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Results 81 - 90 of 155 for RankedTensorType (0.23 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/passes/insert_save_op.cc
TF::ConstOp Create1DStringConst(const ArrayRef<std::string> str_values, const Location loc, OpBuilder& builder) { const auto tensor_type = RankedTensorType::get(/*shape=*/{static_cast<int64_t>(str_values.size())}, /*elementType=*/builder.getType<TF::StringType>()); return builder.create<TF::ConstOp>( loc, DenseStringElementsAttr::get(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 05:52:39 UTC 2024 - 9.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/odml_converter/transforms/outline_composites.cc
return custom_call.getCallTargetName() == "mhlo.erf"; } return llvm::isa<chlo::ErfOp>(op); } // Builds a reference implementation of non-approximate GELU. func::FuncOp BuildGELUDecomposition(RankedTensorType type, PatternRewriter& rewriter, Block* insertion_point) { rewriter.setInsertionPointToStart(insertion_point);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 9.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/dense_to_sparse.cc
dense_data.data(), inst, &builder, &s_param); auto compressed_data_type = RankedTensorType::get( {static_cast<int64_t>(compressed_data.size())}, builder.getF32Type()); auto new_value = DenseElementsAttr::get<float>(compressed_data_type,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 16.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf_patterns.td
def GetHLOAxisFromTFAxis : NativeCodeCall< "GetHLOAxisFromTFAxis(" "$0, $1.getType().cast<RankedTensorType>().getRank(), &$_builder)">; // Same as the above but with $1 of type operand_range from variadic TensorFlow // input. def GetHLOAxisFromTFAxisVariadic : NativeCodeCall< "GetHLOAxisFromTFAxis(" "$0, (*$1.begin()).getType().cast<RankedTensorType>().getRank(), " "&$_builder)">; def CastElementsToI64Elements : NativeCodeCall<
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 34.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/xla_sharding_util.cc
mlir::OpBuilder* builder, mlir::TF::SplitOp* split_op) { // Creates a const op to hold split dimension value. auto split_dim_type = mlir::RankedTensorType::get({}, builder->getIntegerType(32)); auto split_dimension_attr = mlir::DenseElementsAttr::get(split_dim_type, split_dimension); auto split_dimension_op = builder->create<mlir::TF::ConstOp>(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 21:28:13 UTC 2024 - 34K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_composite_functions_tf.cc
}; LogicalResult CheckFusableLayerNormalizedLstmCellSimple( func::FuncOp lstm_func) { for (int i = 0; i < 5; ++i) { auto input = lstm_func.getArgument(i); auto input_type = mlir::dyn_cast_or_null<RankedTensorType>(input.getType()); if (!input_type) { lstm_func.emitWarning( "we cannot fuse this lstm func because all the inputs have not " "ranked tensor type."); return failure(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 17.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/import_quant_stats_pass.cc
ElementsAttr layer_stats = DenseFPElementsAttr::get( RankedTensorType::get({2}, b.getF32Type()), {min_maxs[0], min_maxs[1]}); ElementsAttr axis_stats; IntegerAttr axis; if (info.params_size() > 1) { SmallVector<int64_t, 4> axis_stats_shape{info.params_size(), 2}; axis_stats = DenseFPElementsAttr::get( RankedTensorType::get(axis_stats_shape, b.getF32Type()), min_maxs);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 08 10:41:08 UTC 2024 - 9.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/attrs_and_constraints.h
if constexpr (std::is_integral_v<T>) { auto shape_type = RankedTensorType::get(shape, builder.getIntegerType(sizeof(T) * 8)); const auto attr = DenseIntElementsAttr::get(shape_type, values); return builder.create<TF::ConstOp>(loc, attr); } const auto type = RankedTensorType::get(shape, builder.getF32Type()); const auto value_attr = DenseFPElementsAttr::get(type, values);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 9.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/preprocess_op.cc
if (cur_rank != 4 || cur_shape[2] == 1) return failure(); TensorType new_shape = RankedTensorType::get( {cur_shape[0], cur_shape[1], 1, cur_shape[2] * cur_shape[3]}, attr.getElementType()); // Inserts a reshape op. auto shape_spec_type = RankedTensorType::get({cur_rank}, rewriter.getIntegerType(64)); auto new_shape_const_attr =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/internal/passes/extract_outside_compilation.cc
LogicalResult GetShardShapedType(Operation* context_op, int num_cores_per_replica, Type full_type, Type& shard_type) { RankedTensorType ranked_type = mlir::dyn_cast<RankedTensorType>(full_type); if (!ranked_type) return context_op->emitOpError() << "A map_outside_compilation op's input and output types must be " "ranked tensors.";
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 21:25:12 UTC 2024 - 68.3K bytes - Viewed (0)