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Results 1 - 5 of 5 for Hudgins (0.1 sec)

  1. cni/test/testdata/pre/noplugins_calico.conflist

    {
      "name": "k8s-pod-network",
      "cniVersion": "0.3.1",
      "pugins": [
        {
          "type": "calico",
          "etcd_endpoints": "http://10.110.0.136:6666",
          "plugin_log_level": "info",
          "mtu": 1500,
          "ipam": {
            "type": "calico-ipam"
          },
          "policy": {
            "type": "k8s"
          },
          "kubernetes": {
            "kubeconfig": "/etc/cni/net.d/calico-kubeconfig"
          }
        },
        {
    Registered: Fri Jun 14 15:00:06 UTC 2024
    - Last Modified: Tue May 21 18:32:01 UTC 2024
    - 527 bytes
    - Viewed (0)
  2. tensorflow/compiler/mlir/quantization/common/ir/FakeQuantSupport.cc

        }
      } else {
        return true;
      }
    
      // Handle narrowRange.
      if (narrowRange) {
        qmin += 1;
      }
      return false;
    }
    
    // This is a specific implementation of nudging:
    // If 0.0 < rmin < rmax or rmin < rmax < 0.0, the range will be shifted
    // to include 0.0, but the range width size (rmax-rmin) isn't changed. The zero
    // point is derived from the shifted range, and the scale isn't changed. As
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Mar 21 11:52:27 UTC 2024
    - 7.7K bytes
    - Viewed (0)
  3. tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_utils.h

          for (auto it = stats.begin(), e = stats.end(); it != e; ++it) {
            double rmin = FloatAttr::getValueAsDouble(*it++);
            double rmax = FloatAttr::getValueAsDouble(*it);
            // The default nudging implementation of mlir quant library might cause
            // clamping during inference if the calibration range isn't wide enough.
            // So here we adjust the range to include 0.0.
            rmin = std::min(rmin, 0.0);
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed Apr 24 20:30:06 UTC 2024
    - 41.7K bytes
    - Viewed (0)
  4. tensorflow/compiler/mlir/tensorflow/transforms/lower_tf.cc

    // floating point and quantized space. It is designed to reproduce TF's
    // implementation, mirroring the previous XLA implementation.
    //
    // 1. Computing proper quantized bounds. This involves nudging the input bounds.
    // 2. Converting the input bounds to quantized space, rounding values.
    // 3. Convert back into floating point space.
    class ConvertFakeQuantWithMinMaxVarsOp : public RewritePattern {
     public:
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Apr 25 16:01:03 UTC 2024
    - 74.9K bytes
    - Viewed (0)
  5. src/net/http/h2_bundle.go

    		// duplicate entries.
    		return sc.countError("settings_big_or_dups", http2ConnectionError(http2ErrCodeProtocol))
    	}
    	if err := f.ForeachSetting(sc.processSetting); err != nil {
    		return err
    	}
    	// TODO: judging by RFC 7540, Section 6.5.3 each SETTINGS frame should be
    	// acknowledged individually, even if multiple are received before the ACK.
    	sc.needToSendSettingsAck = true
    	sc.scheduleFrameWrite()
    	return nil
    }
    
    Registered: Wed Jun 12 16:32:35 UTC 2024
    - Last Modified: Tue Jun 04 16:19:04 UTC 2024
    - 364.1K bytes
    - Viewed (0)
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