public class SDVariable extends Object implements Serializable
Modifier and Type  Field and Description 

protected DataType 
dataType 
protected SameDiff 
sameDiff 
protected long[] 
shape 
protected VariableType 
variableType 
protected String 
varName 
Constructor and Description 

SDVariable(@NonNull String varName,
@NonNull VariableType varType,
@NonNull SameDiff sameDiff,
long[] shape,
DataType dataType) 
Modifier and Type  Method and Description 

SDVariable 
add(double scalar)

SDVariable 
add(SDVariable other)

SDVariable 
add(String varName,
double scalar)
Scalar addition:
out = this + scalar Output variable has the same shape as the input variable 
SDVariable 
add(String name,
SDVariable x)
Addition operation: elementwise
this + x If this and x variables have equal shape, the output shape is the same as the inputs. Supports broadcasting: if this and x have different shapes and are broadcastable, the output shape is broadcast. 
void 
addControlDependency(SDVariable controlDependency)
Add a control dependency for this variable on the specified variable.
Control dependencies can be used to enforce the execution order. 
SDVariable 
argmax(int... dimensions)

SDVariable 
argmax(String name,
boolean keepDims,
int... dimensions)
Argmax array reduction operation, optionally along specified dimensions.
Output values are the index of the maximum value of each slice along the specified dimension. Note that if keepDims = true, the output variable has the same rank as the input variable, with the reduced dimensions having size 1. 
SDVariable 
argmax(String name,
int... dimensions)

SDVariable 
argmin(int... dimensions)

SDVariable 
argmin(String name,
boolean keepDims,
int... dimensions)
Argmin array reduction operation, optionally along specified dimensions.
Output values are the index of the minimum value of each slice along the specified dimension. Note that if keepDims = true, the output variable has the same rank as the input variable, with the reduced dimensions having size 1. 
SDVariable 
argmin(String name,
int... dimensions)

SDVariable 
assign(Number value)
Return a variable with equal shape to the input, but all elements set to the specified value

SDVariable 
castTo(@NonNull DataType dataType) 
SDVariable 
castTo(String name,
@NonNull DataType dataType) 
SDVariable 
clone(SameDiff sd) 
SDVariable 
convertToConstant()
Convert this variable to a constant.

SDVariable 
convertToVariable()
Convert this variable to a VARIABLE type SDVariable.
This can only be done for constants and placeholders, not ARRAY type variables (which are usually network activations). 
DataType 
dataType() 
SDVariable 
div(double scalar)

SDVariable 
div(SDVariable x)

SDVariable 
div(String varName,
double scalar)
Scalar division:
out = this / scalar Output variable has the same shape as the input variable 
SDVariable 
div(String name,
SDVariable x)
Division operation: elementwise
this / x If this and x variables have equal shape, the output shape is the same as the inputs. Supports broadcasting: if this and x have different shapes and are broadcastable, the output shape is broadcast. 
SDVariable 
dot(SDVariable other,
int... dimensions)

SDVariable 
dot(String name,
SDVariable other,
int... dimensions)
Matrix dot product: out = dot(this,other, dimensions)

SDVariable 
dup()
Create a new SDVariable, the contents of which is copied from this current variable

SDVariable 
eq(double value)

SDVariable 
eq(SDVariable other)

SDVariable 
eq(String name,
double value)
Equals operation: elementwise
this == value Returns an array with the same shape/size as the input, with values 1 where condition is satisfied, or value 0 otherwise 
SDVariable 
eq(String name,
SDVariable other)
Equal to operation: elementwise
this == y If x and y arrays have equal shape, the output shape is the same as the inputs. Supports broadcasting: if x and y have different shapes and are broadcastable, the output shape is broadcast. Returns an array with values 1 where condition is satisfied, or value 0 otherwise. 
boolean 
equals(Object o) 
INDArray 
eval()
Evaluate the result of this variable

INDArray 
eval(Map<String,INDArray> placeholders)
Evaluate the result of this variable

