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andreped/fast-python-intel-opencl-runtime-fix.ipynb

Created September 4, 2023 09:29
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fast-python-intel-opencl-runtime-fix.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/andreped/21749b8f89983b97622719ba4f9c9bbf/fast-python-intel-opencl-runtime-fix.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "YJBII5KZUE1X",
"outputId": "2ccb6245-00cd-4f74-f091-be18a4a649af"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"--2023-09-04 09:27:46-- https://github.com/intel/llvm/releases/download/2023-WW27/oclcpuexp-2023.16.6.0.28_rel.tar.gz\n",
"Resolving github.com (github.com)... 140.82.112.4\n",
"Connecting to github.com (github.com)|140.82.112.4|:443... connected.\n",
"HTTP request sent, awaiting response... 302 Found\n",
"Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/166008577/d012b9ed-449a-44e6-a945-ab162813e817?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230904%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230904T092746Z&X-Amz-Expires=300&X-Amz-Signature=c578e609c44508704b247274420e185e89947187fcfa9d18474711e3a042a4e5&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=166008577&response-content-disposition=attachment%3B%20filename%3Doclcpuexp-2023.16.6.0.28_rel.tar.gz&response-content-type=application%2Foctet-stream [following]\n",
"--2023-09-04 09:27:46-- https://objects.githubusercontent.com/github-production-release-asset-2e65be/166008577/d012b9ed-449a-44e6-a945-ab162813e817?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230904%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230904T092746Z&X-Amz-Expires=300&X-Amz-Signature=c578e609c44508704b247274420e185e89947187fcfa9d18474711e3a042a4e5&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=166008577&response-content-disposition=attachment%3B%20filename%3Doclcpuexp-2023.16.6.0.28_rel.tar.gz&response-content-type=application%2Foctet-stream\n",
"Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
"Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.108.133|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 148579727 (142M) [application/octet-stream]\n",
"Saving to: ‘oclcpuexp-2023.16.6.0.28_rel.tar.gz’\n",
"\n",
"oclcpuexp-2023.16.6 100%[===================>] 141.70M 163MB/s in 0.9s \n",
"\n",
"2023-09-04 09:27:47 (163 MB/s) - ‘oclcpuexp-2023.16.6.0.28_rel.tar.gz’ saved [148579727/148579727]\n",
"\n",
"oclcpuexp-2023.16.6.0.28_rel\n",
"x64/\n",
"x64/__ocl_svml_e9.so\n",
"x64/clbltfnz1.rtl\n",
"x64/clbltfne9.rtl\n",
"x64/cllibraryz1.o\n",
"x64/libintlc.so.5\n",
"x64/__ocl_svml_l9.so\n",
"x64/libintelocl.so.2023.16.6.0\n",
"x64/libintelocl.so\n",
"x64/cllibraryz0.o\n",
"x64/__ocl_svml_z0.so\n",
"x64/libimf.so\n",
"x64/clbltfnz0.rtl\n",
"x64/libintelocl.so-gdb.py\n",
"x64/cllibraryl9.o\n",
"x64/libcommon_clang.so\n",
"x64/libirng.so\n",
"x64/__ocl_svml_z1.so\n",
"x64/libOpenCL.so.1\n",
"x64/cllibrarye9.o\n",
"x64/clbltfnh8.rtl\n",
"x64/__ocl_svml_h8.so\n",
"x64/cllibraryh8.o\n",
"x64/cl.cfg\n",
"x64/clbltfnl9.rtl\n",
"x64/cllibrary.rtl\n",
"x64/libOpenCL.so.1.2\n",
"x64/libOpenCL.so\n",
"x64/libsvml.so\n",
"clbltfnshared.rtl\n",
"Reading package lists... Done\n",
"Building dependency tree... Done\n",
"Reading state information... Done\n",
"libopengl0 is already the newest version (1.4.0-1).\n",
"0 upgraded, 0 newly installed, 0 to remove and 16 not upgraded.\n"
]
}
],
"source": [
"## Setup OpenCL: https://github.com/intel/llvm/blob/sycl/sycl/doc/GetStartedGuide.md#install-low-level-runtime\n",
"\n",
"# download OpenCL CPU-only RunTime (RT)\n",
"!wget \"https://github.com/intel/llvm/releases/download/2023-WW27/oclcpuexp-2023.16.6.0.28_rel.tar.gz\"\n",
"cpu_version=\"oclcpuexp-2023.16.6.0.28_rel\"\n",
"!echo $cpu_version\n",
"\n",
"# Extract OpenCL CPU RT\n",
"!mkdir -p /opt/intel/oclcpuexp_{cpu_version}\n",
"!cd /opt/intel/oclcpuexp_{cpu_version}\n",
"!tar -zxvf {cpu_version}.tar.gz\n",
"!cp -r x64/ /opt/intel/oclcpuexp_{cpu_version}/\n",
