msp.datasets package

Module contents

The mps.datasets module includes utility to generate sample data.

msp.datasets.make_sparse_data(n_samples: int, batch_size: int = 1, n_node_feat: int = 5, n_edge_feat: int = 3, msp_size: Optional[Tuple[int, int]] = None, msp_rand_size: Optional[Tuple[Tuple[int, int], Tuple[int, int]]] = None, is_machine_idle: bool = True, seed=None) → tensorflow.python.data.ops.dataset_ops.DatasetV2[source]

Generate samples of synthetic data set for MSP problem.

Parameters

  • n_samples – number of instances

  • batch_size – batch_size is only used in conjunction with msp_rand_size

  • n_node_feat – number of node features

  • n_edge_feat – number of edge features

  • msp_size – size of msp instance (number of jobs, number of machines)

  • msp_rand_size – range for number of jobs and machines

  • is_machine_idle – if false all machines will be connected in a graph

  • seed – seed to reproduce same data

Returns

tensorflow dataset