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tensorflow/compiler/mlir/quantization/tensorflow/python/quantize_model.py
related config. representative_dataset: a generator that returns a dictionary in {input_key: input_value} format or a tuple with signature key and a dictionary in {input_key: input_value} format that feeds calibration data for quantizing model. This should be provided when the model is not a QAT model. Returns: A SavedModel object with TF quantization applied. Raises:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 34.2K bytes - Viewed (0) -
src/internal/trace/summary.go
syscallingP: make(map[ProcID]GoID), syscallingG: make(map[GoID]ProcID), rangesP: make(map[rangeP]GoID), } } type rangeP struct { id ProcID name string } // Event feeds a single event into the stats summarizer. func (s *Summarizer) Event(ev *Event) { if s.syncTs == 0 { s.syncTs = ev.Time() } s.lastTs = ev.Time() switch ev.Kind() {
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu May 23 01:00:11 UTC 2024 - 20.7K bytes - Viewed (0)