| /third_party/mindspore/tests/ut/python/dataset/ |
| D | test_batch.py | 31 drop_remainder = True
35 data1 = data1.batch(batch_size, drop_remainder)
49 drop_remainder = True
53 data1 = data1.batch(batch_size, drop_remainder=drop_remainder)
67 drop_remainder = False
71 data1 = data1.batch(batch_size=batch_size, drop_remainder=drop_remainder)
85 drop_remainder = False
89 data1 = data1.batch(batch_size, drop_remainder)
120 drop_remainder = False
124 data1 = data1.batch(drop_remainder=drop_remainder, batch_size=batch_size)
[all …]
|
| D | test_pad_batch.py | 63 …data1 = data1.batch(batch_size=2, drop_remainder=False, pad_info={"col2d": ([2, 2], -2), "col1d": …
72 data1 = data1.batch(batch_size=2, drop_remainder=False, pad_info={"col2d": ([1, 2], -2)})
81 …data1 = data1.batch(batch_size=2, drop_remainder=False, pad_info={"col": (None, -1)}) # pad autom…
94 data1 = data1.batch(batch_size=2, drop_remainder=False, pad_info={}) # pad automatically
103 data1 = data1.batch(batch_size=3, drop_remainder=False,
117 data1 = data1.batch(batch_size=24, drop_remainder=True, pad_info=pad_info)
133 data1 = data1.batch(batch_size=24, drop_remainder=True, pad_info=pad_info)
149 data1 = data1.batch(batch_size=24, drop_remainder=True)
164 data1 = data1.batch(batch_size=24, drop_remainder=True)
181 data1 = data1.batch(batch_size=25, drop_remainder=True)
[all …]
|
| D | test_mixup_op.py | 42 ds_original = ds_original.batch(5, drop_remainder=True)
57 data1 = data1.batch(5, drop_remainder=True)
86 ds_original = ds_original.batch(4, pad_info={}, drop_remainder=True)
105 data1 = data1.batch(4, pad_info={}, drop_remainder=True)
133 ds_original = ds_original.batch(5, drop_remainder=True)
148 data1 = data1.batch(5, drop_remainder=True)
178 ds_original = ds_original.batch(2, drop_remainder=True)
197 data1 = data1.batch(2, drop_remainder=True)
230 data = data.batch(5, drop_remainder=True)
313 ds_original = ds_original.batch(5, drop_remainder=True)
[all …]
|
| D | test_cutmix_batch_op.py | 42 ds_original = ds_original.batch(5, drop_remainder=True)
58 data1 = data1.batch(5, drop_remainder=True)
85 ds_original = ds_original.batch(5, drop_remainder=True)
101 data1 = data1.batch(5, drop_remainder=True)
131 ds_original = ds_original.batch(4, pad_info={}, drop_remainder=True)
153 data1 = data1.batch(4, pad_info={}, drop_remainder=True)
183 ds_original = ds_original.batch(2, drop_remainder=True)
205 data1 = data1.batch(2, drop_remainder=True)
238 data = data.batch(5, drop_remainder=True)
264 data = data.batch(5, drop_remainder=True)
[all …]
|
| D | test_2ops.py | 76 data1 = data1.batch(batch_size, drop_remainder=True)
93 data1 = data1.batch(batch_size, drop_remainder=True)
112 data1 = data1.batch(batch_size, drop_remainder=True)
134 data1 = data1.batch(batch_size, drop_remainder=True)
|
| D | test_deviceop_cpu.py | 61 data = data.batch(batch_size, drop_remainder=True)
86 data = data.batch(batch_size, drop_remainder=True)
116 data = data.batch(batch_size, drop_remainder=True)
|
| D | test_tensor_string.py | 80 data = data.batch(2, drop_remainder=True)
232 …data1 = data1.batch(batch_size=2, drop_remainder=False, pad_info={"col2d": ([2, 2], b"-2"), "col1d…
242 data1 = data1.batch(batch_size=2, drop_remainder=False, pad_info={"col2d": ([1, 2], "")})
251 …data1 = data1.batch(batch_size=2, drop_remainder=False, pad_info={"col": (None, "PAD_VALUE")}) # …
264 data1 = data1.batch(batch_size=2, drop_remainder=False, pad_info={}) # pad automatically
273 data1 = data1.batch(batch_size=3, drop_remainder=False,
|
| D | test_repeat.py | 84 data1 = data1.batch(batch_size, drop_remainder=True)
204 data = data.batch(2, drop_remainder=False)
267 data1 = data1.batch(batch_size, drop_remainder=False)
289 data1 = data1.batch(batch_size, drop_remainder=False)
|
| D | test_var_batch_map.py | 83 … drop_remainder=drop)
91 … .batch(batch_size=func, drop_remainder=drop, input_columns=["num"], per_batch_map=simple_copy)
97 …neratorDataset((lambda: gen(gen_num)), ["num"]).batch(batch_size=func, drop_remainder=drop).repeat(
106 ….batch(batch_size=func, drop_remainder=drop, input_columns=["num"], per_batch_map=simple_copy).rep…
277 …data1 = data1.batch(batch_size=add_one, drop_remainder=True, input_columns=["image"], per_batch_ma…
|
