Provides methods to access partial result obtained with the compute() method of the neural network training algorithm in the distributed processing mode.
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- Deprecated:
- This item will be removed in a future release.
def allocate_{Float64|Float32} |
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input, |
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parameter, |
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method |
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Registers user-allocated memory to store partial results of the neural network model based training
- Parameters
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input | Pointer to an object containing input data |
method | Computation method for the algorithm |
parameter | Parameter of the neural network training |
- Returns
- Status of computations
- Deprecated:
- This item will be removed in a future release. { Distributed<step2Master>.allocatePartialResult() }
- Full Names
allocate_Float64
is for float64
allocate_Float32
is for float32
def check |
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self, |
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input, |
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par, |
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method |
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Checks partial result of the neural network algorithm
- Parameters
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input | Input object of algorithm |
par | Parameter of algorithm |
method | Computation method |
- Returns
- Status of computations
- Deprecated:
- This item will be removed in a future release.
Returns the partial result of the neural network model based training
- Parameters
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id | Identifier of the partial result |
- Returns
- Partial result that corresponds to the given identifier
- Deprecated:
- This item will be removed in a future release.
def getSerializationTag |
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self | ) |
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getSerializationTag(DistributedPartialResult self) -> int
def set |
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id, |
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value |
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Sets the partial result of neural network model based training
- Parameters
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id | Identifier of the partial result |
value | Partial result |
- Deprecated:
- This item will be removed in a future release.
The documentation for this class was generated from the following file:
- neural_networks/training.py