Searched refs:BATCH_SIZE (Results 1 – 8 of 8) sorted by relevance
| /third_party/mindspore/mindspore/lite/examples/transfer_learning/model/ |
| D | transfer_learning_export.py | 42 BATCH_SIZE = 16 variable
43 X = M.Tensor(np.ones((BATCH_SIZE, 3, 224, 224)), M.float32)
46 label = M.Tensor(np.zeros([BATCH_SIZE, 10]).astype(np.float32))
55 backbone_out = M.Tensor(np.zeros([BATCH_SIZE, 1000]).astype(np.float32))
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| /third_party/mindspore/mindspore/lite/examples/train_lenet_java/model/ |
| D | lenet_export.py | 28 BATCH_SIZE = 4 variable
29 x = Tensor(np.ones((BATCH_SIZE, 1, 32, 32)), mstype.float32)
30 label = Tensor(np.zeros([BATCH_SIZE]).astype(np.int32))
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| /third_party/mindspore/mindspore/lite/examples/unified_api/model/ |
| D | lenet_export.py | 30 BATCH_SIZE = int(sys.argv[1]) variable
31 x = Tensor(np.ones((BATCH_SIZE, 1, 32, 32)), mstype.float32)
32 label = Tensor(np.zeros([BATCH_SIZE]).astype(np.int32))
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| /third_party/mindspore/mindspore/lite/examples/train_lenet/model/ |
| D | lenet_export.py | 30 BATCH_SIZE = int(sys.argv[1]) variable
31 x = Tensor(np.ones((BATCH_SIZE, 1, 32, 32)), mstype.float32)
32 label = Tensor(np.zeros([BATCH_SIZE]).astype(np.int32))
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| /third_party/mindspore/scripts/ |
| D | get_bert_shape_from_pytest.sh | 38 export BATCH_SIZE="${batch_size}"
39 target_file="${PROJECT_PATH}/${SHP_BASENAME}.${VERSION}.${BATCH_SIZE}.shp"
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| /third_party/mindspore/mindspore/lite/examples/export_models/models/ |
| D | effnet_tune_train_export.py | 63 BATCH_SIZE = 8 variable
64 X = Tensor(np.random.randn(BATCH_SIZE, 3, 224, 224), mstype.float32)
65 label = Tensor(np.zeros([BATCH_SIZE, 10]).astype(np.float32))
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| /third_party/protobuf/js/experimental/runtime/kernel/ |
| D | textencoding.js | 17 const BATCH_SIZE = 10000;
19 const end = Math.min(i + BATCH_SIZE, length);
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| /third_party/mindspore/third_party/proto/caffe/ |
| D | caffe.proto | 468 BATCH_SIZE = 2; enumerator
473 // SigmoidCrossEntropyLoss is BATCH_SIZE and *not* VALID.
477 // normalization = BATCH_SIZE to be consistent with previous behavior.
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