Searched refs:ys (Results 1 - 25 of 93) sorted by relevance

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/external/okhttp/okio/okio/src/test/java/okio/
H A DSegmentSharingTest.java30 private static final String ys = TestUtil.repeat('y', Segment.SIZE / 2 + 2); field in class:SegmentSharingTest
39 ByteString byteString = concatenateBuffers(xs, ys, zs).snapshot();
40 assertEquivalent(byteString, concatenateBuffers(xs, ys + zs).snapshot());
41 assertEquivalent(byteString, concatenateBuffers(xs + ys + zs).snapshot());
42 assertEquivalent(byteString, ByteString.encodeUtf8(xs + ys + zs));
46 ByteString byteString = concatenateBuffers(xs, ys, zs).snapshot();
50 assertEquals('y', byteString.getByte(xs.length() + ys.length() - 1));
51 assertEquals('z', byteString.getByte(xs.length() + ys.length()));
52 assertEquals('z', byteString.getByte(xs.length() + ys.length() + zs.length() - 1));
59 byteString.getByte(xs.length() + ys
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/external/kernel-headers/original/uapi/linux/
H A Dtiocl.h16 unsigned short ys; /* Y start */ member in struct:tiocl_selection
/external/mesa3d/src/mesa/drivers/dri/i965/
H A Dbrw_fs_cse.cpp121 fs_reg *ys = b->src; local
124 return xs[0].equals(ys[0]) &&
125 ((xs[1].equals(ys[1]) && xs[2].equals(ys[2])) ||
126 (xs[2].equals(ys[1]) && xs[1].equals(ys[2])));
131 bool ys0_negate = ys[0].negate;
132 bool ys1_negate = ys[1].file == IMM ? ys[1].f < 0.0f
133 : ys[
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H A Dbrw_vec4_cse.cpp101 const src_reg *ys = b->src; local
104 return xs[0].equals(ys[0]) &&
105 ((xs[1].equals(ys[1]) && xs[2].equals(ys[2])) ||
106 (xs[2].equals(ys[1]) && xs[1].equals(ys[2])));
108 return xs[0].equals(ys[0]) && xs[1].equals(ys[1]) && xs[2].equals(ys[2]);
110 return (xs[0].equals(ys[
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/external/tensorflow/tensorflow/contrib/nn/python/ops/
H A Dfwd_gradients.py27 def fwd_gradients(ys, xs, grad_xs=None, assert_unused=False):
40 ys: A list of tensors.
46 A list of tensors of the same shapes as ys. The directional derivatives of
47 ys with respect to xs in the direction grad_xs. Leaving grad_xs unspecified
52 # ys doesn't depend on one or more of the xs, and when tf.IndexedSlices are
55 us = [array_ops.zeros_like(y) + float('nan') for y in ys]
57 dydxs = gradients(ys, xs, grad_ys=us)
/external/tensorflow/tensorflow/cc/framework/
H A Dgradient_checker.cc106 const std::vector<Tensor>& x_datas, const OutputList& ys,
117 ops::Cast(scope, ops::Const(scope, 1.0, y_shape), ys[0].type()));
120 TF_RETURN_IF_ERROR(AddSymbolicGradients(scope, ys, xs, dys, &dxs));
125 dy_datas[i] = Tensor(ys[i].type(), y_shapes[i]);
180 const OutputList& ys, std::vector<Tensor>* x_datas,
188 TF_RETURN_IF_ERROR(session->Run(feed_list, ys, y_datas));
207 const OutputList& ys,
238 TF_RETURN_IF_ERROR(EvaluateGraph(&session, xs, ys, x_datas, &y_pos));
242 TF_RETURN_IF_ERROR(EvaluateGraph(&session, xs, ys, x_datas, &y_neg));
327 const OutputList& ys,
103 ComputeTheoreticalJacobianTranspose( const Scope& scope, const OutputList& xs, const std::vector<TensorShape>& x_shapes, const std::vector<Tensor>& x_datas, const OutputList& ys, const std::vector<TensorShape>& y_shapes, std::vector<Tensor>* jacobian_ts) argument
179 EvaluateGraph(ClientSession* session, const OutputList& xs, const OutputList& ys, std::vector<Tensor>* x_datas, std::vector<Tensor>* y_datas) argument
205 ComputeNumericJacobianTranspose(const Scope& scope, const OutputList& xs, const std::vector<TensorShape>& x_shapes, const OutputList& ys, const std::vector<TensorShape>& y_shapes, const JAC_T delta, std::vector<Tensor>* x_datas, std::vector<Tensor>* jacobian_ts) argument
325 ComputeGradientErrorInternal(const Scope& scope, const OutputList& xs, const std::vector<TensorShape>& x_shapes, const OutputList& ys, const std::vector<TensorShape>& y_shapes, std::vector<Tensor>* x_datas, JAC_T* max_error) argument
364 ComputeGradientError(const Scope& scope, const OutputList& xs, const std::vector<TensorShape>& x_shapes, const OutputList& ys, const std::vector<TensorShape>& y_shapes, JAC_T* max_error) argument
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H A Dgradient_checker.h26 /// computed and numeric Jacobian matrices where 'xs' and 'ys' are tensors.