"\n",
"# OpenCL CPU RT\n",
"!mkdir -p /etc/OpenCL/vendors\n",
"!echo /opt/intel/oclcpuexp_{cpu_version}/x64/libintelocl.so > \\\n",
" /etc/OpenCL/vendors/intel_expcpu.icd\n",
"\n",
"!echo /opt/intel/oclcpuexp_{cpu_version}/x64 >> \\\n",
" /etc/ld.so.conf.d/libintelopenclexp.conf\n",
"!ldconfig -f /etc/ld.so.conf.d/libintelopenclexp.conf\n",
"\n",
"## Setup OpenGL\n",
"!sudo apt-get install -y libopengl0"
]
},
{
"cell_type": "code",
"source": [
"!ls /etc/OpenCL/vendors/\n",
"!clinfo"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "FMNIFAiuRo0C",
"outputId": "61a65c2c-2874-4f77-99f8-10315e1f2d1e"
},
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"intel_expcpu.icd\n",
"Number of platforms 1\n",
" Platform Name Intel(R) OpenCL\n",
" Platform Vendor Intel(R) Corporation\n",
" Platform Version OpenCL 3.0 LINUX\n",
" Platform Profile FULL_PROFILE\n",
" Platform Extensions cl_khr_spirv_linkonce_odr cl_khr_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_3d_image_writes cl_khr_byte_addressable_store cl_khr_depth_images cl_khr_icd cl_khr_il_program cl_khr_subgroup_shuffle cl_khr_subgroup_shuffle_relative cl_khr_subgroup_extended_types cl_khr_subgroup_non_uniform_arithmetic cl_intel_subgroups cl_intel_subgroups_char cl_intel_subgroups_short cl_intel_subgroups_long cl_intel_required_subgroup_size cl_intel_spirv_subgroups cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_intel_unified_shared_memory cl_intel_device_attribute_query cl_intel_exec_by_local_thread cl_intel_vec_len_hint cl_intel_device_partition_by_names cl_khr_spir cl_khr_image2d_from_buffer\n",
" Platform Extensions with Version cl_khr_spirv_linkonce_odr 0x400000 (1.0.0)\n",
" cl_khr_fp64 0x400000 (1.0.0)\n",
" cl_khr_global_int32_base_atomics 0x400000 (1.0.0)\n",
" cl_khr_global_int32_extended_atomics 0x400000 (1.0.0)\n",
" cl_khr_local_int32_base_atomics 0x400000 (1.0.0)\n",
" cl_khr_local_int32_extended_atomics 0x400000 (1.0.0)\n",
" cl_khr_3d_image_writes 0x400000 (1.0.0)\n",
" cl_khr_byte_addressable_store 0x400000 (1.0.0)\n",
" cl_khr_depth_images 0x400000 (1.0.0)\n",
" cl_khr_icd 0x400000 (1.0.0)\n",
" cl_khr_il_program 0x400000 (1.0.0)\n",
" cl_khr_subgroup_shuffle 0x400000 (1.0.0)\n",
" cl_khr_subgroup_shuffle_relative 0x400000 (1.0.0)\n",
" cl_khr_subgroup_extended_types 0x400000 (1.0.0)\n",
" cl_khr_subgroup_non_uniform_arithmetic 0x400000 (1.0.0)\n",
" cl_intel_subgroups 0x400000 (1.0.0)\n",
" cl_intel_subgroups_char 0x400000 (1.0.0)\n",
" cl_intel_subgroups_short 0x400000 (1.0.0)\n",
" cl_intel_subgroups_long 0x400000 (1.0.0)\n",
" cl_intel_required_subgroup_size 0x400000 (1.0.0)\n",
" cl_intel_spirv_subgroups 0x400000 (1.0.0)\n",
" cl_khr_int64_base_atomics 0x400000 (1.0.0)\n",
" cl_khr_int64_extended_atomics 0x400000 (1.0.0)\n",
" cl_intel_unified_shared_memory 0x400000 (1.0.0)\n",
" cl_intel_device_attribute_query 0x400000 (1.0.0)\n",
" cl_intel_exec_by_local_thread 0x400000 (1.0.0)\n",
" cl_intel_vec_len_hint 0x400000 (1.0.0)\n",
" cl_intel_device_partition_by_names 0x400000 (1.0.0)\n",
" cl_khr_spir 0x400000 (1.0.0)\n",
" cl_khr_image2d_from_buffer 0x400000 (1.0.0)\n",
" Platform Numeric Version 0xc00000 (3.0.0)\n",
" Platform Extensions function suffix INTEL\n",
" Platform Host timer resolution 1ns\n",
"\n",
" Platform Name Intel(R) OpenCL\n",
"Number of devices 1\n",
" Device Name Intel(R) Xeon(R) CPU @ 2.20GHz\n",
" Device Vendor Intel(R) Corporation\n",
" Device Vendor ID 0x8086\n",
" Device Version OpenCL 3.0 (Build 0)\n",
" Device Numeric Version 0xc00000 (3.0.0)\n",
" Driver Version 2023.16.6.0.28_042959\n",
" Device OpenCL C Version OpenCL C 3.0 \n",
" Device OpenCL C all versions OpenCL C 0xc00000 (3.0.0)\n",
" OpenCL C 0x800000 (2.0.0)\n",
" OpenCL C 0x402000 (1.2.0)\n",
" OpenCL C 0x401000 (1.1.0)\n",
" OpenCL C 0x400000 (1.0.0)\n",
" Device OpenCL C features __opencl_c_3d_image_writes 0xc00000 (3.0.0)\n",
" __opencl_c_atomic_order_acq_rel 0xc00000 (3.0.0)\n",
" __opencl_c_atomic_order_seq_cst 0xc00000 (3.0.0)\n",
