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Searched refs:BATCH_SIZE (Results 1 – 14 of 14) sorted by relevance

/external/tensorflow/tensorflow/python/keras/wrappers/
Dscikit_learn_test.py32 BATCH_SIZE = 5 variable
57 clf.fit(x_train, y_train, batch_size=BATCH_SIZE, epochs=EPOCHS)
59 score = clf.score(x_train, y_train, batch_size=BATCH_SIZE)
62 preds = clf.predict(x_test, batch_size=BATCH_SIZE)
67 proba = clf.predict_proba(x_test, batch_size=BATCH_SIZE)
93 reg.fit(x_train, y_train, batch_size=BATCH_SIZE, epochs=EPOCHS)
95 score = reg.score(x_train, y_train, batch_size=BATCH_SIZE)
98 preds = reg.predict(x_test, batch_size=BATCH_SIZE)
109 batch_size=BATCH_SIZE,
125 batch_size=BATCH_SIZE,
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/external/tensorflow/tensorflow/python/keras/
Dcallbacks_v1_test.py41 BATCH_SIZE = 5 variable
63 max_batch_index = len(x_train) // BATCH_SIZE
65 max_batch_index = len(x_test) // BATCH_SIZE
69 yield (x_train[i * BATCH_SIZE:(i + 1) * BATCH_SIZE],
70 y_train[i * BATCH_SIZE:(i + 1) * BATCH_SIZE])
72 yield (x_test[i * BATCH_SIZE:(i + 1) * BATCH_SIZE],
73 y_test[i * BATCH_SIZE:(i + 1) * BATCH_SIZE])
102 batch_size=BATCH_SIZE,
112 batch_size=BATCH_SIZE,
172 max_batch_index = len(x_train) // BATCH_SIZE
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Dcallbacks_test.py60 BATCH_SIZE = 5 variable
313 batch_size=BATCH_SIZE,
333 batch_size=BATCH_SIZE,
354 batch_size=BATCH_SIZE,
374 batch_size=BATCH_SIZE,
392 batch_size=BATCH_SIZE,
417 batch_size=BATCH_SIZE,
467 batch_size=BATCH_SIZE,
586 batch_size=BATCH_SIZE,
603 batch_size=BATCH_SIZE,
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/external/libaom/libaom/common/
Drawenc.c15 #define BATCH_SIZE 8 macro
18 static const uint8_t batched[BATCH_SIZE] = { 128, 128, 128, 128,
20 static const uint8_t batched_hbd[BATCH_SIZE] = {
48 high_bitdepth ? n / (BATCH_SIZE / 2) : n / BATCH_SIZE; in write_greyscale()
50 writer_func(file_or_md5, b, sizeof(uint8_t), BATCH_SIZE); in write_greyscale()
52 const int remaining = high_bitdepth ? n % (BATCH_SIZE / 2) : n % BATCH_SIZE; in write_greyscale()
/external/tensorflow/tensorflow/python/kernel_tests/
Dcandidate_sampler_ops_test.py34 BATCH_SIZE = 3 variable in RangeSamplerOpsTest
47 true_candidates_vec, [self.BATCH_SIZE, self.NUM_TRUE])
75 self.assertAllEqual(result, [[0.0] * self.NUM_TRUE] * self.BATCH_SIZE)
77 [self.BATCH_SIZE, self.NUM_TRUE])
79 [self.BATCH_SIZE, self.NUM_TRUE])
/external/tensorflow/tensorflow/contrib/eager/python/examples/rnn_ptb/
Drnn_ptb_graph_test.py62 BATCH_SIZE = 20 variable in PTBBenchmark
83 [PTBBenchmark.SEQ_LEN, PTBBenchmark.BATCH_SIZE],
100 tf.test.gpu_device_name(), PTBBenchmark.BATCH_SIZE)
123 [PTBBenchmark.SEQ_LEN, PTBBenchmark.BATCH_SIZE],
145 tf.test.gpu_device_name(), PTBBenchmark.BATCH_SIZE)
Drnn_ptb_test.py60 BATCH_SIZE = 20 variable in PTBBenchmark
79 [PTBBenchmark.SEQ_LEN, PTBBenchmark.BATCH_SIZE], dtype=tf.int64)
117 [PTBBenchmark.SEQ_LEN, PTBBenchmark.BATCH_SIZE], dtype=tf.int64)
