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/external/skqp/site/dev/design/conical/
Dindex.md61 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/
Dindex.md61 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/
Ddebug_stripper_test.cc126 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()
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Darithmetic_optimizer_test.cc911 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
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Dconstant_folding_test.cc47 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()
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/external/skia/src/gpu/gradients/
DGrTwoPointConicalGradientLayout.fp39 // 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) {
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/external/skqp/src/gpu/gradients/
DGrTwoPointConicalGradientLayout.fp39 // 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/
DREADME.md33 x_t = tf.constant(x)
39 matricized_x_t = tf.reshape(x_t, [-1, num_features])
/external/tensorflow/tensorflow/python/kernel_tests/
Dsparse_tensor_dense_matmul_op_test.py352 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)
Dfunctional_ops_test.py393 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/
Dstudent_t.py282 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/
Dtensor_util_test.cc529 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/
Drnn.py62 x_t = array_ops.transpose(
65 x_t.set_shape(
69 return x_t
/external/python/cpython3/Lib/test/
Dmime.types1192 model/vnd.parasolid.transmit.text x_t xmt_txt
/external/webrtc/talk/media/testdata/
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/external/honggfuzz/examples/apache-httpd/corpus_http1/
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