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FAIL: //tensorflow/python/estimator:dnn_linear_combined_test #78

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lukeiwanski opened this issue Jun 12, 2017 · 0 comments
Open

FAIL: //tensorflow/python/estimator:dnn_linear_combined_test #78

lukeiwanski opened this issue Jun 12, 2017 · 0 comments

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@lukeiwanski
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lukeiwanski commented Jun 12, 2017

System Info

  Name:						 Hawaii
  Vendor:					 Advanced Micro Devices, Inc.
  Device OpenCL C version:			 OpenCL C 2.0 
  Driver version:				 1912.5 (VM)
  Profile:					 FULL_PROFILE
  Version:					 OpenCL 2.0 AMD-APP (1912.5)
  Extensions:					 cl_khr_fp64 cl_amd_fp64 cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_gl_sharing cl_khr_gl_depth_images cl_ext_atomic_counters_32 cl_amd_device_attribute_query cl_amd_vec3 cl_amd_printf cl_amd_media_ops cl_amd_media_ops2 cl_amd_popcnt cl_khr_image2d_from_buffer cl_khr_spir cl_khr_subgroups cl_khr_gl_event cl_khr_depth_images cl_khr_mipmap_image cl_khr_mipmap_image_writes

ComputeCpp 0.2.0

To reproduce

bazel test --config=sycl --local_test_jobs=4 -k --test_lang_filters=cc,py --action_env=LD_PRELOAD=/usr/lib/libOpenCL.so.1 --test_timeout 300,750,1200,3600 //tensorflow/python/estimator:dnn_linear_combined_test

Error

FAIL: test_evaluation_weights (__main__.LinearOnlyRegressorEvaluationTest)
Tests evaluation with weights.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/luke/.cache/bazel/_bazel_luke/6b8509cbd1cb09897b517a53b72ea21d/execroot/tensorflow/bazel-out/local_linux-opt/bin/tensorflow/python/estimator/dnn_linear_combined_test.runfiles/org_tensorflow/tensorflow/python/estimator/canned/linear_testing_utils.py", line 315, in test_evaluation_weights
    }, eval_metrics)
AssertionError: {'loss': 27.0, 'global_step': 100, 'average_loss': 9.0} != {'average_loss': 8.999999, 'global_step': 100, 'loss': 27.0}
- {'average_loss': 9.0, 'global_step': 100, 'loss': 27.0}
?                   ^^

+ {'average_loss': 8.999999, 'global_step': 100, 'loss': 27.0}
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