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tensorflow/compiler/mlir/lite/utils/tftext_utils.cc
!mlir::isa<StringType>(output_values.getElementType())) { return func.emitError() << "Output " << kValues << " should be a string tensor"; } if (input_values.hasRank() && output_values.hasRank() && input_values.getRank() != output_values.getRank()) { return func.emitError() << "Input " << kValues << " and output " << kValues << " should have the same rank";
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 14.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/attrs_and_constraints.td
def AreTheSameValue : Constraint< CPred<"$0 == $1">>; // Checks if the value has rank. def HasRank : Constraint< CPred<"$0.getType().cast<ShapedType>().hasRank()">>; // Checks if the value has rank of `n`. class HasRankOf<int n> : Constraint< CPred<"$0.getType().cast<ShapedType>().hasRank() && " "$0.getType().cast<ShapedType>().getRank() == " # n>, "Checks if the value has rank of 'n'.">;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 08 04:55:44 UTC 2024 - 6.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/export_utils.h
// ShapeContainerT is any type with the following methods: // bool hasRank() // ArrayRef<int64_t> getShape() // This includes mlir::TF::ShapeAttr and mlir::ShapedType. template <typename ShapeContainerT> void SetTensorShapeProto(ShapeContainerT shape, TensorShapeProto* proto) { if (shape.hasRank()) { for (int64_t dim : shape.getShape()) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Apr 26 09:37:10 UTC 2024 - 3.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_lifting.td
def ReshapeTo1DTensor : NativeCodeCall< "quant::ReshapeTo1DTensor($_builder, $_loc, $0)">; def HasEqualShape : Constraint<CPred< "$0.getType().cast<ShapedType>().hasRank() && " "$1.getType().cast<ShapedType>().hasRank() && " "$0.getType().cast<ShapedType>().getShape() == $1.getType().cast<ShapedType>().getShape()">, "Checks if the shapes of tensors are same.">;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 14 03:24:59 UTC 2024 - 8.4K bytes - Viewed (0) -
subprojects/core/src/main/java/org/gradle/internal/build/DefaultBuildLifecycleController.java
private final BuildModelController modelController; private final StateTransitionController<State> state; private final GradleInternal gradle; private boolean hasTasks; private boolean hasFiredBeforeModelDiscarded; public DefaultBuildLifecycleController( GradleInternal gradle, BuildModelController buildModelController,
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Tue May 21 11:17:11 UTC 2024 - 16.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/replace_cast_hacks_with_tf_xla_ops.cc
auto input_shape = mlir::cast<ShapedType>(input.getType()); auto filter_shape = mlir::cast<ShapedType>(filter.getType()); if (!input_shape.hasRank() || input_shape.getRank() != 4 || !filter_shape.hasRank() || filter_shape.getRank() != 4) { emitError(loc, "input and filter are expected to be 4D tensors"); return {}; } const int feature_group_cnt =
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/tensorflow/transforms/optimize.cc
auto input_type = mlir::cast<ShapedType>(op.getInput().getType()); auto output_type = mlir::cast<ShapedType>(op.getOutput().getType()); if (!input_type.hasRank() || !output_type.hasRank()) return failure(); // The pattern attempts to reduce the rank of the input to BroadcastTo. // Thus, we fail to match if the consuming reshape rank is larger.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_lifting.cc
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; for (auto idx : val1_indices) { if (idx < 0) idx = idx + val1_shape.getRank();
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/tensorflow/ir/tf_ops_n_z.cc
// If data is unranked or data_rank is 0, this will remain -2. Otherwise // refers to first dimension of then and/or else. int64_t data_first_dim = -2; bool then_has_rank = then_tensor.hasRank(); bool else_has_rank = else_tensor.hasRank(); if (then_has_rank && else_has_rank) { data_rank = then_tensor.getRank(); if (then_tensor.getRank() > 0) data_first_dim = then_tensor.getShape().front();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 22:07:10 UTC 2024 - 170.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/shape_inference.cc
// taking the most specialized. This combines `10x?x?` and `?x?x8` into // `10x?x8`. if (!lhs_shape_type.hasRank()) { if (rhs_shape_type.hasRank()) { shape.append(rhs_shape_type.getShape().begin(), rhs_shape_type.getShape().end()); refined_shape = true; } } else if (rhs_shape_type.hasRank()) { for (auto shape_elts : llvm::enumerate(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jun 08 07:28:49 UTC 2024 - 134.1K bytes - Viewed (0)