| /prebuilts/gdb/darwin-x86/lib/python2.7/ |
| formatter.py | 154 ones = ['i', 'x', 'c', 'm']
161 label = ones[index] + ones[index+1] + label
163 label = ones[index] + fives[index] + label
170 s = s + ones[index]*x
|
| /prebuilts/gdb/linux-x86/lib/python2.7/ |
| formatter.py | 154 ones = ['i', 'x', 'c', 'm']
161 label = ones[index] + ones[index+1] + label
163 label = ones[index] + fives[index] + label
170 s = s + ones[index]*x
|
| /prebuilts/go/darwin-x86/src/net/ |
| ip.go | 68 // CIDRMask returns an IPMask consisting of `ones' 1 bits
71 func CIDRMask(ones, bits int) IPMask {
75 if ones < 0 || ones > bits {
80 n := uint(ones)
425 // Size returns the number of leading ones and total bits in the mask.
426 // If the mask is not in the canonical form--ones followed by zeros--then
428 func (m IPMask) Size() (ones, bits int) {
429 ones, bits = simpleMaskLength(m), len(m)*8
430 if ones == -1
[all...] |
| /prebuilts/go/linux-x86/src/net/ |
| ip.go | 68 // CIDRMask returns an IPMask consisting of `ones' 1 bits
71 func CIDRMask(ones, bits int) IPMask {
75 if ones < 0 || ones > bits {
80 n := uint(ones)
425 // Size returns the number of leading ones and total bits in the mask.
426 // If the mask is not in the canonical form--ones followed by zeros--then
428 func (m IPMask) Size() (ones, bits int) {
429 ones, bits = simpleMaskLength(m), len(m)*8
430 if ones == -1
[all...] |
| /prebuilts/python/darwin-x86/2.7.5/lib/python2.7/ |
| formatter.py | 154 ones = ['i', 'x', 'c', 'm']
161 label = ones[index] + ones[index+1] + label
163 label = ones[index] + fives[index] + label
170 s = s + ones[index]*x
|
| /prebuilts/python/linux-x86/2.7.5/lib/python2.7/ |
| formatter.py | 154 ones = ['i', 'x', 'c', 'm']
161 label = ones[index] + ones[index+1] + label
163 label = ones[index] + fives[index] + label
170 s = s + ones[index]*x
|
| /external/tensorflow/tensorflow/python/estimator/ |
| warm_starting_util_test.py | 36 ones = init_ops.ones_initializer variable
314 "linear_model/sc_int/weights", shape=[10, 1], initializer=ones())
316 self.assertAllEqual(np.ones([10, 1]), prev_int_val)
382 "linear_model/sc_vocab/weights", shape=[4, 1], initializer=ones())
419 "linear_model/sc_vocab/weights", shape=[4, 1], initializer=ones())
465 "linear_model/sc_vocab/weights", shape=[2, 1], initializer=ones())
557 "linear_model/sc_int/weights", shape=[10, 1], initializer=ones())
563 "linear_model/sc_vocab/weights", shape=[4, 1], initializer=ones())
[all...] |
| /external/valgrind/none/tests/amd64/ |
| fma4.stdout.exp | 1 VFMADDPD_xmm ones
43 VFMADDPD_xmm_src_dst ones
85 VFMADDPD_xmm_mem1 ones
127 VFMADDPD_xmm_mem2 ones
169 VFMADDPS_xmm ones
211 VFMADDPS_xmm_src_dst ones
253 VFMADDPS_xmm_mem1 ones
295 VFMADDPS_xmm_mem2 ones
337 VFMADDSD_xmm ones
379 VFMADDSD_xmm_src_dst ones
[all...] |
| /external/tensorflow/tensorflow/contrib/rnn/python/kernel_tests/ |
| core_rnn_cell_test.py | 209 m.name: 0.1 * np.ones([1, 8])
232 m.name: 0.1 * np.ones([1, 4], dtype=np_dtype)
253 x.name: 1 * np.ones([batch_size, input_size]),
254 m.name: 0.1 * np.ones([batch_size - 1, state_size])
274 x.name: 1 * np.ones([batch_size, input_size]),
275 m.name: 0.1 * np.ones([batch_size, state_size])
327 m0.name: 0.1 * np.ones([1, 4]),
328 m1.name: 0.1 * np.ones([1, 4])
363 m.name: 0.1 * np.ones((batch_size, state_size))
423 x.name: np.ones((batch_size, input_size))
[all...] |
| /external/tensorflow/tensorflow/python/keras/_impl/keras/ |
| backend_test.py | 236 x = keras.backend.ones((3, 4))
238 self.assertAllClose(val, np.ones((3, 4)))
258 self.assertAllClose(val, np.ones((3, 4)))
319 x = keras.backend.ones(shape=(32, 20, 1))
320 y = keras.backend.ones(shape=(32, 30, 20))
420 a = keras.backend.variable(np.ones((1, 2, 3)))
421 b = keras.backend.variable(np.ones((1, 2, 2)))
437 x = keras.backend.variable(np.ones((1, 2, 2, 3)))
445 x = keras.backend.variable(np.ones((1, 3, 2, 2)))
