सार्वजनिक स्थैतिक अंतिम वर्ग TensorShapeProto.Builder
Dimensions of a tensor.प्रोटोबफ़ प्रकार
tensorflow.TensorShapeProto
सार्वजनिक तरीके
TensorShapeProto.बिल्डर | addAllDim (Iterable<? TensorShapeProto.Dim > मान बढ़ाता है) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.बिल्डर | addDim ( TensorShapeProto.Dim.Builder BuilderForValue) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.बिल्डर | addDim (int इंडेक्स, TensorShapeProto.Dim.Builder BuilderForValue) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.बिल्डर | addDim (int सूचकांक, TensorShapeProto.Dim मान) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.बिल्डर | addDim ( TensorShapeProto.Dim मान) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Dim.Builder | addDimबिल्डर () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Dim.Builder | addDimBuilder (int अनुक्रमणिका) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.बिल्डर | addRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड, ऑब्जेक्ट मान) |
टेंसरशेपप्रोटो | निर्माण () |
टेंसरशेपप्रोटो | बिल्डआंशिक () |
TensorShapeProto.बिल्डर | स्पष्ट () |
TensorShapeProto.बिल्डर | क्लीयरडिम () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.बिल्डर | क्लियरफ़ील्ड (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड) |
TensorShapeProto.बिल्डर | ClearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof) |
TensorShapeProto.बिल्डर | स्पष्टअज्ञातरैंक () If true, the number of dimensions in the shape is unknown. |
TensorShapeProto.बिल्डर | क्लोन () |
टेंसरशेपप्रोटो | |
अंतिम स्थिर com.google.protobuf.Descriptors.Descriptor | |
com.google.protobuf.Descriptors.Descriptor | |
TensorShapeProto.Dim | getDim (int सूचकांक) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.Dim.Builder | getDimBuilder (int सूचकांक) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
सूची < TensorShapeProto.Dim.Builder > | getDimBuilderList () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
int यहाँ | getDimCount () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
सूची < TensorShapeProto.Dim > | getDimList () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.DimOrBuilder | getDimOrBuilder (int अनुक्रमणिका) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
सूची<? TensorShapeProto.DimOrBuilder > का विस्तार करता है | getDimOrBuilderList () Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
बूलियन | अज्ञातरैंक प्राप्त करें () If true, the number of dimensions in the shape is unknown. |
अंतिम बूलियन | |
TensorShapeProto.बिल्डर | मर्जफ्रॉम (com.google.protobuf.CodedInputStream इनपुट, com.google.protobuf.ExtensionRegistryLite एक्सटेंशनरजिस्ट्री) |
TensorShapeProto.बिल्डर | मर्जफ्रॉम (com.google.protobuf.Message अन्य) |
अंतिम TensorShapeProto.Builder | मर्जअज्ञातफ़ील्ड्स (com.google.protobuf.UnknownFieldSet अज्ञातफ़ील्ड्स) |
TensorShapeProto.बिल्डर | रिमूवडिम (इंट इंडेक्स) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.बिल्डर | setDim (int सूचकांक, TensorShapeProto.Dim मान) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.बिल्डर | सेटडिम (int इंडेक्स, TensorShapeProto.Dim.Builder BuilderForValue) Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x 40 2D tensor. |
TensorShapeProto.बिल्डर | सेटफ़ील्ड (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड, ऑब्जेक्ट मान) |
TensorShapeProto.बिल्डर | setRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड, इंट इंडेक्स, ऑब्जेक्ट वैल्यू) |
अंतिम TensorShapeProto.Builder | अज्ञात फ़ील्ड सेट करें (com.google.protobuf. अज्ञात फ़ील्ड सेट अज्ञात फ़ील्ड) |
TensorShapeProto.बिल्डर | setUnknownRank (बूलियन मान) If true, the number of dimensions in the shape is unknown. |
विरासत में मिली विधियाँ
सार्वजनिक तरीके
सार्वजनिक TensorShapeProto.Builder addAllDim (Iterable<? TensorShapeProto.Dim > मान बढ़ाता है)
