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tensorflow/compiler/mlir/lite/quantization/lite/quantize_weights.h
// reaching feature parity with the old quantizer for dynamic range // quantization, specifically for // third_party/tensorflow/lite/tools/optimize/quantize_weights.h. // TODO(b/202468183): Selective quantization + quant debugger support for // dynamic range quantization for verify_numeric and whole_model_verify flags. TfLiteStatus QuantizeWeights( flatbuffers::FlatBufferBuilder* builder, const tflite::Model* input_model,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 4.2K bytes - Viewed (0) -
samples/addons/README.md
You may also want to remove the Jaeger deployment, which will not be used, with `kubectl delete deployment jaeger`, or avoid installing it to begin with by following the selective installation steps in [Getting Started](#getting-started). For more information about integrating with Zipkin, please see the [Zipkin integration page](https://istio.io/docs/tasks/observability/distributed-tracing/zipkin/).
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Thu Jul 27 18:28:55 UTC 2023 - 5.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_xla_selective_quantization.mlir
// This file test the selective quantiation feature in TF Quantizer. In the test // config, the op named "test_opt_out" will not be quantized. module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 1269 : i32}} {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 6.8K bytes - Viewed (0)