| /external/tensorflow/tensorflow/python/util/ |
| future_api.py | 25 import tensorflow as tf
28 delattr(tf, 'arg_max')
29 delattr(tf, 'arg_min')
30 delattr(tf, 'create_partitioned_variables')
31 delattr(tf, 'deserialize_many_sparse')
32 delattr(tf, 'lin_space')
33 delattr(tf, 'parse_single_sequence_example')
34 delattr(tf, 'serialize_many_sparse')
35 delattr(tf, 'serialize_sparse')
36 delattr(tf, 'sparse_matmul') # Use tf.matmul instead
[all...] |
| future_api_test.py | 20 import tensorflow as tf
27 class ExampleParserConfigurationTest(tf.test.TestCase):
30 self.assertFalse(hasattr(tf, 'arg_max'))
31 self.assertTrue(hasattr(tf, 'argmax'))
35 tf.test.main()
|
| /toolchain/binutils/binutils-2.27/gold/testsuite/ |
| testmain.cc | 36 Test_framework tf; local
37 Register_test::run_tests(&tf);
39 exit(tf.failures());
|
| /external/tensorflow/tensorflow/examples/tutorials/mnist/ |
| mnist_deep.py | 35 import tensorflow as tf
56 with tf.name_scope('reshape'):
57 x_image = tf.reshape(x, [-1, 28, 28, 1])
60 with tf.name_scope('conv1'):
63 h_conv1 = tf.nn.relu(conv2d(x_image, W_conv1) + b_conv1)
66 with tf.name_scope('pool1'):
70 with tf.name_scope('conv2'):
73 h_conv2 = tf.nn.relu(conv2d(h_pool1, W_conv2) + b_conv2)
76 with tf.name_scope('pool2'):
81 with tf.name_scope('fc1')
[all...] |
| mnist.py | 35 import tensorflow as tf
57 with tf.name_scope('hidden1'):
58 weights = tf.Variable(
59 tf.truncated_normal([IMAGE_PIXELS, hidden1_units],
62 biases = tf.Variable(tf.zeros([hidden1_units]),
64 hidden1 = tf.nn.relu(tf.matmul(images, weights) + biases)
66 with tf.name_scope('hidden2'):
67 weights = tf.Variable
[all...] |
| mnist_with_summaries.py | 18 tf.name_scope to make a graph legible in the TensorBoard graph explorer, and of
31 import tensorflow as tf
43 sess = tf.InteractiveSession()
47 with tf.name_scope('input'):
48 x = tf.placeholder(tf.float32, [None, 784], name='x-input')
49 y_ = tf.placeholder(tf.int64, [None], name='y-input')
51 with tf.name_scope('input_reshape'):
52 image_shaped_input = tf.reshape(x, [-1, 28, 28, 1]
[all...] |
| mnist_softmax.py | 29 import tensorflow as tf
39 x = tf.placeholder(tf.float32, [None, 784])
40 W = tf.Variable(tf.zeros([784, 10]))
41 b = tf.Variable(tf.zeros([10]))
42 y = tf.matmul(x, W) + b
45 y_ = tf.placeholder(tf.int64, [None]
[all...] |
| mnist_softmax_xla.py | 25 import tensorflow as tf
38 x = tf.placeholder(tf.float32, [None, 784])
39 w = tf.Variable(tf.zeros([784, 10]))
40 b = tf.Variable(tf.zeros([10]))
41 y = tf.matmul(x, w) + b
44 y_ = tf.placeholder(tf.int64, [None]
[all...] |
| /external/clang/test/PCH/ |
| headersearch.cpp | 10 // RUN: echo 'template <typename T> void tf() { orig_sub2_1(); T::foo(); }' >> %t_orig/sub2/orig_sub2.h
44 tf<int>();
|
| missing-file.cpp | 5 // RUN: echo 'template <typename T> void tf() { T::foo(); }' >> %t.h
24 tf<int>();
|
| /external/tensorflow/tensorflow/examples/adding_an_op/ |
| fact_test.py | 21 import tensorflow as tf
24 class FactTest(tf.test.TestCase):
28 print(tf.user_ops.my_fact().eval())
32 tf.test.main()
|
| cuda_op.py | 22 import tensorflow as tf
24 if tf.test.is_built_with_cuda():
25 _cuda_op_module = tf.load_op_library(os.path.join(
26 tf.resource_loader.get_data_files_path(), 'cuda_op_kernel.so'))
|
| zero_out_op_1.py | 22 import tensorflow as tf
24 _zero_out_module = tf.load_op_library(
25 os.path.join(tf.resource_loader.get_data_files_path(),
|
| zero_out_op_3.py | 22 import tensorflow as tf
24 _zero_out_module = tf.load_op_library(
25 os.path.join(tf.resource_loader.get_data_files_path(),
|
| /external/curl/packages/vms/ |
| config_h.com | 171 $ write tf ""
172 $ write tf -
174 $ write tf -
176 $ write tf -
180 $ write tf -
183 $ write tf -
185 $ write tf ""
256 $ write tf ""
267 $ write tf line_in
293 $ write tf "/* ", xline, " */
[all...] |
| /external/tensorflow/tensorflow/examples/speech_commands/ |
| models.py | 24 import tensorflow as tf
122 saver = tf.train.Saver(tf.global_variables())
152 dropout_prob = tf.placeholder(tf.float32, name='dropout_prob')
155 weights = tf.Variable(
156 tf.truncated_normal([fingerprint_size, label_count], stddev=0.001))
157 bias = tf.Variable(tf.zeros([label_count]))
158 logits = tf.matmul(fingerprint_input, weights) + bia
[all...] |
| /external/tensorflow/tensorflow/tools/compatibility/testdata/ |
| test_file_v0_11.py | 15 """Tests for tf upgrader."""
