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Results 41 - 50 of 106 for getRank (0.23 sec)
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tensorflow/compiler/mlir/tensorflow/transforms/tpu_annotate_dynamic_shape_inputs.cc
BlockArgument arg = func.getArgument(index); auto inputType = mlir::dyn_cast<RankedTensorType>(arg.getType()); // Only rank 1 tensor is supported for now. if (!inputType || inputType.getRank() != 1) continue; auto shape = llvm::to_vector<4>(inputType.getShape()); llvm::SmallVector<int64_t, 4> bounds(shape.begin(), shape.end()); // Mark the dim as dynamic dim.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_arith_ops_folder.h
// Scalar identity is broadcastable to any operand shape, we only need to // check that operand has the same shape as a result. bool scalar_identity = identity_ty.hasRank() && identity_ty.getRank() == 0; if (scalar_identity) return operand_ty == result_ty; // If identity is not a scalar, we must verify that identity shape is // statically known to be broadcastable to the operand shape and the operand
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/tf2xla/transforms/legalize_tf_collective.cc
hlo::convertElementsAttr(group_assignment, builder.getIntegerType(64))); if (replica_groups.getType().getRank() != 2) { return op->emitOpError() << "group_assignment should have rank 2, got " << replica_groups.getType().getRank(); } return success(); } ChannelHandleAttr ConvertChannel(OpBuilder& builder, int64_t channel_id,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 16K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/utils.td
// Checks if the value has rank at most 'n'. class HasRankAtLeast<int n> : Constraint< CPred<"$0.getType().cast<ShapedType>().hasRank() && " "$0.getType().cast<ShapedType>().getRank() >= " # n>>; // Checks value is not produced by a TFL_Quant or // from TFL_Quant Op with same quant type. def NotFromQuantOpOrSameQuantType : Constraint< CPred<"tflite::NotFromQuantOpOrSameQuantType($0,$1)">>;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 4.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/lower_tf.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 74.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_tf.cc
// tensor, for setting depth_multiplier attribute, etc.). auto filter = tf_op.getFilter(); auto filter_type = mlir::dyn_cast<RankedTensorType>(filter.getType()); if (!filter_type || filter_type.getRank() != 4 || !filter_type.hasStaticShape()) return failure(); Value input = tf_op.getInput(); RankedTensorType input_type = mlir::dyn_cast<RankedTensorType>(input.getType());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 21:49:50 UTC 2024 - 64.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/set_tpu_infeed_layout.cc
* layout using the TPU API. Running legalize_tf.cc on non-TPU nodes * thus is a potential source of bugs. */ minor_to_major.resize(t.getRank()); std::iota(minor_to_major.begin(), minor_to_major.end(), 0); std::sort(minor_to_major.begin(), minor_to_major.end(), [=](int64_t a, int64_t b) { int64_t da = t.getDimSize(a);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/lower_tf.td
//===----------------------------------------------------------------------===// def GetBiasAddGradReductionIndices : NativeCodeCall< "GetBiasAddGradReductionIndices(" "$0.getType().cast<RankedTensorType>().getRank(), $1, &$_builder)">; def LowerBiasAddGradOp : Pat<(TF_BiasAddGradOp AnyRankedTensor:$out_backprop, $data_format), (TF_SumOp $out_backprop, (TF_ConstOp (GetBiasAddGradReductionIndices $out_backprop,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 04 13:30:42 UTC 2024 - 24.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/post_quantize.cc
(getElementTypeOrSelf(op.getOutput().getType())))) return failure(); ElementsAttr input_tensor = qconst_op.getValue(); assert(perm_tensor.getType().getRank() == 1); const int num_dimensions = input_tensor.getShapedType().getRank(); assert(perm_tensor.getType().getNumElements() == num_dimensions); ArrayRef<int64_t> input_shape = input_tensor.getShapedType().getShape();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 17.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/fake_quant_utils.h
return failure(); } int quant_dim = -1; if (PerAxis) { // This is a special case that the quant_dim is the last dimensions. quant_dim = mlir::cast<ShapedType>(res.getType()).getRank() - 1; } // Use the min/max from the operands and the num_bits and narrow_range // attribute to create the quantization parameter for the new quantize op. rewriter.setInsertionPointAfter(tf_op.getOperation());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.6K bytes - Viewed (0)