- Sort Score
- Result 10 results
- Languages All
Results 141 - 150 of 185 for Axis (0.06 sec)
-
src/testdata/Isaac.Newton-Opticks.txt
Convex or Concave or Plane on either side, and let CD be its Axis (that is, the Line which cuts both its Surfaces perpendicularly, and passes through the Centres of the Spheres,) and in this Axis produced let F and _f_ be the Foci of the refracted Rays found as above, when the incident Rays on both sides the Lens are parallel to the same Axis; and upon the Diameter F_f_ bisected in E, describe a Circle. Suppose now that any
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Oct 01 16:16:21 UTC 2018 - 553.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/decompose_resource_ops.td
$resource, $indices, $batch_dims, $validate_indices), (TF_GatherV2Op:$dest (CreateTFReadVariableOp $old_result, $old_result, $resource), $indices, (TF_ConstOp $batch_dims), // axis $batch_dims ), [], [(CopyXlaOutsideCompilationAttr $old_result, $dest)]>; // Pattern to decompose tf.ResourceScatterAdd into tf.ReadVariable, // tf.TensorScatterAdd, and tf.AssignVariable.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 19:47:48 UTC 2024 - 20.7K bytes - Viewed (0) -
cmd/kubeadm/app/phases/upgrade/compute.go
// between v1.(X-1).0-beta.0 and v1.(X-1).Z-beta.0. At some point in time, latest-1.(X-1) will point to v1.(X-1).0-rc.1. Then we should show it. // The flow looks like this (with time on the X axis): // v1.8.0-alpha.1 -> v1.8.0-alpha.2 -> v1.8.0-alpha.3 | release-1.8 branch | v1.8.0-beta.0 -> v1.8.0-beta.1 -> v1.8.0-beta.2 -> v1.8.0-rc.1 -> v1.8.0 -> v1.8.1
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Sun Mar 03 03:03:29 UTC 2024 - 14.3K bytes - Viewed (0) -
tensorflow/c/eager/parallel_device/parallel_device.cc
// Non-parallel tensors from _EagerConst/tf.constant are implicitly // broadcast, i.e. set as the input to each parallel operation. This // allows code like "tf.constant(1.)" or "tf.reduce_sum(..., axis=1)" // (where the value starts on the host), without allowing other implicit // copies/broadcasts. Other implicit copies may be supported eventually,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 29 22:05:31 UTC 2023 - 18.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_tf.cc
// In above calculation, they are replaced by new values. These new mean and // variance are calculated as following: // new_mean = mean(x, axis=[0, 1, 2]) // new_variance = mean(squared_difference(x, new_mean), axis=[0, 1, 2]) // // The DDR rule for the is_training equals true case is as following: // def : Pattern< // (TF_FusedBatchNormV3Op:$root
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 21:49:50 UTC 2024 - 64.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/flatbuffer_import.cc
mlir::IntegerAttr axis; if (mins.size() > 1) { llvm::SmallVector<int64_t, 4> axis_stats_shape{ static_cast<int64_t>(mins.size()), 2}; axis_stats = mlir::DenseFPElementsAttr::get( tensorflow::GetTypeFromTFTensorShape(axis_stats_shape, b.getF32Type()), min_maxs); // TODO(fengliuai): this quantization dimension isn't correct.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 18:21:50 UTC 2024 - 66.8K bytes - Viewed (0) -
tensorflow/cc/gradients/math_grad_test.cc
TEST_P(CumsumGradTest, CumsumGrad) { int axis = std::get<2>(GetParam()); TensorShape shape({2, 3, 2}); auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(shape)); Cumsum::Attrs attrs; attrs.exclusive_ = std::get<0>(GetParam()); attrs.reverse_ = std::get<1>(GetParam()); auto y = Cumsum(scope_, x, axis, attrs); RunTest({x}, {shape}, {y}, {shape}); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Aug 25 18:20:20 UTC 2023 - 36K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_weights.mlir
// CHECK-DAG: %[[W_3:.*]] = "tf.Const"() <{value = dense<127> : tensor<1024x3x4x3xi8>}> : () -> tensor<1024x3x4x3xi8> // CHECK-DAG: %[[AXIS:.*]] = "tf.Const"() <{value = dense<0> : tensor<i32>}> {device = ""} : () -> tensor<i32> // CHECK: %[[IDENTITY_1:.*]] = "tf.Identity"(%[[W_1]]) : (tensor<2x3x3x1024xi8>) -> tensor<2x3x3x1024xi8>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 42K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tensor_list_ops_decomposition.mlir
%tl = "tf.TensorListFromTensor"(%arg0, %elem_shape) : (tensor<10x8x9xf32>, tensor<2xi32>) -> tensor<!tf_type.variant<tensor<8x9xf32>>> // CHECK: %[[AXIS:.*]] = "tf.Const"() <{value = dense<0> : tensor<i32>}> : () -> tensor<i32> // CHECK: %[[GATHER:.*]] = "tf.GatherV2"(%[[BUFFER]], %[[ARG1]], %[[AXIS]]) : (tensor<10x8x9xf32>, tensor<3xi32>, tensor<i32>) -> tensor<3x8x9xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 38.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/uniform-quantized-stablehlo-to-tfl.mlir
// ----- // Tests that when the weight tensor for `stablehlo.dot_general` is per-axis // quantized, it is converted to `tfl.fully_connected` op. // CHECK-LABEL: dot_general_upstream_srq_per_axis_quantized_filter
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 106.2K bytes - Viewed (0)