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Results 1 - 10 of 18 for rmaxs (0.26 sec)
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tensorflow/compiler/mlir/quantization/common/ir/FakeQuantSupport.cc
double rmin = rmins[axis]; double rmax = rmaxs[axis]; if (std::fabs(rmax - rmin) < std::numeric_limits<double>::epsilon()) { scales.push_back(1.0); zeroPoints.push_back(qmin); continue; } double scale; int64_t nudgedZeroPoint; getNudgedScaleAndZeroPoint(qmin, qmax, rmin, rmax, scale, nudgedZeroPoint); scales.push_back(scale);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 21 11:52:27 UTC 2024 - 7.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_utils.h
// supports only symmetric quantization. rmax = std::max(std::abs(rmin), std::abs(rmax)); rmin = -rmax; } TensorRangeSanityCheck(op, rmin, rmax); mins.push_back(rmin); maxs.push_back(rmax); } quant_type = quantfork::fakeQuantAttrsToType( op.getLoc(), num_bits, *op.getAxis(), mins, maxs, narrow_range, expressed, is_signed);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 20:30:06 UTC 2024 - 41.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/numerical_utils.cc
std::optional<double> rmax, int32_t qmin, int32_t qmax) { auto quantize = [scale, zero_point](float f) { return zero_point + static_cast<int32_t>(std::round(f / scale)); }; if (rmin.has_value() && rmax.has_value()) { return {std::max(qmin, quantize(rmin.value())), std::min(qmax, quantize(rmax.value()))}; } else if (rmin.has_value()) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 17 19:57:04 UTC 2023 - 3.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_utils.cc
maxs[channel_index] = std::max(maxs[channel_index], ele_value); } // Expand range to include 0. for (int i = 0; i < dim_size; ++i) { maxs[i] = std::max(maxs[i], 0.0); mins[i] = std::min(mins[i], 0.0); } if (symmetric) { for (int i = 0; i < dim_size; ++i) { maxs[i] = std::max(std::abs(mins[i]), std::abs(maxs[i])); mins[i] = -maxs[i];
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 02:10:16 UTC 2024 - 43.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/numerical_utils.h
// range is the minimum range defined by [rmin, rmax] and [qmin, qmax]. QuantizedRange CalculateQuantizedRange(double scale, int32_t zero_point, std::optional<double> rmin, std::optional<double> rmax, int32_t qmin, int32_t qmax); } // namespace quant } // namespace mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 07 18:43:51 UTC 2022 - 1.8K bytes - Viewed (0) -
test/codegen/floats.go
// arm64:"FMINS" // riscv64:"FMINS" // ppc64/power9:"XSMINJDP" // ppc64/power10:"XSMINJDP" return min(a, b) } func Float32Max(a, b float32) float32 { // amd64:"MINSS" // arm64:"FMAXS" // riscv64:"FMAXS" // ppc64/power9:"XSMAXJDP" // ppc64/power10:"XSMAXJDP" return max(a, b) } // ------------------------ // // Constant Optimizations // // ------------------------ //
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu Apr 04 15:24:29 UTC 2024 - 4.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/ir/FakeQuantSupport.h
/// originating op. quant::UniformQuantizedType fakeQuantAttrsToType(Location loc, unsigned numBits, double rmin, double rmax, bool narrowRange, Type expressedType, bool isSigned = false);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 21 11:52:27 UTC 2024 - 3.7K bytes - Viewed (0) -
src/cmd/internal/obj/riscv/anames.go
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed Mar 20 14:19:33 UTC 2024 - 2.9K bytes - Viewed (0) -
src/cmd/internal/obj/arm64/anames.go
"FCVTZSSW", "FCVTZUD", "FCVTZUDW", "FCVTZUS", "FCVTZUSW", "FDIVD", "FDIVS", "FLDPD", "FLDPQ", "FLDPS", "FMADDD", "FMADDS", "FMAXD", "FMAXNMD", "FMAXNMS", "FMAXS", "FMIND", "FMINNMD", "FMINNMS", "FMINS", "FMOVD", "FMOVQ", "FMOVS", "FMSUBD", "FMSUBS", "FMULD", "FMULS", "FNEGD", "FNEGS", "FNMADDD", "FNMADDS",
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu May 18 01:40:37 UTC 2023 - 5.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_quantize_helper.h
SmallVector<double, 4> maxs(1, std::numeric_limits<double>::min()); // Computes the effective min/max values of the attribute values. quant::ExtractMinMaxFromAttr(attr, /*dim_size=*/1, /*slice_size=*/1, /*symmetric=*/true, mins, maxs); double scale = maxs[0] / -llvm::minIntN(tensor_property.number_of_bits);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 28K bytes - Viewed (0)