SDVariable 
fdiv(String name,
SDVariable x)
Floor division operation: elementwise
this // x If this and x variables have equal shape, the output shape is the same as the inputs. Supports broadcasting: if this and x have different shapes and are broadcastable, the output shape is broadcast. 
SDVariable 
get(SDIndex... indices)
Get a variable with content equal to a specified subarray of this variable.
Can be used (for example) to get rows, columns, submatrices, etc. 
INDArray 
getArr()
A getter for the allocated ndarray with this
SDVariable . 
INDArray 
getArr(boolean enforceExistence)
A getter for the allocated ndarray with this
SDVariable . 
SDVariable 
getGradient()
The gradient variable is the variable that represents the derivative of the loss function with respect
to the output of this variable.

long[] 
getShape()
Returns the shape of this variable

LongShapeDescriptor 
getShapeDescriptor() 
String 
getVarName()
Deprecated.
Use
name() 
SDVariable 
gradient()
Alias for the gradient variable  same as
getGradient() . 
SDVariable 
gt(double value)

SDVariable 
gt(SDVariable other)

SDVariable 
gt(String name,
double value)
Greater than operation: elementwise
this > value Returns an array with the same shape/size as the input, with values 1 where condition is satisfied, or value 0 otherwise 
SDVariable 
gt(String name,
SDVariable other)
Greater than operation: elementwise
this > y If x and y arrays have equal shape, the output shape is the same as the inputs. Supports broadcasting: if x and y have different shapes and are broadcastable, the output shape is broadcast. Returns an array with values 1 where condition is satisfied, or value 0 otherwise. 
SDVariable 
gte(double value)

SDVariable 
gte(SDVariable other)

SDVariable 
gte(String name,
double value)
Greater than or equals operation: elementwise
this >= value Returns an array with the same shape/size as the input, with values 1 where condition is satisfied, or value 0 otherwise 
SDVariable 
gte(String name,
SDVariable other)
Greater than or equal to operation: elementwise
this >= y If x and y arrays have equal shape, the output shape is the same as the inputs. Supports broadcasting: if x and y have different shapes and are broadcastable, the output shape is broadcast. Returns an array with values 1 where condition is satisfied, or value 0 otherwise. 
boolean 
hasGradient()
Determine if this variable has a gradient with respect to the current loss.

int 
hashCode() 
boolean 
isConstant() 
boolean 
isPlaceHolder()
Returns true if this variable is a place holder

SDVariable 
lt(double value)

SDVariable 
lt(SDVariable other)

SDVariable 
lt(String name,
double value)
Less than operation: elementwise
this < value Returns an array with the same shape/size as the input, with values 1 where condition is satisfied, or value 0 otherwise 
SDVariable 
lt(String name,
SDVariable other)
Less than operation: elementwise
this < y If x and y arrays have equal shape, the output shape is the same as the inputs. Supports broadcasting: if x and y have different shapes and are broadcastable, the output shape is broadcast. Returns an array with values 1 where condition is satisfied, or value 0 otherwise. 
SDVariable 
lte(double value)

SDVariable 
lte(SDVariable other)

SDVariable 
lte(String name,
double value)
Less than or equals operation: elementwise
this <= value Returns an array with the same shape/size as the input, with values 1 where condition is satisfied, or value 0 otherwise 
SDVariable 
lte(String name,
SDVariable other)
Less than or equal to operation: elementwise
this <= y If x and y arrays have equal shape, the output shape is the same as the inputs. Supports broadcasting: if x and y have different shapes and are broadcastable, the output shape is broadcast. Returns an array with values 1 where condition is satisfied, or value 0 otherwise. 
void 
markAsLoss()
Mark this variable as a loss function variable.

SDVariable 
max(boolean keepDims,
int... dimensions)

SDVariable 
max(int... dimensions)

SDVariable 
max(String name,
boolean keepDims,
int... dimensions)
Maximum array reduction operation, optionally along specified dimensions
Note that if keepDims = true, the output variable has the same rank as the input variable, with the reduced dimensions having size 1. 
SDVariable 
max(String name,
int... dimensions)

SDVariable 
mean(boolean keepDims,
int... dimensions)

SDVariable 
mean(int... dimensions)

SDVariable 
mean(String name,
boolean keepDims,
int... dimensions)
Mean (average) array reduction operation, optionally along specified dimensions
Note that if keepDims = true, the output variable has the same rank as the input variable, with the reduced dimensions having size 1. 
SDVariable 
mean(String name,
int... dimensions)

SDVariable 
min(boolean keepDims,
int... dimensions)

SDVariable 
min(int... dimensions)

SDVariable 
min(String name,
boolean keepDims,
int... dimensions)
Minimum array reduction operation, optionally along specified dimensions.