23 import tensorflow as tf
46 tf.reduce_any(
49 tf.reduce_all(
52 tf.reduce_all(
55 tf.reduce_sum(
58 tf.reduce_sum(
60 self.assertAllEqual(tf.reduce_sum(a, [0, 1]).eval(), 21.0)
62 tf.reduce_prod(
65 tf.reduce_prod
[all...] |
| /external/tensorflow/tensorflow/examples/saved_model/ |
| saved_model_half_plus_two.py | 46 import tensorflow as tf
68 tf.compat.as_bytes(assets_directory), tf.compat.as_bytes(assets_filename))
75 input_tensor_info = tf.saved_model.utils.build_tensor_info(input_tensor)
77 tf.saved_model.signature_constants.REGRESS_INPUTS: input_tensor_info
79 output_tensor_info = tf.saved_model.utils.build_tensor_info(output_tensor)
81 tf.saved_model.signature_constants.REGRESS_OUTPUTS: output_tensor_info
83 return tf.saved_model.signature_def_utils.build_signature_def(
85 tf.saved_model.signature_constants.REGRESS_METHOD_NAME)
92 input_tensor_info = tf.saved_model.utils.build_tensor_info(input_tensor
[all...] |
| /external/tensorflow/tensorflow/examples/learn/ |
| mnist.py | 25 import tensorflow as tf
36 feature = tf.reshape(features[X_FEATURE], [-1, 28, 28, 1])
39 with tf.variable_scope('conv_layer1'):
40 h_conv1 = tf.layers.conv2d(
45 activation=tf.nn.relu)
46 h_pool1 = tf.layers.max_pooling2d(
50 with tf.variable_scope('conv_layer2'):
51 h_conv2 = tf.layers.conv2d(
56 activation=tf.nn.relu)
57 h_pool2 = tf.layers.max_pooling2d
[all...] |
| text_classification_cnn.py | 25 import tensorflow as tf
48 word_vectors = tf.contrib.layers.embed_sequence(
50 word_vectors = tf.expand_dims(word_vectors, 3)
51 with tf.variable_scope('CNN_Layer1'):
53 conv1 = tf.layers.conv2d(
59 activation=tf.nn.relu)
61 pool1 = tf.layers.max_pooling2d(
67 pool1 = tf.transpose(pool1, [0, 1, 3, 2])
68 with tf.variable_scope('CNN_Layer2'):
70 conv2 = tf.layers.conv2d
[all...] |
| /system/core/adb/ |
| adb_io_test.cpp | 48 TemporaryFile tf; local
49 ASSERT_NE(-1, tf.fd);
51 ASSERT_TRUE(android::base::WriteStringToFd(expected, tf.fd)) << strerror(errno);
52 ASSERT_EQ(0, lseek(tf.fd, 0, SEEK_SET));
56 ASSERT_TRUE(ReadFdExactly(tf.fd, buf, sizeof(buf) - 1)) << strerror(errno);
62 TemporaryFile tf; local
63 ASSERT_NE(-1, tf.fd);
65 ASSERT_TRUE(android::base::WriteStringToFd(expected, tf.fd)) << strerror(errno);
66 ASSERT_EQ(0, lseek(tf.fd, 0, SEEK_SET));
70 ASSERT_FALSE(ReadFdExactly(tf.fd, buf, sizeof(buf)))
76 TemporaryFile tf; local
93 TemporaryFile tf; local
108 TemporaryFile tf; local
134 TemporaryFile tf; local
147 TemporaryFile tf; local
[all...] |
| /external/tensorflow/tensorflow/user_ops/ |
| duplicate_op_test.py | 22 import tensorflow as tf
25 class DuplicateOpTest(tf.test.TestCase):
28 library_filename = os.path.join(tf.resource_loader.get_data_files_path(),
30 duplicate = tf.load_op_library(library_filename)
35 self.assertEqual(tf.add(1, 41).eval(), 42)
39 tf.test.main()
|
| invalid_op_test.py | 22 import tensorflow as tf
25 class InvalidOpTest(tf.test.TestCase):
28 library_filename = os.path.join(tf.resource_loader.get_data_files_path(),
30 with self.assertRaises(tf.errors.InvalidArgumentError):
31 tf.load_op_library(library_filename)
35 tf.test.main()
|
| /external/tensorflow/tensorflow/examples/tutorials/layers/ |
| cnn_mnist.py | 14 """Convolutional Neural Network Estimator for MNIST, built with tf.layers."""
21 import tensorflow as tf
23 tf.logging.set_verbosity(tf.logging.INFO)
31 input_layer = tf.reshape(features["x"], [-1, 28, 28, 1])
38 conv1 = tf.layers.conv2d(
43 activation=tf.nn.relu)
49 pool1 = tf.layers.max_pooling2d(inputs=conv1, pool_size=[2, 2], strides=2)
56 conv2 = tf.layers.conv2d(
61 activation=tf.nn.relu
[all...] |
| /external/tensorflow/tensorflow/contrib/session_bundle/example/ |
| export_half_plus_two.py | 35 import tensorflow as tf
43 with tf.Session() as sess:
46 a = tf.Variable(0.5, name="a")
47 b = tf.Variable(2.0, name="b")
50 serialized_tf_example = tf.placeholder(tf.string, name="tf_example")
54 feature_configs = {"x": tf.FixedLenFeature([1], dtype=tf.float32),}
55 tf_example = tf.parse_example(serialized_tf_example, feature_configs)
56 # Use tf.identity() to assign nam
[all...] |
