I had trained my own stylegan model, and convert the pkl file to pt format by using stylegan-pytorch project. But when I run PULSE, it come up with some errors as follow:

Loading Synthesis Network Traceback (most recent call last): File "run.py", line 58, in model = PULSE(cache_dir=kwargs["cache_dir"]) File "H:\Pulse\PULSE.py", line 25, in init self.synthesis.load_state_dict(torch.load("./models/karras2019stylegan-ffhq-1024x1024.for_g_all.pt")) File "D:\Anaconda3\envs\pulse\lib\site-packages\torch\nn\modules\module.py", line 846, in load_state_dict raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for G_synthesis: Missing key(s) in state_dict: "torgb.weight", "torgb.bias", "blocks.4x4.const", "blocks.4x4.bias", "blocks.4x4.epi1.noise.weight", "blocks.4x4.epi1.style_mod.lin.weight", "blocks.4x4.epi1.style_mod.lin.bias", "blocks.4x4.conv.weight", "blocks.4x4.conv.bias", "blocks.4x4.epi2.noise.weight", "blocks.4x4.epi2.style_mod.lin.weight", "blocks.4x4.epi2.style_mod.lin.bias", "blocks.8x8.conv0_up.weight", "blocks.8x8.conv0_up.bias", "blocks.8x8.conv0_up.intermediate.kernel", "blocks.8x8.epi1.noise.weight", "blocks.8x8.epi1.style_mod.lin.weight", "blocks.8x8.epi1.style_mod.lin.bias", "blocks.8x8.conv1.weight", "blocks.8x8.conv1.bias", "blocks.8x8.epi2.noise.weight", "blocks.8x8.epi2.style_mod.lin.weight", "blocks.8x8.epi2.style_mod.lin.bias", "blocks.16x16.conv0_up.weight", "blocks.16x16.conv0_up.bias", "blocks.16x16.conv0_up.intermediate.kernel", "blocks.16x16.epi1.noise.weight", "blocks.16x16.epi1.style_mod.lin.weight", "blocks.16x16.epi1.style_mod.lin.bias", "blocks.16x16.conv1.weight", "blocks.16x16.conv1.bias", "blocks.16x16.epi2.noise.weight", "blocks.16x16.epi2.style_mod.lin.weight", "blocks.16x16.epi2.style_mod.lin.bias", "blocks.32x32.conv0_up.weight", "blocks.32x32.conv0_up.bias", "blocks.32x32.conv0_up.intermediate.kernel", "blocks.32x32.epi1.noise.weight", "blocks.32x32.epi1.style_mod.lin.weight", "blocks.32x32.epi1.style_mod.lin.bias", "blocks.32x32.conv1.weight", "blocks.32x32.conv1.bias", "blocks.32x32.epi2.noise.weight", "blocks.32x32.epi2.style_mod.lin.weight", "blocks.32x32.epi2.style_mod.lin.bias", "blocks.64x64.conv0_up.weight", "blocks.64x64.conv0_up.bias", "blocks.64x64.conv0_up.intermediate.kernel", "blocks.64x64.epi1.noise.weight", "blocks.64x64.epi1.style_mod.lin.weight", "blocks.64x64.epi1.style_mod.lin.bias", "blocks.64x64.conv1.weight", "blocks.64x64.conv1.bias", "blocks.64x64.epi2.noise.weight", "blocks.64x64.epi2.style_mod.lin.weight", "blocks.64x64.epi2.style_mod.lin.bias", "blocks.128x128.conv0_up.weight", "blocks.128x128.conv0_up.bias", "blocks.128x128.conv0_up.intermediate.kernel", "blocks.128x128.epi1.noise.weight", "blocks.128x128.epi1.style_mod.lin.weight", "blocks.128x128.epi1.style_mod.lin.bias", "blocks.128x128.conv1.weight", "blocks.128x128.conv1.bias", "blocks.128x128.epi2.noise.weight", "blocks.128x128.epi2.style_mod.lin.weight", "blocks.128x128.epi2.style_mod.lin.bias", "blocks.256x256.conv0_up.weight", "blocks.256x256.conv0_up.bias", "blocks.256x256.conv0_up.intermediate.kernel", "blocks.256x256.epi1.noise.weight", "blocks.256x256.epi1.style_mod.lin.weight", "blocks.256x256.epi1.style_mod.lin.bias", "blocks.256x256.conv1.weight", "blocks.256x256.conv1.bias", "blocks.256x256.epi2.noise.weight", "blocks.256x256.epi2.style_mod.lin.weight", "blocks.256x256.epi2.style_mod.lin.bias", "blocks.512x512.conv0_up.weight", "blocks.512x512.conv0_up.bias", "blocks.512x512.conv0_up.intermediate.kernel", "blocks.512x512.epi1.noise.weight", "blocks.512x512.epi1.style_mod.lin.weight", "blocks.512x512.epi1.style_mod.lin.bias", "blocks.512x512.conv1.weight", "blocks.512x512.conv1.bias", "blocks.512x512.epi2.noise.weight", "blocks.512x512.epi2.style_mod.lin.weight", "blocks.512x512.epi2.style_mod.lin.bias", "blocks.1024x1024.conv0_up.weight", "blocks.1024x1024.conv0_up.bias", "blocks.1024x1024.conv0_up.intermediate.kernel", "blocks.1024x1024.epi1.noise.weight", "blocks.1024x1024.epi1.style_mod.lin.weight", "blocks.1024x1024.epi1.style_mod.lin.bias", "blocks.1024x1024.conv1.weight", "blocks.1024x1024.conv1.bias", "blocks.1024x1024.epi2.noise.weight", "blocks.1024x1024.epi2.style_mod.lin.weight", "blocks.1024x1024.epi2.style_mod.lin.bias". Unexpected key(s) in state_dict: "g_mapping.dense0.weight", "g_mapping.dense0.bias", "g_mapping.dense1.weight", "g_mapping.dense1.bias", "g_mapping.dense2.weight", "g_mapping.dense2.bias", "g_mapping.dense3.weight", "g_mapping.dense3.bias", "g_mapping.dense4.weight", "g_mapping.dense4.bias", "g_mapping.dense5.weight", "g_mapping.dense5.bias", "g_mapping.dense6.weight", "g_mapping.dense6.bias", "g_mapping.dense7.weight", "g_mapping.dense7.bias", "g_synthesis.torgb.weight", "g_synthesis.torgb.bias", "g_synthesis.blocks.4x4.const", "g_synthesis.blocks.4x4.bias", "g_synthesis.blocks.4x4.epi1.top_epi.noise.weight", "g_synthesis.blocks.4x4.epi1.style_mod.lin.weight", "g_synthesis.blocks.4x4.epi1.style_mod.lin.bias", "g_synthesis.blocks.4x4.conv.weight", "g_synthesis.blocks.4x4.conv.bias", "g_synthesis.blocks.4x4.epi2.top_epi.noise.weight", "g_synthesis.blocks.4x4.epi2.style_mod.lin.weight", "g_synthesis.blocks.4x4.epi2.style_mod.lin.bias", "g_synthesis.blocks.8x8.conv0_up.weight", "g_synthesis.blocks.8x8.conv0_up.bias", "g_synthesis.blocks.8x8.conv0_up.intermediate.kernel", "g_synthesis.blocks.8x8.epi1.top_epi.noise.weight", "g_synthesis.blocks.8x8.epi1.style_mod.lin.weight", "g_synthesis.blocks.8x8.epi1.style_mod.lin.bias", "g_synthesis.blocks.8x8.conv1.weight", "g_synthesis.blocks.8x8.conv1.bias", "g_synthesis.blocks.8x8.epi2.top_epi.noise.weight", "g_synthesis.blocks.8x8.epi2.style_mod.lin.weight", "g_synthesis.blocks.8x8.epi2.style_mod.lin.bias", "g_synthesis.blocks.16x16.conv0_up.weight", "g_synthesis.blocks.16x16.conv0_up.bias", "g_synthesis.blocks.16x16.conv0_up.intermediate.kernel", "g_synthesis.blocks.16x16.epi1.top_epi.noise.weight", "g_synthesis.blocks.16x16.epi1.style_mod.lin.weight", "g_synthesis.blocks.16x16.epi1.style_mod.lin.bias", "g_synthesis.blocks.16x16.conv1.weight", "g_synthesis.blocks.16x16.conv1.bias", "g_synthesis.blocks.16x16.epi2.top_epi.noise.weight", "g_synthesis.blocks.16x16.epi2.style_mod.lin.weight", "g_synthesis.blocks.16x16.epi2.style_mod.lin.bias", "g_synthesis.blocks.32x32.conv0_up.weight", "g_synthesis.blocks.32x32.conv0_up.bias", "g_synthesis.blocks.32x32.conv0_up.intermediate.kernel", "g_synthesis.blocks.32x32.epi1.top_epi.noise.weight", "g_synthesis.blocks.32x32.epi1.style_mod.lin.weight", "g_synthesis.blocks.32x32.epi1.style_mod.lin.bias", "g_synthesis.blocks.32x32.conv1.weight", "g_synthesis.blocks.32x32.conv1.bias", "g_synthesis.blocks.32x32.epi2.top_epi.noise.weight", "g_synthesis.blocks.32x32.epi2.style_mod.lin.weight", "g_synthesis.blocks.32x32.epi2.style_mod.lin.bias", "g_synthesis.blocks.64x64.conv0_up.weight", "g_synthesis.blocks.64x64.conv0_up.bias", "g_synthesis.blocks.64x64.conv0_up.intermediate.kernel", "g_synthesis.blocks.64x64.epi1.top_epi.noise.weight", "g_synthesis.blocks.64x64.epi1.style_mod.lin.weight", "g_synthesis.blocks.64x64.epi1.style_mod.lin.bias", "g_synthesis.blocks.64x64.conv1.weight", "g_synthesis.blocks.64x64.conv1.bias", "g_synthesis.blocks.64x64.epi2.top_epi.noise.weight", "g_synthesis.blocks.64x64.epi2.style_mod.lin.weight", "g_synthesis.blocks.64x64.epi2.style_mod.lin.bias", "g_synthesis.blocks.128x128.conv0_up.weight", "g_synthesis.blocks.128x128.conv0_up.bias", "g_synthesis.blocks.128x128.conv0_up.intermediate.kernel", "g_synthesis.blocks.128x128.epi1.top_epi.noise.weight", "g_synthesis.blocks.128x128.epi1.style_mod.lin.weight", "g_synthesis.blocks.128x128.epi1.style_mod.lin.bias", "g_synthesis.blocks.128x128.conv1.weight", "g_synthesis.blocks.128x128.conv1.bias", "g_synthesis.blocks.128x128.epi2.top_epi.noise.weight", "g_synthesis.blocks.128x128.epi2.style_mod.lin.weight", "g_synthesis.blocks.128x128.epi2.style_mod.lin.bias", "g_synthesis.blocks.256x256.conv0_up.weight", "g_synthesis.blocks.256x256.conv0_up.bias", "g_synthesis.blocks.256x256.conv0_up.intermediate.kernel", "g_synthesis.blocks.256x256.epi1.top_epi.noise.weight", "g_synthesis.blocks.256x256.epi1.style_mod.lin.weight", "g_synthesis.blocks.256x256.epi1.style_mod.lin.bias", "g_synthesis.blocks.256x256.conv1.weight", "g_synthesis.blocks.256x256.conv1.bias", "g_synthesis.blocks.256x256.epi2.top_epi.noise.weight", "g_synthesis.blocks.256x256.epi2.style_mod.lin.weight", "g_synthesis.blocks.256x256.epi2.style_mod.lin.bias", "g_synthesis.blocks.512x512.conv0_up.weight", "g_synthesis.blocks.512x512.conv0_up.bias", "g_synthesis.blocks.512x512.conv0_up.intermediate.kernel", "g_synthesis.blocks.512x512.epi1.top_epi.noise.weight", "g_synthesis.blocks.512x512.epi1.style_mod.lin.weight", "g_synthesis.blocks.512x512.epi1.style_mod.lin.bias", "g_synthesis.blocks.512x512.conv1.weight", "g_synthesis.blocks.512x512.conv1.bias", "g_synthesis.blocks.512x512.epi2.top_epi.noise.weight", "g_synthesis.blocks.512x512.epi2.style_mod.lin.weight", "g_synthesis.blocks.512x512.epi2.style_mod.lin.bias", "g_synthesis.blocks.1024x1024.conv0_up.weight", "g_synthesis.blocks.1024x1024.conv0_up.bias", "g_synthesis.blocks.1024x1024.conv0_up.intermediate.kernel", "g_synthesis.blocks.1024x1024.epi1.top_epi.noise.weight", "g_synthesis.blocks.1024x1024.epi1.style_mod.lin.weight", "g_synthesis.blocks.1024x1024.epi1.style_mod.lin.bias", "g_synthesis.blocks.1024x1024.conv1.weight", "g_synthesis.blocks.1024x1024.conv1.bias", "g_synthesis.blocks.1024x1024.epi2.top_epi.noise.weight", "g_synthesis.blocks.1024x1024.epi2.style_mod.lin.weight", "g_synthesis.blocks.1024x1024.epi2.style_mod.lin.bias".