" __opencl_c_atomic_scope_device 0xc00000 (3.0.0)\n",
" __opencl_c_atomic_scope_all_devices 0xc00000 (3.0.0)\n",
" __opencl_c_device_enqueue 0xc00000 (3.0.0)\n",
" __opencl_c_generic_address_space 0xc00000 (3.0.0)\n",
" __opencl_c_fp64 0xc00000 (3.0.0)\n",
" __opencl_c_images 0xc00000 (3.0.0)\n",
" __opencl_c_int64 0xc00000 (3.0.0)\n",
" __opencl_c_pipes 0xc00000 (3.0.0)\n",
" __opencl_c_program_scope_global_variables 0xc00000 (3.0.0)\n",
" __opencl_c_read_write_images 0xc00000 (3.0.0)\n",
" __opencl_c_subgroups 0xc00000 (3.0.0)\n",
" __opencl_c_work_group_collective_functions 0xc00000 (3.0.0)\n",
" Latest comfornace test passed v2022-10-05-00\n",
" Device Type CPU\n",
" Device Profile FULL_PROFILE\n",
" Device Available Yes\n",
" Compiler Available Yes\n",
" Linker Available Yes\n",
" Max compute units 2\n",
" Max clock frequency 2200MHz\n",
" Device Partition (core)\n",
" Max number of sub-devices 2\n",
" Supported partition types by counts, equally, by names (Intel)\n",
" Supported affinity domains (n/a)\n",
" Max work item dimensions 3\n",
" Max work item sizes 8192x8192x8192\n",
" Max work group size 8192\n",
" Preferred work group size multiple (device) 128\n",
" Preferred work group size multiple (kernel) <getWGsizes:1474: create context : error -2>\n",
" Max sub-groups per work group 2048\n",
" Sub-group sizes (Intel) 4, 8, 16, 32, 64\n",
" Preferred / native vector sizes \n",
" char 1 / 32 \n",
" short 1 / 16 \n",
" int 1 / 8 \n",
" long 1 / 4 \n",
" half 0 / 0 (n/a)\n",
" float 1 / 8 \n",
" double 1 / 4 (cl_khr_fp64)\n",
" Half-precision Floating-point support (n/a)\n",
" Single-precision Floating-point support (core)\n",
" Denormals Yes\n",
" Infinity and NANs Yes\n",
" Round to nearest Yes\n",
" Round to zero No\n",
" Round to infinity No\n",
" IEEE754-2008 fused multiply-add No\n",
" Support is emulated in software No\n",
" Correctly-rounded divide and sqrt operations No\n",
" Double-precision Floating-point support (cl_khr_fp64)\n",
" Denormals Yes\n",
" Infinity and NANs Yes\n",
" Round to nearest Yes\n",
" Round to zero Yes\n",
" Round to infinity Yes\n",
" IEEE754-2008 fused multiply-add Yes\n",
" Support is emulated in software No\n",
" Address bits 64, Little-Endian\n",
" Global memory size 13613305856 (12.68GiB)\n",
" Error Correction support No\n",
" Max memory allocation 6806652928 (6.339GiB)\n",
" Unified memory for Host and Device Yes\n",
" Shared Virtual Memory (SVM) capabilities (core)\n",
" Coarse-grained buffer sharing Yes\n",
" Fine-grained buffer sharing Yes\n",
" Fine-grained system sharing Yes\n",
" Atomics Yes\n",
" Minimum alignment for any data type 128 bytes\n",
" Alignment of base address 1024 bits (128 bytes)\n",
" Preferred alignment for atomics \n",
" SVM 64 bytes\n",
" Global 64 bytes\n",
" Local 0 bytes\n",
" Atomic memory capabilities relaxed, acquire/release, sequentially-consistent, work-group scope, device scope, all-devices scope\n",
" Atomic fence capabilities relaxed, acquire/release, sequentially-consistent, work-item scope, work-group scope, device scope, all-devices scope\n",
" Max size for global variable 65536 (64KiB)\n",
" Preferred total size of global vars 65536 (64KiB)\n",
" Global Memory cache type Read/Write\n",
" Global Memory cache size 262144 (256KiB)\n",
" Global Memory cache line size 64 bytes\n",
" Image support Yes\n",
" Max number of samplers per kernel 480\n",
" Max size for 1D images from buffer 425415808 pixels\n",
" Max 1D or 2D image array size 2048 images\n",
" Base address alignment for 2D image buffers 64 bytes\n",
" Pitch alignment for 2D image buffers 64 pixels\n",
" Max 2D image size 16384x16384 pixels\n",
" Max 3D image size 2048x2048x2048 pixels\n",
" Max number of read image args 480\n",
" Max number of write image args 480\n",
" Max number of read/write image args 480\n",
" Pipe support Yes\n",
" Max number of pipe args 16\n",
" Max active pipe reservations 131071\n",
" Max pipe packet size 1024\n",
" Local memory type Global\n",
" Local memory size 32768 (32KiB)\n",