SDVariable 
min(String name,
int... dimensions)

SDVariable 
minus(double other)
For Kotlin operator interop

SDVariable 
minus(SDVariable other)
For Kotlin operator interop

SDVariable 
mmul(SDVariable other)

SDVariable 
mmul(String name,
SDVariable other)
Matrix multiplication: out = mmul(this,other)

SDVariable 
mmul(String name,
SDVariable other,
@NonNull MMulTranspose mMulTranspose)
Matrix multiplication: out = mmul(this,other)

SDVariable 
mod(String name,
SDVariable x)
Modulo operation: elementwise
this / x If this and x variables have equal shape, the output shape is the same as the inputs. Supports broadcasting: if this and x have different shapes and are broadcastable, the output shape is broadcast. 
SDVariable 
mul(double scalar)

SDVariable 
mul(SDVariable x)

SDVariable 
mul(String varName,
double scalar)
Scalar multiplication:
out = this * scalar Output variable has the same shape as the input variable 
SDVariable 
mul(String name,
SDVariable x)
Multiplication operation: elementwise
this * x If this and x variables have equal shape, the output shape is the same as the inputs. Supports broadcasting: if this and x have different shapes and are broadcastable, the output shape is broadcast. 
String 
name()
Get the name of the SDVariable

SDVariable 
neg()
Negate op  returns a new variable with the values of the current variable negated

SDVariable 
neg(String name)
Negate op  returns a new variable with the values of the current variable negated

SDVariable 
neq(double value)
See
neq(SDVariable) 
SDVariable 
neq(SDVariable other)

SDVariable 
neq(String name,
double value)
Not equals operation: elementwise
this != value Returns an array with the same shape/size as the input, with values 1 where condition is satisfied, or value 0 otherwise 
SDVariable 
neq(String name,
SDVariable other)
Not equal to operation: elementwise
this != y If x and y arrays have equal shape, the output shape is the same as the inputs. Supports broadcasting: if x and y have different shapes and are broadcastable, the output shape is broadcast. Returns an array with values 1 where condition is satisfied, or value 0 otherwise. 
SDVariable 
norm1(boolean keepDims,
int... dimensions)

SDVariable 
norm1(int... dimensions)

SDVariable 
norm1(String name,
boolean keepDims,
int... dimensions)
Norm1 (L1 norm) reduction operation: The output contains the L1 norm for each tensor/subset along the specified dimensions:
out = sum_i abs(x[i]) Note that if keepDims = true, the output variable has the same rank as the input variable, with the reduced dimensions having size 1. 
SDVariable 
norm1(String name,
int... dimensions)

SDVariable 
norm2(boolean keepDims,
int... dimensions)

SDVariable 
norm2(int... dimensions)

SDVariable 
norm2(String name,
boolean keepDims,
int... dimensions)
Norm2 (L2 norm) reduction operation: The output contains the L2 norm for each tensor/subset along the specified dimensions:
out = sqrt(sum_i x[i]^2) Note that if keepDims = true, the output variable has the same rank as the input variable, with the reduced dimensions having size 1. 
SDVariable 
norm2(String name,
int... dimensions)

SDVariable 
normmax(boolean keepDims,
int... dimensions)

SDVariable 
normmax(int... dimensions)

SDVariable 
normmax(String name,
boolean keepDims,
int... dimensions)
Max norm (infinity norm) reduction operation: The output contains the max norm for each tensor/subset along the
specified dimensions:
out = max(abs(x[i])) Note that if keepDims = true, the output variable has the same rank as the input variable, with the reduced dimensions having size 1. 
SDVariable 
normmax(String name,
int... dimensions)

SDVariable 
permute(int... dimensions)
Permute the dimensions of the current variable according to the specified permutation indices.
Example: if the current variable has shape [a,b,c] and dimensions = [2,0,1] the output has shape [c,a,b] 
SDVariable 
permute(SDVariable dimensions) 
long[] 
placeholderShape() 
SDVariable 
plus(double other)
For Kotlin operator interop

SDVariable 
plus(SDVariable other)
For Kotlin operator interop

SDVariable 
pow(double scalar)

