Searched refs:embedding_indices (Results 1 – 18 of 18) sorted by relevance
321 embedding_indices, argument364 embedding_indices=embedding_indices,378 embedding_indices, argument441 embedding_indices=embedding_indices,458 embedding_indices, argument521 embedding_indices=embedding_indices,
8 embedding_indices and aggregation_weights into rows.14 name: "embedding_indices"63 embedding_indices and aggregation_weights.68 sample_splits[i], embedding_indices[i] and aggregation_weights[i] correspond73 embedding_indices and aggregation_weights, must have the same shape, i.e. rank 1
8 which the corresponding embedding_indices and aggregation_weights values13 name: "embedding_indices"61 embedding_indices and aggregation_weights.66 sample_indices[i], embedding_indices[i] and aggregation_weights[i] correspond71 embedding_indices and aggregation_weights) must have the same shape, i.e. rank 1
8 feature to which the corresponding embedding_indices and aggregation_weights15 name: "embedding_indices"
9 name: "embedding_indices"57 name: "embedding_indices"144 name: "embedding_indices"239 name: "embedding_indices"
9 name: "embedding_indices"53 name: "embedding_indices"
9 name: "embedding_indices"104 name: "embedding_indices"
9 name: "embedding_indices"57 name: "embedding_indices"144 name: "embedding_indices"
9 name: "embedding_indices"
189 embedding_indices, argument213 return super(EnqueueData, cls).__new__(cls, embedding_indices,231 embedding_indices, argument255 cls).__new__(cls, embedding_indices, sample_splits,1665 data.device != enqueue_data.embedding_indices.device):1722 device = enqueue_data.embedding_indices.device1725 if device != enqueue_data.embedding_indices.device:1730 enqueue_data.embedding_indices.device, feature,1751 with ops.colocate_with(enqueue_data0.embedding_indices):1798 kwargs['embedding_indices'].append(enqueue_data.embedding_indices)[all …]
1019 embedding_indices=values,1028 embedding_indices=values,
3744 sample_splits[i], embedding_indices[i] and aggregation_weights[i] correspond3749 embedding_indices and aggregation_weights, must have the same shape, i.e. rank 13756 embedding_indices and aggregation_weights into rows.3760 …corresponds to ids.values in embedding_lookup(), when ids is a RaggedTensor.}]>:$embedding_indices,3804 feature to which the corresponding embedding_indices and aggregation_weights3808 …OrI64Tensor>, [{A list of rank 1 Tensors, indices into the embedding tables.}]>:$embedding_indices,3834 sample_indices[i], embedding_indices[i] and aggregation_weights[i] correspond3839 embedding_indices and aggregation_weights) must have the same shape, i.e. rank 13846 which the corresponding embedding_indices and aggregation_weights values3849 It corresponds to sp_ids.values in embedding_lookup_sparse().}]>:$embedding_indices,
1349 …argspec: "args=[\'sample_splits\', \'embedding_indices\', \'aggregation_weights\', \'mode_override…1353 …argspec: "args=[\'sample_indices\', \'embedding_indices\', \'aggregation_weights\', \'mode_overrid…1357 …argspec: "args=[\'sample_indices\', \'embedding_indices\', \'aggregation_weights\', \'mode_overrid…
40494 func EnqueueTPUEmbeddingSparseBatch(scope *Scope, sample_indices []tf.Output, embedding_indices []t…40505 …tf.OutputList(sample_indices), tf.OutputList(embedding_indices), tf.OutputList(aggregation_weights…48796 …mbeddingSparseTensorBatch(scope *Scope, sample_indices []tf.Output, embedding_indices []tf.Output,…48807 …tf.OutputList(sample_indices), tf.OutputList(embedding_indices), tf.OutputList(aggregation_weights…52102 …EmbeddingRaggedTensorBatch(scope *Scope, sample_splits []tf.Output, embedding_indices []tf.Output,…52113 …tf.OutputList(sample_splits), tf.OutputList(embedding_indices), tf.OutputList(aggregation_weights)…
14018 name: "embedding_indices"14121 name: "embedding_indices"14204 name: "embedding_indices"
22218 name: "embedding_indices"22262 name: "embedding_indices"22345 name: "embedding_indices"22393 name: "embedding_indices"