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// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: tensorflow/core/framework/tensor_shape.proto
package org.tensorflow.framework;
/**
*
* Dimensions of a tensor.
*
*
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*
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*
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* Size of the tensor in that dimension.
* This value must be >= -1, but values of -1 are reserved for "unknown"
* shapes (values of -1 mean "unknown" dimension). Certain wrappers
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* a TensorShapeProto containing a dim value of -1.
*
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* This value must be >= -1, but values of -1 are reserved for "unknown"
* shapes (values of -1 mean "unknown" dimension). Certain wrappers
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/**
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* The first entry in "dim" is the outermost dimension used to layout the
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* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
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/**
*
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* for a 30 x 40 2D tensor. If an entry has size -1, this
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* The order of entries in "dim" matters: It indicates the layout of the
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* values, the last entry is the innermost dimension. This matches the
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* The order of entries in "dim" matters: It indicates the layout of the
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* The first entry in "dim" is the outermost dimension used to layout the
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* If "dim.size()" > 0, "unknown_rank" must be false.
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*
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* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
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* The order of entries in "dim" matters: It indicates the layout of the
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* The first entry in "dim" is the outermost dimension used to layout the
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/**
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*
*
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*/
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// @@protoc_insertion_point(builder_implements:tensorflow.TensorShapeProto)
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/**
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
* corresponds to a dimension of unknown size. The names are
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* The order of entries in "dim" matters: It indicates the layout of the
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* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
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/**
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
* corresponds to a dimension of unknown size. The names are
* optional.
* The order of entries in "dim" matters: It indicates the layout of the
* values in the tensor in-memory representation.
* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
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/**
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
* corresponds to a dimension of unknown size. The names are
* optional.
* The order of entries in "dim" matters: It indicates the layout of the
* values in the tensor in-memory representation.
* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
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/**
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
* corresponds to a dimension of unknown size. The names are
* optional.
* The order of entries in "dim" matters: It indicates the layout of the
* values in the tensor in-memory representation.
* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
public Builder setDim(
int index, org.tensorflow.framework.TensorShapeProto.Dim value) {
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throw new NullPointerException();
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ensureDimIsMutable();
dim_.set(index, value);
onChanged();
} else {
dimBuilder_.setMessage(index, value);
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return this;
}
/**
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
* corresponds to a dimension of unknown size. The names are
* optional.
* The order of entries in "dim" matters: It indicates the layout of the
* values in the tensor in-memory representation.
* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
public Builder setDim(
int index, org.tensorflow.framework.TensorShapeProto.Dim.Builder builderForValue) {
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dim_.set(index, builderForValue.build());
onChanged();
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dimBuilder_.setMessage(index, builderForValue.build());
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return this;
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/**
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
* corresponds to a dimension of unknown size. The names are
* optional.
* The order of entries in "dim" matters: It indicates the layout of the
* values in the tensor in-memory representation.
* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
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dim_.add(value);
onChanged();
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/**
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
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* The order of entries in "dim" matters: It indicates the layout of the
* values in the tensor in-memory representation.
* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
public Builder addDim(
int index, org.tensorflow.framework.TensorShapeProto.Dim value) {
if (dimBuilder_ == null) {
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ensureDimIsMutable();
dim_.add(index, value);
onChanged();
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dimBuilder_.addMessage(index, value);
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/**
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
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* The order of entries in "dim" matters: It indicates the layout of the
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* The first entry in "dim" is the outermost dimension used to layout the
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* If "dim.size()" > 0, "unknown_rank" must be false.
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
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* The order of entries in "dim" matters: It indicates the layout of the
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* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
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* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
public Builder addDim(
int index, org.tensorflow.framework.TensorShapeProto.Dim.Builder builderForValue) {
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dim_.add(index, builderForValue.build());
onChanged();
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/**
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
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* The order of entries in "dim" matters: It indicates the layout of the
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* The first entry in "dim" is the outermost dimension used to layout the
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* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
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* The order of entries in "dim" matters: It indicates the layout of the
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* The first entry in "dim" is the outermost dimension used to layout the
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* If "dim.size()" > 0, "unknown_rank" must be false.
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
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* optional.
* The order of entries in "dim" matters: It indicates the layout of the
* values in the tensor in-memory representation.
* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
* corresponds to a dimension of unknown size. The names are
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* The order of entries in "dim" matters: It indicates the layout of the
* values in the tensor in-memory representation.
* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
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int index) {
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/**
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
* corresponds to a dimension of unknown size. The names are
* optional.
* The order of entries in "dim" matters: It indicates the layout of the
* values in the tensor in-memory representation.
* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
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/**
*
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* for a 30 x 40 2D tensor. If an entry has size -1, this
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* The order of entries in "dim" matters: It indicates the layout of the
* values in the tensor in-memory representation.
* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
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/**
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
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* The order of entries in "dim" matters: It indicates the layout of the
* values in the tensor in-memory representation.
* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
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org.tensorflow.framework.TensorShapeProto.Dim.getDefaultInstance());
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/**
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
* corresponds to a dimension of unknown size. The names are
* optional.
* The order of entries in "dim" matters: It indicates the layout of the
* values in the tensor in-memory representation.
* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
*
* repeated .tensorflow.TensorShapeProto.Dim dim = 2;
*/
public org.tensorflow.framework.TensorShapeProto.Dim.Builder addDimBuilder(
int index) {
return getDimFieldBuilder().addBuilder(
index, org.tensorflow.framework.TensorShapeProto.Dim.getDefaultInstance());
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/**
*
* Dimensions of the tensor, such as {"input", 30}, {"output", 40}
* for a 30 x 40 2D tensor. If an entry has size -1, this
* corresponds to a dimension of unknown size. The names are
* optional.
* The order of entries in "dim" matters: It indicates the layout of the
* values in the tensor in-memory representation.
* The first entry in "dim" is the outermost dimension used to layout the
* values, the last entry is the innermost dimension. This matches the
* in-memory layout of RowMajor Eigen tensors.
* If "dim.size()" > 0, "unknown_rank" must be false.
*
