| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| ops_test.py | 33 x = tf.random_normal(shape=[batch_size, 32, 32, 3])
45 x = tf.random_normal(shape=[batch_size, 32, 32, 3])
50 dy = tf.random_normal(shape=[batch_size, 3, 32, 32])
56 x = tf.random_normal(shape=[batch_size, 3, 32, 32])
68 x = tf.random_normal(shape=[batch_size, 3, 32, 32])
73 dy = tf.random_normal(shape=[batch_size, 3, 32, 32])
|
| blocks_test.py | 59 x = tf.random_normal(shape=data_shape)
100 x = tf.random_normal(shape=data_shape)
134 x = tf.random_normal(shape=data_shape, dtype=tf.float64)
135 dy = tf.random_normal(shape=data_shape, dtype=tf.float64)
163 x = tf.random_normal(shape=data_shape, dtype=tf.float64)
164 dy = tf.random_normal(shape=(16, 128, 4, 4), dtype=tf.float64)
197 x = tf.random_normal(shape=data_shape, dtype=tf.float64)
198 dy = tf.random_normal(shape=data_shape, dtype=tf.float64)
237 x_true = tf.random_normal(shape=data_shape, dtype=tf.float64)
238 dy = tf.random_normal(shape=data_shape, dtype=tf.float64
[all...] |
| /external/tensorflow/tensorflow/contrib/gan/python/eval/python/ |
| sliced_wasserstein_test.py | 80 d2 = random_ops.random_normal([256, 32, 32, 3])
96 d2 = random_ops.random_normal([256, 32, 32, 3])
112 d2 = random_ops.random_normal([256, 32, 31, 3])
113 d3 = random_ops.random_normal([256, 31, 32, 3])
114 d4 = random_ops.random_normal([255, 32, 32, 3])
125 d2 = random_ops.random_normal([256, 32, 32, 1])
|
| /external/tensorflow/tensorflow/contrib/model_pruning/python/layers/ |
| rnn_cells_test.py | 42 random_ops.random_normal([self.batch_size, self.dim]))
44 random_ops.random_normal([self.batch_size, self.dim]))
46 random_ops.random_normal([self.batch_size, self.dim]))
66 random_ops.random_normal([self.batch_size, self.dim]))
68 random_ops.random_normal([self.batch_size, self.dim]))
70 random_ops.random_normal([self.batch_size, self.dim]))
|
| /external/tensorflow/tensorflow/python/ops/ |
| initializers_ns.py | 29 random_normal = init_ops.random_normal_initializer variable
|
| /external/tensorflow/tensorflow/python/kernel_tests/signal/ |
| mfcc_ops_test.py | 53 signal = random_ops.random_normal((2, 3, 5))
62 random_ops.random_normal((2, 3, 5)), tensor_shape.TensorShape(None))
|
| /external/tensorflow/tensorflow/contrib/gan/python/features/python/ |
| virtual_batchnorm_test.py | 56 tensors = random_ops.random_normal([4, 5, 7, 3])
74 partial_batch = random_ops.random_normal([4, 5, 7, 3])
75 single_example = random_ops.random_normal([1, 5, 7, 3])
107 batch = random_ops.random_normal([6, 5, 7, 3, 3])
131 examples = [random_ops.random_normal([5, 7, 3]) for _ in
177 examples = [random_ops.random_normal([7, 3]) for _ in
|
| /external/tensorflow/tensorflow/python/client/ |
| session_benchmark.py | 84 v = variables.Variable(random_ops.random_normal([size]))
112 v = variables.Variable(random_ops.random_normal([size]))
139 v = variables.Variable(random_ops.random_normal([]))
165 v = variables.Variable(random_ops.random_normal([]))
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/gan/ |
| mnist_test.py | 58 burn_images = [tf.random_normal([batch_size, 784])
61 measure_images = [tf.random_normal([batch_size, 784])
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/linear_regression/ |
| linear_regression.py | 113 x = tf.random_normal([batch_size, num_features])
114 y = tf.matmul(x, w) + b + noise_level * tf.random_normal([])
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/spinn/ |
| spinn_test.py | 172 left_in.append(tf.random_normal((1, size * 2)))
173 right_in.append(tf.random_normal((1, size * 2)))
174 tracking.append(tf.random_normal((1, tracker_size * 2)))
214 buf.append(tf.random_normal((batch_size, size * 2)))
223 stack.append(tf.random_normal((batch_size, size * 2)))
255 buffers = tf.random_normal((sequence_length, 1, config.d_proj))
278 embed = tf.random_normal((vocab_size, d_embed))
450 embed = tf.random_normal((vocab_size, d_embed))
|
| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/state_space_models/ |
| test_utils.py | 70 raw=random_ops.random_normal(
74 random_ops.random_normal(
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| matrix_square_root_op_test.py | 109 matrix1 = random_ops.random_normal([5, 5], seed=42)
110 matrix2 = random_ops.random_normal([5, 5], seed=42)
|
| matrix_solve_op_test.py | 128 lhs1 = random_ops.random_normal([3, 3], seed=42)
129 lhs2 = random_ops.random_normal([3, 3], seed=42)
130 rhs1 = random_ops.random_normal([3, 3], seed=42)
131 rhs2 = random_ops.random_normal([3, 3], seed=42)
|
| matmul_op_test.py | 150 a = variables.Variable(random_ops.random_normal([25, 16]))
151 b = variables.Variable(random_ops.random_normal([16, 9]))
161 a = variables.Variable(random_ops.random_normal([16, 25]))
162 b = variables.Variable(random_ops.random_normal([16, 9]))
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/l2hmc/ |
| l2hmc_test.py | 66 samples = tf.random_normal(
110 samples = tf.random_normal(shape=[hparams.n_samples, hparams.x_dim])
154 x = tf.random_normal([hparams.n_samples, hparams.x_dim],
221 samples = tf.random_normal(
|
| main.py | 78 samples = tf.random_normal(shape=[n_samples, x_dim])
111 samples = tf.random_normal(shape=[n_samples, x_dim])
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/rnn_colorbot/ |
| rnn_colorbot_test.py | 43 labels = tf.random_normal([batch_size, LABEL_DIMENSION])
|