns):
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shape_mismatch = "dynamic column [" + col + "] with shape " + str(dynamic_columns[col]) + \
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" does not match dataset column [" + col + "] with shape " + str(list(data[col].shape))
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if data[col].ndim != len(dynamic_columns[col]):
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raise RuntimeError(shape_mismatch)
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for dim in range(len(dynamic_columns[col])):
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if dynamic_columns[col][dim] is not None and dynamic_columns[col][dim] != data[col].shape[dim]:
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raise RuntimeError(shape_mismatch)
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def num_classes(self):
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"""
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Get the number of classes in a dataset.
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@ -30,7 +30,6 @@ class MindData:
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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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self.dynamic_setting = [False, None]
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def get_dataset_size(self):
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return self._size
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