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Results 1 - 10 of 194 for Franko (0.29 sec)
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src/runtime/lockrank_on.go
// //go:systemstack func checkRanks(gp *g, prevRank, rank lockRank) { rankOK := false if rank < prevRank { // If rank < prevRank, then we definitely have a rank error rankOK = false } else if rank == lockRankLeafRank { // If new lock is a leaf lock, then the preceding lock can // be anything except another leaf lock. rankOK = prevRank < lockRankLeafRank } else { // We've now verified the total lock ranking, but we
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Apr 22 14:29:04 UTC 2024 - 10.6K bytes - Viewed (0) -
src/runtime/mklockrank.go
} return lockNames[rank] } `) // Create partial order structure. fmt.Fprintf(w, ` // lockPartialOrder is the transitive closure of the lock rank graph. // An entry for rank X lists all of the ranks that can already be held // when rank X is acquired. // // Lock ranks that allow self-cycles list themselves. var lockPartialOrder [][]lockRank = [][]lockRank{ `) for _, rank := range topo {
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed May 08 17:47:01 UTC 2024 - 9.1K bytes - Viewed (0) -
src/runtime/lockrank.go
} func (rank lockRank) String() string { if rank == 0 { return "UNKNOWN" } if rank == lockRankLeafRank { return "LEAF" } if rank < 0 || int(rank) >= len(lockNames) { return "BAD RANK" } return lockNames[rank] } // lockPartialOrder is the transitive closure of the lock rank graph. // An entry for rank X lists all of the ranks that can already be held
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed May 08 17:47:01 UTC 2024 - 19.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/hlo_matchers.cc
// // $iota = "mhlo.iota"(){iota_dimension = $dimensions[0]}, // // where $dimensions must have size 1 and iota can have rank>=1. // It usually used for matching rank 1 iota since the iotaOp will be folded to // IotaOp + BroadCastInDimOp except for the case when result shape is rank 1. bool MatchSingleIota(DenseIntElementsAttr dimensions, Value iota) { auto iota_op = dyn_cast_or_null<mhlo::IotaOp>(iota.getDefiningOp());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops_n_z.cc
auto shape = ranked_ty.getShape(); int rank = shape.size(); SmallVector<APInt, 4> dimensions; dimensions.reserve(rank); for (int i = 0; i < rank; ++i) dimensions.push_back(APInt(out_width, shape[i])); auto result_type = tensorflow::GetTypeFromTFTensorShape( {rank}, IntegerType::get(input_ty.getContext(), out_width));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 22:07:10 UTC 2024 - 170.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/fold_constant_transpose.cc
current_indices.push_back(i); TransposeRecursively(original_values, target_values, current_indices); current_indices.pop_back(); } } int rank_; // Rank of the input values. SmallVector<int64_t> original_shape_; // Shape of the original tensor. SmallVector<int64_t> target_shape_; // Shape of the target tensor. SmallVector<int64_t> permutation_; };
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 7.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/unroll_batch_matmul.cc
RankedTensorType tensorType = mlir::cast<RankedTensorType>(value.getType()); Type element_type = tensorType.getElementType(); int rank = tensorType.getShape().size(); int num_rows = tensorType.getShape()[rank - 2]; int num_cols = tensorType.getShape()[rank - 1]; std::vector<Value> sliced; if (batch_size == 1) { // Batch size is 1, no splitting is required
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/ir/tfl_ops.cc
} const int64_t rank = input_type.getRank(); if (rank <= 0) { return emitOptionalError(loc, "input should be of rank larger than 0"); } int64_t axis_value = op.getAxisAttr().getInt(); if (axis_value < 0) { axis_value += rank; } if (axis_value < 0 || axis_value >= rank) { return emitOptionalError(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 169.2K bytes - Viewed (0) -
pkg/controller/controller_utils.go
// If one of the two pods is on the same node as one or more additional // ready pods that belong to the same replicaset, whichever pod has more // colocated ready pods is less if s.Rank[i] != s.Rank[j] { return s.Rank[i] > s.Rank[j] } // TODO: take availability into account when we push minReadySeconds information from deployment into pods, // see https://github.com/kubernetes/kubernetes/issues/22065
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Fri Jan 12 15:34:44 UTC 2024 - 47.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops_tensor_helper.h
} // Returns true if the given `value` has at least the specified rank or has // unranked type. inline bool HasRankAtLeast(Value value, int64_t rank) { RankedTensorType type = GetRankedTensorTypeForOperand(value); return !type || type.getRank() >= rank; } // Returns true if the given `value` has at most the specified rank or has // unranked type. inline bool HasRankAtMost(Value value, int64_t rank) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 3.8K bytes - Viewed (0)