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tensorflow/core/profiler/backends/gpu/device_tracer_rocm.cc:1102:27: warning: ignoring returned value of type 'tensorflow::Status', declared with attribute nodiscard [-Wunused-result] | |
tensorflow/compiler/xla/stream_executor/rocm/rocm_dnn.cc:599:58: warning: ignoring returned value of type 'tensorflow::Status', declared with attribute nodiscard [-Wunused-result] | |
tensorflow/compiler/xla/stream_executor/rocm/rocm_dnn.cc:605:55: warning: ignoring returned value of type 'tensorflow::Status', declared with attribute nodiscard [-Wunused-result] | |
tensorflow/compiler/xla/stream_executor/rocm/rocm_dnn.cc:609:56: warning: ignoring returned value of type 'tensorflow::Status', declared with attribute nodiscard [-Wunused-result] | |
tensorflow/compiler/xla/stream_executor/rocm/rocm_dnn.cc:4134:25: warning: ignoring returned value of type 'hipError_t', declared with attribute nodiscard [-Wunused-result] | |
tensorflow/compiler/xla/stream_executor/rocm/rocm_dnn.cc:4163:40: warning: ignoring returned value of type 'hipError_t', declar |
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HloModule module | |
%scalar_add_computation (scalar_lhs: f32[], scalar_rhs: f32[]) -> f32[] { | |
%scalar_lhs = f32[] parameter(0) | |
%scalar_rhs = f32[] parameter(1) | |
ROOT %add.23852 = f32[] add(f32[] %scalar_lhs, f32[] %scalar_rhs) | |
} | |
%primitive_computation_max.289663 (parameter.289664: f32[], parameter.289665: f32[]) -> f32[] { | |
%parameter.289664 = f32[] parameter(0) |
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// | |
// Generated by LLVM NVPTX Back-End | |
// | |
.version 6.0 | |
.target sm_70 | |
.address_size 64 | |
// .globl fusion_2287 | |
.shared .align 4 .b8 shared_cache_0[128]; |
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I! CuDNN (v7604) function cudnnSetFilterNdDescriptor() called: | |
i! dataType: type=cudnnDataType_t; val=CUDNN_DATA_HALF (2); | |
i! format: type=cudnnTensorFormat_t; val=CUDNN_TENSOR_NHWC (1); | |
i! nbDims: type=int; val=4; | |
i! filterDimA: type=int; val=[256,256,3,3]; | |
i! Time: 2021-05-20T12:38:10.745481 (0d+0h+0m+24s since start) | |
i! Process=1524391; Thread=1524637; GPU=NULL; Handle=NULL; StreamId=NULL. | |
I! CuDNN (v7604) function cudnnCreateConvolutionDescriptor() called: |
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I! CuDNN (v7604) function cudnnSetFilterNdDescriptor() called: | |
i! dataType: type=cudnnDataType_t; val=CUDNN_DATA_HALF (2); | |
i! format: type=cudnnTensorFormat_t; val=CUDNN_TENSOR_NHWC (1); | |
i! nbDims: type=int; val=4; | |
i! filterDimA: type=int; val=[256,256,3,3]; | |
i! Time: 2021-05-20T12:38:10.745481 (0d+0h+0m+24s since start) | |
i! Process=1524391; Thread=1524637; GPU=NULL; Handle=NULL; StreamId=NULL. | |
I! CuDNN (v7604) function cudnnCreateConvolutionDescriptor() called: |
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Loading: | |
Loading: 0 packages loaded | |
Analyzing: target //third_party/tensorflow/compiler/xla/client/lib:svd_test_gpu (0 packages loaded, 0 targets configured) | |
INFO: Analyzed target //third_party/tensorflow/compiler/xla/client/lib:svd_test_gpu (0 packages loaded, 0 targets configured). | |
INFO: Found 1 target... | |
[0 / 1] [Prepa] action 'BuildInfo build-info.txt' | |
Target //third_party/tensorflow/compiler/xla/client/lib:svd_test_gpu up-to-date: | |
blaze-bin/third_party/tensorflow/compiler/xla/client/lib/svd_test_gpu | |
INFO: Elapsed time: 0.365s, Critical Path: 0.09s, Remote (0.00% of the time): [queue: 0.00%, setup: 0.00%, process: 0.00%] | |
INFO: Build completed successfully, 1 total action |
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diff --git a//tensorflow/compiler/jit/BUILD b//tensorflow/compiler/jit/BUILD | |
--- a//tensorflow/compiler/jit/BUILD | |
+++ b//tensorflow/compiler/jit/BUILD | |
@@ -151,6 +151,7 @@ cc_library( | |
":jit_compilation_passes", | |
":xla_device", | |
":xla_kernel_creator", # buildcleaner: keep | |
+ ":xla_device_no_jit_rewrite_registration", | |
"//third_party/absl/memory", | |
"//third_party/absl/strings", |
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HloModule Module | |
ENTRY computation { | |
tmp_0 = u8[32,224,224,3]{3,2,1,0} parameter(0) | |
tmp_1 = f32[] constant(1) | |
tmp_2 = f32[32,7,7,352]{3,2,1,0} broadcast(f32[] tmp_1), dimensions={} | |
tmp_3 = f32[32,7,7,352]{3,2,1,0} constant({ { /*i0=0*/ { /*i1=0*/ { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 |
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hello |
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package org.sosy_lab.solver.test; | |
import org.sosy_lab.common.UniqueIdGenerator; | |
import org.sosy_lab.solver.api.FormulaManager; | |
import org.sosy_lab.solver.api.IntegerFormulaManager; | |
import org.sosy_lab.solver.api.NumeralFormula.IntegerFormula; | |
import java.util.Random; | |
import java.util.stream.IntStream; |
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