/external/libtextclassifier/ |
H A D | quantization.cc | 28 void DequantizeAdd8bit(const float* scales, const uint8* embeddings, argument 36 embeddings[bucket_id * bytes_per_embedding + k]); 40 void DequantizeAddNBit(const float* scales, const uint8* embeddings, argument 50 uint16 data = embeddings[bucket_id * bytes_per_embedding + read16_offset]; 54 data |= embeddings[bucket_id * bytes_per_embedding + read16_offset + 1] 73 bool DequantizeAdd(const float* scales, const uint8* embeddings, argument 78 DequantizeAdd8bit(scales, embeddings, bytes_per_embedding, 81 DequantizeAddNBit(scales, embeddings, bytes_per_embedding,
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H A D | quantization.h | 28 // Dequantizes embeddings (quantized to 1 to 8 bits) into the floats they 32 bool DequantizeAdd(const float* scales, const uint8* embeddings,
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H A D | quantization_test.cc | 41 std::vector<uint8> embeddings{{/*0: */ 0x00, 0xFF, 0x09, 0x00, 51 DequantizeAdd(scales.data(), embeddings.data(), bytes_per_embedding, 69 DequantizeAdd(scales.data(), embeddings.data(), bytes_per_embedding, 93 std::vector<uint8> embeddings(bytes_per_embedding * num_buckets); 95 std::fill(embeddings.begin(), embeddings.end(), 0); 98 DequantizeAdd(scales.data(), embeddings.data(), bytes_per_embedding, 116 std::vector<uint8> embeddings(bytes_per_embedding * num_buckets, 0xFF); 119 DequantizeAdd(scales.data(), embeddings.data(), bytes_per_embedding, 137 std::vector<uint8> embeddings(bytes_per_embeddin [all...] |
H A D | model-executor.cc | 59 TC_LOG(ERROR) << "Could not build TFLite interpreter for embeddings."; 66 const TfLiteTensor* embeddings = interpreter->tensor(0); local 67 if (embeddings->dims->size != 2) { 70 int num_buckets = embeddings->dims->data[0]; 76 int bytes_per_embedding = embeddings->dims->data[1]; 85 embedding_size, scales, embeddings, std::move(interpreter))); 91 const TfLiteTensor* scales, const TfLiteTensor* embeddings, 99 embeddings_(embeddings), 88 TFLiteEmbeddingExecutor( std::unique_ptr<const tflite::FlatBufferModel> model, int quantization_bits, int num_buckets, int bytes_per_embedding, int output_embedding_size, const TfLiteTensor* scales, const TfLiteTensor* embeddings, std::unique_ptr<tflite::Interpreter> interpreter) argument
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H A D | model-executor.h | 118 const TfLiteTensor* embeddings,
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/external/tensorflow/tensorflow/contrib/layers/python/layers/ |
H A D | encoders.py | 41 """Maps a sequence of symbols to a vector per example by averaging embeddings. 52 initializer: An initializer for the embeddings, if `None` default for 54 regularizer: Optional regularizer for the embeddings. 63 averaging embeddings. 72 embeddings = variables.model_variable( 73 'embeddings', shape=[vocab_size, embed_dim], 82 [embeddings], sparse_ids, combiner='mean', default_id=0) 87 embedding_ops.embedding_lookup(embeddings, ids), 100 """Maps a sequence of symbols to a sequence of embeddings. 102 Typical use case would be reusing embeddings betwee [all...] |
H A D | embedding_ops.py | 89 max_norm: If not None, all embeddings are l2-normalized to max_norm before 203 """Looks up embeddings using parameter hashing for each value in `values`. 212 complexity. It also allows for us to maintain embeddings for possibly 252 """Looks up embeddings using parameter hashing for each value in `values`. 264 complexity. It also allows for us to maintain embeddings for possibly 373 """Looks up embeddings of a sparse feature using parameter hashing. 430 embeddings = scattered_embedding_lookup( 434 embeddings = math_ops.sparse_segment_sum(embeddings, idx, segment_ids, 437 embeddings [all...] |
