/external/okhttp/okio/okio/src/test/java/okio/ |
H A D | SegmentSharingTest.java | 30 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 [all...] |
/external/kernel-headers/original/uapi/linux/ |
H A D | tiocl.h | 16 unsigned short ys; /* Y start */ member in struct:tiocl_selection
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/external/mesa3d/src/mesa/drivers/dri/i965/ |
H A D | brw_fs_cse.cpp | 121 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[ [all...] |
H A D | brw_vec4_cse.cpp | 101 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[ [all...] |
/external/tensorflow/tensorflow/contrib/nn/python/ops/ |
H A D | fwd_gradients.py | 27 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)
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/external/tensorflow/tensorflow/cc/framework/ |
H A D | gradient_checker.cc | 106 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 [all...] |
H A D | gradient_checker.h | 26 /// computed and numeric Jacobian matrices where 'xs' and 'ys' are tensors. 51 const OutputList& ys,
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/external/tensorflow/tensorflow/contrib/eager/python/examples/linear_regression/ |
H A D | linear_regression.py | 61 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)
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H A D | linear_regression_test.py | 58 (xs, ys) = it.next() 60 self.assertEqual((batch_size, 1), ys.shape) 62 self.assertEqual(tf.float32, ys.dtype)
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/external/blktrace/btt/ |
H A D | btt_plot.py | 109 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} [all...] |
/external/tensorflow/tensorflow/cc/gradients/ |
H A D | data_flow_grad_test.cc | 38 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
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/external/universal-tween-engine/java/applets/src/aurelienribon/utils/swing/ |
H A D | GroupBorder.java | 33 int[] ys = {0, 0, titleHeight, titleHeight}; 34 gg.fillPolygon(xs, ys, 4);
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/external/apache-commons-math/src/main/java/org/apache/commons/math/util/ |
H A D | FastMath.java | 988 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[ [all...] |
/external/libvpx/libvpx/vp9/common/ |
H A D | vp9_reconinter.h | 28 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
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H A D | vp9_reconinter.c | 154 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);
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/external/tensorflow/tensorflow/core/kernels/ |
H A D | resize_bilinear_op.cc | 108 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 [all...] |
/external/tensorflow/tensorflow/python/ops/ |
H A D | gradients_impl.py | 209 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` [all...] |
/external/tensorflow/tensorflow/python/debug/examples/ |
H A D | debug_mnist.py | 50 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}
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/external/mksh/src/ |
H A D | syn.c | 1136 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 [all...] |
/external/autotest/client/site_tests/graphics_SanAngeles/src/ |
H A D | matrixop.c | 89 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;
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/external/icu/android_icu4j/src/main/java/android/icu/util/ |
H A D | HebrewCalendar.java | 772 long ys = startOfYear(year); // 1st day of year 773 int dayOfYear = (int)(d - ys); 778 ys = startOfYear(year); 779 dayOfYear = (int)(d - ys);
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/external/icu/icu4j/main/classes/core/src/com/ibm/icu/util/ |
H A D | HebrewCalendar.java | 798 long ys = startOfYear(year); // 1st day of year 799 int dayOfYear = (int)(d - ys); 804 ys = startOfYear(year); 805 dayOfYear = (int)(d - ys);
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/external/tensorflow/tensorflow/python/kernel_tests/ |
H A D | bcast_ops_test.py | 30 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))
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/external/libhevc/decoder/ |
H A D | ihevcd_parse_residual.c | 474 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;
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/external/pdfium/third_party/lcms/src/ |
H A D | cmswtpnt.c | 149 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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