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Results 1 - 10 of 16 for getZeroPoints (0.18 sec)
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tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_utils.cc
SmallVector<double, 4> scales(qtype.getScales().begin(), qtype.getScales().end()); SmallVector<int64_t, 4> zero_points(qtype.getZeroPoints().begin(), qtype.getZeroPoints().end()); if (new_shape.size() == shape.size()) { // same rank // Broadcast the scales and zero points to match the target size, which is
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/quantization/stablehlo/passes/bridge/convert_tf_quant_ops_to_mhlo.cc
PatternRewriter &rewriter) const override { auto output_type = GetUniformQuantizedType( op, op.getOutput().getType(), op.getScales(), op.getZeroPoints(), /*expressed_type=*/rewriter.getF32Type(), op.getQuantizationMinVal(), op.getQuantizationMaxVal(), op.getQuantizationAxis(), rewriter); if (failed(output_type)) { return failure(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 30.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_lifting.cc
return uniform_type.getZeroPoint() == 0; } else if (auto per_axis_type = llvm::dyn_cast_or_null<UniformQuantizedPerAxisType>(qtype)) { return absl::c_all_of(per_axis_type.getZeroPoints(), [](int64_t x) { return x == 0; }); } return false; } // Multiplies two 1D arrays with broadcasting support. template <typename T>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 13.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/uniform_quantized_types_test.cc
/*zero_points=*/SmallVector<int64_t, 2>{98, 99}, /*quantization_dimension=*/0); EXPECT_THAT(quantized_type.getScales(), ElementsAreArray({8.0, 9.0})); EXPECT_THAT(quantized_type.getZeroPoints(), ElementsAreArray({98, 99})); } class CreateI32F32UniformQuantizedPerAxisTypeTest : public Test { protected: CreateI32F32UniformQuantizedPerAxisTypeTest() : ctx_() {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 28.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/ir/UniformSupport.h
public: explicit UniformQuantizedPerAxisValueConverter( quant::UniformQuantizedPerAxisType uniform_type) : scales_(uniform_type.getScales()), zero_points_(uniform_type.getZeroPoints()), clamp_min_(static_cast<double>(uniform_type.getStorageTypeMin())), clamp_max_(static_cast<double>(uniform_type.getStorageTypeMax())), storage_bit_width_(uniform_type.getStorageTypeIntegralWidth()),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 02:10:16 UTC 2024 - 9.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/uniform_quantized_stablehlo_to_tfl_pass.cc
new_filter_quantized_type = CreateI8F32UniformQuantizedPerAxisType( filter_constant_op->getLoc(), *rewriter.getContext(), filter_quantized_type.getScales(), filter_quantized_type.getZeroPoints(), /*quantization_dimension=*/0, /*narrow_range=*/true); } else { auto filter_quantized_type = GetElementType(filter_constant_op.getResult())
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 22 09:00:19 UTC 2024 - 99.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/ir/tfr_ops.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Nov 21 16:55:41 UTC 2023 - 38.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_driver.cc
quant::UniformQuantizedPerAxisType::getChecked( bias_op->getLoc(), params.getFlags(), params.getStorageType(), params.getExpressedType(), new_bias_scales, bias_quantized_type.getZeroPoints(), bias_quantized_type.getQuantizedDimension(), params.getStorageTypeMin(), params.getStorageTypeMax())); arith::ConstantOp filter_op = DuplicateConstantOpIfNeeded(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 38.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_quantize_helper.h
auto new_qtype = quant::CreateI8F32UniformQuantizedPerAxisType( transpose_op.getLoc(), *rewriter.getContext(), aqtype.getScales(), aqtype.getZeroPoints(), new_out_quant_dim, /*narrow_range=*/true); auto new_tensor_type = RankedTensorType::getChecked( transpose_op.getLoc(), transpose_op.getType().getShape(), new_qtype);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 28K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/quantization_patterns.cc
} const ArrayRef<int64_t> zero_points = mlir::cast<UniformQuantizedPerAxisType>( getElementTypeOrSelf(filter_type)) .getZeroPoints(); // `stablehlo.convolution` assumes the following format: // [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f] // `stablehlo.dot_general` can take various formats. We only per-channel
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 06:04:36 UTC 2024 - 41.7K bytes - Viewed (0)