H A D | feature_column.py | 267 """Returns arguments to look up embeddings for this column.""" 1194 """Returns embeddings for a column based on the computed arguments. 1200 trainable: whether these embeddings should be trainable. 1205 the embeddings. 1219 embeddings = contrib_variables.model_variable( 1228 embeddings, 1248 embeddings = shared_embedding_collection[0] 1249 if embeddings.get_shape() != shape: 1255 "shared embeddings.".format(args.shared_embedding_name)) 1257 embeddings [all...] |
/external/tensorflow/tensorflow/python/ops/ |
H A D | embedding_ops.py | 15 """Operations for embeddings.""" 41 This function gathers embeddings from a single tensor. The gather deals with 45 params: A `Tensor` of embeddings. 46 ids: A `Tensor` indexing the embeddings to be retrieved from `params`. 61 This function optionally clips embeddings to an l2-norm of max_norm. 64 params: A `Tensor` of embeddings retrieved by `_gather`. 66 max_norm: If provided, the embeddings are l2-normalized to the value of 113 applied to each partitioned tensor of retrieved embeddings, colocated 114 with the embeddings. This function will be called with a single `Tensor` 128 embeddings [all...] |
/external/tensorflow/tensorflow/contrib/tensorboard/plugins/projector/ |
H A D | projector_config.proto | 42 repeated EmbeddingInfo embeddings = 2;
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H A D | projector_api_test.py | 39 emb1 = config.embeddings.add()
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/external/tensorflow/tensorflow/contrib/learn/python/learn/ops/ |
H A D | embeddings_ops.py | 16 """TensorFlow Ops to work with embeddings. 18 Note: categorical variables are handled via embeddings in many cases. 40 leading dimension of the size of the embeddings. 86 embeddings = vs.get_variable(name + '_embeddings', 88 return embedding_lookup(embeddings, tensor_in)
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H A D | ops_test.py | 65 embeddings = ops.categorical_variable( 68 emb1 = sess.run(embeddings, 70 emb2 = sess.run(embeddings,
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/external/icu/icu4j/eclipse-build/plugins.template/com.ibm.icu.base/src/com/ibm/icu/text/ |
H A D | Bidi.java | 1304 // * 62 indicate embeddings. Where values are zero or not defined, the base 2197 * 62 indicate embeddings. Where values are zero or not defined, the base 2220 * The embeddings array may be null. If present, the values represent 2223 * 61 indicate embeddings. Where values are zero, the base embedding level 2231 * @param embeddings an array containing embedding values for each character 2237 * embeddings arrays. 2243 * @throws IllegalArgumentException if the values in embeddings are 2254 byte[] embeddings, 2261 this(new java.text.Bidi(text, textStart, embeddings, embStart, paragraphLength, flags)); 2252 Bidi(char[] text, int textStart, byte[] embeddings, int embStart, int paragraphLength, int flags) argument
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/external/tensorflow/tensorflow/examples/tutorials/word2vec/ |
H A D | word2vec_basic.py | 189 # Look up embeddings for inputs. 190 with tf.name_scope('embeddings'): 191 embeddings = tf.Variable( variable 193 embed = tf.nn.embedding_lookup(embeddings, train_inputs) 226 # Compute the cosine similarity between minibatch examples and all embeddings. 227 norm = tf.sqrt(tf.reduce_sum(tf.square(embeddings), 1, keep_dims=True)) 228 normalized_embeddings = embeddings / norm 300 # Write corresponding labels for the embeddings. 308 # Create a configuration for visualizing embeddings with the labels in TensorBoard. 310 embedding_conf = config.embeddings [all...] |
/external/tensorflow/tensorflow/contrib/nn/python/ops/ |
H A D | sampling_ops.py | 48 reduce_logsumexp(matmul(embeddings, 52 The computation of the first term is colocated with the embeddings using 87 def logsumexp_logit(embeddings): 89 math_ops.matmul(embeddings, reweighted_inputs, transpose_b=True), 177 has shape [num_classes, dim]. The (possibly-sharded) class embeddings. 296 [num_classes, dim]. The (possibly-sharded) class embeddings.
