| /external/tensorflow/tensorflow/lite/kernels/ctc/ |
| D | ctc_decoder.h | 43 CTCDecoder(int num_classes, int batch_size, bool merge_repeated) in CTCDecoder()
61 int num_classes() { return num_classes_; } in num_classes() function
74 CTCGreedyDecoder(int num_classes, int batch_size, bool merge_repeated) in CTCGreedyDecoder()
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| /external/tensorflow/tensorflow/core/util/ctc/ |
| D | ctc_decoder.h | 46 CTCDecoder(int num_classes, int batch_size, bool merge_repeated) in CTCDecoder()
64 int num_classes() { return num_classes_; } in num_classes() function
79 CTCGreedyDecoder(int num_classes, int batch_size, bool merge_repeated) in CTCGreedyDecoder()
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| D | ctc_beam_search_test.cc | 109 const int num_classes = 6; in ctc_beam_search_decoding_with_and_without_dictionary() local
199 const int num_classes = 6; in ctc_beam_search_decoding_all_beam_elements_have_finite_scores() local
277 const int num_classes = 6; in ctc_beam_search_label_selection() local
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| /external/tensorflow/tensorflow/python/ops/ |
| D | confusion_matrix.py | 94 num_classes=None, argument
202 num_classes=None, argument
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| D | nn_impl.py | 1830 num_classes, argument
2017 num_classes, argument
2122 num_classes, argument
2234 num_classes, argument
2326 num_classes, argument
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| /external/tensorflow/tensorflow/python/keras/ |
| D | testing_utils.py | 60 num_classes, argument
422 def get_small_sequential_mlp(num_hidden, num_classes, input_dim=None): argument
433 def get_small_functional_mlp(num_hidden, num_classes, input_dim): argument
446 num_classes, argument
474 def __init__(self, num_hidden, num_classes): argument
491 def get_small_subclass_mlp(num_hidden, num_classes): argument
495 def get_small_subclass_mlp_with_custom_build(num_hidden, num_classes): argument
499 def get_small_mlp(num_hidden, num_classes, input_dim): argument
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | in_topk_op_gpu.cu.cc | 43 int num_targets, int num_classes) { in ComputePredictionMaskKernel()
96 const Eigen::Index num_classes = predictions.dimension(1); in operator ()() local
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| D | softmax_op_functor.h | 50 const int num_classes = logits.dimension(kClassDim); in Compute() local
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| D | xent_op.h | 70 const int num_classes = shape[kClassDim]; in Compute() local
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| D | xent_op_test.cc | 25 static Graph* Xent(int batch_size, int num_classes, DataType type) { in Xent()
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| D | multinomial_op_test.cc | 27 static Graph* Multinomial(int batch_size, int num_classes, int num_samples) { in Multinomial()
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| D | one_hot_op_test.cc | 25 static Graph* OneHot(int batch_size, int num_classes, int axis) { in OneHot()
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| D | sparse_xent_op_test.cc | 27 static Graph* SparseXent(int batch_size, int num_classes, DataType type) { in SparseXent()
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| D | in_topk_op_test.cc | 36 static Graph* InTopK(int num_targets, int num_classes, T top_k) { in InTopK()
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| /external/pytorch/benchmarks/functional_autograd_benchmark/ |
| D | torchvision_models.py | 150 num_classes=1000, argument
420 def _segm_resnet(name, backbone_name, num_classes, aux, pretrained_backbone=True): argument
453 arch_type, backbone, pretrained, progress, num_classes, aux_loss, **kwargs argument
470 pretrained=False, progress=True, num_classes=21, aux_loss=None, **kwargs argument
499 num_classes, argument
668 def __init__(self, num_classes, matcher, weight_dict, eos_coef, losses): argument
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| /external/pytorch/aten/src/ATen/native/ |
| D | Onehot.cpp | 17 Tensor one_hot(const Tensor &self, int64_t num_classes) { in one_hot()
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| /external/tensorflow/tensorflow/python/keras/utils/ |
| D | np_utils.py | 22 def to_categorical(y, num_classes=None, dtype='float32'): argument
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| /external/pytorch/test/ |
| D | test_expanded_weights.py | 478 def convnet(num_classes, num_dim): argument
501 def convnet(num_classes, num_dim): argument
527 def instance_norm_model(num_classes, num_dim): argument
553 def group_norm_model(num_classes, num_dim): argument
572 def layer_norm_model(num_classes, num_dim): argument
590 def embedding_model(num_classes, num_embedding): argument
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| /external/tensorflow/tensorflow/python/ops/numpy_ops/integration_test/benchmarks/ |
| D | numpy_mlp.py | 30 def __init__(self, num_classes=NUM_CLASSES, input_size=INPUT_SIZE, argument
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| D | tf_numpy_mlp.py | 32 def __init__(self, num_classes=NUM_CLASSES, input_size=INPUT_SIZE, argument
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| /external/pytorch/test/onnx/model_defs/ |
| D | squeezenet.py | 31 def __init__(self, version=1.0, num_classes=1000, ceil_mode=False): argument
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| /external/ComputeLibrary/src/cpu/kernels/boundingboxtransform/generic/neon/ |
| D | impl.cpp | 32 const size_t num_classes = deltas->info()->tensor_shape()[0] >> 2; in bounding_box_transform_qsymm16() local
89 const size_t num_classes = deltas->info()->tensor_shape()[0] >> 2; in bounding_box_transform() local
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| /external/armnn/tests/TfLiteYoloV3Big-Armnn/ |
| D | NMS.hpp | 14 unsigned int num_classes{0}; /**< Number of classes in the detected boxes */ member
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| /external/executorch/examples/mediatek/eval_utils/ |
| D | eval_oss_result.py | 119 def make_confusion(goldens, predictions, num_classes): argument
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| /external/tensorflow/tensorflow/compiler/mlir/tfr/examples/mnist/ |
| D | mnist_train.py | 32 num_classes = 10 # total classes (0-9 digits). variable
|