Removed TENSOR_OP disable env vars.

* TF_DISABLE_CUBLAS_TENSOR_OP_MATH
* TF_DISABLE_CUDNN_TENSOR_OP_MATH
* TF_DISABLE_CUDNN_RNN_TENSOR_OP_MATH

tensorflow/stream_executor/cuda/cuda_blas.cc

@@ -101,18 +101,6 @@ static std::string ToString(cublasStatus_t status) {
   }
 }
 
-// Decide whether to enable TENSOR_OP_MATH
-static bool TensorOpMathEnabled() {
-  static bool is_enabled = [] {
-    bool is_disabled;
-    TF_CHECK_OK(
-        tensorflow::ReadBoolFromEnvVar("TF_DISABLE_CUBLAS_TENSOR_OP_MATH",
-                                       /*default_val=*/false, &is_disabled));
-    return !is_disabled;
-  }();
-  return is_enabled;
-}
-
 // cuBLAS has interfaces that permit pointers to be passed from either the host
 // memory space or the device memory space; however, you must instruct it as to
 // which address space those pointers are in with cublasSetPointerMode.
@@ -1640,7 +1628,7 @@ bool CUDABlas::DoBlasGemm(
                                                                    &cc_minor);
 
   // GPUs < sm_70 don't support tensor ops.
-  if (cc_major >= 7 && TensorOpMathEnabled()) {
+  if (cc_major >= 7) {
     use_tensor_ops = true;
   }
 #endif
@@ -1921,8 +1909,7 @@ static bool TensorOpsAvailable(int cc_major) {
   // strictly correct.  We can't simply enable it, though, as that would change
   // clients' behavior significantly: Using tensor ops on fp32 inputs cause them
   // to be rounded to fp16.
-  if (cc_major >= 7 && TensorOpMathEnabled() &&
+  if (cc_major >= 7 && std::is_same<InType, Eigen::half>::value) {
-      std::is_same<InType, Eigen::half>::value) {
     return true;
   }
 #endif
@@ -2270,7 +2257,7 @@ port::Status CUDABlas::DoBlasGemmBatchedInternal(
   if (stream->parent()->GetDeviceDescription().cuda_compute_capability(
           &cc_major, &cc_minor) &&
       cc_major >= 5) {
-    bool use_tensor_ops = TensorOpMathEnabled() && data_type == CUDA_R_16F;
+    bool use_tensor_ops = data_type == CUDA_R_16F;
     cublasGemmAlgo_t algo =
         (use_tensor_ops ? CUBLAS_GEMM_DFALT_TENSOR_OP : CUBLAS_GEMM_DFALT);
     cudaDataType_t compute_type =
@@ -2425,7 +2412,7 @@ bool CUDABlas::DoBlasGemmStridedBatched(
   if (stream->parent()->GetDeviceDescription().cuda_compute_capability(
           &cc_major, &cc_minor)) {
     // GPUs < sm_70 don't support tensor ops.
-    if (cc_major >= 7 && TensorOpMathEnabled()) {
+    if (cc_major >= 7) {
       use_tensor_ops = true;
     }
 #if CUDA_VERSION >= 9010

tensorflow/stream_executor/cuda/cuda_dnn.cc

@@ -601,31 +601,6 @@ class CudnnFilterDescriptor {
   SE_DISALLOW_COPY_AND_ASSIGN(CudnnFilterDescriptor);
 };
 
-// A helper function to decide whether to enable the TENSOR_OP_MATH math type
-bool TensorOpMathEnabled() {
-  static bool is_enabled = [] {
-    bool is_disabled = false;
-    TF_CHECK_OK(
-        tensorflow::ReadBoolFromEnvVar("TF_DISABLE_CUDNN_TENSOR_OP_MATH",
-                                       /*default_val=*/false, &is_disabled));
-    return !is_disabled;
-  }();
-  return is_enabled;
-}
-
-// A helper function to decide whether to enable the TENSOR_OP_MATH math type
-// for RNNs.
-bool RnnTensorOpMathEnabled() {
-  static bool is_enabled = [] {
-    bool is_disabled = false;
-    TF_CHECK_OK(
-        tensorflow::ReadBoolFromEnvVar("TF_DISABLE_CUDNN_RNN_TENSOR_OP_MATH",
-                                       /*default_val=*/false, &is_disabled));
-    return !is_disabled;
-  }();
-  return is_enabled;
-}
-
 // A helper function to decide whether to use
 // CUDNN_BATCHNORM_SPATIAL_PERSISTENT in batchnorm. This mode can be faster in
 // some tasks because an optimized path may be selected for CUDNN_DATA_FLOAT
@@ -749,9 +724,7 @@ class CudnnConvolutionDescriptor {
 #if CUDNN_VERSION >= 7000
     cudnnMathType_t math_type =
         (use_tensor_op_math ? CUDNN_TENSOR_OP_MATH : CUDNN_DEFAULT_MATH);
-    if (TensorOpMathEnabled()) {
     CHECK_CUDNN_OK(cudnnSetConvolutionMathType(handle_.get(), math_type));
-    }
 #endif
   }
 
@@ -1155,7 +1128,6 @@ class CudnnRnnDescriptor : public dnn::RnnDescriptor {
     // in profile mode, which is run with algorithms returned from
     // GetRnnAlgorithms() (which are non-default and explicitly set whether to
     // use tensor ops). CuDNN 7.2.1 fixed this issue
-    if (RnnTensorOpMathEnabled()) {
     cudnnMathType_t math_type;
     if (algorithm_config.algorithm().has_value()) {
       math_type = algorithm_config.algorithm()->tensor_ops_enabled()
@@ -1169,7 +1141,6 @@ class CudnnRnnDescriptor : public dnn::RnnDescriptor {
 #endif  // CUDNN_VERSION >= 7201
     }
     CHECK_CUDNN_OK(cudnnSetRNNMatrixMathType(rnn_desc.get(), math_type));
-    }
 #endif  // CUDNN_VERSION >= 7000
 
     return CudnnRnnDescriptor(cudnn, std::move(rnn_desc), std::move(rnn_plan),
@@ -2686,7 +2657,7 @@ AllocateCudnnConvolutionBackwardFilterWorkspace(
 }
 
 static bool TensorOpMathAvailable(int cc_major) {
-  return cc_major >= 7 && CUDNN_VERSION >= 7000 && TensorOpMathEnabled();
+  return cc_major >= 7 && CUDNN_VERSION >= 7000;
 }
 
 port::StatusOr<dnn::AlgorithmDesc> GetCudnnConvolutionForwardAlgorithm(
@@ -3480,9 +3451,7 @@ bool CudnnSupport::GetRnnAlgorithms(
   for (auto i : algo_types) {
     out_algorithms->push_back({i, /*use_tensor_ops=*/false});
 #if CUDNN_VERSION >= 7100
-    if (RnnTensorOpMathEnabled()) {
     out_algorithms->push_back({i, /*use_tensor_ops=*/true});
-    }
 #endif
   }
   return true;