SDVariable 
pow(String varName,
double scalar)
Scalar power operation:
out = this ^ scalar Output variable has the same shape as the input variable 
SDVariable 
prod(boolean keepDims,
int... dimensions)

SDVariable 
prod(int... dimensions)

SDVariable 
prod(String name,
boolean keepDims,
int... dimensions)
Product array reduction operation, optionally along specified dimensions
Note that if keepDims = true, the output variable has the same rank as the input variable, with the reduced dimensions having size 1. 
SDVariable 
prod(String name,
int... dimensions)

SDVariable 
rank()
Get the rank of this variable as a dynamic SDVariable

SDVariable 
rdiv(double scalar)

SDVariable 
rdiv(SDVariable sameDiffVariable)

SDVariable 
rdiv(String varName,
double scalar)
Scalar reverse division:
out = scalar / this Output variable has the same shape as the input variable 
SDVariable 
rdiv(String name,
SDVariable x)
Reverse division operation: elementwise
x / this If this and x variables have equal shape, the output shape is the same as the inputs. Supports broadcasting: if this and x have different shapes and are broadcastable, the output shape is broadcast. 
SDVariable 
rename(String newName)
Rename this variable to a new name.

SDVariable 
reshape(int... newShape)
Reshape the current variable to the specified shape.

SDVariable 
reshape(long... newShape)
Reshape the current variable to the specified shape.

SDVariable 
reshape(SDVariable newShape)
Reshape the current variable to the specified (dynamic) shape.

SDVariable 
rsub(double scalar)

SDVariable 
rsub(SDVariable x)

SDVariable 
rsub(String varName,
double scalar)
Scalar reverse subtraction:
out = scalar  this Output variable has the same shape as the input variable 
SDVariable 
rsub(String name,
SDVariable x)
Reverse subtraction operation: elementwise
x  this If this and x variables have equal shape, the output shape is the same as the inputs. Supports broadcasting: if this and x have different shapes and are broadcastable, the output shape is broadcast. 
SDVariable 
setArray(INDArray array)
Associate the specified array with this variable

void 
setShape(long... shape) 
SDVariable 
shape()
Get the shape of the array as a dynamic SDVariable

SDVariable 
squaredDifference(SDVariable x)

SDVariable 
squaredDifference(String name,
SDVariable x)
Squared difference operation:
(this  x)^2 
SDVariable 
std(boolean biasCorrected,
int... dimensions)

SDVariable 
std(String name,
boolean biasCorrected,
boolean keepDims,
int... dimensions)
Stardard deviation array reduction operation, optionally along specified dimensions
Note that if keepDims = true, the output variable has the same rank as the input variable, with the reduced dimensions having size 1. 
SDVariable 
std(String name,
boolean biasCorrected,
int... dimensions)

SDVariable 
sub(double scalar)

SDVariable 
sub(SDVariable x)

SDVariable 
sub(String varName,
double scalar)
Scalar subtraction:
out = this  scalar Output variable has the same shape as the input variable 
SDVariable 
sub(String name,
SDVariable x)
Subtraction operation: elementwise
this  x If this and x variables have equal shape, the output shape is the same as the inputs. Supports broadcasting: if this and x have different shapes and are broadcastable, the output shape is broadcast. 
SDVariable 
sum(boolean keepDims,
int... dimensions)

SDVariable 
sum(int... dimensions)

SDVariable 
sum(String name,
boolean keepDims,
int... dimensions)
Sum array reduction operation, optionally along specified dimensions.
Note that if keepDims = true, the output variable has the same rank as the input variable, with the reduced dimensions having size 1. 
SDVariable 
sum(String name,
int... dimensions)