So, is there any way that I can make it right? FULLY RESPECT.

with several pics from FFHQ dataset,i used align_face.py to downsample 32X, and runned run.py, the output pics were not the same person as inputs,why?

It turns out, as long as you have GTX 970 or higher, prerequisites installation is quite simple

0. Fresh nVidia drivers.
1. Python
2. Visual Studio with c++ workload and cmake, needed for dlib. Possibly, only buildtools are needed, I didn't check that. There may be precompiled dlib, I also didn't check.
3. Precompiled pytorch and pytorchvision
4. Pillow, numpy, scipy and dlib.

Looks like there is no need to install CUDA SDK to use precompiled pytorch on Windows.

So, from clean slate:

1. Install chocolatey, used to install Cmake, Visual Studio and Python

from admin cmd

@"%SystemRoot%\System32\WindowsPowerShell\v1.0\powershell.exe" -NoProfile -InputFormat None -ExecutionPolicy Bypass -Command "[System.Net.ServicePointManager]::SecurityProtocol = 3072; iex ((New-Object System.Net.WebClient).DownloadString('https://chocolatey.org/install.ps1'))" && SET "PATH=%PATH%;%ALLUSERSPROFILE%\chocolatey\bin"

or from admin PowerShell

Set-ExecutionPolicy Bypass -Scope Process -Force; [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072; iex ((New-Object System.Net.WebClient).DownloadString('https://chocolatey.org/install.ps1'))

2. Reopen admin cmd/Powershell and run

cinst -y visualstudio2019community visualstudio2017-workload-nativedesktop

to install Visual Studio with C++ compiler. Then reboot and, again, from admin cmd/Powershell

cinst -y python
cinst -y cmake --installargs 'ADD_CMAKE_TO_PATH=System'

3. Finally, install all python libraries. I used pytorch 1.5.0, and it supports only GTX 970 and newer. Maybe older versions supports your hardware.

from non-admin cmd/PowerShell

pip install numpy
pip install scipy
pip install https://download.pytorch.org/whl/cu102/torch-1.5.0-cp38-cp38-win_amd64.whl
pip install https://download.pytorch.org/whl/cu102/torchvision-0.6.0-cp38-cp38-win_amd64.whl
pip install pillow
pip install dlib

Everything's ready for use, from Data section of the Readme.

Warning, though, for some reason dlib module align_face.py didn't work well with pngs and bmps. So jpg realpics it is.

@adamian98 @georgzoeller Hi there,

• it's would be great to know how to train pulse from scratch
• Also how to use the trained model to inference
• Note that the download links have reached a daily quota, so you might want to upload the files into a multiple services, example: gdrive, onedrive, dropbox, etc..

I have done everything needed, then run python run.py, and the only output is [1] 36213 illegal hardware instruction python run.py.

Did not it support in Apple Arm64 architecture?

I'm running on a single image and getting the following error.

Traceback (most recent call last):
  File "run.py", line 79, in <module>
    for j,(HR,LR) in enumerate(model(ref_im,**kwargs)):
  File "/home/ubuntu/pulse/PULSE.py", line 149, in forward
    loss, loss_dict = loss_builder(latent_in, gen_im)
  File "/home/ubuntu/miniconda3/envs/pulse/lib/python3.8/site-packages/torch/nn/modules/module.py", line 550, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/ubuntu/pulse/loss.py", line 54, in forward
    tmp_loss = loss_fun_dict[loss_type](**var_dict)
  File "/home/ubuntu/pulse/loss.py", line 23, in _loss_l2
    return ((gen_im_lr - ref_im).pow(2).mean((1, 2, 3)).clamp(min=self.eps).sum())
RuntimeError: The size of tensor a (3) must match the size of tensor b (4) at non-singleton dimension 1

I printed the variables gen_im_lr & ref_im and got the following:

torch.Size([1, 3, 32, 32]) torch.Size([1, 4, 32, 32])

Thank you for your impressive work and for sharing the code. I put two png images into input folder:

| size | 256x256 | 32x32 | |----------|----------|-------------| | input | | | | result | | |

Moreover if I downscale enhanced image back to 32x32 I got very different thumbnail from the original one:

Could you assist me what am I doing wrong and how to reproduce results from paper?

(As a student I am kinda new to this but did quite a bit of research and I got pretty far, i'm super into learning something new through this!)

This issue is for the project pulse -> https://github.com/adamian98/pulse

error log for runing out of memory--> (after executing the "run.py" file)

Loading Synthesis Network Loading Mapping Network Running Mapping Network Traceback (most recent call last): File "C:\Users\micha\anaconda3\envs\Pulse1\pulse-master\run.py", line 58, in model = PULSE(cache_dir=kwargs["cache_dir"]) File "C:\Users\micha\anaconda3\envs\Pulse1\pulse-master\PULSE.py", line 44, in init latent_out = torch.nn.LeakyReLU(5)(mapping(latent)) File "C:\Users\micha\anaconda3\envs\pulse3\lib\site-packages\torch\nn\modules\module.py", line 550, in call result = self.forward(*input, **kwargs) File "C:\Users\micha\anaconda3\envs\Pulse1\pulse-master\stylegan.py", line 233, in forward x = super().forward(x) File "C:\Users\micha\anaconda3\envs\pulse3\lib\site-packages\torch\nn\modules\container.py", line 100, in forward input = module(input) File "C:\Users\micha\anaconda3\envs\pulse3\lib\site-packages\torch\nn\modules\module.py", line 550, in call result = self.forward(*input, **kwargs) File "C:\Users\micha\anaconda3\envs\Pulse1\pulse-master\stylegan.py", line 38, in forward return F.linear(x, self.weight * self.w_mul, bias) File "C:\Users\micha\anaconda3\envs\pulse3\lib\site-packages\torch\nn\functional.py", line 1610, in linear ret = torch.addmm(bias, input, weight.t()) RuntimeError: CUDA out of memory. Tried to allocate 1.91 GiB (GPU 0; 6.00 GiB total capacity; 3.92 GiB already allocated; 744.91 MiB free; 3.93 GiB reserved in total by PyTorch)

end error log --

DETAILS PART 1:

Hi, I have an nvidia gpu with 6gb of memory which, (according to other logs-> should have enough memory for this to work "We ran our tests with 8GB of memory but I believe that you should be able to run the code with 4GB as well" -adamian98 ). I'm trying to fix that error and get the run.py to work as intended. If you have anything else to add for learning purposes i'll gladly take it!

Here is the system info using "numba -s" (includes: gpu, my windows version, memory, python version etc.)

START CUDA INFO Hardware Information Machine : AMD64 CPU Name : znver1 CPU Count : 16 Number of accessible CPUs : 16 List of accessible CPUs cores : 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 CFS Restrictions (CPUs worth of runtime) : None

CPU Features : 64bit adx aes avx avx2 bmi bmi2 clflushopt clwb clzero cmov cx16 cx8 f16c fma fsgsbase fxsr lzcnt mmx movbe mwaitx pclmul popcnt prfchw rdpid rdrnd rdseed sahf sha sse sse2 sse3 sse4.1 sse4.2 sse4a ssse3 wbnoinvd xsave xsavec xsaveopt xsaves

Memory Total (MB) : 15789 Memory Available (MB) : 8421

OS Information Platform Name : Windows-10-10.0.18362-SP0 Platform Release : 10 OS Name : Windows OS Version : 10.0.18362 OS Specific Version : 10 10.0.18362 SP0 Multiprocessor Free Libc Version : ?