" Max number of constant args 480\n",
" Max constant buffer size 131072 (128KiB)\n",
" Generic address space support Yes\n",
" Max size of kernel argument 3840 (3.75KiB)\n",
" Queue properties (on host) \n",
" Out-of-order execution Yes\n",
" Profiling Yes\n",
" Local thread execution (Intel) Yes\n",
" Device enqueue capabilities supported, replaceable default queue\n",
" Queue properties (on device) \n",
" Out-of-order execution Yes\n",
" Profiling Yes\n",
" Preferred size 4294967295 (4GiB)\n",
" Max size 4294967295 (4GiB)\n",
" Max queues on device 4294967295\n",
" Max events on device 4294967295\n",
" Prefer user sync for interop No\n",
" Profiling timer resolution 1ns\n",
" Execution capabilities \n",
" Run OpenCL kernels Yes\n",
" Run native kernels Yes\n",
" Non-uniform work-groups Yes\n",
" Work-group collective functions Yes\n",
" Sub-group independent forward progress No\n",
" IL version SPIR-V_1.0\n",
" ILs with version SPIR-V 0x400000 (1.0.0)\n",
" SPIR versions 1.2\n",
" printf() buffer size 1048576 (1024KiB)\n",
" Built-in kernels (n/a)\n",
" Built-in kernels with version (n/a)\n",
" Device Extensions cl_khr_spirv_linkonce_odr cl_khr_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_3d_image_writes cl_khr_byte_addressable_store cl_khr_depth_images cl_khr_icd cl_khr_il_program cl_khr_subgroup_shuffle cl_khr_subgroup_shuffle_relative cl_khr_subgroup_extended_types cl_khr_subgroup_non_uniform_arithmetic cl_intel_subgroups cl_intel_subgroups_char cl_intel_subgroups_short cl_intel_subgroups_long cl_intel_required_subgroup_size cl_intel_spirv_subgroups cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_intel_unified_shared_memory cl_intel_device_attribute_query cl_intel_exec_by_local_thread cl_intel_vec_len_hint cl_intel_device_partition_by_names cl_khr_spir cl_khr_image2d_from_buffer\n",
" Device Extensions with Version cl_khr_spirv_linkonce_odr 0x400000 (1.0.0)\n",
" cl_khr_fp64 0x400000 (1.0.0)\n",
" cl_khr_global_int32_base_atomics 0x400000 (1.0.0)\n",
" cl_khr_global_int32_extended_atomics 0x400000 (1.0.0)\n",
" cl_khr_local_int32_base_atomics 0x400000 (1.0.0)\n",
" cl_khr_local_int32_extended_atomics 0x400000 (1.0.0)\n",
" cl_khr_3d_image_writes 0x400000 (1.0.0)\n",
" cl_khr_byte_addressable_store 0x400000 (1.0.0)\n",
" cl_khr_depth_images 0x400000 (1.0.0)\n",
" cl_khr_icd 0x400000 (1.0.0)\n",
" cl_khr_il_program 0x400000 (1.0.0)\n",
" cl_khr_subgroup_shuffle 0x400000 (1.0.0)\n",
" cl_khr_subgroup_shuffle_relative 0x400000 (1.0.0)\n",
" cl_khr_subgroup_extended_types 0x400000 (1.0.0)\n",
" cl_khr_subgroup_non_uniform_arithmetic 0x400000 (1.0.0)\n",
" cl_intel_subgroups 0x400000 (1.0.0)\n",
" cl_intel_subgroups_char 0x400000 (1.0.0)\n",
" cl_intel_subgroups_short 0x400000 (1.0.0)\n",
" cl_intel_subgroups_long 0x400000 (1.0.0)\n",
" cl_intel_required_subgroup_size 0x400000 (1.0.0)\n",
" cl_intel_spirv_subgroups 0x400000 (1.0.0)\n",
" cl_khr_int64_base_atomics 0x400000 (1.0.0)\n",
" cl_khr_int64_extended_atomics 0x400000 (1.0.0)\n",
" cl_intel_unified_shared_memory 0x400000 (1.0.0)\n",
" cl_intel_device_attribute_query 0x400000 (1.0.0)\n",
" cl_intel_exec_by_local_thread 0x400000 (1.0.0)\n",
" cl_intel_vec_len_hint 0x400000 (1.0.0)\n",
" cl_intel_device_partition_by_names 0x400000 (1.0.0)\n",
" cl_khr_spir 0x400000 (1.0.0)\n",
" cl_khr_image2d_from_buffer 0x400000 (1.0.0)\n",
"\n",
"NULL platform behavior\n",
" clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...) No platform\n",
" clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...) No platform\n",
" clCreateContext(NULL, ...) [default] No platform\n",
" clCreateContext(NULL, ...) [other] <checkNullCtx:3402: create context with device from non-default platform : error -2>\n",
" clCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT) No devices available in platform\n",
" clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU) No devices available in platform\n",
" clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU) No devices found in platform\n",
" clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR) No devices found in platform\n",
" clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM) No devices found in platform\n",
" clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL) No devices available in platform\n",
"\n",
"ICD loader properties\n",
" ICD loader Name Khronos OpenCL ICD Loader\n",
" ICD loader Vendor Khronos Group\n",
" ICD loader Version 3.0.5\n",
" ICD loader Profile OpenCL 3.0\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"# install pyFAST\n",
"!pip install pyFAST matplotlib"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "K6yZu93tZvsZ",
"outputId": "6626b46f-aedb-4e7a-ec0e-d4c4b33d7614"
},
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Collecting pyFAST\n",
" Downloading pyFAST-4.7.1-cp36-abi3-manylinux1_x86_64.whl (385.8 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m385.8/385.8 MB\u001b[0m \u001b[31m1.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hRequirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (3.7.1)\n",
"Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from pyFAST) (1.23.5)\n",
"Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (1.1.0)\n",
"Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (0.11.0)\n",
"Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (4.42.1)\n",
"Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (1.4.4)\n",
"Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (23.1)\n",
"Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (9.4.0)\n",
"Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (3.1.1)\n",
"Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (2.8.2)\n",
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n",
"Installing collected packages: pyFAST\n",
"Successfully installed pyFAST-4.7.1\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!wget https://folk.ntnu.no/andpeder/FastPathology/test_data/WSI/CMU-1.svs"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "r1nJxKBGnpIg",
"outputId": "61a54c39-7682-4e5f-9b18-3299488bfefb"
},
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"--2023-09-04 09:28:39-- https://folk.ntnu.no/andpeder/FastPathology/test_data/WSI/CMU-1.svs\n",
"Resolving folk.ntnu.no (folk.ntnu.no)... 129.241.56.95, 2001:700:300:3::95\n",
"Connecting to folk.ntnu.no (folk.ntnu.no)|129.241.56.95|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 177552579 (169M) [image/tiff]\n",
"Saving to: ‘CMU-1.svs’\n",
"\n",
"CMU-1.svs 100%[===================>] 169.33M 24.8MB/s in 7.6s \n",
"\n",
"2023-09-04 09:28:47 (22.4 MB/s) - ‘CMU-1.svs’ saved [177552579/177552579]\n",
"\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"# create tissue segmentation pipeline\n",
"!git clone https://github.com/andreped/FP-DSA-plugin.git"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "LCwiqDA0HeO0",
"outputId": "4e089f93-e3d4-451d-bdca-145530bed228"
},
"execution_count": 5,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cloning into 'FP-DSA-plugin'...\n",
"remote: Enumerating objects: 447, done.\u001b[K\n",
"remote: Counting objects: 100% (59/59), done.\u001b[K\n",
"remote: Compressing objects: 100% (52/52), done.\u001b[K\n",
"remote: Total 447 (delta 25), reused 22 (delta 7), pack-reused 388\u001b[K\n",
"Receiving objects: 100% (447/447), 6.91 MiB | 21.32 MiB/s, done.\n",
"Resolving deltas: 100% (261/261), done.\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!runPipeline \"FP-DSA-plugin/dsa/fastpathology/fastpathology/pipelines/tissue_segmentation.fpl\" --verbose --opencl-platform intel --input CMU-1.svs --output result"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "S5I5Y90GITWA",
"outputId": "622e038a-1460-45e0-fa38-9e4707605b24"
},
"execution_count": 6,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[32;1m\n",
" - Powered by - \n",
" _______ __________ \n",
" / __/ _ | / __/_ __/ https://fast.eriksmistad.no\n",
" / _// __ |_\\ \\ / / v4.7.1\n",
"/_/ /_/ |_/___/ /_/ \n",
"\n",
