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Results 1 - 3 of 3 for quantization_dimension (0.15 sec)
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tensorflow/compiler/mlir/quantization/common/uniform_quantized_types.cc
const ArrayRef<int64_t> zero_points, const int quantization_dimension, const bool narrow_range) { return UniformQuantizedPerAxisType::getChecked( loc, /*flags=*/QuantizationFlags::Signed, /*storageType=*/IntegerType::get(&context, /*width=*/8), /*expressedType=*/FloatType::getF32(&context), SmallVector<double>(scales), SmallVector<int64_t>(zero_points), quantization_dimension,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/uniform_quantized_types.h
UniformQuantizedPerAxisType CreateI8F32UniformQuantizedPerAxisType( Location loc, MLIRContext& context, ArrayRef<double> scales, ArrayRef<int64_t> zero_points, int quantization_dimension, bool narrow_range = false); // Creates a `UniformQuantizedPerAxisType` with the given `scales` and // `zero_points` values. The produced type has f32 as its expressed type and
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/attrs_and_constraints.cc
// - size(rhs_contracting_dimensions) = 1 // - lhs_contracting_dimension = last dimension of lhs. // - `stablehlo.dot_general` should not have `lhs_batching_dim`. // - quantization_dimension(rhs) should not be in // `rhs_contracting_dimensions`. // https://github.com/openxla/stablehlo/blob/main/docs/spec.md#dot_general const bool has_proper_rank =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.8K bytes - Viewed (0)