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tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_per_channel_4bit.pbtxt
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/debuginfo/v1_1.0_224_frozen.wrong_attr.line.part.pbtxt
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 27 18:59:05 UTC 2023 - 16.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_driver.h
const bool disable_per_channel_; // We should distinguish weights and bias constants. Biases are specified by // the quantization spec or are the operands of ops with same scale spec. The // rest are weights. DenseSet<Operation*> weights_; // The weights require narrow_range quantization. This map collects all the // weight operands defined by the op quant spec. The value of each entry is
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 20 11:42:17 UTC 2024 - 16.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/insert_weight_param.cc
namespace { using ::stablehlo::quantization::Method; using ::stablehlo::quantization::QuantizedType; using ::stablehlo::quantization::WeightOnlyPtq; // Inserts quantization parameters of weights for weight-only quantization and // dynamic range quantization of `stablehlo.convolution` and // `stablehlo.dot_general`. class InsertWeightParamPass : public impl::InsertWeightParamPassBase<InsertWeightParamPass> { public:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 05:56:10 UTC 2024 - 10.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/debuginfo/v1_1.0_224_frozen.wrong_attr.stack.part.pbtxt
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 27 18:59:05 UTC 2023 - 16.4K bytes - Viewed (0) -
releasenotes/notes/new_lb_algorithm_default.yaml
area: traffic-management releaseNotes: - | **Updated** Istio's default load balancing algorithm from `ROUND_ROBIN` to `LEAST_REQUEST`. The `ROUND_ROBIN` algorithm can lead to overburdened endpoints, especially when weights are used. The `LEAST_REQUEST` algorithm, distributes more evenly across and is far less likely to overburden endpoints. A number of experiments (by both the Istio and
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Wed Feb 09 20:55:01 UTC 2022 - 856 bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/cc/config.cc
"composite_conv.*"); // Enable per-channel quantization for convolution weights. QuantizedType conv_weight_quantized_type{}; // Assumes NHWC format, specifying the channel dimension (3) as the // quantized axis. conv_weight_quantized_type.mutable_dimension_specs()->set_dimension(3); // The index of weight operands passed to lifted functions for convolution // is 1.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 8.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantize_weights.cc
// This is the argument used to refer to the pass in // the textual format (on the commandline for example). return "quant-quantize-weights"; } StringRef getDescription() const final { // This is a brief description of the pass. return "Quantize weights used by quantizable ops."; } void getDependentDialects(DialectRegistry& registry) const override {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 05 07:39:40 UTC 2024 - 11.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_driver.cc
// For now, restrict scale adjustment to ops with affine quantized weights, // and having weights and biases as constants. This currently only applies to // FC and Conv* ops. Restriction for the weight can be relaxed if there are // needs for adjusting scale of variable weights. auto affine_op = dyn_cast<AffineQuantizedOpInterface>(op);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 38.1K bytes - Viewed (0) -
pilot/pkg/config/kube/gateway/conversion.go
if forwardTo == nil { return nil, nil, nil } weights := []int{} action := []k8s.BackendRef{} for _, w := range forwardTo { wt := int(ptr.OrDefault(w.Weight, 1)) if wt == 0 { continue } action = append(action, w) weights = append(weights, wt) } if len(weights) == 1 { weights = []int{0} } var invalidBackendErr *ConfigError
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Fri Jun 14 04:34:37 UTC 2024 - 84.7K bytes - Viewed (0)