"\u001b[0mINFO [139296783949504] Processing token --opencl-platform\u001b[0m\n",
"INFO [139296783949504] Processing token --input\u001b[0m\n",
"INFO [139296783949504] Processing token CMU-1.svs\u001b[0m\n",
"INFO [139296783949504] CommandLineParser: Assigning variable input with value CMU-1.svs\u001b[0m\n",
"INFO [139296783949504] Processing token --output\u001b[0m\n",
"INFO [139296783949504] Processing token result\u001b[0m\n",
"INFO [139296783949504] CommandLineParser: Assigning variable output with value result\u001b[0m\n",
"INFO [139296783949504] Running pipeline in headless mode\u001b[0m\n",
"INFO [139296783949504] Loaded configuration file: /usr/local/lib/python3.10/dist-packages/fast/bin/../bin/fast_configuration.txt\u001b[0m\n",
"INFO [139296783949504] Test data path: /root/FAST/data/\u001b[0m\n",
"INFO [139296783949504] Kernel source path: /usr/local/lib/python3.10/dist-packages/fast/bin/../bin//..//kernels/\u001b[0m\n",
"INFO [139296783949504] Kernel binary path: /root/FAST//kernel_binaries/\u001b[0m\n",
"INFO [139296783949504] Documentation path: /usr/local/lib/python3.10/dist-packages/fast/bin/../bin//..//doc/\u001b[0m\n",
"INFO [139296783949504] Pipeline path: /root/FAST//pipelines/\u001b[0m\n",
"INFO [139296783949504] Qt plugins path: /usr/local/lib/python3.10/dist-packages/fast/bin/../bin//..//plugins/\u001b[0m\n",
"INFO [139296783949504] Library path: /usr/local/lib/python3.10/dist-packages/fast/bin/../bin//..//lib/\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"INFO [139296783949504] Found variable input in pipeline file\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"INFO [139296783949504] Found variable output in pipeline file\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"Pipeline execution started.\n",
"INFO [139296783949504] Found pipeline attribute classes in pipeline file with value Background;Tissue\u001b[0m\n",
"INFO [139296783949504] Creating new QApp\u001b[0m\n",
"\u001b[1mWARNING [139296783949504] Unable to open X display. Disabling visualization.\u001b[0m\n",
"QStandardPaths: XDG_RUNTIME_DIR not set, defaulting to '/tmp/runtime-root'\n",
"INFO [139296783949504] Found 1 OpenCL platforms.\u001b[0m\n",
"INFO [139296783949504] 1 platforms selected for inspection.\u001b[0m\n",
"INFO [139296783949504] Platform 0: Intel(R) Corporation\u001b[0m\n",
"INFO [139296783949504] This platform has 1 available devices in total\u001b[0m\n",
"INFO [139296783949504] Looking for GPU devices only.\u001b[0m\n",
"INFO [139296783949504] 0 selected.\u001b[0m\n",
"INFO [139296783949504] NO suitable GPU found! Trying to find other devices\u001b[0m\n",
"INFO [139296783949504] Found 1 OpenCL platforms.\u001b[0m\n",
"INFO [139296783949504] 1 platforms selected for inspection.\u001b[0m\n",
"INFO [139296783949504] Platform 0: Intel(R) Corporation\u001b[0m\n",
"INFO [139296783949504] This platform has 1 available devices in total\u001b[0m\n",
"INFO [139296783949504] Looking for all types of devices.\u001b[0m\n",
"INFO [139296783949504] 1 selected.\u001b[0m\n",
"INFO [139296783949504] Inspecting device 0 with the name Intel(R) Xeon(R) CPU @ 2.20GHz\u001b[0m\n",
"INFO [139296783949504] The device was accepted.\u001b[0m\n",
"INFO [139296783949504] Intel(R) Xeon(R) CPU @ 2.20GHz has 2 compute units\u001b[0m\n",
"INFO [139296783949504] The device Intel(R) Xeon(R) CPU @ 2.20GHz got a score of 2\u001b[0m\n",
"INFO [139296783949504] The platform Intel(R) OpenCL was selected as the best platform.\u001b[0m\n",
"INFO [139296783949504] A total of 1 devices were selected for the context from this platform:\u001b[0m\n",
"INFO [139296783949504] The best device was: Intel(R) Xeon(R) CPU @ 2.20GHz\u001b[0m\n",
"\u001b[31;1mERROR [139296783949504] Terminated with unhandled exception: clCreateContext\n",
"\u001b[0m"
]
}
]
},
{
"cell_type": "code",
"source": [
"!runPipeline --datahub nuclei-segmentation --verbose --opencl-platform intel --filename CMU-1.svs"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "JNBxu8lDmlqp",
"outputId": "39072438-9a3c-4452-bbc1-9fd266dd7982"