Python Information Python Compiler : MSC v.1916 64 bit (AMD64) Python Implementation : CPython Python Version : 3.8.5 Python Locale : en_CA.cp1252

LLVM Information LLVM Version : 10.0.1

CUDA Information CUDA Device Initialized : True CUDA Driver Version : 10020 CUDA Detect Output: Found 1 CUDA devices id 0 b'GeForce GTX 1660 Ti with Max-Q Design' [SUPPORTED] compute capability: 7.5 pci device id: 0 pci bus id: 1 Summary: 1/1 devices are supported

CUDA Librairies Test Output: Finding cublas from named cublas.dll trying to open library... ERROR: failed to open cublas: Could not find module 'cublas.dll' (or one of its dependencies). Try using the full path with constructor syntax. Finding cusparse from named cusparse.dll trying to open library... ERROR: failed to open cusparse: Could not find module 'cusparse.dll' (or one of its dependencies). Try using the full path with constructor syntax. Finding cufft from named cufft.dll trying to open library... ERROR: failed to open cufft: Could not find module 'cufft.dll' (or one of its dependencies). Try using the full path with constructor syntax. Finding curand from named curand.dll trying to open library... ERROR: failed to open curand: Could not find module 'curand.dll' (or one of its dependencies). Try using the full path with constructor syntax. Finding nvvm from named nvvm.dll trying to open library... ERROR: failed to open nvvm: Could not find module 'nvvm.dll' (or one of its dependencies). Try using the full path with constructor syntax. Finding cudart from named cudart.dll trying to open library... ERROR: failed to open cudart: Could not find module 'cudart.dll' (or one of its dependencies). Try using the full path with constructor syntax. Finding libdevice from searching for compute_20... ERROR: can't open libdevice for compute_20 searching for compute_30... ERROR: can't open libdevice for compute_30 searching for compute_35... ERROR: can't open libdevice for compute_35 searching for compute_50... ERROR: can't open libdevice for compute_50

ROC information ROC Available : False ROC Toolchains : None HSA Agents Count : 0 HSA Agents: None HSA Discrete GPUs Count : 0 HSA Discrete GPUs : None

SVML Information SVML State, config.USING_SVML : True SVML Library Loaded : True llvmlite Using SVML Patched LLVM : True SVML Operational : True

Threading Layer Information TBB Threading Layer Available : False +--> Disabled due to Unknown import problem. OpenMP Threading Layer Available : True +-->Vendor: MS Workqueue Threading Layer Available : True +-->Workqueue imported successfully.

Numba Environment Variable Information None found.

Conda Information Conda Build : 3.20.5 Conda Env : 4.9.2 Conda Platform : win-64 Conda Python Version : 3.8.5.final.0 Conda Root Writable : True

Installed Packages blas 1.0 mkl ca-certificates 2020.12.8 haa95532_0 certifi 2020.12.5 py38haa95532_0 cffi 1.14.0 py38h7a1dbc1_0 chardet 3.0.4 py38haa95532_1003 cryptography 2.9.2 py38h7a1dbc1_0 cudatoolkit 10.2.89 h74a9793_1 anaconda cycler 0.10.0 py38_0 freetype 2.9.1 ha9979f8_1 icc_rt 2019.0.0 h0cc432a_1 icu 58.2 ha925a31_3 idna 2.9 py_1 intel-openmp 2019.4 245 jpeg 9b hb83a4c4_2 kiwisolver 1.2.0 py38h74a9793_0 libcxx 7.0.0 h1ad3211_1002 conda-forge libpng 1.6.37 h2a8f88b_0 libtiff 4.1.0 h56a325e_0 llvm-meta 7.0.0 0 conda-forge m2-bash 4.3.042 5 m2-gcc-libs 5.3.0 4 m2-libedit 3.1 20150326 m2-libffi 3.2.1 2 m2-libreadline 6.3.008 8 m2-msys2-runtime 2.5.0.17080.65c939c 3 m2-ncurses 6.0.20160220 2 m2w64-gcc-libgfortran 5.3.0 6 m2w64-gcc-libs-core 5.3.0 7 m2w64-gmp 6.1.0 2 m2w64-libwinpthread-git 5.0.0.4634.697f757 2 matplotlib 3.1.3 py38_0 matplotlib-base 3.1.3 py38h64f37c6_0 mkl 2019.4 245 mkl-service 2.3.0 py38h196d8e1_0 mkl_fft 1.0.15 py38h14836fe_0 mkl_random 1.1.0 py38hf9181ef_0 msys2-conda-epoch 20160418 1 ninja 1.9.0 py38h74a9793_0 numpy 1.18.1 py38h93ca92e_0 numpy-base 1.18.1 py38hc3f5095_1 olefile 0.46 py_0 openssl 1.1.1i h2bbff1b_0 pandas 1.0.3 py38h47e9c7a_0 pillow 7.1.2 py38hcc1f983_0 pip 20.0.2 py38_3 powershell_shortcut 0.0.1 3 pycparser 2.20 py_2 pyopenssl 19.1.0 pyhd3eb1b0_1 pyparsing 2.4.7 py_0 pyqt 5.9.2 py38ha925a31_4 pysocks 1.7.1 py38haa95532_0 python 3.8.2 he1778fa_13 python-dateutil 2.8.1 py_0 pytorch 1.5.0 py3.8_cuda102_cudnn7_0 pytorch pytz 2020.1 py_0 qt 5.9.7 vc14h73c81de_0 requests 2.23.0 py38_0 scipy 1.4.1 py38h9439919_0 setuptools 46.2.0 py38_0 sip 4.19.13 py38ha925a31_0 six 1.14.0 py38haa95532_0 sqlite 3.31.1 h2a8f88b_1 tk 8.6.8 hfa6e2cd_0 torchvision 0.6.0 py38_cu102 pytorch tornado 6.0.4 py38he774522_1 urllib3 1.25.8 py38_0 vc 14.2 h21ff451_1 vs2015_runtime 14.27.29016 h5e58377_2 wheel 0.34.2 py38_0 win_inet_pton 1.1.0 py38haa95532_0 wincertstore 0.2 py38_0 xz 5.2.5 h62dcd97_0 zlib 1.2.11 h62dcd97_4 zstd 1.3.7 h508b16e_0

No errors reported.

Warning log Warning (roc): Error initialising ROC: No ROC toolchains found. Warning (roc): No HSA Agents found, encountered exception when searching: Error at driver init:

HSA is not currently supported on this platform (win32). : END CUDA INFO

DETAILS PART 2 (It sounded like dlib (and cmake) were only required to align the faces before therefore theoretically it isnt needed in run.py, but im not 100 percent sure so I included the errors.):

I got the .yml installed successfully into the anaconda environment I named "pulse3" with no errors as well as the CUDA toolkit 10.2 and cmake 3.17.2. Dlib is the only thing that gave me some trouble spiting out a bunch of incompatibility errors with the other packages on windows (ill post a log at the end) but I was able to install it into a seperate virtual environment successfully with no errors (this video https://www.youtube.com/watch?v=xXbouOlAyoo). Go to 3:40 for a snapshot of where I ended.

START CONFLICTS TRYING TO INSTALL DLIB INTO ENVIRONMENT DIRECTLY (everything else including cmake was installed correctly, this is windows python version 3.8.2)

Downloading and Extracting Packages cmake-3.17.2 | 10.5 MB | ############################################################################ | 100% Preparing transaction: done Verifying transaction: done Executing transaction: done (pulse3) PS C:\Users\micha> conda install -c conda-forge dlib Collecting package metadata (current_repodata.json): done Solving environment: failed with initial frozen solve. Retrying with flexible solve. Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source. Collecting package metadata (repodata.json): done Solving environment: failed with initial frozen solve. Retrying with flexible solve. Solving environment: | Found conflicts! Looking for incompatible packages. This can take several minutes. Press CTRL-C to abort. Examining icu: 70%|██████████████████████████████████████████████▋ | 55/79 [00:08<00:04, 5.25it/s]|Examining conflict for jpeg pyparsing pyqt pytz pyopenssl powershell_shortcut chardet sip cffi mkl-service cycler qt re|Examining conflict for pyparsing pyqt pytz pyopenssl powershell_shortcut kiwisolver chardet sip cffi mkl_random mkl-ser/Examining conflict for pyparsing pyqt pytz pyopenssl powershell_shortcut kiwisolver chardet sip cffi mkl_random mkl-ser|Examining conflict for pyparsing pyqt pytz pyopenssl powershell_shortcut chardet sip cffi mkl-service cycler qt python /Examining conflict for pandas pytz: 15%|██████▉ | 12/79 [00:25<02:34, 2.30s/it]|Examining conflict for cffi pytorch cryptography: 29%|█████████▎ | 23/79 [00:31<00:56, 1.01s/it]|Examining conflict for matplotlib-base pip wincertstore setuptools wheel: 38%|███ | 30/79 [00:34<00:29, 1.69it/s]-Examining conflict for pytorch cudatoolkit torchvision: 49%|████████████▊ | 39/79 [00:48<01:03, 1.58s/it]/Examining conflict for pillow libtiff torchvision: 56%|█████████████████▎ | 44/79 [11:02<53:04, 90.98s/it]\Examining conflict for mkl_fft blas scipy matplotlib-base dlib torchvision mkl_random pytorch pandas: 62%|▌| 49/79 [11-Examining conflict for requests python: 96%|████████████████████████████████████████▍ | 76/79 [11:11<00:04, 1.58s/it]-failed

UnsatisfiableError: The following specifications were found to be incompatible with the existing python installation in your environment:

Specifications:

• cffi=1.14.0 -> python[version='2.7.|3.5.|3.6.|3.4.|>=3.5,<3.6.0a0']
• cffi=1.14.0 -> python[version='3.6.9|3.6.9|>=2.7,<2.8.0a0|>=3.8,<3.9.0a0|>=3.7,<3.8.0a0|>=3.6,<3.7.0a0',build='2_73_pypy|1_73_pypy|0_73_pypy']
• cryptography=2.9.2 -> python[version='2.7.|3.5.|3.6.|3.6.12|3.6.9|3.6.9|3.6.9|>=2.7,<2.8.0a0|3.6.9|>=3.5,<3.6.0a0|3.4.|3.8.|3.7.',build='4_73_pypy|3_73_pypy|2_73_pypy|1_73_pypy|0_73_pypy']
• matplotlib-base=3.1.3 -> python[version='2.7.|3.4.|3.5.|3.6.|>=3.9,<3.10.0a0|>=3.5,<3.6.0a0|>=2.7,<2.8.0a0']
• matplotlib=3.1.3 -> python[version='2.7.|3.5.|3.6.|>=2.7,<2.8.0a0|>=3.9,<3.10.0a0|>=3.5,<3.6.0a0|3.4.']
• mkl_fft=1.0.15 -> python[version='3.5.|3.6.|>=3.5,<3.6.0a0|>=3.9,<3.10.0a0']
• mkl_random=1.1.0 -> python[version='3.5.|3.6.|>=2.7,<2.8.0a0|>=3.9,<3.10.0a0|>=3.5,<3.6.0a0']
• numpy-base=1.18.1 -> python[version='>=2.7,<2.8.0a0|>=3.9,<3.10.0a0']
• olefile=0.46 -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.7,<3.8.0a0|>=3.6,<3.7.0a0']
• pip=20.0.2 -> python[version='2.7.|3.5.|3.6.|>=3.5,<3.6.0a0|>=3.9,<3.10.0a0|3.4.']
• pyopenssl=19.1.0 -> python[version='2.7.|3.5.|3.6.|>=3.9,<3.10.0a0|3.4.|>=3.5,<3.6.0a0']
• pytorch=1.5.0 -> python[version='2.7.|3.5.|3.6.|3.6.12|>=3.6,<3.7.0a0|>=3.9,<3.10.0a0|3.6.9|3.6.9|3.6.9|>=2.7,<2.8.0a0|3.6.9|>=3.5,<3.6.0a0|3.4.',build='4_73_pypy|3_73_pypy|2_73_pypy|1_73_pypy|0_73_pypy']
• scipy=1.4.1 -> python[version='>=2.7,<2.8.0a0|>=3.9,<3.10.0a0|>=3.5,<3.6.0a0']
• torchvision=0.6.0 -> python[version='2.7.|3.5.|3.6.*|>=2.7,<2.8.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0|>=3.9,<3.10.0a0|>=3.5,<3.6.0a0']
• wheel=0.34.2 -> python[version='2.7.|3.5.|3.6.|>=3.5,<3.6.0a0|>=3.9,<3.10.0a0|3.4.']

