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tensorflow/compiler/mlir/quantization/tensorflow/tests/duplicate_shape_determining_constants.mlir
%axis = "tf.Const"() {device = "", value = dense<1> : tensor<i32>} : () -> tensor<i32> // tf.ConcatV2 accepts a variadic operand. The last operand should be compile // time constant. %0 = "tf.ConcatV2"(%arg0, %arg0, %arg0, %arg0, %axis) : (tensor<16x1xf32>, tensor<16x1xf32>, tensor<16x1xf32>, tensor<16x1xf32>, tensor<i32>) -> tensor<16x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Nov 24 07:44:46 UTC 2022 - 11K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/convert_ref_variables.mlir
// CHECK-SAME: (tensor<i32>, tensor<i32>, tensor<i32>) -> tensor<2xi32> %axis = "tf.Const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32> %0 = "tf.VariableV2"() {container = "", shape = #tf_type.shape<>, shared_name = "x"} : () -> tensor<!tf_type.int32ref> %1 = "tf.ConcatV2"(%0, %0, %axis) : (tensor<!tf_type.int32ref>, tensor<!tf_type.int32ref>, tensor<i32>) -> tensor<2xi32> func.return %1 : tensor<2xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 28 12:06:33 UTC 2022 - 4.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/dilated_conv.h
} // Make sure that the axis in `expand_op` is constant. if (auto const_op = llvm::dyn_cast<TF::ConstOp>(expand_op.getDim().getDefiningOp())) { expand_axis = (*mlir::cast<DenseElementsAttr>(const_op.getValue()) .getValues<APInt>() .begin()) .getSExtValue(); // Canonicalize axis. Some TF python functions, such as
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 20K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization.td
">::Impl")>; // Specify the operand index of the coefficient operand for an affine op // and also the quantization dimension if per-axis quantization is support. // If the quantization dimension is -1, per-axis quantization isn't supported. class AffineOpCoefficient<int dim, int index> : NativeOpTrait< !strconcat("quant::AffineOpCoefficient<", !interleave([dim, index], ", "),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 05 07:39:40 UTC 2024 - 8.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_utils.cc
// new quantization dimension. Only if the new quantization dimension can // be inferred, it is safe to reset the per-axis quantized type. if (axis == -1) return {}; qtype = ResetAxisAndBroadcast(source_type.getShape(), per_axis, target, axis); } if (!qtype) return {}; const Type final_type = qtype.castFromExpressedType(target); if (!final_type) return {};
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/experimental/tac/README.md
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 29 18:32:13 UTC 2022 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize_patterns.td
// Eliminate cumulative summations if the input's dimension in axis is 1. def EliminateCumSumInclusive : Pat< (TFL_CumsumOp $input, (Arith_ConstantOp I32ElementsAttr:$axis), ConstBoolAttrFalse, $reverse), (replaceWithValue $input), [(AreInputDimensionsOneInAxes $input, $axis)]>; // Fusing raw computation of GELU op into one native tfl_gelu op. //
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 66.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/reduce.h
Value operand = reduce_op.getInputs().front(); int64_t axis = reduce_op.getDimensions().getValues<int64_t>()[0]; auto dim_type = RankedTensorType::get({1}, rewriter.getI32Type()); auto reduction_indices = rewriter.create<arith::ConstantOp>( reduce_op.getLoc(), dim_type, rewriter.getI32TensorAttr({static_cast<int32_t>(axis)})); // Generate a Max and an ArgMax of as the mhlo op returns both while in TF
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/ir/QuantOps.cc
return emitOpError("layerStats must have shape [2]"); } } // Verify axisStats (optional) attribute. if (getAxisStats()) { if (!getAxis()) return emitOpError("axis must be specified for axisStats"); auto shape = tensorArg.getShape(); auto argSliceSize = std::accumulate(std::next(shape.begin(), *getAxis()), shape.end(), 1,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/ir/QuantOps.cc
return emitOpError("layerStats must have shape [2]"); } } // Verify axisStats (optional) attribute. if (getAxisStats()) { if (!getAxis()) return emitOpError("axis must be specified for axisStats"); auto shape = tensorArg.getShape(); auto argSliceSize = std::accumulate(std::next(shape.begin(), *getAxis()), shape.end(), 1,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.3K bytes - Viewed (0)