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tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_algorithm.py
self._hist_freq = np.array(hist_stats.hist_freq) self._num_bins = len(self._hist_freq) self._num_bits = 8 # i-th bin has a range [bins[i], bins[i + 1]). # bins[i] = lower_bound + i * bin_width # bins[i + 1] = lower_bound + (i + 1) * bin_width # So hist_mids[i] = (lower_bound + bin_width / 2) + bin_width * i first_mid = self._lower_bound + self._bin_width / 2
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 11 19:29:56 UTC 2024 - 14.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.proto
// range. CALIBRATION_METHOD_HISTOGRAM_MSE_SYMMETRIC = 6; } // Parameters required for calibration. // Next ID: 4 message CalibrationParameters { // The number of histogram bins. Default to 512. int32 num_bins = 1; // min_percentile is only used in HISTOGRAM_PERCENTILE. // min_percentile is 0.001 by default. float min_percentile = 2;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 14.3K bytes - Viewed (0) -
android/guava/src/com/google/common/util/concurrent/Striped.java
* stripes, the intended concurrency level, and the typical number of keys used in a {@code * bulkGet(keys)} operation. See <a href="http://www.mathpages.com/home/kmath199.htm">Balls in * Bins model</a> for mathematical formulas that can be used to estimate the probability of * collisions. * * @param keys arbitrary non-null keys
Registered: Wed Jun 12 16:38:11 UTC 2024 - Last Modified: Mon Apr 10 20:55:18 UTC 2023 - 20.3K bytes - Viewed (0) -
src/cmd/compile/internal/ssa/schedule.go
count[i] += count[i-1] } if count[len(count)-1] != int32(len(values)) { f.Fatalf("storeOrder: value is missing, total count = %d, values = %v", count[len(count)-1], values) } // place values in count-indexed bins, which are in the desired store order order := make([]*Value, len(values)) for _, v := range values { s := storeNumber[v.ID] order[count[s-1]] = v count[s-1]++ }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Apr 08 15:53:17 UTC 2024 - 16.4K bytes - Viewed (0) -
guava/src/com/google/common/util/concurrent/Striped.java
* stripes, the intended concurrency level, and the typical number of keys used in a {@code * bulkGet(keys)} operation. See <a href="http://www.mathpages.com/home/kmath199.htm">Balls in * Bins model</a> for mathematical formulas that can be used to estimate the probability of * collisions. * * @param keys arbitrary non-null keys
Registered: Wed Jun 12 16:38:11 UTC 2024 - Last Modified: Mon Apr 10 20:55:18 UTC 2023 - 20.3K bytes - Viewed (0) -
src/runtime/hash_test.go
var a [16]byte m := make(map[uint16]struct{}, 1<<16) for n := 0; n < 1<<16; n++ { a[i] = byte(n) a[j] = byte(n >> 8) m[uint16(BytesHash(a[:], 0))] = struct{}{} } // N balls in N bins, for N=65536 avg := 41427 stdDev := 123 if len(m) < avg-40*stdDev || len(m) > avg+40*stdDev { t.Errorf("bad number of collisions i=%d j=%d outputs=%d out of 65536\n", i, j, len(m)) } } }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon May 06 17:50:18 UTC 2024 - 18.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/einsum.mlir
// CHECK: return %[[v0]] } func.func @batch_multilhs_einsum(%arg0: tensor<2x1x1x11xf32>, %arg1: tensor<2x11x2xf32>) -> tensor<2x1x1x2xf32> { %0 = "tf.Einsum"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", equation = "BiNj,BjS->BiNS"} : (tensor<2x1x1x11xf32>, tensor<2x11x2xf32>) -> tensor<2x1x1x2xf32> func.return %0 : tensor<2x1x1x2xf32> // CHECK-LABEL: batch_multilhs_einsum // CHECK-DAG: %[[cst:.*]] = arith.constant dense<[2, 1, 11]> : tensor<3xi64>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 25.9K bytes - Viewed (0)