{in=Variable(name=in, variable=SDVariable(name="in",variableType=PLACEHOLDER,dtype=FLOAT,shape=[784]), inputsForOp=[xw_plus_b], controlDepsForOp=null, controlDepsForVar=null, outputOfOp=null, controlDeps=null, outputOfOpIdx=0, gradient=null, variableIndex=0), sd_var=Variable(name=sd_var, variable=SDVariable(name="sd_var",variableType=VARIABLE,dtype=FLOAT), inputsForOp=[xw_plus_b], controlDepsForOp=null, controlDepsForVar=null, outputOfOp=null, controlDeps=null, outputOfOpIdx=0, gradient=null, variableIndex=0), sd_var_1=Variable(name=sd_var_1, variable=SDVariable(name="sd_var_1",variableType=VARIABLE,dtype=FLOAT), inputsForOp=[xw_plus_b], controlDepsForOp=null, controlDepsForVar=null, outputOfOp=null, controlDeps=null, outputOfOpIdx=0, gradient=null, variableIndex=0), xw_plus_b=Variable(name=xw_plus_b, variable=SDVariable(name="xw_plus_b",variableType=ARRAY,dtype=FLOAT), inputsForOp=[xw_plus_b_1], controlDepsForOp=null, controlDepsForVar=null, outputOfOp=xw_plus_b, controlDeps=null, outputOfOpIdx=0, gradient=null, variableIndex=0), sd_var_2=Variable(name=sd_var_2, variable=SDVariable(name="sd_var_2",variableType=VARIABLE,dtype=FLOAT), inputsForOp=[xw_plus_b_1], controlDepsForOp=null, controlDepsForVar=null, outputOfOp=null, controlDeps=null, outputOfOpIdx=0, gradient=null, variableIndex=0), sd_var_3=Variable(name=sd_var_3, variable=SDVariable(name="sd_var_3",variableType=VARIABLE,dtype=FLOAT), inputsForOp=[xw_plus_b_1], controlDepsForOp=null, controlDepsForVar=null, outputOfOp=null, controlDeps=null, outputOfOpIdx=0, gradient=null, variableIndex=0), xw_plus_b_1=Variable(name=xw_plus_b_1, variable=SDVariable(name="xw_plus_b_1",variableType=ARRAY,dtype=FLOAT), inputsForOp=[xw_plus_b_2], controlDepsForOp=null, controlDepsForVar=null, outputOfOp=xw_plus_b_1, controlDeps=null, outputOfOpIdx=0, gradient=null, variableIndex=0), sd_var_4=Variable(name=sd_var_4, variable=SDVariable(name="sd_var_4",variableType=VARIABLE,dtype=FLOAT), inputsForOp=[xw_plus_b_2], controlDepsForOp=null, controlDepsForVar=null, outputOfOp=null, controlDeps=null, outputOfOpIdx=0, gradient=null, variableIndex=0), sd_var_5=Variable(name=sd_var_5, variable=SDVariable(name="sd_var_5",variableType=VARIABLE,dtype=FLOAT), inputsForOp=[xw_plus_b_2], controlDepsForOp=null, controlDepsForVar=null, outputOfOp=null, controlDeps=null, outputOfOpIdx=0, gradient=null, variableIndex=0), xw_plus_b_2=Variable(name=xw_plus_b_2, variable=SDVariable(name="xw_plus_b_2",variableType=ARRAY,dtype=FLOAT), inputsForOp=[std], controlDepsForOp=null, controlDepsForVar=null, outputOfOp=xw_plus_b_2, controlDeps=null, outputOfOpIdx=0, gradient=null, variableIndex=0), loss=Variable(name=loss, variable=SDVariable(name="loss",variableType=ARRAY,dtype=FLOAT), inputsForOp=null, controlDepsForOp=null, controlDepsForVar=null, outputOfOp=std, controlDeps=null, outputOfOpIdx=0, gradient=null, variableIndex=0)}
DenselyTest:
SameDiff
14:26:16.397 [ScalaTest-main-running-DenselyTest] ERROR o.n.l.c.n.ops.NativeOpExecutioner - Failed to execute op xw_plus_b. Attempted to execute with 3 inputs, 1 outputs, 0 targs,0 bargs and 0 iargs. Inputs: [(FLOAT,[784],c), (FLOAT,[1,784],c), (FLOAT,[1,784],c)]. Outputs: [(FLOAT,[784,784],f)]. tArgs: -. iArgs: -. bArgs: -. Input var names: [in, sd_var, sd_var_1]. Output var names: [xw_plus_b] - Please see above message (printed out from c++) for a possible cause of error.
- should construct models with dense layers *** FAILED ***
  java.lang.RuntimeException: Op [xw_plus_b] execution failed
  at org.nd4j.linalg.cpu.nativecpu.ops.NativeOpExecutioner.exec(NativeOpExecutioner.java:1710)
  at org.nd4j.autodiff.samediff.internal.InferenceSession.getOutputsHelper(InferenceSession.java:505)
  at org.nd4j.autodiff.samediff.internal.InferenceSession.getOutputs(InferenceSession.java:119)
  at org.nd4j.autodiff.samediff.internal.InferenceSession.getOutputs(InferenceSession.java:56)
  at org.nd4j.autodiff.samediff.internal.AbstractSession.output(AbstractSession.java:335)
  at org.nd4j.autodiff.samediff.SameDiff.directExecHelper(SameDiff.java:3233)
  at org.nd4j.autodiff.samediff.SameDiff.execBackwards(SameDiff.java:4770)
  at org.nd4j.autodiff.samediff.SameDiff.execBackwards(SameDiff.java:4706)
  at org.nd4j.autodiff.samediff.SameDiff.fitHelper(SameDiff.java:2204)
  at org.nd4j.autodiff.samediff.SameDiff.fit(SameDiff.java:2093)
  ...
  Cause: java.lang.RuntimeException: MmulHelper::dot cuda: Z array must be scalar !
  at org.nd4j.linalg.cpu.nativecpu.ops.NativeOpExecutioner.exec(NativeOpExecutioner.java:2006)
  at org.nd4j.linalg.cpu.nativecpu.ops.NativeOpExecutioner.exec(NativeOpExecutioner.java:1700)
  at org.nd4j.autodiff.samediff.internal.InferenceSession.getOutputsHelper(InferenceSession.java:505)
  at org.nd4j.autodiff.samediff.internal.InferenceSession.getOutputs(InferenceSession.java:119)
  at org.nd4j.autodiff.samediff.internal.InferenceSession.getOutputs(InferenceSession.java:56)
  at org.nd4j.autodiff.samediff.internal.AbstractSession.output(AbstractSession.java:335)
  at org.nd4j.autodiff.samediff.SameDiff.directExecHelper(SameDiff.java:3233)
  at org.nd4j.autodiff.samediff.SameDiff.execBackwards(SameDiff.java:4770)
  at org.nd4j.autodiff.samediff.SameDiff.execBackwards(SameDiff.java:4706)
  at org.nd4j.autodiff.samediff.SameDiff.fitHelper(SameDiff.java:2204)