(lbann, weekly)
| 103 | file = inspect.getfile(f) |
| 104 | |
| 105 | def setup_func(lbann, weekly): |
| 106 | # Get minibatch size from tensor |
| 107 | mini_batch_size = tester.input_tensor.shape[0] |
| 108 | |
| 109 | # Save combined input/reference data to file |
| 110 | work_dir = _get_work_dir(file) |
| 111 | os.makedirs(work_dir, exist_ok=True) |
| 112 | if tester.reference_tensor is not None: |
| 113 | flat_inp = tester.input_tensor.reshape(mini_batch_size, -1) |
| 114 | flat_ref = tester.reference_tensor.reshape( |
| 115 | mini_batch_size, -1) |
| 116 | np.save(os.path.join(work_dir, 'data.npy'), |
| 117 | np.concatenate((flat_inp, flat_ref), axis=1)) |
| 118 | else: |
| 119 | np.save(os.path.join(work_dir, 'data.npy'), |
| 120 | tester.input_tensor.reshape(mini_batch_size, -1)) |
| 121 | |
| 122 | # Setup data reader |
| 123 | data_reader = lbann.reader_pb2.DataReader() |
| 124 | data_reader.reader.extend([ |
| 125 | tools.create_python_data_reader( |
| 126 | lbann, single_tensor_data_reader.__file__, |
| 127 | 'get_sample', 'num_samples', 'sample_dims', 'train') |
| 128 | ]) |
| 129 | if not train: |
| 130 | data_reader.reader.extend([ |
| 131 | tools.create_python_data_reader( |
| 132 | lbann, single_tensor_data_reader.__file__, |
| 133 | 'get_sample', 'num_samples', 'sample_dims', 'test') |
| 134 | ]) |
| 135 | |
| 136 | trainer = lbann.Trainer(mini_batch_size) |
| 137 | optimizer = lbann.SGD(learn_rate=0) |
| 138 | return trainer, model, data_reader, optimizer, None # Don't request any specific number of nodes |
| 139 | |
| 140 | test = tools.create_tests(setup_func, file, **decorator_kwargs)[0] |
| 141 | cluster = kwargs.get('cluster', None) |
no test coverage detected