/external/skqp/site/dev/design/conical/ |
D | index.md | 61 1. All centers $C_t = (x_t, 0)$ must be on the $x$ axis 62 2. The radius $r_t$ is $x_t r_1$. 63 3. Given $x_t$ , we can derive $t = f + (1 - f) x_t$ 65 From now on, we'll focus on how to quickly computes $x_t$. Note that $r_t > 0$ so we're only 66 interested positive solution $x_t$. Again, if there are multiple $x_t$ solutions, we may want to 72 **Theorem 1.** The solution to $x_t$ is 78 Case 2 always produces a valid $x_t$. Case 1 and 3 requires $x > 0$ to produce valid $x_t > 0$. Case 81 *Proof.* Algebriacally, solving the quadratic equation $(x_t - x)^2 + y^2 = (x_t r_1)^2$ and 82 eliminate negative $x_t$ solutions get us the theorem. 89 1. we still need to compute $t$ from $x_t$ (remember that $t = f + (1-f) x_t$); [all …]
|
/external/skia/site/dev/design/conical/ |
D | index.md | 61 1. All centers $C_t = (x_t, 0)$ must be on the $x$ axis 62 2. The radius $r_t$ is $x_t r_1$. 63 3. Given $x_t$ , we can derive $t = f + (1 - f) x_t$ 65 From now on, we'll focus on how to quickly computes $x_t$. Note that $r_t > 0$ so we're only 66 interested positive solution $x_t$. Again, if there are multiple $x_t$ solutions, we may want to 72 **Theorem 1.** The solution to $x_t$ is 78 Case 2 always produces a valid $x_t$. Case 1 and 3 requires $x > 0$ to produce valid $x_t > 0$. Case 81 *Proof.* Algebriacally, solving the quadratic equation $(x_t - x)^2 + y^2 = (x_t r_1)^2$ and 82 eliminate negative $x_t$ solutions get us the theorem. 89 1. we still need to compute $t$ from $x_t$ (remember that $t = f + (1-f) x_t$); [all …]
|
/external/tensorflow/tensorflow/core/grappler/optimizers/ |
D | debug_stripper_test.cc | 126 Tensor x_t(DT_FLOAT, TensorShape({})); in TEST_F() local 128 x_t.flat<float>()(0) = 1.0f; in TEST_F() 131 EvaluateNodes(item.graph, {"z"}, {{"x", x_t}, {"y", y_t}}); in TEST_F() 133 EvaluateNodes(output, {"z"}, {{"x", x_t}, {"y", y_t}}); in TEST_F() 185 Tensor x_t(DT_FLOAT, TensorShape({})); in TEST_F() local 187 x_t.flat<float>()(0) = 1.0f; in TEST_F() 190 EvaluateNodes(item.graph, {"z"}, {{"x", x_t}, {"y", y_t}}); in TEST_F() 192 EvaluateNodes(output, {"z"}, {{"x", x_t}, {"y", y_t}}); in TEST_F() 223 Tensor x_t(DT_FLOAT, TensorShape({})); in TEST_F() local 224 x_t.flat<float>()(0) = 1.0f; in TEST_F() [all …]
|
D | arithmetic_optimizer_test.cc | 911 auto x_t = GenerateRandomTensor<DT_FLOAT>(TensorShape({3, 3, 28, 28})); in TEST_F() local 913 EvaluateNodes(item.graph, item.fetch, {{"Placeholder", x_t}}); in TEST_F() 922 auto tensors = EvaluateNodes(output, item.fetch, {{"Placeholder", x_t}}); in TEST_F() 948 auto x_t = GenerateRandomTensor<DT_FLOAT>(TensorShape({3, 3, 28, 28})); in TEST_F() local 951 item.feed = {{"Placeholder", x_t}}; in TEST_F() 977 auto x_t = GenerateRandomTensor<DT_FLOAT>(TensorShape({4, 3, 28, 28})); in TEST_F() local 980 item.feed = {{"Placeholder", x_t}}; in TEST_F() 1009 auto x_t = GenerateRandomTensor<DT_FLOAT>(TensorShape({4, 3, 28, 28})); in TEST_F() local 1012 item.feed = {{"Placeholder", x_t}}; in TEST_F() 1041 auto x_t = GenerateRandomTensor<DT_FLOAT>(TensorShape({8, 3, 28, 28})); in TEST_F() local [all …]
|