SDVariable 
times(double other)
For Kotlin operator interop

SDVariable 
times(SDVariable other)
For Kotlin operator interop

String 
toString() 
protected SameDiff sameDiff
protected String varName
protected VariableType variableType
protected long[] shape
protected DataType dataType
public SDVariable(@NonNull @NonNull String varName, @NonNull @NonNull VariableType varType, @NonNull @NonNull SameDiff sameDiff, long[] shape, DataType dataType)
public String name()
@Deprecated public String getVarName()
name()
public boolean isPlaceHolder()
public boolean isConstant()
public INDArray getArr()
SDVariable
.
This getter will lazy initialize an array if one is not found based on the associated shape and
WeightInitScheme
 if this is possible. If this is not possible (due to shapes being unknown, etc)
null is returnedINDArray
associated with this variable.public INDArray getArr(boolean enforceExistence)
SDVariable
.
This getter will lazy initialize an array if one is not found based on the associated shape and
WeightInitScheme
 if this is possible.INDArray
associated with this variable.public SDVariable gradient()
getGradient()
.
The gradient variable is the variable that represents the derivative of the loss function with respect
to the output of this variable. I.e., if this variable is X and loss function is L, then gradient() returns the
variable representing dL/dX.public SDVariable getGradient()
SameDiff.setLossVariables(String...)
and then create the
gradient functions using SameDiff.createGradFunction()
. Alternatively, the gradient function will be
created automatically when training is performed.public long[] getShape()
public void setShape(long... shape)
public long[] placeholderShape()
public DataType dataType()
public LongShapeDescriptor getShapeDescriptor()
public SDVariable castTo(@NonNull @NonNull DataType dataType)
public SDVariable castTo(String name, @NonNull @NonNull DataType dataType)
public SDVariable dup()
public SDVariable assign(Number value)
value
 Value for returned variablepublic SDVariable neg()
public SDVariable neg(String name)
name
 Name of the new variablepublic SDVariable lt(double value)
public SDVariable lt(String name, double value)
this < value
name
 Name of the output variablevalue
 value argument to use in operationpublic SDVariable lte(double value)
public SDVariable lte(String name, double value)
this <= value
name
 Name of the output variablevalue
 value argument to use in operationpublic SDVariable gt(double value)
public SDVariable gt(String name, double value)
this > value
name
 Name of the output variablevalue
 value argument to use in operationpublic SDVariable gte(double value)
public SDVariable gte(String name, double value)
this >= value
name
 Name of the output variablevalue
 value argument to use in operationpublic SDVariable eq(double value)
public SDVariable eq(String name, double value)
this == value
name
 Name of the output variablevalue
 value argument to use in operationpublic SDVariable neq(double value)
neq(SDVariable)
public SDVariable neq(String name, double value)
this != value
name
 Name of the output variablevalue
 value argument to use in operationpublic SDVariable lt(SDVariable other)
public SDVariable lt(String name, SDVariable other)
this < y
name
 Name of the output variableother
 Variable to compare values againstpublic SDVariable lte(SDVariable other)
public SDVariable lte(String name, SDVariable other)
this <= y
name
 Name of the output variableother
 Variable to compare values againstpublic SDVariable gt(SDVariable other)
public SDVariable gt(String name, SDVariable other)
this > y
name
 Name of the output variableother
 Variable to compare values againstpublic SDVariable gte(SDVariable other)
public SDVariable gte(String name, SDVariable other)
this >= y
name
 Name of the output variableother
 Variable to compare values againstpublic SDVariable eq(SDVariable other)
public SDVariable eq(String name, SDVariable other)
this == y
name
 Name of the output variableother
 Variable to compare values againstpublic SDVariable neq(SDVariable other)
public SDVariable neq(String name, SDVariable other)
this != y
name
 Name of the output variableother
 Variable to compare values againstpublic SDVariable mmul(SDVariable other)
public SDVariable mmul(String name, SDVariable other)
name
 Name of the output variableother
 Other variable to perform matrix multiplication withpublic SDVariable mmul(String name, SDVariable other, @NonNull @NonNull MMulTranspose mMulTranspose)
name
 Name of the output variableother
 Other variable to perform matrix multiplication withmMulTranspose
 Matrix transpose configurationpublic SDVariable dot(SDVariable other, int... dimensions)