Your python: python=3.8.2

If python is on the left-most side of the chain, that's the version you've asked for. When python appears to the right, that indicates that the thing on the left is somehow not available for the python version you are constrained to. Note that conda will not change your python version to a different minor version unless you explicitly specify that.

The following specifications were found to be incompatible with a past explicit spec that is not an explicit spec in this operation (mkl-service):

• dlib -> boost==1.65.1 -> numpy[version='>=1.11|>=1.9|>=1.8|>=1.7']
• dlib -> jpeg[version='>=9c,<10a|>=9d,<10a']
• dlib -> libpng[version='>=1.6.21,<1.7|>=1.6.22,<1.6.31|>=1.6.32,<1.6.35|>=1.6.35,<1.7.0a0|>=1.6.37,<1.7.0a0|>=1.6.28,<1.7']
• dlib -> libpng[version='>=1.6.37,<1.7.0a0'] -> zlib[version='1.2.*|1.2.11|>=1.2.11,<1.3.0a0|1.2.8']
• dlib -> numpy[version='1.10.|1.11.|1.9.|>=1.14.6,<2.0a0|>=1.16.5,<2.0a0|>=1.19.4,<2.0a0|>=1.19.2,<2.0a0|1.13.|1.12.*']
• dlib -> numpy[version='>=1.16.5,<2.0a0'] -> blas[version='*|1.0|1.1',build='openblas|mkl|mkl']
• dlib -> numpy[version='>=1.16.5,<2.0a0'] -> mkl-service[version='>=2,<3.0a0']
• dlib -> numpy[version='>=1.16.5,<2.0a0'] -> mkl[version='>=2018.0.0,<2019.0a0|>=2018.0.3,<2019.0a0|>=2019.1,<2021.0a0|>=2019.3,<2021.0a0|>=2019.4,<2020.0a0|>=2019.4,<2021.0a0|>=2018.0.2,<2019.0a0']
• dlib -> numpy[version='>=1.16.5,<2.0a0'] -> mkl_fft[version='>=1.0.14,<2.0a0|>=1.0.6,<2.0a0|>=1.0.4']
• dlib -> numpy[version='>=1.16.5,<2.0a0'] -> numpy-base[version='1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.2|1.16.3|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5|1.16.5|1.16.6|1.16.6|1.16.6|1.16.6|1.16.6|1.17.2.|1.17.3.|1.17.4.|1.18.1.|1.18.5.*|1.19.1|1.19.1|1.19.1|1.19.2|1.17.0|1.17.0|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|1.9.3|>=1.9.3,<2.0a0',build='py27h0bb1d87_7|py35h4a99626_8|py35h8128ebf_9|py27h2753ae9_9|py35h8128ebf_10|py37h8128ebf_10|py36h8128ebf_11|py37h2a9b21d_11|py37hc3f5095_12|py36hc3f5095_12|py27h0bb1d87_6|py27h0bb1d87_7|py35h5c71026_7|py36h8128ebf_4|py27h2753ae9_4|py35h8128ebf_4|py38hc3f5095_4|py37hc3f5095_5|py27hb1d0314_5|py35h4a99626_0|py27hfef472a_0|py37h4a99626_0|py36h8128ebf_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py27hb1d0314_0|py36hc3f5095_0|py36hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py37hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py39h2e04a8b_1|py38ha3acd2a_0|py37ha3acd2a_0|py38ha3acd2a_0|py36ha3acd2a_0|py39hbd0edd7_0|py37ha3acd2a_0|py36ha3acd2a_0|py38hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_1|py36hc3f5095_0|py37hc3f5095_0|py37hc3f5095_1|py37hc3f5095_0|py37hc3f5095_0|py27hb1d0314_0|py36hc3f5095_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_1|py36h8128ebf_0|py27h2753ae9_0|py35h8128ebf_0|py27h2753ae9_0|py35h8128ebf_0|py37h8128ebf_0|py36h4a99626_0|py36hc3f5095_5|py37h8128ebf_4|py37h5c71026_7|py36h5c71026_7|py36h5c71026_6|py37h5c71026_6|py38hc3f5095_12|py27hb1d0314_12|py27hb1d0314_11|py36h2a9b21d_11|py37h8128ebf_11|py27h2753ae9_10|py36h8128ebf_10|py36h8128ebf_9|py37h8128ebf_9|py27hfef472a_9|py37h4a99626_9|py36h4a99626_9|py35h4a99626_9|py27h0bb1d87_8|py37h5c71026_8|py36h5c71026_8|py37h5c71026_7|py36h5c71026_7']
• dlib -> python=2.7 -> ca-certificates
• dlib -> python[version='>=3.8,<3.9.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a']
• dlib -> python[version='>=3.8,<3.9.0a0'] -> pip
• dlib -> python[version='>=3.8,<3.9.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.29.0,<4.0a0|>=3.30.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.28.0,<4.0a0|>=3.27.2,<4.0a0']

The following specifications were found to be incompatible with each other:

Output in format: Requested package -> Available versions

Package pip conflicts for: urllib3=1.25.8 -> python[version='>=2.7,<2.8.0a0'] -> pip requests=2.23.0 -> python -> pip numpy=1.18.1 -> python[version='>=3.7,<3.8.0a0'] -> pip python=3.8.2 -> pip cffi=1.14.0 -> python[version='>=2.7,<2.8.0a0'] -> pip mkl_random=1.1.0 -> python[version='>=3.8,<3.9.0a0'] -> pip wincertstore -> python[version='>=3.9,<3.10.0a0'] -> pip pysocks=1.7.1 -> python[version='>=3.8,<3.9.0a0'] -> pip tornado=6.0.4 -> python[version='>=3.8,<3.9.0a0'] -> pip idna=2.9 -> python -> pip matplotlib=3.1.3 -> python[version='>=3.7,<3.8.0a0'] -> pip olefile=0.46 -> python -> pip pyparsing=2.4.7 -> python -> pip powershell_shortcut -> python -> pip certifi -> python[version='>=3.9,<3.10.0a0'] -> pip win_inet_pton -> python[version='>=3.7,<3.8.0a0'] -> pip scipy=1.4.1 -> python[version='>=3.7,<3.8.0a0'] -> pip pyqt -> python[version='>=3.7,<3.8.0a0'] -> pip pytz=2020.1 -> python -> pip wheel=0.34.2 -> python -> pip ninja=1.9.0 -> python[version='>=3.8,<3.9.0a0'] -> pip mkl_fft=1.0.15 -> python[version='>=2.7,<2.8.0a0'] -> pip torchvision=0.6.0 -> python[version='>=3.8,<3.9.0a0'] -> pip mkl-service=2.3.0 -> python[version='>=3.8,<3.9.0a0'] -> pip six=1.14.0 -> python -> pip cryptography=2.9.2 -> python[version='>=3.8,<3.9.0a0'] -> pip chardet=3.0.4 -> python[version='>=3.7,<3.8.0a0'] -> pip matplotlib-base=3.1.3 -> python[version='>=3.8,<3.9.0a0'] -> pip python-dateutil=2.8.1 -> python -> pip pillow=7.1.2 -> python[version='>=3.8,<3.9.0a0'] -> pip kiwisolver=1.2.0 -> python[version='>=3.9,<3.10.0a0'] -> pip numpy-base=1.18.1 -> python[version='>=3.7,<3.8.0a0'] -> pip pytorch=1.5.0 -> python[version='>=3.7,<3.8.0a0'] -> pip sip -> python[version='>=3.7,<3.8.0a0'] -> pip pyopenssl=19.1.0 -> python -> pip pandas=1.0.3 -> python[version='>=3.7,<3.8.0a0'] -> pip setuptools=46.2.0 -> python[version='>=3.7,<3.8.0a0'] -> pip cycler=0.10.0 -> python -> pip pycparser=2.20 -> python -> pip

Package zlib conflicts for: pyqt -> qt[version='>=5.12.9,<5.13.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0'] qt -> libpng[version='>=1.6.34,<1.7.0a0'] -> zlib==1.2.11 matplotlib-base=3.1.3 -> zlib[version='>=1.2.11,<1.3.0a0'] cmake -> zlib[version='1.2.11|>=1.2.11,<1.3.0a0'] qt -> zlib[version='>=1.2.11,<1.3.0a0'] python=3.8.2 -> sqlite[version='>=3.30.1,<4.0a0'] -> zlib[version='>=1.2.11,<1.3.0a0'] freetype=2.9.1 -> libpng[version='>=1.6.34,<1.7.0a0'] -> zlib==1.2.11 libpng=1.6.37 -> zlib[version='>=1.2.11,<1.3.0a0'] freetype=2.9.1 -> zlib[version='>=1.2.11,<1.3.0a0'] libtiff=4.1.0 -> zlib[version='>=1.2.11,<1.3.0a0'] sqlite=3.31.1 -> zlib[version='>=1.2.11,<1.3.0a0'] torchvision=0.6.0 -> pillow[version='>=4.1.1'] -> zlib[version='1.2.|1.2.11|1.2.11.|>=1.2.11,<1.3.0a0|1.2.8'] matplotlib=3.1.3 -> matplotlib-base==3.1.3=py37h2981e6d_0 -> zlib[version='>=1.2.11,<1.3.0a0'] zstd=1.3.7 -> zlib[version='>=1.2.11,<1.3.0a0'] pillow=7.1.2 -> zlib[version='>=1.2.11,<1.3.0a0']