},
"execution_count": 7,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[32;1m\n",
" - Powered by - \n",
" _______ __________ \n",
" / __/ _ | / __/_ __/ https://fast.eriksmistad.no\n",
" / _// __ |_\\ \\ / / v4.7.1\n",
"/_/ /_/ |_/___/ /_/ \n",
"\n",
"\u001b[0mINFO [136329872953024] Processing token --opencl-platform\u001b[0m\n",
"INFO [136329872953024] Processing token --filename\u001b[0m\n",
"INFO [136329872953024] Processing token CMU-1.svs\u001b[0m\n",
"INFO [136329872953024] CommandLineParser: Assigning variable filename with value CMU-1.svs\u001b[0m\n",
"INFO [136329872953024] Running pipeline in headless mode\u001b[0m\n",
"INFO [136329872953024] Loaded configuration file: /usr/local/lib/python3.10/dist-packages/fast/bin/../bin/fast_configuration.txt\u001b[0m\n",
"INFO [136329872953024] Test data path: /root/FAST/data/\u001b[0m\n",
"INFO [136329872953024] Kernel source path: /usr/local/lib/python3.10/dist-packages/fast/bin/../bin//..//kernels/\u001b[0m\n",
"INFO [136329872953024] Kernel binary path: /root/FAST//kernel_binaries/\u001b[0m\n",
"INFO [136329872953024] Documentation path: /usr/local/lib/python3.10/dist-packages/fast/bin/../bin//..//doc/\u001b[0m\n",
"INFO [136329872953024] Pipeline path: /root/FAST//pipelines/\u001b[0m\n",
"INFO [136329872953024] Qt plugins path: /usr/local/lib/python3.10/dist-packages/fast/bin/../bin//..//plugins/\u001b[0m\n",
"INFO [136329872953024] Library path: /usr/local/lib/python3.10/dist-packages/fast/bin/../bin//..//lib/\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"INFO [136329872953024] Creating new QApp\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Unable to open X display. Disabling visualization.\u001b[0m\n",
"QStandardPaths: XDG_RUNTIME_DIR not set, defaulting to '/tmp/runtime-root'\n",
"Retrieving 'Nuclei segmentation' pipeline from FAST Data Hub\n",
"Retrieving 'Nuclei segmentation model' model from FAST Data Hub\n",
"License: CC BY 4.0\n",
"Downloading [] 100% | 27MB / 27MB | ETA 0.0 mins\n",
"Complete.\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"INFO [136329872953024] Found variable filename in pipeline file\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"\u001b[1mWARNING [136329872953024] Test data was NOT found at /root/FAST/data/. Download the test data by running ./downloadTestData or fast.downloadTestDataIfNotExists() in Python.\u001b[0m\n",
"Pipeline execution started.\n",
"INFO [136329872953024] QApp already exists..\u001b[0m\n",
"INFO [136329872953024] Found 1 OpenCL platforms.\u001b[0m\n",
"INFO [136329872953024] 1 platforms selected for inspection.\u001b[0m\n",
"INFO [136329872953024] Platform 0: Intel(R) Corporation\u001b[0m\n",
"INFO [136329872953024] This platform has 1 available devices in total\u001b[0m\n",
"INFO [136329872953024] Looking for GPU devices only.\u001b[0m\n",
"INFO [136329872953024] 0 selected.\u001b[0m\n",
"INFO [136329872953024] NO suitable GPU found! Trying to find other devices\u001b[0m\n",
"INFO [136329872953024] Found 1 OpenCL platforms.\u001b[0m\n",
"INFO [136329872953024] 1 platforms selected for inspection.\u001b[0m\n",
"INFO [136329872953024] Platform 0: Intel(R) Corporation\u001b[0m\n",
"INFO [136329872953024] This platform has 1 available devices in total\u001b[0m\n",
"INFO [136329872953024] Looking for all types of devices.\u001b[0m\n",
"INFO [136329872953024] 1 selected.\u001b[0m\n",
"INFO [136329872953024] Inspecting device 0 with the name Intel(R) Xeon(R) CPU @ 2.20GHz\u001b[0m\n",
"INFO [136329872953024] The device was accepted.\u001b[0m\n",
"INFO [136329872953024] Intel(R) Xeon(R) CPU @ 2.20GHz has 2 compute units\u001b[0m\n",
"INFO [136329872953024] The device Intel(R) Xeon(R) CPU @ 2.20GHz got a score of 2\u001b[0m\n",
"INFO [136329872953024] The platform Intel(R) OpenCL was selected as the best platform.\u001b[0m\n",
"INFO [136329872953024] A total of 1 devices were selected for the context from this platform:\u001b[0m\n",
"INFO [136329872953024] The best device was: Intel(R) Xeon(R) CPU @ 2.20GHz\u001b[0m\n",