51 const OutputList& ys,
/external/tensorflow/tensorflow/contrib/eager/python/examples/linear_regression/
H A Dlinear_regression.py61 ys: the predictions of the linear mode, as a tensor of size [batch_size]
66 def mean_square_loss(model, xs, ys):
67 return tf.reduce_mean(tf.square(model(xs) - ys))
83 mse = lambda xs, ys: mean_square_loss(model, xs, ys)
93 for i, (xs, ys) in enumerate(tfe.Iterator(dataset)):
94 loss, grads = loss_and_grads(xs, ys)
H A Dlinear_regression_test.py58 (xs, ys) = it.next()
60 self.assertEqual((batch_size, 1), ys.shape)
62 self.assertEqual(tf.float32, ys.dtype)
/external/blktrace/btt/
H A Dbtt_plot.py109 def avg(xs, ys):
123 return xs, ys
126 ays = [ys[0]]
128 _ys = [ys[0]]
131 for idx in range(1, len(ys)):
138 _ys = [ys[idx]]
141 _ys.append(ys[idx])
161 ys = []
169 ys.append(y)
171 db[file] = {'x':xs, 'y':ys}
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/external/tensorflow/tensorflow/cc/gradients/
H A Ddata_flow_grad_test.cc38 const OutputList& ys, const std::vector<TensorShape>& y_shapes) {
42 scope_, xs, x_shapes, ys, y_shapes, &max_error)));
37 RunTest(const OutputList& xs, const std::vector<TensorShape>& x_shapes, const OutputList& ys, const std::vector<TensorShape>& y_shapes) argument
/external/universal-tween-engine/java/applets/src/aurelienribon/utils/swing/
H A DGroupBorder.java33 int[] ys = {0, 0, titleHeight, titleHeight};
34 gg.fillPolygon(xs, ys, 4);
/external/apache-commons-math/src/main/java/org/apache/commons/math/util/
H A DFastMath.java988 final double ys[] = new double[2];
992 ys[0] = ys[1] = 0.0;
995 splitMult(xs, ys, as);
996 ys[0] = as[0];
997 ys[1] = as[1];
1002 splitAdd(ys, facts, as);
1003 ys[0] = as[0];
1004 ys[1] = as[1];
1008 result[0] = ys[
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/external/libvpx/libvpx/vp9/common/
H A Dvp9_reconinter.h28 int ys) {
31 xs, subpel_y, ys, w, h);
38 int w, int h, int ref, const InterpKernel *kernel, int xs, int ys, int bd) {
40 src, src_stride, dst, dst_stride, kernel, subpel_x, xs, subpel_y, ys, w,
23 inter_predictor(const uint8_t *src, int src_stride, uint8_t *dst, int dst_stride, const int subpel_x, const int subpel_y, const struct scale_factors *sf, int w, int h, int ref, const InterpKernel *kernel, int xs, int ys) argument
35 highbd_inter_predictor( const uint16_t *src, int src_stride, uint16_t *dst, int dst_stride, const int subpel_x, const int subpel_y, const struct scale_factors *sf, int w, int h, int ref, const InterpKernel *kernel, int xs, int ys, int bd) argument
H A Dvp9_reconinter.c154 int xs, ys, subpel_x, subpel_y; local
179 ys = sf->y_step_q4;
184 xs = ys = 16;
195 subpel_x, subpel_y, sf, w, h, ref, kernel, xs, ys, local
199 subpel_y, sf, w, h, ref, kernel, xs, ys);
203 subpel_y, sf, w, h, ref, kernel, xs, ys);
/external/tensorflow/tensorflow/core/kernels/
H A Dresize_bilinear_op.cc108 const std::vector<CachedInterpolation>& ys,
116 const std::vector<CachedInterpolation>& ys,
129 const T* ys_input_lower_ptr = input_b_ptr + ys[y].lower * in_row_size;
130 const T* ys_input_upper_ptr = input_b_ptr + ys[y].upper * in_row_size;
131 const float ys_lerp = ys[y].lerp;
174 const T* ys_input_lower_ptr = input_b_ptr + ys[y].lower * in_row_size;
175 const T* ys_input_upper_ptr = input_b_ptr + ys[y].upper * in_row_size;
176 const float ys_lerp = ys[y].lerp;
221 std::vector<CachedInterpolation> ys(out_height + 1);
226 ys
111 resize_image(typename TTypes<T, 4>::ConstTensor images, const int batch_size, const int64 in_height, const int64 in_width, const int64 out_height, const int64 out_width, const int channels, const std::vector<CachedInterpolation>& xs_vec, const std::vector<CachedInterpolation>& ys, typename TTypes<float, 4>::Tensor output) argument
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/external/tensorflow/tensorflow/python/ops/
H A Dgradients_impl.py209 def _DefaultGradYs(grad_ys, ys, colocate_gradients_with_ops):
214 ys: List of tensors.