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;
सार्वजनिक TensorShapeProto.Builder addDim ( TensorShapeProto.Dim.Builder BuilderForValue)
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;
सार्वजनिक TensorShapeProto.Builder addDim (int इंडेक्स, TensorShapeProto.Dim.Builder BuilderForValue)
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;
सार्वजनिक TensorShapeProto.Builder addDim (int सूचकांक, TensorShapeProto.Dim मान)
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;
सार्वजनिक TensorShapeProto.Builder addDim ( TensorShapeProto.Dim मान)
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;
सार्वजनिक TensorShapeProto.Dim.Builder addDimBuilder ()
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;
सार्वजनिक TensorShapeProto.Dim.Builder addDimBuilder (int अनुक्रमणिका)
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;
सार्वजनिक TensorShapeProto.Builder addRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड, ऑब्जेक्ट मान)
सार्वजनिक TensorShapeProto.Builder ClearDim ()
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;
सार्वजनिक TensorShapeProto.Builder ClearField (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड)
सार्वजनिक TensorShapeProto.Builder ClearOneof (com.google.protobuf.Descriptors.OneofDescriptor oneof)
सार्वजनिक TensorShapeProto.Builder ClearUnknownRank ()
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;
सार्वजनिक स्थैतिक अंतिम com.google.protobuf.Descriptors.Descriptor getDescriptor ()
सार्वजनिक com.google.protobuf.Descriptors.Descriptor getDescriptorForType ()
सार्वजनिक TensorShapeProto.Dim getDim (int अनुक्रमणिका)
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;
सार्वजनिक TensorShapeProto.Dim.Builder getDimBuilder (int अनुक्रमणिका)
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;
सार्वजनिक सूची < TensorShapeProto.Dim.Builder > getDimBuilderList ()
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;
सार्वजनिक int getDimCount ()
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;
सार्वजनिक सूची < TensorShapeProto.Dim > getDimList ()
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;
सार्वजनिक TensorShapeProto.DimOrBuilder getDimOrBuilder (int अनुक्रमणिका)
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;
सार्वजनिक सूची<? TensorShapeProto.DimOrBuilder > getDimOrBuilderList () का विस्तार करता है
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;
सार्वजनिक बूलियन getUnknownRank ()
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;
सार्वजनिक अंतिम बूलियन आरंभीकृत है ()
सार्वजनिक TensorShapeProto.Builder mergeFrom (com.google.protobuf.CodedInputStream इनपुट, com.google.protobuf.ExtensionRegistryLite एक्सटेंशनरजिस्ट्री)
फेंकता
आईओ अपवाद |
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सार्वजनिक अंतिम TensorShapeProto.Builder mergeUnknownFields (com.google.protobuf.UnknownFieldSet अज्ञातफील्ड्स)
सार्वजनिक TensorShapeProto.Builder रिमूवडिम (इंट इंडेक्स)
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;
सार्वजनिक TensorShapeProto.Builder setDim (int सूचकांक, TensorShapeProto.Dim मान)
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;
सार्वजनिक TensorShapeProto.Builder setDim (int इंडेक्स, TensorShapeProto.Dim.Builder BuilderForValue)
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;
सार्वजनिक TensorShapeProto.Builder setField (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड, ऑब्जेक्ट मान)
सार्वजनिक TensorShapeProto.Builder setRepeatedField (com.google.protobuf.Descriptors.FieldDescriptor फ़ील्ड, int अनुक्रमणिका, ऑब्जेक्ट मान)
सार्वजनिक अंतिम TensorShapeProto.Builder setUnknownFields (com.google.protobuf.UnknownFieldSet अज्ञातफील्ड्स)
सार्वजनिक TensorShapeProto.Builder setUnknownRank (बूलियन मान)
If true, the number of dimensions in the shape is unknown. If true, "dim.size()" must be 0.
bool unknown_rank = 3;