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/external/tensorflow/tensorflow/python/keras/_impl/keras/layers/ |
H A D | embeddings.py | 61 embeddings_initializer: Initializer for the `embeddings` matrix. 63 the `embeddings` matrix. 65 the `embeddings` matrix. 116 self.embeddings = self.add_weight( 119 name='embeddings', 156 out = K.gather(self.embeddings, inputs)
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H A D | __init__.py | 30 from tensorflow.python.keras._impl.keras.layers.embeddings import *
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H A D | serialization.py | 29 from tensorflow.python.keras._impl.keras.layers.embeddings import *
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/external/tensorflow/tensorflow/contrib/losses/python/metric_learning/ |
H A D | metric_loss_ops_test.py | 140 embeddings=ops.convert_to_tensor(embedding), 193 embeddings=ops.convert_to_tensor(embedding), 532 embeddings, labels = self._genClusters(n_samples=128, n_clusters=64) 535 embeddings, labels, margin_multiplier, enable_pam_finetuning=False) 538 embeddings=ops.convert_to_tensor(embeddings), 549 embeddings, labels = self._genClusters(n_samples=128, n_clusters=64) 552 embeddings, labels, margin_multiplier, enable_pam_finetuning=True) 555 embeddings=ops.convert_to_tensor(embeddings), [all...] |
H A D | metric_loss_ops.py | 161 def triplet_semihard_loss(labels, embeddings, margin=1.0): 164 The loss encourages the positive distances (between a pair of embeddings with 174 embeddings: 2-D float `Tensor` of embedding vectors. Embeddings should 187 pdist_matrix = pairwise_distance(embeddings, squared=True) 412 def lifted_struct_loss(labels, embeddings, margin=1.0): 415 The loss encourages the positive distances (between a pair of embeddings 417 pair of embeddings with different labels) in the mini-batch in a way 424 embeddings: 2-D float `Tensor` of embedding vectors. Embeddings should not 437 pairwise_distances = pairwise_distance(embeddings) 947 embeddings, [all...] |
/external/tensorflow/tensorflow/contrib/seq2seq/python/kernel_tests/ |
H A D | basic_decoder_test.py | 140 embeddings = np.random.randn(vocabulary_size, 143 helper = helper_py.GreedyEmbeddingHelper(embeddings, start_tokens, 192 expected_step_next_inputs = embeddings[expected_sample_ids] 216 embeddings = np.random.randn(vocabulary_size, 219 helper = helper_py.SampleEmbeddingHelper(embeddings, start_tokens, 268 expected_step_next_inputs = embeddings[sample_ids] 284 embeddings = np.random.randn( 291 embedding=embeddings, 355 embeddings[sample_ids[batch_where_sampling]])
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/external/tensorflow/tensorflow/python/kernel_tests/ |
H A D | embedding_ops_test.py | 15 """Functional tests for ops used with embeddings.""" 260 embeddings = constant_op.constant([[2.0]]) 264 [embeddings], ids, max_norm=1.0) 270 embeddings = constant_op.constant([[2.0, 4.0], [3.0, 1.0]]) 274 [embeddings], ids, max_norm=2.0) 277 math_ops.reduce_sum(embeddings * embeddings, axis=1)) 278 normalized = embeddings / array_ops.stack([norms, norms], axis=1) 336 # Fetch num_vals embeddings for random word ids. Since 358 # Fetch num_vals embeddings fo [all...] |
/external/icu/android_icu4j/src/main/tests/android/icu/dev/test/bidi/ |
H A D | TestBidi.java | 585 byte[] embeddings = new byte[2]; // all 0 587 Bidi bidi = new Bidi(text.toCharArray(), 0, embeddings, 0, text.length(), flags); 592 java.text.Bidi jb = new java.text.Bidi(text.toCharArray(), 0, embeddings, 0, text.length(), flags);
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/external/icu/icu4j/main/tests/core/src/com/ibm/icu/dev/test/bidi/ |
H A D | TestBidi.java | 582 byte[] embeddings = new byte[2]; // all 0 584 Bidi bidi = new Bidi(text.toCharArray(), 0, embeddings, 0, text.length(), flags); 589 java.text.Bidi jb = new java.text.Bidi(text.toCharArray(), 0, embeddings, 0, text.length(), flags);
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