- Sort Score
- Result 10 results
- Languages All
Results 11 - 20 of 185 for Axis (0.05 sec)
-
tensorflow/cc/gradients/array_grad.cc
std::vector<Output>* grad_outputs) { int N; TF_RETURN_IF_ERROR(GetNodeAttr(op.node()->attrs(), "N", &N)); int axis; TF_RETURN_IF_ERROR(GetNodeAttr(op.node()->attrs(), "axis", &axis)); grad_outputs->reserve(N); auto grad_op = Unstack(scope, grad_inputs[0], N, Unstack::Axis(axis)); for (const Output& o : grad_op.output) { grad_outputs->emplace_back(o); } return scope.status(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 10 23:33:32 UTC 2023 - 31.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/lower_tf.mlir
// CHECK-DAG: %[[ITEMS1_3:.*]] = "tf.ExpandDims"(%[[ITEMS1]]#3, %[[AXIS]]) // CHECK-DAG: %[[ITEMS1_2:.*]] = "tf.ExpandDims"(%[[ITEMS1]]#2, %[[AXIS]]) // CHECK-DAG: %[[ITEMS1_1:.*]] = "tf.ExpandDims"(%[[ITEMS1]]#1, %[[AXIS]]) // CHECK-DAG: %[[ITEMS1_0:.*]] = "tf.ExpandDims"(%[[ITEMS1]]#0, %[[AXIS]]) // CHECK-DAG: %[[ITEMS0_0:.*]] = "tf.ExpandDims"(%[[ITEMS0]], %[[AXIS]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 92K bytes - Viewed (0) -
android/guava/src/com/google/common/collect/CartesianList.java
@Override public int size() { return axes.size(); } @Override public E get(int axis) { checkElementIndex(axis, size()); int axisIndex = getAxisIndexForProductIndex(index, axis); return axes.get(axis).get(axisIndex); } @Override boolean isPartialView() { return true; }
Registered: Wed Jun 12 16:38:11 UTC 2024 - Last Modified: Thu Nov 30 21:54:06 UTC 2023 - 4.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops_tensor_helper.h
} inline bool IsUnknownDimOrRank(int64_t dim_or_rank) { return dim_or_rank == -1; } // Returns dimension index for the given TensorFlow axis that supports negative // indexing. inline int64_t GetDimForAxis(int64_t axis, int64_t rank) { return axis >= 0 ? axis : axis + rank; } // Returns the tf.Equal/tf.NotEqual result type given `x` and `y` and inputs. If
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 3.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/utils/tf_to_uniform_attribute_utils.cc
kBinaryOp, // Binary ops have lhs/rhs attr. kQuantizationOp, // Quantization ops have input/output attr. }; // For each op type, the following axis carries axis information: // kDynamicRangeOp: rhs_quantization_axis will carry axis information. // kUnaryOp: quantization_axis will carry axis information. // kBinaryOp: Among {lhs, rhs, output}_quantization_axis, only check rhs.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 18.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/tf-tfl-translate-serialize-stablehlo-concat.mlir
module { func.func @main(%arg0: tensor<3x3xf32>, %arg1: tensor<3x3xf32>) -> tensor<6x3xf32> { %axis = "tf.Const"() { value = dense<0> : tensor<i64> } : () -> tensor<i64> %1 = "tf.ConcatV2"(%arg0, %arg1, %axis) : (tensor<3x3xf32>, tensor<3x3xf32>, tensor<i64>) -> tensor<6x3xf32> func.return %1 : tensor<6x3xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 03 03:08:46 UTC 2023 - 443 bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/ir/QuantOps.td
<?x?x3x2>, axis=2 => N=6 ``` }]; let arguments = (ins quant_RealValueType:$arg, ElementsAttr:$layerStats, OptionalAttr<ElementsAttr>:$axisStats, OptionalAttr<I64Attr>:$axis); let results = (outs quant_RealValueType); let hasVerifier = 1; } def Quantization_CoupledRefOp : Quantization_Op<"coupled_ref", [SameOperandsAndResultType]> { let summary = [{
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 09 03:10:59 UTC 2024 - 10.2K bytes - Viewed (0) -
testing/internal-performance-testing/src/main/resources/org/gradle/reporting/performanceGraph.js
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Thu Apr 04 07:21:38 UTC 2024 - 6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/import_quant_stats_pass.cc
ElementsAttr axis_stats, IntegerAttr axis) { auto stats_op = b.create<quantfork::StatisticsOp>( b.getUnknownLoc(), res, layer_stats, axis_stats, axis); res.replaceAllUsesWith(stats_op); stats_op.getOperation()->replaceUsesOfWith(stats_op, res); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 08 10:41:08 UTC 2024 - 9.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_patterns.td
(UpdateShapeWithAxis<-1> $qtype, $old_value))), [(CanUpdateShapeWithAxis<-1> $qtype, $old_value)]>; // The axis is set to 0 because the transpose is from the legalization of // tf.conv2d and the new channel axis is the first dimension. def ReorderTransposeDequantQuantUsedByConv : Pat<(TF_TransposeOp:$old_value (TFL_DequantizeOp (TFL_QuantizeOp $input, $qtype)), $perm),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 10.5K bytes - Viewed (0)