Package python_abi conflicts for: mkl-service=2.3.0 -> python_abi[version='3.6.|3.8.|3.9.|3.7.',build='_cp37m|_cp38|_cp39|_cp36m'] pandas=1.0.3 -> python_abi[version='3.6.|3.7.|3.8.',build='_cp37m|_cp38|_cp36m'] sip -> python_abi[version='3.6.|3.7.|3.9.|3.8.',build='_cp37m|_cp36m|_cp39|_cp38'] numpy=1.18.1 -> mkl-service[version='>=2,<3.0a0'] -> python_abi=3.9[build=*_cp39] wheel=0.34.2 -> setuptools -> python_abi[version='3.6.|3.9.|3.7.|3.8.',build='_cp37m|_cp36m|_cp39|_cp38'] pillow=7.1.2 -> python_abi[version='3.6.|3.7.|3.8.',build='_cp37m|_cp38|_cp36m'] urllib3=1.25.8 -> python_abi[version='2.7.|3.8.|3.7.|3.6.',build='_cp27m|_cp38|_cp37m|_cp36m'] cryptography=2.9.2 -> cffi -> python_abi[version='3.6|3.9.',build='_pypy36_pp73|*_cp39'] pandas=1.0.3 -> numpy[version='>=1.14.6,<2.0a0'] -> python_abi=3.9[build=*_cp39] urllib3=1.25.8 -> certifi -> python_abi=3.9[build=*_cp39] setuptools=46.2.0 -> python_abi[version='3.6.|3.7.|3.8.',build='_cp37m|_cp38|_cp36m'] matplotlib=3.1.3 -> pyqt -> python_abi[version='3.6.|3.7.|3.9.|3.8.',build='_cp36m|_cp37m|_cp39|_cp38'] kiwisolver=1.2.0 -> python_abi[version='3.6.|3.9.|3.7.|3.8.',build='_cp37m|_cp36m|_cp39|_cp38'] setuptools=46.2.0 -> certifi[version='>=2016.9.26'] -> python_abi[version='2.7.|3.9.',build='_cp27m|_cp39'] certifi -> python_abi[version='2.7.|3.6.|3.8.|3.9.|3.7.',build='_cp27m|_cp37m|_cp38|_cp39|_cp36m'] cryptography=2.9.2 -> python_abi[version='3.6.|3.7.|3.8.',build='_cp37m|_cp38|_cp36m'] wincertstore -> python_abi[version='3.6.|3.9.|3.8.|3.7.',build='_cp37m|_cp38|_cp36m|_cp39'] pyqt -> python_abi[version='3.6.|3.7.|3.9.|3.8.',build='_cp36m|_cp37m|_cp39|_cp38'] win_inet_pton -> python_abi[version='3.6.|3.7.|3.8.|3.9.',build='_cp37m|_cp38|_cp39|_cp36m'] pip=20.0.2 -> setuptools -> python_abi[version='3.6.|3.9.|3.7.|3.8.',build='_cp37m|_cp36m|_cp39|_cp38'] numpy-base=1.18.1 -> mkl-service[version='>=2,<3.0a0'] -> python_abi[version='3.6.|3.8.|3.9.|3.7.',build='_cp37m|_cp38|_cp39|_cp36m'] pytorch=1.5.0 -> cffi -> python_abi[version='3.6|3.6.|3.7.|3.8.|3.9.',build='_pypy36_pp73|_cp37m|_cp36m|_cp38|*_cp39'] tornado=6.0.4 -> python_abi[version='3.6.|3.8.|3.7.|3.9.',build='_cp37m|_cp36m|_cp38|_cp39'] zstd=1.3.7 -> lz4 -> python_abi[version='3.6.|3.7.|3.8.|3.9.',build='_cp37m|_cp38|_cp36m|_cp39'] pysocks=1.7.1 -> python_abi[version='2.7.|3.6.|3.8.|3.9.|3.7.',build='_cp27m|_cp37m|_cp38|_cp39|_cp36m'] mkl_fft=1.0.15 -> mkl-service[version='>=2,<3.0a0'] -> python_abi[version='3.6.|3.8.|3.9.|3.7.',build='_cp37m|_cp38|_cp39|_cp36m'] torchvision=0.6.0 -> numpy[version='>=1.11'] -> python_abi[version='3.6.|3.7.|3.8.|3.9.',build='_cp36m|_cp38|_cp39|_cp37m'] pyopenssl=19.1.0 -> cryptography[version='>=2.8'] -> python_abi[version='3.6.|3.8.|3.9.|3.7.',build='_cp37m|_cp38|_cp39|_cp36m'] requests=2.23.0 -> certifi[version='>=2017.4.17'] -> python_abi=3.9[build=*_cp39] matplotlib-base=3.1.3 -> kiwisolver -> python_abi[version='2.7.|3.6.|3.9.|3.8.|3.7.',build='_cp27m|_cp37m|_cp38|_cp36m|_cp39'] mkl_random=1.1.0 -> mkl-service[version='>=2,<3.0a0'] -> python_abi[version='3.6.|3.8.|3.9.|3.7.',build='_cp37m|_cp38|_cp39|_cp36m'] requests=2.23.0 -> python_abi[version='2.7.|3.8.|3.7.|3.6.',build='_cp27m|_cp38|_cp37m|_cp36m'] numpy=1.18.1 -> python_abi[version='3.6.|3.7.|3.8.',build='_cp37m|_cp36m|_cp38'] scipy=1.4.1 -> mkl-service[version='>=2,<3.0a0'] -> python_abi[version='3.6.|3.8.|3.9.|3.7.',build='_cp37m|_cp38|_cp39|_cp36m'] chardet=3.0.4 -> python_abi[version='2.7.|3.6.|3.7.|3.9.|3.8.',build='_cp27m|_cp37m|_cp36m|_cp39|_cp38'] dlib -> python_abi[version='3.6.|3.8.|3.9.|3.7.',build='_cp36m|_cp38|_cp39|_cp37m']

Package ca-certificates conflicts for: urllib3=1.25.8 -> python[version='>=2.7,<2.8.0a0'] -> ca-certificates certifi -> python[version='>=2.7,<2.8.0a0'] -> ca-certificates win_inet_pton -> python[version='>=2.7,<2.8.0a0'] -> ca-certificates olefile=0.46 -> python -> ca-certificates pyparsing=2.4.7 -> python -> ca-certificates pysocks=1.7.1 -> python[version='>=2.7,<2.8.0a0'] -> ca-certificates pytz=2020.1 -> python -> ca-certificates wheel=0.34.2 -> python -> ca-certificates python=3.8.2 -> openssl[version='>=1.1.1g,<1.1.2a'] -> ca-certificates cffi=1.14.0 -> python[version='>=2.7,<2.8.0a0'] -> ca-certificates powershell_shortcut -> python -> ca-certificates six=1.14.0 -> python -> ca-certificates idna=2.9 -> python -> ca-certificates sip -> python[version='>=2.7,<2.8.0a0'] -> ca-certificates wincertstore -> python[version='>=2.7,<2.8.0a0'] -> ca-certificates pip=20.0.2 -> python -> ca-certificates chardet=3.0.4 -> python[version='>=2.7,<2.8.0a0'] -> ca-certificates qt -> openssl[version='>=1.1.1i,<1.1.2a'] -> ca-certificates pyopenssl=19.1.0 -> python -> ca-certificates python-dateutil=2.8.1 -> python -> ca-certificates ninja=1.9.0 -> python[version='>=2.7,<2.8.0a0'] -> ca-certificates mkl_fft=1.0.15 -> python[version='>=2.7,<2.8.0a0'] -> ca-certificates openssl -> ca-certificates cycler=0.10.0 -> python -> ca-certificates pycparser=2.20 -> python -> ca-certificates requests=2.23.0 -> python -> ca-certificates cryptography=2.9.2 -> openssl[version='>=1.1.1g,<1.1.2a'] -> ca-certificates mkl-service=2.3.0 -> python[version='>=2.7,<2.8.0a0'] -> ca-certificates pyqt -> python[version='>=2.7,<2.8.0a0'] -> ca-certificates