public SDVariable dot(String name, SDVariable other, int... dimensions)
name
 Name of the output variableother
 Other variable to perform matrix multiplication withpublic SDVariable add(double scalar)
public SDVariable add(String varName, double scalar)
out = this + scalar
varName
 Output variable namescalar
 Scalar for operationpublic SDVariable add(SDVariable other)
public SDVariable add(String name, SDVariable x)
this + x
name
 Name of the output variablex
 Variable to perform operation withpublic SDVariable plus(SDVariable other)
add(String, SDVariable)
public SDVariable plus(double other)
add(String, double)
public SDVariable sub(double scalar)
public SDVariable sub(String varName, double scalar)
out = this  scalar
varName
 Output variable namescalar
 Scalar for operationpublic SDVariable sub(SDVariable x)
public SDVariable sub(String name, SDVariable x)
this  x
name
 Name of the output variablex
 Variable to perform operation withpublic SDVariable minus(SDVariable other)
sub(String, SDVariable)
public SDVariable minus(double other)
sub(String, double)
public SDVariable div(double scalar)
public SDVariable div(String varName, double scalar)
out = this / scalar
varName
 Output variable namescalar
 Scalar for operationpublic SDVariable div(SDVariable x)
public SDVariable div(String name, SDVariable x)
this / x
name
 Name of the output variablex
 Variable to perform operation withpublic SDVariable fdiv(String name, SDVariable x)
this // x
name
 Name of the output variablex
 Variable to perform operation withpublic SDVariable mod(String name, SDVariable x)
this / x
name
 Name of the output variablex
 Variable to perform operation withpublic SDVariable mul(double scalar)
public SDVariable mul(String varName, double scalar)
out = this * scalar
varName
 Output variable namescalar
 Scalar for operationpublic SDVariable mul(SDVariable x)
public SDVariable mul(String name, SDVariable x)
this * x
name
 Name of the output variablex
 Variable to perform operation withpublic SDVariable times(SDVariable other)
mul(String, SDVariable)
public SDVariable times(double other)
mul(String, double)
public SDVariable pow(double scalar)
public SDVariable pow(String varName, double scalar)
out = this ^ scalar
varName
 Output variable namescalar
 Scalar for operationpublic SDVariable rsub(double scalar)
public SDVariable rsub(String varName, double scalar)
out = scalar  this
varName
 Output variable namescalar
 Scalar for operationpublic SDVariable rsub(SDVariable x)
public SDVariable rsub(String name, SDVariable x)
x  this
name
 Name of the output variablex
 Variable to perform operation withpublic SDVariable rdiv(double scalar)
public SDVariable rdiv(String varName, double scalar)
out = scalar / this
varName
 Output variable namescalar
 Scalar for operationpublic SDVariable rdiv(SDVariable sameDiffVariable)
public SDVariable rdiv(String name, SDVariable x)
x / this
name
 Name of the output variablex
 Variable to perform operation withpublic SDVariable squaredDifference(SDVariable x)
public SDVariable squaredDifference(String name, SDVariable x)
(this  x)^2
x
 Other input variablepublic SDVariable sum(int... dimensions)
public SDVariable sum(boolean keepDims, int... dimensions)
public SDVariable sum(String name, int... dimensions)
public SDVariable sum(String name, boolean keepDims, int... dimensions)
name
 Output variable namekeepDims
 If true: keep the dimensions that are reduced on (as length 1). False: remove the reduction dimensionsdimensions
 Dimensions to reduce over. If dimensions are not specified, full array reduction is performedpublic SDVariable mean(boolean keepDims, int... dimensions)
public SDVariable mean(String name, int... dimensions)
public SDVariable mean(int... dimensions)
public SDVariable mean(String name, boolean keepDims, int... dimensions)
name
 Output variable namekeepDims
 If true: keep the dimensions that are reduced on (as size 1). False: remove the reduction dimensionsdimensions
 Dimensions to reduce over. If dimensions are not specified, full array reduction is performedpublic SDVariable std(boolean biasCorrected, int... dimensions)
public SDVariable std(String name, boolean biasCorrected, int... dimensions)
public SDVariable std(String name, boolean biasCorrected, boolean keepDims, int... dimensions)
biasCorrected
 If true: divide by (N1) (i.e., sample stdev). If false: divide by N (population stdev)keepDims
 If true: keep the dimensions that are reduced on (as size 1). False: remove the reduction dimensionsdimensions
 Dimensions to reduce over. If dimensions are not specified, full array reduction is performedpublic SDVariable prod(int... dimensions)
public SDVariable prod(boolean keepDims, int... dimensions)
