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Results 1 - 3 of 3 for quantization_dimension (0.15 sec)

  1. 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)
  2. 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)
  3. 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
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