Package vs2015_runtime conflicts for: matplotlib-base=3.1.3 -> vs2015_runtime[version='>=14.16.27012,<15.0a0'] pyparsing=2.4.7 -> python -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] wheel=0.34.2 -> python -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] mkl_fft=1.0.15 -> mkl-service[version='>=2,<3.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27012|>=14.28.29325|>=14.16.27033|>=14.27.29016'] python=3.8.2 -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] torchvision=0.6.0 -> cudatoolkit[version='>=10.2,<10.3'] -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] pytorch=1.5.0 -> vs2015_runtime[version='>=14.16.27012,<15.0a0'] icu -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] idna=2.9 -> python -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] openssl -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] zlib=1.2.11 -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] libcxx -> vc[version='>=14,<15.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27012|>=14.16.27033|>=14.28.29325|>=14.27.29016'] cffi=1.14.0 -> vs2015_runtime[version='>=14.16.27012,<15.0a0'] cycler=0.10.0 -> python -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] pandas=1.0.3 -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] powershell_shortcut -> python -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] kiwisolver=1.2.0 -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] mkl_random=1.1.0 -> mkl-service[version='>=2,<3.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27012|>=14.28.29325|>=14.16.27033|>=14.27.29016'] sqlite=3.31.1 -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.15.26706|>=14.16.27012|>=14.16.27033|>=14.28.29325|>=14.27.29016'] pillow=7.1.2 -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] libpng=1.6.37 -> vs2015_runtime[version='>=14.16.27012'] certifi -> python[version='>=3.9,<3.10.0a0'] -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] cmake -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] chardet=3.0.4 -> python[version='>=3.7,<3.8.0a0'] -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] wincertstore -> vs2015_runtime[version='>=14.16.27012,<15.0a0'] mkl-service=2.3.0 -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] pytz=2020.1 -> python -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] win_inet_pton -> python[version='>=3.7,<3.8.0a0'] -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] numpy=1.18.1 -> vs2015_runtime[version='>=14.16.27012,<15.0a0'] pyqt -> python[version='>=3.6,<3.7.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] icu -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] six=1.14.0 -> python -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] wincertstore -> python[version='>=3.9,<3.10.0a0'] -> vs2015_runtime[version='>=14.15.26706|>=14.16.27012|>=14.28.29325|>=14.16.27033|>=14.27.29016'] qt -> openssl[version='>=1.1.1i,<1.1.2a'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27012,<15.0a0|>=14.28.29325|>=14.16.27033|>=14.27.29016'] python=3.8.2 -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] numpy-base=1.18.1 -> mkl-service[version='>=2,<3.0a0'] -> vs2015_runtime[version='>=14.15.26706|>=14.16.27012|>=14.28.29325|>=14.16.27033|>=14.27.29016'] sip -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] pip=20.0.2 -> python -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] olefile=0.46 -> python -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] scipy=1.4.1 -> mkl-service[version='>=2,<3.0a0'] -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] mkl-service=2.3.0 -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] xz=5.2.5 -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] zlib=1.2.11 -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] openssl -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] cryptography=2.9.2 -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] kiwisolver=1.2.0 -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] cryptography=2.9.2 -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] matplotlib=3.1.3 -> pyqt -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] numpy=1.18.1 -> python[version='>=3.7,<3.8.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27012|>=14.28.29325|>=14.16.27033|>=14.27.29016'] cudatoolkit -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] pillow=7.1.2 -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] pycparser=2.20 -> python -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] tk=8.6.8 -> vc=14 -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27012|>=14.16.27033|>=14.28.29325|>=14.27.29016'] ninja=1.9.0 -> vs2015_runtime[version='>=14.16.27012,<15.0a0'] requests=2.23.0 -> python -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] libtiff=4.1.0 -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] libpng=1.6.37 -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016|>=14.16.27012,<15.0a0'] matplotlib-base=3.1.3 -> freetype[version='>=2.9.1,<3.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27012|>=14.28.29325|>=14.16.27033|>=14.27.29016'] pyqt -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] zstd=1.3.7 -> lz4 -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27012|>=14.16.27012,<15.0a0|>=14.28.29325|>=14.16.27033|>=14.27.29016'] numpy-base=1.18.1 -> vs2015_runtime[version='>=14.16.27012,<15.0a0'] python-dateutil=2.8.1 -> python -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] setuptools=46.2.0 -> python[version='>=3.7,<3.8.0a0'] -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] tornado=6.0.4 -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] libtiff=4.1.0 -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] xz=5.2.5 -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] tornado=6.0.4 -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] pysocks=1.7.1 -> python[version='>=3.8,<3.9.0a0'] -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] sqlite=3.31.1 -> vs2015_runtime[version='>=14.16.27012,<15.0a0'] cffi=1.14.0 -> python[version='>=3.8,<3.9.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27012|>=14.28.29325|>=14.16.27033|>=14.27.29016'] dlib -> numpy[version='>=1.16.5,<2.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27012,<15.0a0|>=14.28.29325|>=14.16.27033|>=14.27.29016'] blas=1.0 -> openblas -> vs2015_runtime[version='>=14.16.27012'] mkl_fft=1.0.15 -> vs2015_runtime[version='>=14.16.27012,<15.0a0'] pandas=1.0.3 -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] dlib -> vs2015_runtime[version='>=14.16.27012'] vc -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27012|>=14.16.27033|>=14.28.29325|>=14.27.29016'] freetype=2.9.1 -> libpng[version='>=1.6.35,<1.7.0a0'] -> vs2015_runtime[version='>=14.0.25123,<15.0a0|>=14.0.25420|>=14.15.26706|>=14.16.27012|>=14.16.27012,<15.0a0|>=14.28.29325|>=14.16.27033|>=14.27.29016'] qt -> vs2015_runtime[version='>=14.16.27012'] cudatoolkit -> vc[version='>=14.1,<15.0a0'] -> vs2015_runtime[version='>=14.15.26706|>=14.16.27033|>=14.28.29325|>=14.27.29016'] sip -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] pytorch=1.5.0 -> cffi -> vs2015_runtime[version='>=14.15.26706|>=14.16.27012|>=14.28.29325|>=14.16.27033|>=14.27.29016'] cmake -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] mkl_random=1.1.0 -> vs2015_runtime[version='>=14.16.27012,<15.0a0'] urllib3=1.25.8 -> cryptography[version='>=1.3.4'] -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] pyopenssl=19.1.0 -> cryptography[version='>=2.8'] -> vs2015_runtime[version='>=14.16.27012|>=14.16.27012,<15.0a0'] ninja=1.9.0 -> python[version='>=3.8,<3.9.0a0'] -> vs2015_runtime[version='>=14.15.26706|>=14.16.27012|>=14.28.29325|>=14.16.27033|>=14.27.29016']