"\u001b[31;1mERROR [136329872953024] Terminated with unhandled exception: clCreateContext\n",
"\u001b[0m"
]
}
]
},
{
"cell_type": "code",
"source": [
"# run simple WSI patch generation pipeline\n",
"import fast\n",
"import matplotlib.pyplot as plt\n",
"\n",
"# This will download the test data needed to run the example\n",
"fast.downloadTestDataIfNotExists()\n",
"\n",
"importer = fast.WholeSlideImageImporter.create(\n",
" fast.Config.getTestDataPath() + 'WSI/A05.svs')\n",
"\n",
"tissueSegmentation = fast.TissueSegmentation.create().connect(importer)\n",
"\n",
"patchGenerator = fast.PatchGenerator.create(512, 512, level=0)\\\n",
" .connect(0, importer)\\\n",
" .connect(1, tissueSegmentation)\n",
"\n",
"# Create a 3x3 subplot for every set of 9 patches\n",
"patch_list = []\n",
"for patch in fast.DataStream(patchGenerator):\n",
" patch_list.append(patch)\n",
" if len(patch_list) == 9:\n",
" # Display the 9 last patches\n",
" f, axes = plt.subplots(3,3, figsize=(10,10))\n",
" for i in range(3):\n",
" for j in range(3):\n",
" axes[i, j].imshow(patch_list[i + j*3])\n",
" #plt.show()\n",
" patch_list.clear()\n",
" break\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 399
},
"id": "qZRaLbR_Zzpz",
"outputId": "02d5b3fa-beca-4318-a0e5-b054f3a410e6"
},
"execution_count": 8,
"outputs": [
{
"output_type": "error",
"ename": "RuntimeError",
"evalue": "ignored",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-8-9f65d4035c61>\u001b[0m in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# run simple WSI patch generation pipeline\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mfast\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;31m# This will download the test data needed to run the example\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/fast/__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[0mfast\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mConfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetTerminateHandlerDisabled\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mTrue\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margv\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'UFFviewer'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'runPipeline'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'systemCheck'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 22\u001b[0;31m \u001b[0mfast\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mImageFileImporter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m''\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# Trigger splash, GL context initialization etc.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m/usr/local/lib/python3.10/dist-packages/fast/fast.py\u001b[0m in \u001b[0;36mcreate\u001b[0;34m(filename, grayscale)\u001b[0m\n\u001b[1;32m 14342\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;32mreturn\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0minstance\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 14343\u001b[0m \"\"\"\n\u001b[0;32m> 14344\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0m_fast\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mImageFileImporter_create\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgrayscale\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 14345\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 14346\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0msetGrayscale\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgrayscale\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m\"bool\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;34m\"void\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mRuntimeError\u001b[0m: clCreateContext"
]
}
]
}
],
"metadata": {
"colab": {
"provenance": [],
"gpuType": "T4",
"authorship_tag": "ABX9TyORScOWaBAfJnRFlKXb/pIO",
"include_colab_link": true
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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