public SDVariable prod(String name, int... dimensions)
public SDVariable prod(String name, boolean keepDims, int... dimensions)
name
 Output variable namekeepDims
 If true: keep the dimensions that are reduced on (as length 1). False: remove the reduction dimensionsdimensions
 Dimensions to reduce over. If dimensions are not specified, full array reduction is performedpublic SDVariable min(int... dimensions)
public SDVariable min(boolean keepDims, int... dimensions)
public SDVariable min(String name, int... dimensions)
public SDVariable min(String name, boolean keepDims, int... dimensions)
name
 Output variable namekeepDims
 If true: keep the dimensions that are reduced on (as size 1). False: remove the reduction dimensionsdimensions
 Dimensions to reduce over. If dimensions are not specified, full array reduction is performedpublic SDVariable max(int... dimensions)
public SDVariable max(String name, int... dimensions)
public SDVariable max(boolean keepDims, int... dimensions)
public SDVariable max(String name, boolean keepDims, int... dimensions)
name
 Output variable namekeepDims
 If true: keep the dimensions that are reduced on (as size 1). False: remove the reduction dimensionsdimensions
 Dimensions to reduce over. If dimensions are not specified, full array reduction is performedpublic SDVariable norm1(int... dimensions)
public SDVariable norm1(boolean keepDims, int... dimensions)
public SDVariable norm1(String name, int... dimensions)
public SDVariable norm1(String name, boolean keepDims, int... dimensions)
out = sum_i abs(x[i])
name
 Output variable namekeepDims
 If true: keep the dimensions that are reduced on (as size 1). False: remove the reduction dimensionsdimensions
 dimensions to reduce overpublic SDVariable norm2(int... dimensions)
public SDVariable norm2(boolean keepDims, int... dimensions)
public SDVariable norm2(String name, int... dimensions)
public SDVariable norm2(String name, boolean keepDims, int... dimensions)
out = sqrt(sum_i x[i]^2)
name
 Output variable namekeepDims
 If true: keep the dimensions that are reduced on (as size 1). False: remove the reduction dimensionsdimensions
 dimensions to reduce overpublic SDVariable normmax(int... dimensions)
public SDVariable normmax(boolean keepDims, int... dimensions)
public SDVariable normmax(String name, int... dimensions)
public SDVariable normmax(String name, boolean keepDims, int... dimensions)
out = max(abs(x[i]))
name
 Output variable namekeepDims
 If true: keep the dimensions that are reduced on (as size 1). False: remove the reduction dimensionsdimensions
 dimensions to reduce overpublic SDVariable argmax(int... dimensions)
public SDVariable argmax(String name, int... dimensions)
public SDVariable argmax(String name, boolean keepDims, int... dimensions)
name
 Name of the output variablekeepDims
 If true: keep the dimensions that are reduced on (as size 1). False: remove the reduction dimensionsdimensions
 Dimensions to reduce over. If dimensions are not specified, full array reduction is performedpublic SDVariable argmin(int... dimensions)
public SDVariable argmin(String name, int... dimensions)
public SDVariable argmin(String name, boolean keepDims, int... dimensions)
name
 Name of the output variablekeepDims
 If true: keep the dimensions that are reduced on (as length 1). False: remove the reduction dimensionsdimensions
 Dimensions to reduce over. If dimensions are not specified, full array reduction is performedpublic SDVariable shape()
public SDVariable rank()
public SDVariable reshape(SDVariable newShape)
newShape
 New shape for variablepublic SDVariable reshape(int... newShape)
newShape
 New shape for variablepublic SDVariable reshape(long... newShape)
newShape
 New shape for variablepublic SDVariable permute(int... dimensions)
dimensions
 The new dimension orderpublic SDVariable permute(SDVariable dimensions)
public SDVariable setArray(INDArray array)
array
 Array to associate with this variablepublic INDArray eval()
public INDArray eval(Map<String,INDArray> placeholders)
public void addControlDependency(SDVariable controlDependency)
controlDependency
 Control dependency to add for this variablepublic SDVariable get(SDIndex... indices)
indices
 Indices to getpublic SDVariable convertToConstant()
public SDVariable convertToVariable()
public SDVariable rename(String newName)
SameDiff.renameVariable(String, String)
newName
 The new name for the variable  no variable with this name must already existpublic void markAsLoss()
SameDiff.addLossVariable(String)
public boolean hasGradient()
SameDiff.createGradFunction()
and SameDiff.setLossVariables(String...)
public SDVariable clone(SameDiff sd)
Copyright © 2020. All rights reserved.