Package numpy-base conflicts for: mkl_fft=1.0.15 -> numpy[version='>=1.14.6,<2.0a0'] -> numpy-base[version='1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.14.3|1.14.3|1.14.3|1.14.4|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.2|1.16.3|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5|1.16.5|1.16.6|1.16.6|1.16.6|1.16.6|1.16.6|1.17.2.|1.17.3.|1.17.4.|1.18.1.|1.18.5.*|1.19.1|1.19.1|1.19.1|1.19.2|1.17.0|1.17.0',build='py27h0bb1d87_7|py36h5c71026_8|py37h5c71026_8|py35h4a99626_8|py36h8128ebf_9|py27h2753ae9_9|py35h8128ebf_10|py36h8128ebf_11|py37h2a9b21d_11|py36hc3f5095_12|py38hc3f5095_12|py35h555522e_1|py36h555522e_1|py27h917549b_1|py35h5c71026_0|py36h5c71026_0|py36h5c71026_1|py37h5c71026_1|py36h5c71026_2|py27h0bb1d87_2|py27h0bb1d87_3|py27h0bb1d87_4|py36h5c71026_4|py36h8128ebf_4|py37h8128ebf_4|py35h8128ebf_4|py37hc3f5095_5|py27hb1d0314_5|py35h4a99626_0|py27hfef472a_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py27hb1d0314_0|py37hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py36hc3f5095_0|py36hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py39h2e04a8b_1|py38ha3acd2a_0|py37ha3acd2a_0|py38ha3acd2a_0|py36ha3acd2a_0|py39hbd0edd7_0|py37ha3acd2a_0|py36ha3acd2a_0|py38hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py37hc3f5095_1|py37hc3f5095_0|py36hc3f5095_1|py36hc3f5095_0|py27hb1d0314_0|py37hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_1|py27h2753ae9_0|py35h8128ebf_0|py27h2753ae9_0|py35h8128ebf_0|py37h4a99626_0|py36h4a99626_0|py36hc3f5095_5|py38hc3f5095_4|py27h2753ae9_4|py36hc3f5095_0|py37hc3f5095_0|py35h4a99626_4|py37h5c71026_4|py37h5c71026_3|py36h5c71026_3|py37h5c71026_2|py27h0bb1d87_1|py37h5c71026_0|py36h5c71026_0|py27h0bb1d87_0|py35h5c71026_0|py27h0bb1d87_0|py27hb1d0314_12|py37hc3f5095_12|py27hb1d0314_11|py36h2a9b21d_11|py37h8128ebf_11|py27h2753ae9_10|py37h8128ebf_10|py36h8128ebf_10|py35h8128ebf_9|py37h8128ebf_9|py27hfef472a_9|py37h4a99626_9|py36h4a99626_9|py35h4a99626_9|py27h0bb1d87_8|py37h5c71026_7|py36h5c71026_7'] pandas=1.0.3 -> numpy[version='>=1.14.6,<2.0a0'] -> numpy-base[version='1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.2|1.16.3|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5|1.16.5|1.16.6|1.16.6|1.16.6|1.16.6|1.16.6|1.17.2.|1.17.3.|1.17.4.|1.18.1.|1.18.5.*|1.19.1|1.19.1|1.19.1|1.19.2|1.17.0|1.17.0',build='py36h8128ebf_4|py37h8128ebf_4|py35h8128ebf_4|py37hc3f5095_5|py27hb1d0314_5|py35h4a99626_0|py27hfef472a_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py27hb1d0314_0|py37hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py36hc3f5095_0|py36hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py39h2e04a8b_1|py38ha3acd2a_0|py37ha3acd2a_0|py38ha3acd2a_0|py36ha3acd2a_0|py39hbd0edd7_0|py37ha3acd2a_0|py36ha3acd2a_0|py38hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py37hc3f5095_1|py37hc3f5095_0|py36hc3f5095_1|py36hc3f5095_0|py27hb1d0314_0|py37hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_1|py27h2753ae9_0|py35h8128ebf_0|py27h2753ae9_0|py35h8128ebf_0|py37h4a99626_0|py36h4a99626_0|py36hc3f5095_5|py38hc3f5095_4|py27h2753ae9_4|py36hc3f5095_0|py37hc3f5095_0'] matplotlib-base=3.1.3 -> numpy[version='>=1.14.6,<2.0a0'] -> numpy-base[version='1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.2|1.16.3|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5|1.16.5|1.16.6|1.16.6|1.16.6|1.16.6|1.16.6|1.17.2.|1.17.3.|1.17.4.|1.18.1.|1.18.5.*|1.19.1|1.19.1|1.19.1|1.19.2|1.17.0|1.17.0',build='py36h8128ebf_4|py37h8128ebf_4|py35h8128ebf_4|py37hc3f5095_5|py27hb1d0314_5|py35h4a99626_0|py27hfef472a_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py27hb1d0314_0|py37hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py36hc3f5095_0|py36hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py39h2e04a8b_1|py38ha3acd2a_0|py37ha3acd2a_0|py38ha3acd2a_0|py36ha3acd2a_0|py39hbd0edd7_0|py37ha3acd2a_0|py36ha3acd2a_0|py38hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py37hc3f5095_1|py37hc3f5095_0|py36hc3f5095_1|py36hc3f5095_0|py27hb1d0314_0|py37hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_1|py27h2753ae9_0|py35h8128ebf_0|py27h2753ae9_0|py35h8128ebf_0|py37h4a99626_0|py36h4a99626_0|py36hc3f5095_5|py38hc3f5095_4|py27h2753ae9_4|py36hc3f5095_0|py37hc3f5095_0'] pytorch=1.5.0 -> numpy[version='>=1.11.3,<2.0a0'] -> numpy-base[version='1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.14.3|1.14.3|1.14.3|1.14.4|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.2|1.16.3|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5|1.16.5|1.16.6|1.16.6|1.16.6|1.16.6|1.16.6|1.17.2.|1.17.3.|1.17.4.|1.18.1.|1.18.5.*|1.19.1|1.19.1|1.19.1|1.19.2|1.17.0|1.17.0',build='py27h0bb1d87_7|py27h0bb1d87_8|py35h4a99626_8|py37h4a99626_9|py35h8128ebf_9|py27h2753ae9_9|py35h8128ebf_10|py27h2753ae9_10|py36h8128ebf_11|py37h2a9b21d_11|py37hc3f5095_12|py38hc3f5095_12|py36h555522e_1|py27h917549b_1|py36h5c71026_1|py37h5c71026_1|py36h5c71026_2|py27h0bb1d87_4|py36h5c71026_4|py35h4a99626_4|py36h8128ebf_4|py37h8128ebf_4|py35h8128ebf_4|py37hc3f5095_5|py27hb1d0314_5|py35h4a99626_0|py27hfef472a_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py27hb1d0314_0|py37hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py36hc3f5095_0|py36hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py39h2e04a8b_1|py38ha3acd2a_0|py37ha3acd2a_0|py38ha3acd2a_0|py36ha3acd2a_0|py39hbd0edd7_0|py37ha3acd2a_0|py36ha3acd2a_0|py38hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py37hc3f5095_1|py37hc3f5095_0|py36hc3f5095_1|py36hc3f5095_0|py27hb1d0314_0|py37hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_1|py27h2753ae9_0|py35h8128ebf_0|py27h2753ae9_0|py35h8128ebf_0|py37h4a99626_0|py36h4a99626_0|py36hc3f5095_5|py38hc3f5095_4|py27h2753ae9_4|py37h5c71026_4|py37h5c71026_3|py36h5c71026_3|py27h0bb1d87_3|py27h0bb1d87_2|py37h5c71026_2|py27h0bb1d87_1|py37h5c71026_0|py36h5c71026_0|py27h0bb1d87_0|py35h5c71026_0|py27h0bb1d87_0|py36h5c71026_0|py35h5c71026_0|py35h555522e_1|py36hc3f5095_12|py27hb1d0314_12|py27hb1d0314_11|py36h2a9b21d_11|py37h8128ebf_11|py37h8128ebf_10|py36h8128ebf_10|py36h8128ebf_9|py37h8128ebf_9|py27hfef472a_9|py36h4a99626_9|py35h4a99626_9|py37h5c71026_8|py36h5c71026_8|py37h5c71026_7|py36h5c71026_7|py36hc3f5095_0|py37hc3f5095_0'] mkl_random=1.1.0 -> numpy[version='>=1.14.6,<2.0a0'] -> numpy-base[version='1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.14.3|1.14.3|1.14.3|1.14.4|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.2|1.16.3|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5|1.16.5|1.16.6|1.16.6|1.16.6|1.16.6|1.16.6|1.17.2.|1.17.3.|1.17.4.|1.18.1.|1.18.5.*|1.19.1|1.19.1|1.19.1|1.19.2|1.17.0|1.17.0',build='py27h0bb1d87_7|py36h5c71026_8|py37h5c71026_8|py35h4a99626_8|py36h8128ebf_9|py27h2753ae9_9|py35h8128ebf_10|py36h8128ebf_11|py37h2a9b21d_11|py36hc3f5095_12|py38hc3f5095_12|py35h555522e_1|py36h555522e_1|py27h917549b_1|py35h5c71026_0|py36h5c71026_0|py36h5c71026_1|py37h5c71026_1|py36h5c71026_2|py27h0bb1d87_2|py27h0bb1d87_3|py27h0bb1d87_4|py36h5c71026_4|py36h8128ebf_4|py37h8128ebf_4|py35h8128ebf_4|py37hc3f5095_5|py27hb1d0314_5|py35h4a99626_0|py27hfef472a_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py27hb1d0314_0|py37hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py36hc3f5095_0|py36hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py39h2e04a8b_1|py38ha3acd2a_0|py37ha3acd2a_0|py38ha3acd2a_0|py36ha3acd2a_0|py39hbd0edd7_0|py37ha3acd2a_0|py36ha3acd2a_0|py38hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py37hc3f5095_1|py37hc3f5095_0|py36hc3f5095_1|py36hc3f5095_0|py27hb1d0314_0|py37hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_1|py27h2753ae9_0|py35h8128ebf_0|py27h2753ae9_0|py35h8128ebf_0|py37h4a99626_0|py36h4a99626_0|py36hc3f5095_5|py38hc3f5095_4|py27h2753ae9_4|py36hc3f5095_0|py37hc3f5095_0|py35h4a99626_4|py37h5c71026_4|py37h5c71026_3|py36h5c71026_3|py37h5c71026_2|py27h0bb1d87_1|py37h5c71026_0|py36h5c71026_0|py27h0bb1d87_0|py35h5c71026_0|py27h0bb1d87_0|py27hb1d0314_12|py37hc3f5095_12|py27hb1d0314_11|py36h2a9b21d_11|py37h8128ebf_11|py27h2753ae9_10|py37h8128ebf_10|py36h8128ebf_10|py35h8128ebf_9|py37h8128ebf_9|py27hfef472a_9|py37h4a99626_9|py36h4a99626_9|py35h4a99626_9|py27h0bb1d87_8|py37h5c71026_7|py36h5c71026_7'] numpy=1.18.1 -> numpy-base=1.18.1 scipy=1.4.1 -> numpy[version='>=1.14.6,<2.0a0'] -> numpy-base[version='1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.2|1.16.3|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5|1.16.5|1.16.6|1.16.6|1.16.6|1.16.6|1.16.6|1.17.2.|1.17.3.|1.17.4.|1.18.1.|1.18.5.*|1.19.1|1.19.1|1.19.1|1.19.2|1.17.0|1.17.0',build='py36h8128ebf_4|py37h8128ebf_4|py35h8128ebf_4|py37hc3f5095_5|py27hb1d0314_5|py35h4a99626_0|py27hfef472a_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py27hb1d0314_0|py37hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py36hc3f5095_0|py36hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py39h2e04a8b_1|py38ha3acd2a_0|py37ha3acd2a_0|py38ha3acd2a_0|py36ha3acd2a_0|py39hbd0edd7_0|py37ha3acd2a_0|py36ha3acd2a_0|py38hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py37hc3f5095_1|py37hc3f5095_0|py36hc3f5095_1|py36hc3f5095_0|py27hb1d0314_0|py37hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_1|py27h2753ae9_0|py35h8128ebf_0|py27h2753ae9_0|py35h8128ebf_0|py37h4a99626_0|py36h4a99626_0|py36hc3f5095_5|py38hc3f5095_4|py27h2753ae9_4|py36hc3f5095_0|py37hc3f5095_0'] torchvision=0.6.0 -> numpy[version='>=1.11'] -> numpy-base[version='1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.11.3|1.14.3|1.14.3|1.14.3|1.14.4|1.14.4|1.14.4|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.5|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.14.6|1.15.0|1.15.0|1.15.0|1.15.0|1.15.1|1.15.1|1.15.1|1.15.1|1.15.2|1.15.2|1.15.2|1.15.2|1.15.2|1.15.3|1.15.3|1.15.3|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.15.4|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.0|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.1|1.16.2|1.16.2|1.16.2|1.16.3|1.16.3|1.16.3|1.16.4|1.16.4|1.16.5|1.16.5|1.16.5|1.16.6|1.16.6|1.16.6|1.16.6|1.16.6|1.17.2.|1.17.3.|1.17.4.|1.18.1.|1.18.5.*|1.19.1|1.19.1|1.19.1|1.19.2|1.17.0|1.17.0',build='py27h0bb1d87_7|py27h0bb1d87_8|py35h4a99626_8|py37h4a99626_9|py35h8128ebf_9|py27h2753ae9_9|py35h8128ebf_10|py27h2753ae9_10|py36h8128ebf_11|py37h2a9b21d_11|py37hc3f5095_12|py38hc3f5095_12|py36h555522e_1|py27h917549b_1|py36h5c71026_1|py37h5c71026_1|py36h5c71026_2|py27h0bb1d87_4|py36h5c71026_4|py35h4a99626_4|py36h8128ebf_4|py37h8128ebf_4|py35h8128ebf_4|py37hc3f5095_5|py27hb1d0314_5|py35h4a99626_0|py27hfef472a_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py37h8128ebf_0|py36h8128ebf_0|py36h8128ebf_0|py27hb1d0314_0|py37hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py36hc3f5095_0|py36hc3f5095_1|py27hb1d0314_1|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py27hb1d0314_0|py39h2e04a8b_1|py38ha3acd2a_0|py37ha3acd2a_0|py38ha3acd2a_0|py36ha3acd2a_0|py39hbd0edd7_0|py37ha3acd2a_0|py36ha3acd2a_0|py38hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py37hc3f5095_0|py37hc3f5095_1|py37hc3f5095_0|py36hc3f5095_1|py36hc3f5095_0|py27hb1d0314_0|py37hc3f5095_0|py37hc3f5095_0|py36hc3f5095_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_0|py37h8128ebf_0|py27h2753ae9_1|py27h2753ae9_0|py35h8128ebf_0|py27h2753ae9_0|py35h8128ebf_0|py37h4a99626_0|py36h4a99626_0|py36hc3f5095_5|py38hc3f5095_4|py27h2753ae9_4|py37h5c71026_4|py37h5c71026_3|py36h5c71026_3|py27h0bb1d87_3|py27h0bb1d87_2|py37h5c71026_2|py27h0bb1d87_1|py37h5c71026_0|py36h5c71026_0|py27h0bb1d87_0|py35h5c71026_0|py27h0bb1d87_0|py36h5c71026_0|py35h5c71026_0|py35h555522e_1|py36hc3f5095_12|py27hb1d0314_12|py27hb1d0314_11|py36h2a9b21d_11|py37h8128ebf_11|py37h8128ebf_10|py36h8128ebf_10|py36h8128ebf_9|py37h8128ebf_9|py27hfef472a_9|py36h4a99626_9|py35h4a99626_9|py37h5c71026_8|py36h5c71026_8|py37h5c71026_7|py36h5c71026_7|py36hc3f5095_0|py37hc3f5095_0'] numpy=1.18.1 -> mkl_fft -> numpy-base[version='>=1.0.14,<2.0a0|>=1.0.6,<2.0a0|>=1.0.2,<2.0a0|>=1.0.4,<2.0a0']