225 if len(grad_ys) != len(ys):
226 raise ValueError("Passed %d grad_ys for %d ys" % (len(grad_ys), len(ys)))
231 y = ys[i]
400 def gradients(ys,
408 """Constructs symbolic derivatives of sum of `ys` w.r.t. x in `xs`.
410 `ys` and `xs` are each a `Tensor` or a list of tensors. `grad_ys`
412 `ys`
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/external/tensorflow/tensorflow/python/debug/examples/
H A Ddebug_mnist.py50 xs, ys = mnist.train.next_batch(FLAGS.train_batch_size,
53 xs, ys = mnist.test.images, mnist.test.labels
55 return {x: xs, y_: ys}
/external/mksh/src/
H A Dsyn.c1136 struct yyrecursive_state *ys; local
1147 ys = alloc(sizeof(struct yyrecursive_state), ATEMP);
1150 ys->old_nesting_type = subshell_nesting_type;
1154 ys->old_reject = reject;
1155 ys->old_symbol = symbol;
1157 memcpy(ys->old_heres, heres, sizeof(heres));
1158 ys->old_herep = herep;
1160 ys->next = e->yyrecursive_statep;
1161 e->yyrecursive_statep = ys;
1176 struct yyrecursive_state *ys; local
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/external/autotest/client/site_tests/graphics_SanAngeles/src/
H A Dmatrixop.c89 float xx, yy, zz, xy, yz, xz, xs, ys, zs; local
102 ys = ay * s;
107 rot[2*4 + 0] = xz * one_c + ys;
115 rot[0*4 + 2] = xz * one_c - ys;
/external/icu/android_icu4j/src/main/java/android/icu/util/
H A DHebrewCalendar.java772 long ys = startOfYear(year); // 1st day of year
773 int dayOfYear = (int)(d - ys);
778 ys = startOfYear(year);
779 dayOfYear = (int)(d - ys);
/external/icu/icu4j/main/classes/core/src/com/ibm/icu/util/
H A DHebrewCalendar.java798 long ys = startOfYear(year); // 1st day of year
799 int dayOfYear = (int)(d - ys);
804 ys = startOfYear(year);
805 dayOfYear = (int)(d - ys);
/external/tensorflow/tensorflow/python/kernel_tests/
H A Dbcast_ops_test.py30 def _GetBroadcastShape(self, xs, ys):
32 return sess.run(_broadcast_args(xs, ys))
34 def _GetGradientArgs(self, xs, ys):
36 return sess.run(_broadcast_gradient_args(xs, ys))
/external/libhevc/decoder/
H A Dihevcd_parse_residual.c474 WORD32 xs, ys; local
481 /* Get xs and ys from scan position */
484 ys = sub_blk_pos >> (log2_trafo_size - 2);
493 nbr_csbf |= (au2_csbf[ys + 1] >> xs) & 1;
501 nbr_csbf |= (au2_csbf[ys] >> (xs + 1)) & 1;
536 au2_csbf[ys] |= u4_mask;
538 au2_csbf[ys] &= ~u4_mask;
646 ps_tu_sblk_coeff_data->u2_subblk_pos = (ys << 8) | xs;
/external/pdfium/third_party/lcms/src/
H A Dcmswtpnt.c149 cmsFloat64Number xs, ys; local
156 ys = WhitePoint -> y;
160 us = (2*xs) / (-xs + 6*ys + 1.5);
161 vs = (3*ys) / (-xs + 6*ys + 1.5);

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