briansp2020

128 160 -nan -nan -nan 26.6658 -nan -nan -nan 29.6141 27.6627 27.9796 26.3767 26.3673 25.4185 26.2039 29.0172 25.4696 -nan -nan -nan 30.1051 -nan -nan -nan 28.8625 24.8018 29.5769 28.1883 26.6705 26.7396 26.7087 25.6257 27.2467 -nan -nan -nan 27.1828 -nan -nan -nan 32.6176 24.7737 28.7341 27.714 23.2053 23.9329 27.7605 27.536 26.1272 -nan -nan -nan 26.8141 -nan -nan -nan 27.1162 28.8162 26.2344 28.094 26.3658 26.4144 26.9917 27.4659 26.7797 23.457 25.3666 28.2823 27.0539 25.4196 25.6229 28.8974 27.0214 25.4114 24.8982 29.3005 25.8265 28.0748 26.368 27.8294 28.716 25.0269 28.0744 24.3188 27.1742 26.6524 24.8727 25.7083 25.2672 25.7511 25.6884 26.3613 27.4005 27.2513 27.0392 26.0624 28.071 25.6106 25.2469 25.9089 28.3915 27.6297 25.1925 26.9032 31.3683 25.7977 26.1799 28.3532 27.8372 28.4149 27.778 23.1457 26.5313 27.5213 29.1664 26.4055 25.9429 26.4542 27.9505 26.7873 26.046 30.0916 27.6084 27.0636 27.2682 27.8904 26.0423 24.8227 29.1673 25.5703 23.6353 23.9712 22.0347 21.2455 20.9034 20.7535 23.9329 21.7742 2

briansp2020

; ModuleID = '<stdin>'
target datalayout = "e-m:e-i64:64-f80:128-n8:16:32:64-S128"
target triple = "x86_64-unknown-linux-gnu"

%struct.LocalQueues = type { [8 x i32], [8 x [400 x i32]], [8 x i32] }
%"class.hc::short_vector::int_2.0" = type { i32, i32 }
%struct.grid_launch_parm = type { %struct.gl_dim3, %struct.gl_dim3, %struct.gl_dim3, %struct.gl_dim3, i32, %"class.hc::accelerator_view"*, %"class.hc::completion_future"* }
%struct.gl_dim3 = type { i32, i32, i32 }
%"class.hc::accelerator_view" = type { %"class.std::__1::shared_ptr" }
%"class.std::__1::shared_ptr" = type { %"class.Kalmar::KalmarQueue"*, %"class.std::__1::__shared_weak_count"* }

briansp2020

00:00.0 Host bridge: Intel Corporation Sky Lake Host Bridge/DRAM Registers (rev 07)
00: 86 80 1f 19 06 00 90 20 07 00 00 06 00 00 00 00
10: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00
20: 00 00 00 00 00 00 00 00 00 00 00 00 43 10 94 86
30: 00 00 00 00 e0 00 00 00 00 00 00 00 00 00 00 00
40: 01 90 d1 fe 00 00 00 00 01 00 d1 fe 00 00 00 00
50: 03 00 00 00 29 00 00 00 04 00 00 00 01 00 c0 a7
60: 05 00 00 f8 00 00 00 00 01 80 d1 fe 00 00 00 00
70: 00 00 00 ff 03 00 00 00 00 0c 00 ff 7f 00 00 00
80: 11 00 00 00 00 11 11 00 1a 00 00 00 00 00 00 00

briansp2020

00:00.0 Host bridge: Intel Corporation Sky Lake Host Bridge/DRAM Registers (rev 07)
	Subsystem: ASUSTeK Computer Inc. Device 8694
	Control: I/O- Mem+ BusMaster+ SpecCycle- MemWINV- VGASnoop- ParErr- Stepping- SERR- FastB2B- DisINTx-
	Status: Cap+ 66MHz- UDF- FastB2B+ ParErr- DEVSEL=fast >TAbort- <TAbort- <MAbort+ >SERR- <PERR- INTx-
	Latency: 0
	Capabilities: [e0] Vendor Specific Information: Len=10 <?>
	Kernel driver in use: skl_uncore

00:01.0 PCI bridge: Intel Corporation Sky Lake PCIe Controller (x16) (rev 07) (prog-if 00 [Normal decode])
	Control: I/O+ Mem+ BusMaster+ SpecCycle- MemWINV- VGASnoop- ParErr- Stepping- SERR- FastB2B- DisINTx+

briansp2020

-[0000:00]-+-00.0
           +-01.0-[01]--+-00.0
           |            \-00.1
           +-14.0
           +-16.0
           +-17.0
           +-1b.0-[02]--
           +-1c.0-[03]--
           +-1c.2-[04-05]----00.0-[05]--
           +-1c.3-[06]----00.0

briansp2020

briansp@Ryzen1800X:~/git/keras-rcnn$ python setup.py build
running build
running build_py
briansp@Ryzen1800X:~/git/keras-rcnn$ python setup.py install
running install
running bdist_egg
running egg_info
writing keras_rcnn.egg-info/PKG-INFO
writing dependency_links to keras_rcnn.egg-info/dependency_links.txt
writing requirements to keras_rcnn.egg-info/requires.txt

briansp2020

root@C-c6fe3f8f-7781-431b-9423-4071ddb07676-146:~/git/Mask_RCNN/samples/shapes# export
declare -x HCC_HOME="/opt/rocm/hcc"
declare -x HIP_PATH="/opt/rocm/hip"
declare -x HIP_VISIBLE_DEVICES="0"
declare -x HOME="/root"
declare -x HSA_ENABLE_SDMA="0"
declare -x LANG="en_US.UTF-8"
declare -x LC_ALL="en_US.UTF-8"
declare -x LC_CTYPE="en_US.UTF-8"
declare -x LD_LIBRARY=":/opt/rocm/opencl/lib/x86_64"

briansp2020

root@C-c6fe3f8f-7781-431b-9423-4071ddb07676-146:~/git/Mask_RCNN# python NucleiExperiment.py 
Using TensorFlow backend.
Downloading pretrained model to /root/git/Mask_RCNN/mask_rcnn_coco.h5 ...
... done downloading pretrained model!
ROOT_DIR :  /root/git/Mask_RCNN
MODEL_DIR :  /root/git/Mask_RCNN/logs
COCO_MODEL_PATH :  /root/git/Mask_RCNN/mask_rcnn_coco.h5

Configurations:
BACKBONE                       resnet101

briansp2020

2018-05-22 03:48:25.326959: I tensorflow/core/common_runtime/gpu/gpu_device.cc:907] Found device 0 with properties: 
name: Device 6863
AMDGPU ISA: gfx900
memoryClockRate (GHz) 1.6
pciBusID 0000:03:00.0
Total memory: 15.98GiB
Free memory: 15.73GiB
2018-05-22 03:48:25.326977: I tensorflow/core/common_runtime/gpu/gpu_device.cc:929] DMA: 0 
2018-05-22 03:48:25.326983: I tensorflow/core/common_runtime/gpu/gpu_device.cc:939] 0:   Y 
2018-05-22 03:48:25.326990: I tensorflow/core/common_runtime/gpu/gpu_device.cc:997] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Device 6863, pci bus id: 0000:03:00.0)

briansp2020

:~$ python
Python 3.5.2 (default, Nov 23 2017, 16:37:01) 
[GCC 5.4.0 20160609] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
Traceback (most recent call last):
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
    from tensorflow.python.pywrap_tensorflow_internal import *
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
    _pywrap_tensorflow_internal = swig_import_helper()