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Results 1 - 10 of 54 for ShapedType (0.21 sec)
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tensorflow/compiler/mlir/lite/utils/utils.h
return shaped_type.clone(new_shape); } // Returns a ShapedType for a permutation and the shape of input after // applying the permutation to the given shape through a transpose. inline ShapedType GetTransposedType(Value input, llvm::ArrayRef<int64_t> permutation_array) { auto input_type = input.getType().cast<ShapedType>(); if (permutation_array.size() != input_type.getRank()) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_lifting.cc
// indices in `val2`. bool HasEqualElementSize(Value val1, Value val2, ArrayRef<int> val1_indices, ArrayRef<int> val2_indices) { ShapedType val1_shape = mlir::cast<ShapedType>(val1.getType()); ShapedType val2_shape = mlir::cast<ShapedType>(val2.getType()); if (!val1_shape.hasRank() || !val2_shape.hasRank()) return false; int val1_result = 1; int val2_result = 1;
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/tensorflow/ops/tf_quantize_op.cc
// logics. std::optional<TF::PartitionedCallOp> RegisterOperationsInFuncOp( StringRef func_name, PatternRewriter& rewriter, QuantizedType quant_type, Value input_val, ShapedType result_type, std::function<Operation*(PatternRewriter&, Operation*, Value, ShapedType, QuantizedType)> quantization_operations_func) { Operation* input_op = input_val.getDefiningOp();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/dense_to_sparse.cc
const float ratio_threshold) { ElementsAttr attr; ShapedType type; InspectResult result = {}; if (auto cst = dyn_cast<ConstOp>(inst)) { attr = cst.getValue(); type = mlir::cast<ShapedType>(cst.getType()); } else if (auto cst = dyn_cast<QConstOp>(inst)) { attr = cst.getValue(); type = mlir::cast<ShapedType>(cst.getType()); } else { result.can_compress = false;
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/lite/transforms/legalize_tf.cc
if (!mlir::cast<ShapedType>(lhs.getType()).hasStaticShape() || !mlir::cast<ShapedType>(rhs.getType()).hasStaticShape() || !mlir::cast<ShapedType>(cond.getType()).hasStaticShape()) { return rewriteOpWithDynamicInput(op, rewriter); } auto lhs_shape = mlir::cast<ShapedType>(lhs.getType()).getShape(); auto rhs_shape = mlir::cast<ShapedType>(rhs.getType()).getShape();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 20 20:06:54 UTC 2024 - 45.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/scatter.h
if (operands.size() != 1 || updates.size() != 1) return failure(); ShapedType operand_type = mlir::cast<ShapedType>(operands[0].getType()); ShapedType indices_type = mlir::cast<ShapedType>(indices.getType()); ShapedType updates_type = mlir::cast<ShapedType>(updates[0].getType()); Value new_updates = updates[0]; // Can only convert with static shaped scatter.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/dot_general.cc
Value ConvertDot(PatternRewriter& rewriter, Value lhs, Value rhs, mhlo::DotDimensionNumbersAttr dot_dimension_numbers, ShapedType result_type, mlir::Location loc) { auto lhs_type = mlir::cast<ShapedType>(lhs.getType()); auto rhs_type = mlir::cast<ShapedType>(rhs.getType()); const int lhs_rank = lhs_type.getRank(); const int rhs_rank = rhs_type.getRank(); ImplicitLocOpBuilder builder(loc, rewriter);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 19.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/replace_cast_hacks_with_tf_xla_ops.cc
void BroadcastBatchDimensionsForBatchMatMul(OpBuilder &builder, Location loc, Value &input, Value &weight) { ShapedType input_type = mlir::cast<ShapedType>(input.getType()); ShapedType weight_type = mlir::cast<ShapedType>(weight.getType()); const int32_t input_rank = input_type.getRank(); const int32_t weight_rank = weight_type.getRank();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 47.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/utils/tf_to_xla_attribute_utils.cc
return builder.create<TF::ReshapeOp>( loc, RankedTensorType::get(shape, builder.getI32Type()), value, CreateConstValue<int64_t>(builder, loc, {rank}, shape)); }; ShapedType filter_shape = mlir::cast<ShapedType>(filter.getType()); Value input_shape_value = builder.create<TF::ShapeOp>( loc, RankedTensorType::get({num_dims}, builder.getI32Type()), input);
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/tensorflow/passes/convert_tf_xla_op_to_tf_op.cc
dot_dimension_numbers.ParseFromString(dot_dimension_numbers_str.str()); SmallVector<Value> input_arguments = {lhs, rhs}; const int lhs_rank = mlir::cast<ShapedType>(lhs.getType()).getShape().size(); const int rhs_rank = mlir::cast<ShapedType>(rhs.getType()).getShape().size(); const std::string einsum_equation = CreateEinsumEquation(dot_dimension_numbers, lhs_rank, rhs_rank);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 13.2K bytes - Viewed (0)