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tensorflow/compiler/mlir/quantization/stablehlo/quantization_options.proto
// Apply float16 quantization to all the weights. Quantized weights will be // dequantized before running inference. // Activation: f32, Weight: f16, Bias: f16 FLOAT16 = 3; // Apply static range quantization. The quantization range is determined // via calibration phase and quantized during conversion. // Activation: qi8, Weight: qi8, Bias: qi32 POST_TRAINING_QUANTIZATION_STATIC_RANGE = 4; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 22 02:20:05 UTC 2023 - 3.6K bytes - Viewed (0) -
src/cmd/internal/pgo/pgo.go
} // NamedEdgeMap contains all unique call edges in the profile and their // edge weight. type NamedEdgeMap struct { Weight map[NamedCallEdge]int64 // ByWeight lists all keys in Weight, sorted by edge weight from // highest to lowest. ByWeight []NamedCallEdge } func emptyProfile() *Profile { // Initialize empty maps/slices for easier use without a requiring a
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed Mar 27 20:20:01 UTC 2024 - 1.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/examples/mnist/mnist_train.py
# output shape: [-1, 1024] fc1 = gen_mnist_ops.new_fully_connected(reshape, self.weights['f3'], self.biases['b3'], 'RELU') # output shape: [-1, 10] return gen_mnist_ops.new_fully_connected(fc1, self.weights['f4'], self.biases['b4']) def main(strategy):
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Oct 20 03:05:18 UTC 2021 - 6.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/replace_cast_hacks_with_tf_xla_ops.td
(HasStaticShapeConstraint $weight)], [], (addBenefit 10)>; // Convert Matmul with hybrid inputs (f32 activation/int8 weight) to XlaDotV2 def ConvertTFMatMulToXLADotV2OpWeightOnly : Pat< (TF_MatMulOp:$matmul $input, (TF_MulOp (TF_CastOp (TF_IdentityOp $weight), $truncate1), $scale), $transpose_a, $transpose_b, $grad_a, $grad_b), (TF_MulOp (CreateXlaDotV2OpFromTfMatMulOp
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Dec 10 05:52:02 UTC 2023 - 21.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_without_identity.pbtxt
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 13.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_without_identity_4bit.pbtxt
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 13.8K bytes - Viewed (0) -
src/go/doc/testdata/examples/issue43658.golden
g, err := community.NewUndirectedLayers(friends, enemies) if err != nil { log.Fatal(err) } weights := []float64{1, -1} // Get the profile of internal node weight for resolutions // between 0.1 and 10 using logarithmic bisection. p, err := community.Profile( community.ModularMultiplexScore(g, weights, true, community.WeightMultiplex, 10, src), true, 1e-3, 0.1, 10, ) if err != nil { log.Fatal(err)
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Tue May 10 23:13:45 UTC 2022 - 4.5K bytes - Viewed (0) -
pilot/pkg/networking/core/loadbalancer/loadbalancer.go
// by providing weights in LocalityLbEndpoints via load_balancing_weight. // By setting weights across different localities, it can allow // Envoy to do weighted load balancing across different zones and geographical locations. for _, localityWeightSetting := range distribute { if localityWeightSetting != nil && util.LocalityMatch(locality, localityWeightSetting.From) {
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Tue Apr 23 05:38:57 UTC 2024 - 11.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/graph-default-attr.pbtxt
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 10 19:32:15 UTC 2020 - 12K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/passes.td
}]; let dependentDialects = ["mlir::stablehlo::StablehloDialect"]; } def InsertWeightParamPass : Pass<"stablehlo-insert-weight-param", "mlir::func::FuncOp"> { let summary = "Insert quantization parameters of weights for weight-only quantization and dynamic range quantization."; let dependentDialects = [ "mlir::stablehlo::StablehloDialect", "TF::TensorFlowDialect",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 10.3K bytes - Viewed (0)