464 x = keras.backend.variable(np.ones((1, 2, 2, 2, 3))
[all...] |
| /external/tensorflow/tensorflow/python/ops/ |
| control_flow_ops_test.py | 681 array_ops.ones([3, 3], dtype=dtype))
688 return (array_ops.ones([2, 2], dtype=dtype),
700 (np.zeros([2, 2]), np.ones([3, 3])),
701 (np.ones([2, 2]), np.zeros([3, 3])))
727 np.zeros([2, 2]), np.ones([2, 2]),
729 false_tensor: np.ones([2, 2])})
771 (np.zeros([2, 2]), np.zeros(5), np.ones([3, 3])),
772 (np.zeros([2, 2]), np.zeros(5), np.ones([3, 3])),
777 true_tensors[2]: np.ones([3, 3]),
778 false_tensors[2]: np.ones([3, 3])}
[all...] |
| /external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/state_space_models/ |
| state_space_model_test.py | 394 array_ops.ones([1, 4, 1], dtype=dtype)
424 original_covariance = array_ops.diag(array_ops.ones(shape=[5]))
429 array_ops.ones(shape=[1, 5]), original_covariance[None], [0]
449 array_ops.ones(shape=[5], dtype=dtype))
454 -array_ops.ones(shape=[1, 5], dtype=dtype),
611 return array_ops.ones(shape=[1, 1])
614 return array_ops.ones(shape=[1, 1])
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| quantized_distribution.py | 280 ones = array_ops.ones_like(x_samps)
287 low * ones, result_so_far)
291 high * ones, result_so_far)
|
| sinh_arcsinh.py | 159 scale=array_ops.ones([], dtype=dtype),
|
| vector_sinh_arcsinh_diag.py | 114 scale = diag(scale_diag + scale_identity_multiplier * ones(k))
204 scale=array_ops.ones([], dtype=dtype),
|
| /external/tensorflow/tensorflow/contrib/image/python/ops/ |
| image_ops.py | 204 array_ops.ones((num_translations, 1), dtypes.float32),
208 array_ops.ones((num_translations, 1), dtypes.float32),
325 # Add a column of ones for the implicit last entry in the matrix.
328 [transforms, array_ops.ones([num_transforms, 1])], axis=1),
|
| /external/tensorflow/tensorflow/python/kernel_tests/linalg/ |
| linear_operator_low_rank_update_test.py | 256 u = array_ops.ones(shape=[2, 3, 2])
257 diag = array_ops.ones(shape=[2, 2])
272 u = array_ops.ones(shape=u_shape_ph)
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| losses_test.py | 481 logits: np.ones((32, 1)),
482 labels: np.ones((32, 1)),
497 logits: np.ones((32, 2)),
498 labels: np.ones((32, 2)),
[all...] |
| /external/libmojo/third_party/jinja2/ |
| filters.py | 846 or the attribute and only selecting the ones with the test succeeding.
862 or the attribute and rejecting the ones with the test succeeding.
878 or the attribute and only selecting the ones with the test succeeding.
895 or the attribute and rejecting the ones with the test succeeding.
|
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| conv_ops.cc | 413 std::vector<int64> ones(num_spatial_dims_, 1);
440 out_backprop, mirrored_weights, /*window_strides=*/ones, padding,
574 std::vector<int64> ones(num_spatial_dims_, 1);
639 /*lhs_dilation=*/ones, rhs_dilation, dnums);
|
| pooling_ops.cc | 212 auto ones = ctx->builder()->Broadcast( local
218 ones, XlaHelpers::Zero(ctx->builder(), dtype),
490 // in_backprop = padded_gradients <conv> ones
491 std::vector<int64> ones(num_dims(), 1LL);
494 /* window_strides=*/ones, xla::Padding::kValid);
|
| /external/tensorflow/tensorflow/contrib/bayesflow/python/ops/ |
| halton_sequence_impl.py | 251 sieve = np.ones(n // 3 + (n % 6 == 2), dtype=np.bool)
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/bijectors/ |
| softmax_centered_test.py | 101 y_0 = np.ones(5).astype(np.float32)
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| kumaraswamy_test.py | 363 self.assertAllEqual(np.ones(shape, dtype=np.bool), 0. <= x)
364 self.assertAllEqual(np.ones(shape, dtype=np.bool), 1. >= x)
379 self.assertAllEqual(np.ones(shape, dtype=np.bool), 0. <= x)
380 self.assertAllEqual(np.ones(shape, dtype=np.bool), 1. >= x)
|
| /external/tensorflow/tensorflow/contrib/mpi_collectives/ |
| mpi_allgather_test.py | 79 ones_tensor = tf.ones([tensor_width])
|