| D | test_sync_wait.py | 120 dataset = dataset.batch(batch_size, drop_remainder=True)
143 dataset = dataset.batch(batch_size, drop_remainder=True)
150 dataset2 = dataset2.batch(batch_size, drop_remainder=True)
|
| D | test_get_size.py | 106 data = ds.TFRecordDataset(FILES, num_samples=10).batch(3, drop_remainder=True)
108 data = ds.TFRecordDataset(FILES, num_samples=10).batch(3, drop_remainder=False)
|
| D | test_mixup_label_smoothing.py | 78 ds1 = ds1.batch(batch_size, drop_remainder=True)
128 ds1 = ds1.batch(batch_size, drop_remainder=True)
|
| /third_party/mindspore/tests/st/fl/albert/src/ |
| D | dataset.py | 79 drop_remainder=True, output_dir=None, i=0, cyclic_trunc=False): argument
90 … do_shuffle=do_shuffle, drop_remainder=drop_remainder, cyclic_trunc=cyclic_trunc)
101 drop_remainder=True, output_dir=None, cyclic_trunc=False): argument
116 … do_shuffle=do_shuffle, drop_remainder=drop_remainder, cyclic_trunc=cyclic_trunc)
127 drop_remainder=True, cyclic_trunc=False): argument
146 dataset = dataset.batch(batch_size=batch_size, drop_remainder=drop_remainder)
|
| /third_party/mindspore/mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/ |
| D | batch_node.cc | 33 BatchNode::BatchNode(std::shared_ptr<DatasetNode> child, int32_t batch_size, bool drop_remainder, b… in BatchNode() argument
39 drop_remainder_(drop_remainder), in BatchNode()
52 BatchNode::BatchNode(std::shared_ptr<DatasetNode> child, int32_t batch_size, bool drop_remainder) in BatchNode() argument
53 : batch_size_(batch_size), drop_remainder_(drop_remainder), pad_(false) { in BatchNode()
180 bool drop_remainder = json_obj["drop_remainder"]; in from_json() local
181 *result = std::make_shared<BatchNode>(ds, batch_size, drop_remainder); in from_json()
|
| D | batch_node.h | 36 BatchNode(std::shared_ptr<DatasetNode> child, int32_t batch_size, bool drop_remainder, bool pad,
43 BatchNode(std::shared_ptr<DatasetNode> child, int32_t batch_size, bool drop_remainder);
|
| D | bucket_batch_by_length_node.cc | 36 bool drop_remainder) in BucketBatchByLengthNode() argument
43 drop_remainder_(drop_remainder) { in BucketBatchByLengthNode()
|
| /third_party/mindspore/tests/st/data_transfer/ |
| D | test_tdt_data_transfer.py | 32 … drop_remainder=True, usage=None, shuffle=False, num_workers=8, resize_size=32, pad_info=None): argument
48 …ds = ds.batch(batch_size, drop_remainder=drop_remainder, num_parallel_workers=num_workers, pad_inf…
|
| /third_party/mindspore/tests/st/model_zoo_tests/yolov3_darknet53/src/ |
| D | yolo_dataset.py | 173 num_parallel_workers=min(32, num_parallel_workers), drop_remainder=True)
177 num_parallel_workers=min(8, num_parallel_workers), drop_remainder=True)
187 ds = ds.batch(batch_size, drop_remainder=True)
|
| /third_party/mindspore/tests/st/model_zoo_tests/wide_and_deep/python_file_for_ci/ |
| D | datasets.py | 57 drop_remainder=True)
99 data_set = data_set.batch(int(batch_size / line_per_sample), drop_remainder=True)
|
| /third_party/mindspore/mindspore/ccsrc/minddata/dataset/engine/datasetops/ |
| D | bucket_batch_by_length_op.cc | 36 bool pad_to_bucket_boundary, bool drop_remainder, in BucketBatchByLengthOp() argument
45 drop_remainder_(drop_remainder), in BucketBatchByLengthOp()
|
| D | bucket_batch_by_length_op.h | 41 … bool pad_to_bucket_boundary, bool drop_remainder, int32_t op_connector_size);
|
| /third_party/mindspore/mindspore/ccsrc/minddata/dataset/api/python/bindings/dataset/engine/ir/datasetops/ |
| D | bindings.cc | 99 … .def(py::init([](std::shared_ptr<DatasetNode> self, int32_t batch_size, bool drop_remainder, in __anon4440814b0802()
111 self, batch_size, drop_remainder, pad, toStringVector(in_col_names), in __anon4440814b0802()
124 bool drop_remainder) { in __anon4440814b0a02() argument
131 pad_to_bucket_boundary, drop_remainder); in __anon4440814b0a02()
|
| /third_party/mindspore/tests/st/quantization/mobilenetv2_quant/ |
| D | dataset.py | 62 cifar_ds = cifar_ds.batch(batch_size, drop_remainder=True)
|
| /third_party/mindspore/tests/st/quantization/resnet50_quant/ |
| D | dataset.py | 62 data_set = data_set.batch(batch_size, drop_remainder=True)
|
| /third_party/mindspore/tests/st/summary/ |
| D | dataset.py | 50 mnist_ds = mnist_ds.batch(batch_size=batch_size, drop_remainder=True)
|