Revert "cuda implementation of Gated Linear Unit, fixed issues with genericization"revert-430-newCudaGLU

4 files changed, 0 insertions, 117 deletions

diff --git a/lib/THCUNN/GatedLinearUnit.cu b/lib/THCUNN/GatedLinearUnit.cu
deleted file mode 100644
index d9f3471..0000000
--- a/lib/THCUNN/GatedLinearUnit.cu
+++ /dev/null
@@ -1,29 +0,0 @@
-#include "THCUNN.h"
-#include "THCHalf.h"
-#include "THCHalfAutoNumerics.cuh"
-#include "common.h"
-
-template <typename Dtype, typename Acctype>
-struct gatedLinearCSigMul_functor
-{
-  __device__ void operator()(Dtype *target, const Dtype *sigTensor, const Dtype *mulTensor) const
-  {
-    const Acctype sigNum = Acctype(1)/(Acctype(1)+ exp(ScalarConvert<Dtype, Acctype>::to(-*sigTensor)));
-    const Dtype mulNum = *mulTensor;
-    *target = ScalarConvert<Acctype, Dtype>::to(sigNum * mulNum);
-  }
-};
-
-template <typename Dtype, typename Acctype>
-struct gatedLinearDerivativeSecondHalf_functor
-{
-  __device__ void operator()(Dtype *target, const Dtype *sigTensor, const Dtype *mulTensor) const
-  {
-    const Acctype sigNum = Acctype(1)/(Acctype(1)+ exp(ScalarConvert<Dtype, Acctype>::to(-*sigTensor)));
-    const Dtype mulNum = *mulTensor;
-    *target *= ScalarConvert<Acctype, Dtype>::to((Acctype(1) - sigNum) * sigNum * mulNum);
-  }
-};
-
-#include "generic/GatedLinearUnit.cu"
-#include "THCGenerateFloatTypes.h"
\ No newline at end of file
diff --git a/lib/THCUNN/generic/GatedLinearUnit.cu b/lib/THCUNN/generic/GatedLinearUnit.cu
deleted file mode 100644
index 0684878..0000000
--- a/lib/THCUNN/generic/GatedLinearUnit.cu
+++ /dev/null
@@ -1,64 +0,0 @@
-#ifndef THC_GENERIC_FILE
-#define THC_GENERIC_FILE "generic/GatedLinearUnit.cu"
-#else
-
-void THNN_(GatedLinear_updateOutput)(
-           THCState *state,
-           THCTensor *input,
-           THCTensor *output,
-           int dim)
-{
-  THCUNN_assertSameGPU(state, 2, input, output);
-
-  // size output to half of input
-  dim = dim - 1;
-  const long nIn = THCTensor_(size)(state, input, dim);
-  THArgCheck(nIn % 2 == 0, 2, "Halving dimension must be even. Dim %d is size %ld", dim+1, nIn);
-  const long inputSize = THCTensor_(size)(state, input, dim) / 2;
-  THLongStorage *newSizes = THCTensor_(newSizeOf)(state, input);
-  THLongStorage_set(newSizes, dim, inputSize);
-  THCTensor_(resize)(state, output, newSizes, NULL);
-
-  // halve tensor
-  THCTensor *firstHalf = THCTensor_(newNarrow)(state, input, dim, 0, inputSize);
-  THCTensor *secondHalf = THCTensor_(newNarrow)(state, input, dim, inputSize, inputSize);
-
-  // x = x1:cmul( sigmoid(x2) )
-  THC_pointwiseApply3(state, output, secondHalf, firstHalf, gatedLinearCSigMul_functor<real, accreal>());
-
-  THLongStorage_free(newSizes);
-  THCTensor_(free)(state, firstHalf);
-  THCTensor_(free)(state, secondHalf);
-}
-
-void THNN_(GatedLinear_updateGradInput)(
-           THCState *state,
-           THCTensor *input,
-           THCTensor *gradOutput,
-           THCTensor *gradInput,
-           int dim)
-{
-  THCUNN_assertSameGPU(state, 2, gradOutput, gradInput);
-  dim = dim - 1;
-  const long nIn = THCTensor_(size)(state, input, dim);
-  THArgCheck(nIn % 2 == 0, 2, "Halving dimension must be even. Dim %d is size %ld", dim+1, nIn);
-
-  THCTensor_(resizeAs)(state, gradInput, input);
-  const long inputSize = THCTensor_(size)(state, input, dim) / 2;
-  THCTensor *firstHalf = THCTensor_(newNarrow)(state, input, dim, 0, inputSize);
-  THCTensor *secondHalf = THCTensor_(newNarrow)(state, input, dim, inputSize, inputSize);
-  THCTensor *gradInputfirstHalf = THCTensor_(newNarrow)(state, gradInput, dim, 0, inputSize);
-  THCTensor *gradInputsecondHalf = THCTensor_(newNarrow)(state, gradInput, dim, inputSize, inputSize);
-  // first half of derivative
-  THC_pointwiseApply3(state, gradInputfirstHalf, secondHalf, gradOutput, gatedLinearCSigMul_functor<real, accreal>());
-  // second half of derivative
-  THCTensor_(copy)(state, gradInputsecondHalf, firstHalf);
-  THC_pointwiseApply3(state, gradInputsecondHalf, secondHalf, gradOutput, gatedLinearDerivativeSecondHalf_functor<real, accreal>());
-
-  THCTensor_(free)(state, firstHalf);
-  THCTensor_(free)(state, secondHalf);
-  THCTensor_(free)(state, gradInputfirstHalf);
-  THCTensor_(free)(state, gradInputsecondHalf);
-}
-
-#endif
\ No newline at end of file
diff --git a/lib/THCUNN/generic/THCUNN.h b/lib/THCUNN/generic/THCUNN.h
index de05294..ec3d287 100644
--- a/lib/THCUNN/generic/THCUNN.h
+++ b/lib/THCUNN/generic/THCUNN.h
@@ -138,19 +138,6 @@ TH_API void THNN_(HardTanh_updateGradInput)(
                   real max_val,
                   bool inplace);
 