/external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/
Dcifar10_pruning.py53 BATCH_SIZE = 128 variable
145 data_dir=data_dir, batch_size=BATCH_SIZE)
166 eval_data=eval_data, data_dir=data_dir, batch_size=BATCH_SIZE)
235 reshape = tf.reshape(pool2, [BATCH_SIZE, -1])
338 num_batches_per_epoch = NUM_EXAMPLES_PER_EPOCH_FOR_TRAIN / BATCH_SIZE
/external/tensorflow/tensorflow/contrib/distribute/python/
Destimator_training_test.py56 BATCH_SIZE = 10 variable
59 0., 2., BATCH_SIZE * LABEL_DIMENSION, dtype=np.float32).reshape(
60 BATCH_SIZE, LABEL_DIMENSION)
169 batch_size=BATCH_SIZE // train_distribute.num_replicas_in_sync,
172 eval_batch_size = BATCH_SIZE // eval_distribute.num_replicas_in_sync
174 eval_batch_size = BATCH_SIZE
244 }).batch(BATCH_SIZE)
250 self.assertAllEqual((BATCH_SIZE, LABEL_DIMENSION), predicted_proba.shape)
/external/tensorflow/tensorflow/contrib/layers/python/layers/
Drev_block_lib_test.py43 BATCH_SIZE = 16 variable in RevBlockTest
54 [self.BATCH_SIZE, self.CHANNELS], dtype=dtypes.float32)
77 [self.BATCH_SIZE, self.CHANNELS], dtype=dtypes.float32)
117 [self.BATCH_SIZE, self.CHANNELS], dtype=dtypes.float32)
166 [self.BATCH_SIZE, self.CHANNELS // 2])
187 [self.BATCH_SIZE, 10, self.CHANNELS], dtype=dtypes.float32)
207 [self.BATCH_SIZE, self.CHANNELS], dtype=dtypes.float32)
/external/tensorflow/tensorflow/contrib/eager/python/examples/nmt_with_attention/
Dnmt_with_attention.ipynb329 "BATCH_SIZE = 64\n",
330 "N_BATCH = BUFFER_SIZE//BATCH_SIZE\n",
337 "dataset = dataset.batch(BATCH_SIZE, drop_remainder=True)"
506 "encoder = Encoder(vocab_inp_size, embedding_dim, units, BATCH_SIZE)\n",
507 "decoder = Decoder(vocab_tar_size, embedding_dim, units, BATCH_SIZE)"
610 …" dec_input = tf.expand_dims([targ_lang.word2idx['<start>']] * BATCH_SIZE, 1) \n",
/external/tensorflow/tensorflow/tools/docker/notebooks/
D3_mnist_from_scratch.ipynb985 "BATCH_SIZE = 60\n",
996 " shape=(BATCH_SIZE, IMAGE_SIZE, IMAGE_SIZE, NUM_CHANNELS))\n",
998 " shape=(BATCH_SIZE, NUM_LABELS))\n",
1225 " batch * BATCH_SIZE, # Current index into the dataset.\n",
1358 "BATCH_SIZE = 60\n",
1360 "# Grab the first BATCH_SIZE examples and labels.\n",
1361 "batch_data = train_data[:BATCH_SIZE, :, :, :]\n",
1362 "batch_labels = train_labels[:BATCH_SIZE]\n",
1510 "# But, predictions is actually a list of BATCH_SIZE probability vectors.\n",
1823 "steps = train_size // BATCH_SIZE\n",
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/external/tensorflow/tensorflow/core/kernels/
Dnn_ops_test.cc1284 #define BM_ImageNetSoftmaxFwd(BATCH_SIZE, NODE_DEPTH, TH, GPU, LABEL) \ argument
1286 BM_ImageNetSoftmaxFwd_##BATCH_SIZE##_##NODE_DEPTH##_##TH##_##GPU( \
1288 BM_ImageNetSoftmaxFwd(iters, BATCH_SIZE, NODE_DEPTH, TH, GPU, LABEL); \
1290 BENCHMARK(BM_ImageNetSoftmaxFwd_##BATCH_SIZE##_##NODE_DEPTH##_##TH##_##GPU)
/external/tensorflow/tensorflow/python/framework/
Dfunction_test.py1488 BATCH_SIZE = 16 variable in UnrollLSTMTest
1498 [self.NUM_UNROLL, self.BATCH_SIZE, self.LSTM_DIMS], seed=654321)