D | constant_folding_test.cc | 47 Tensor x_t(DTYPE, TensorShape({2, 2})); in SimpleNeutralElementTest() local 51 x_t.flat<T>()(i) = T(i + 1); in SimpleNeutralElementTest() 114 EvaluateNodes(item.graph, item.fetch, {{"x", x_t}}); in SimpleNeutralElementTest() 115 auto tensors = EvaluateNodes(output, item.fetch, {{"x", x_t}}); in SimpleNeutralElementTest() 653 auto x_t = GenerateRandomTensor<DT_FLOAT>(TensorShape({2, 2})); in TEST_F() local 659 {{"x", x_t}, {"y", y_t}, {"a", a_t}, {"b", b_t}, {"bias", bias_t}}); in TEST_F() 663 {{"x", x_t}, {"y", y_t}, {"a", a_t}, {"b", b_t}, {"bias", bias_t}}); in TEST_F() 3044 Tensor x_t(DT_BOOL, TensorShape({})); in TEST_F() local 3045 x_t.flat<bool>()(0) = true; in TEST_F() 3046 auto tensors_expected = EvaluateNodes(item.graph, {"id_true"}, {{"x", x_t}}); in TEST_F() [all …]
|
/external/skia/src/gpu/gradients/ |
D | GrTwoPointConicalGradientLayout.fp | 39 // calculations of t and x_t below overflow and produce an incorrect interpolant (which then 69 float x_t = -1; 71 x_t = dot(p, p) / p.x; 73 x_t = length(p) - p.x * invR1; 81 // is really critical, maybe we should just compute the area where temp and x_t are 85 x_t = -sqrt(temp) - p.x * invR1; 87 x_t = sqrt(temp) - p.x * invR1; 92 // The final calculation of t from x_t has lots of static optimizations but only do them 93 // when x_t is positive (which can be assumed true if isWellBehaved is true) 97 if (x_t <= 0.0) { [all …]
|
/external/skqp/src/gpu/gradients/ |
D | GrTwoPointConicalGradientLayout.fp | 39 // calculations of t and x_t below overflow and produce an incorrect interpolant (which then 69 float x_t = -1; 71 x_t = dot(p, p) / p.x; 73 x_t = length(p) - p.x * invR1; 81 // is really critical, maybe we should just compute the area where temp and x_t are 85 x_t = -sqrt(temp) - p.x * invR1; 87 x_t = sqrt(temp) - p.x * invR1; 92 // The final calculation of t from x_t has lots of static optimizations but only do them 93 // when x_t is positive (which can be assumed true if isWellBehaved is true) 97 if (x_t <= 0.0) { [all …]
|
/external/tensorflow/tensorflow/contrib/crf/ |
D | README.md | 33 x_t = tf.constant(x) 39 matricized_x_t = tf.reshape(x_t, [-1, num_features])
|
/external/tensorflow/tensorflow/python/kernel_tests/ |
D | sparse_tensor_dense_matmul_op_test.py | 352 x_t = constant_op.constant(x) 355 x_t, y_t, adjoint_a, adjoint_b) 358 x_t = constant_op.constant(x) 361 x_t, y_t, adjoint_a, adjoint_b)
|
D | functional_ops_test.py | 393 x_t = array_ops.transpose(x) 397 result_t = functional_ops.scan(lambda a, x: a + x, x_t, infer_shape=False) 400 result_t_grad = gradients_impl.gradients(result_t, [x_t])[0]
|
/external/tensorflow/tensorflow/python/ops/distributions/ |
D | student_t.py | 282 x_t = self.df / (y**2. + self.df) 283 neg_cdf = 0.5 * math_ops.betainc(0.5 * self.df, 0.5, x_t)
|
/external/tensorflow/tensorflow/core/framework/ |
D | tensor_util_test.cc | 529 Tensor x_t; in CompareTensorValues() local 530 EXPECT_TRUE(x_t.FromProto(x)); in CompareTensorValues() 533 test::ExpectTensorEqual<T>(x_t, y_t); in CompareTensorValues()
|
/external/tensorflow/tensorflow/python/ops/ |
D | rnn.py | 62 x_t = array_ops.transpose( 65 x_t.set_shape( 69 return x_t
|
/external/python/cpython3/Lib/test/ |
D | mime.types | 1192 model/vnd.parasolid.transmit.text x_t xmt_txt
|
/external/webrtc/talk/media/testdata/ |
D | h264-svc-99-640x360.rtpdump | 7208 …���Xl��f�娞�U+�E����@�B@��{���d���C�l��ӿ"�������mh��6�kz��8Ȗ��ۿPt^��x_t�F�� �2�p͌x�Z��7…
|
/external/honggfuzz/examples/apache-httpd/corpus_http1/ |
D | 67154715f57204df236d04030732b84d.000eb1d3.honggfuzz.cov | 1289 …����\D� BI=��k4d��&�¶���10������,[��եW:�����$��;�_��pN6FG�*�ӑ�Ea~����J�6���x_t����e�
|