-TH_API void THNN_(GatedLinear_updateOutput)(
-                  THCState *state,
-                  THCudaTensor *input,
-                  THCudaTensor *output,
-                  int dim);
-
-TH_API void THNN_(GatedLinear_updateGradInput)(
-                  THCState *state,
-                  THCudaTensor *input,
-                  THCudaTensor *gradOutput,
-                  THCudaTensor *gradInput,
-                  int dim);
-
 TH_API void THNN_(LeakyReLU_updateOutput)(
                   THCState *state,
                   THCTensor *input,
diff --git a/test.lua b/test.lua
index 1fb1205..14d072d 100644
--- a/test.lua
+++ b/test.lua
@@ -84,7 +84,6 @@ end
 
 local function pointwise_forward(proto_module, name, max_error)
    local size = math.random(1,100)
-   if name == 'GatedLinearUnit' then size = size*2 end
 
    for k, typename in ipairs(typenames) do
       local input = torch.randn(size):type(typename)
@@ -106,12 +105,10 @@ end
 
 local function pointwise_backward(proto_module, name, max_error)
    local size = math.random(1,100)
-   if name == 'GatedLinearUnit' then size = size*2 end
 
    for k, typename in ipairs(typenames) do
       local input = torch.randn(size):type(typename)
       local gradOutput = torch.randn(size):type(typename)
-      if name == 'GatedLinearUnit' then gradOutput = torch.randn(size/2) end
 
       local ctype = t2cpu[typename]
       input = makeNonContiguous(input:type(ctype))
@@ -270,14 +267,6 @@ function cunntest.LogSigmoid_transposed()
    pointwise_transposed(nn.LogSigmoid(), 'LogSigmoid', 1e-6)
 end
 
-function cunntest.GatedLinearUnit_forward()
-   pointwise_forward(nn.GatedLinearUnit(), 'GatedLinearUnit', precision_forward)
-end
-
-function cunntest.GatedLinearUnit_backward()
-   pointwise_backward(nn.GatedLinearUnit(), 'GatedLinearUnit', precision_backward)
-end
-
 function cunntest.Threshold_forward()
   pointwise_forward(nn.Threshold(), 'Threshold', precision_forward)
   pointwise_forward(nn.Threshold(nil, nil, true), 'Threshold_inplace', precision_forward)