Package openssl conflicts for: mkl-service=2.3.0 -> python[version='>=3.8,<3.9.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] cycler=0.10.0 -> python -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] scipy=1.4.1 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1i,<1.1.2a'] olefile=0.46 -> python -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] idna=2.9 -> python -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] qt -> openssl[version='1.0.|1.1.|>=1.1.1b,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1a,<1.1.2a|>=1.0.2p,<1.0.3a|>=1.0.2o,<1.0.3a'] kiwisolver=1.2.0 -> python[version='>=3.9,<3.10.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] chardet=3.0.4 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1i,<1.1.2a'] pyparsing=2.4.7 -> python -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] pyqt -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='1.0.|1.1.|>=1.1.1a,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.0.2p,<1.0.3a|>=1.0.2o,<1.0.3a'] pytz=2020.1 -> python -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] torchvision=0.6.0 -> python[version='>=3.8,<3.9.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a'] wheel=0.34.2 -> python -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] pytorch=1.5.0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1i,<1.1.2a'] wincertstore -> python[version='>=3.9,<3.10.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] cffi=1.14.0 -> python[version='>=3.8,<3.9.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] setuptools=46.2.0 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1i,<1.1.2a'] powershell_shortcut -> python -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] sip -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1i,<1.1.2a'] pandas=1.0.3 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1i,<1.1.2a'] urllib3=1.25.8 -> cryptography[version='>=1.3.4'] -> openssl[version='1.0.*|>=1.0.2o,<1.0.3a|>=1.0.2p,<1.0.3a|>=1.1.1a,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.0.2n,<1.0.3a|>=1.0.2m,<1.0.3a|>=1.1.1f,<1.1.2a|>=1.1.1e,<1.1.2a'] certifi -> python[version='>=3.9,<3.10.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] matplotlib-base=3.1.3 -> python[version='>=3.8,<3.9.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] numpy=1.18.1 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1i,<1.1.2a'] pyopenssl=19.1.0 -> cryptography[version='>=2.8'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] six=1.14.0 -> python -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] numpy-base=1.18.1 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1i,<1.1.2a'] pillow=7.1.2 -> python[version='>=3.8,<3.9.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] cryptography=2.9.2 -> python[version='>=3.8,<3.9.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] pip=20.0.2 -> python -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] cryptography=2.9.2 -> openssl[version='>=1.1.1g,<1.1.2a|>=1.1.1i,<1.1.2a'] ninja=1.9.0 -> python[version='>=3.8,<3.9.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] requests=2.23.0 -> python -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] pycparser=2.20 -> python -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] python=3.8.2 -> openssl[version='>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a'] python-dateutil=2.8.1 -> python -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] win_inet_pton -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1i,<1.1.2a'] mkl_fft=1.0.15 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1i,<1.1.2a'] matplotlib=3.1.3 -> python[version='>=3.7,<3.8.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a|>=1.1.1i,<1.1.2a'] mkl_random=1.1.0 -> python[version='>=3.8,<3.9.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] tornado=6.0.4 -> python[version='>=3.8,<3.9.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a'] pysocks=1.7.1 -> python[version='>=3.8,<3.9.0a0'] -> openssl[version='>=1.1.1a,<1.1.2a|>=1.1.1d,<1.1.2a|>=1.1.1e,<1.1.2a|>=1.1.1f,<1.1.2a|>=1.1.1g,<1.1.2a|>=1.1.1h,<1.1.2a|>=1.1.1i,<1.1.2a|>=1.1.1c,<1.1.2a|>=1.1.1b,<1.1.2a']

Package vc conflicts for: libtiff=4.1.0 -> zlib[version='>=1.2.11,<1.3.0a0'] -> vc[version='14.|9.|>=14,<15.0a0|>=9,<10.0a0'] qt -> zlib[version='>=1.2.11,<1.3.0a0'] -> vc[version='10.*|14|9|>=14,<15.0a0|>=9,<10.0a0'] cryptography=2.9.2 -> vc[version='>=14.1,<15.0a0'] matplotlib-base=3.1.3 -> vc[version='>=14,<15.0a0|>=14.1,<15.0a0'] cffi=1.14.0 -> python[version='>=2.7,<2.8.0a0'] -> vc[version='14.*|>=9,<10.0a0'] tornado=6.0.4 -> python[version='>=3.6,<3.7.0a0'] -> vc=14 dlib -> vc[version='>=14,<15.0a0|>=14.1,<15.0a0'] requests=2.23.0 -> python -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] pytorch=1.5.0 -> vc[version='>=14.1,<15.0a0'] qt -> vc[version='14.|>=14.1,<15.0a0|9.'] win_inet_pton -> python[version='>=3.7,<3.8.0a0'] -> vc[version='14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.'] python-dateutil=2.8.1 -> python -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] zlib=1.2.11 -> vc[version='14.|9.|>=14,<15.0a0|>=14.1,<15.0a0|>=9,<10.0a0'] zstd=1.3.7 -> lz4 -> vc=14 freetype=2.9.1 -> libpng[version='>=1.6.35,<1.7.0a0'] -> vc[version='14|9|>=14.1,<15.0a0|>=9,<10.0a0'] blas=1.0 -> openblas -> vc[version='14|>=14,<15.0a0|>=14.1,<15.0a0'] setuptools=46.2.0 -> python[version='>=3.7,<3.8.0a0'] -> vc[version='14.*|>=14.1,<15.0a0|>=14,<15.0a0'] dlib -> libpng[version='>=1.6.37,<1.7.0a0'] -> vc[version='10.|10|14|14.|9.*|9|>=9,<10.0a0'] pillow=7.1.2 -> freetype[version='>=2.9.1,<3.0a0'] -> vc[version='14|14.|9.|>=14,<15.0a0|>=9,<10.0a0|9'] wincertstore -> python[version='>=3.6,<3.7.0a0'] -> vc[version='10.|14.|>=14,<15.0a0|>=9,<10.0a0|9.*'] ninja=1.9.0 -> python[version='>=3.7,<3.8.0a0'] -> vc[version='14.*|>=14,<15.0a0|>=9,<10.0a0'] mkl_fft=1.0.15 -> vc[version='9.*|>=14,<15.0a0|>=14.1,<15.0a0'] mkl_random=1.1.0 -> vc[version='>=14,<15.0a0|>=14.1,<15.0a0'] openssl -> vc[version='10.|14.|9.*|>=14,<15.0a0|>=14.1,<15.0a0'] cycler=0.10.0 -> python -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] pycparser=2.20 -> python -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] pyopenssl=19.1.0 -> cryptography[version='>=2.8'] -> vc[version='10.|14.|9.*|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0'] wincertstore -> vc[version='>=14.1,<15.0a0'] chardet=3.0.4 -> python[version='>=3.7,<3.8.0a0'] -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] python=3.8.2 -> vc[version='>=14.1,<15.0a0'] libtiff=4.1.0 -> vc[version='>=14.1,<15.0a0'] pyparsing=2.4.7 -> python -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] cryptography=2.9.2 -> cffi -> vc[version='14.|9.|>=14,<15.0a0'] ninja=1.9.0 -> vc[version='9.*|>=14.1,<15.0a0'] sqlite=3.31.1 -> vc[version='>=14.1,<15.0a0'] pytz=2020.1 -> python -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] numpy=1.18.1 -> vc[version='>=14,<15.0a0|>=14.1,<15.0a0'] pyqt -> python[version='>=2.7,<2.8.0a0'] -> vc[version='10.*|>=9,<10.0a0'] xz=5.2.5 -> vc[version='>=14.1,<15.0a0'] scipy=1.4.1 -> mkl-service[version='>=2,<3.0a0'] -> vc[version='14.|9.|>=14,<15.0a0|>=14.1,<15.0a0'] tk=8.6.8 -> vc[version='14|14.|9.|9'] kiwisolver=1.2.0 -> python[version='>=3.6,<3.7.0a0'] -> vc=14 sip -> vc[version='14.|9.|>=14.1,<15.0a0|>=14,<15.0a0'] mkl_fft=1.0.15 -> mkl-service[version='>=2,<3.0a0'] -> vc[version='14.*|>=9,<10.0a0'] mkl-service=2.3.0 -> python[version='>=3.6,<3.7.0a0'] -> vc[version='14.*|>=9,<10.0a0'] python=3.8.2 -> sqlite[version='>=3.30.1,<4.0a0'] -> vc[version='9.*|>=14,<15.0a0'] matplotlib-base=3.1.3 -> freetype[version='>=2.9.1,<3.0a0'] -> vc[version='14.|9.|>=9,<10.0a0'] olefile=0.46 -> python -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] cffi=1.14.0 -> vc[version='9.*|>=14,<15.0a0|>=14.1,<15.0a0'] powershell_shortcut -> python -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] certifi -> python[version='>=3.9,<3.10.0a0'] -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] idna=2.9 -> python -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] mkl_random=1.1.0 -> mkl-service[version='>=2,<3.0a0'] -> vc[version='14.|9.'] pandas=1.0.3 -> numpy[version='>=1.14.6,<2.0a0'] -> vc[version='14.|9.'] pillow=7.1.2 -> vc[version='>=14.1,<15.0a0'] numpy-base=1.18.1 -> mkl-service[version='>=2,<3.0a0'] -> vc[version='14.|9.|>=14,<15.0a0'] pandas=1.0.3 -> vc[version='>=14,<15.0a0|>=14.1,<15.0a0'] libpng=1.6.37 -> zlib[version='>=1.2.11,<1.3.0a0'] -> vc[version='>=14,<15.0a0|>=9,<10.0a0'] cudatoolkit -> vc[version='>=14.1,<15.0a0'] sqlite=3.31.1 -> zlib[version='>=1.2.11,<1.3.0a0'] -> vc[version='14.|9.|>=14,<15.0a0|>=9,<10.0a0'] kiwisolver=1.2.0 -> vc[version='>=14,<15.0a0|>=14.1,<15.0a0'] pytorch=1.5.0 -> cffi -> vc[version='14|14.|9.|>=14,<15.0a0'] wheel=0.34.2 -> python -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] freetype=2.9.1 -> vc[version='14.|9.|>=14,<15.0a0'] pyqt -> vc[version='14.|9.|>=14,<15.0a0|>=14.1,<15.0a0'] libpng=1.6.37 -> vc[version='14.|>=14.1,<15.0a0|9.'] numpy-base=1.18.1 -> vc[version='>=14.1,<15.0a0'] zstd=1.3.7 -> vc[version='9.*|>=14,<15.0a0|>=9,<10.0a0|>=14.1,<15.0a0'] torchvision=0.6.0 -> cudatoolkit[version='>=10.2,<10.3'] -> vc[version='14.|9.|>=14,<15.0a0|>=14.1,<15.0a0'] cmake -> vc[version='14.*|>=14.1,<15.0a0'] icu -> vc[version='10.|14.|14|9|>=14,<15.0a0|>=14.1,<15.0a0|9.*'] cmake -> bzip2=1.0 -> vc[version='10.|14|9|9.|>=14,<15.0a0|>=9,<10.0a0'] six=1.14.0 -> python -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] urllib3=1.25.8 -> cryptography[version='>=1.3.4'] -> vc[version='14.|9.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0'] sip -> python[version='>=2.7,<2.8.0a0'] -> vc[version='10.*|>=9,<10.0a0'] pysocks=1.7.1 -> python[version='>=3.8,<3.9.0a0'] -> vc[version='14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.'] tornado=6.0.4 -> vc[version='>=14,<15.0a0|>=14.1,<15.0a0'] pip=20.0.2 -> python -> vc[version='10.|14.|>=14.1,<15.0a0|>=14,<15.0a0|>=9,<10.0a0|9.*'] libcxx -> vc[version='>=14,<15.0a0'] mkl-service=2.3.0 -> vc[version='9.*|>=14,<15.0a0|>=14.1,<15.0a0'] matplotlib=3.1.3 -> matplotlib-base==3.1.3=py37h2981e6d_0 -> vc[version='14.|9.|>=14,<15.0a0|>=14.1,<15.0a0'] numpy=1.18.1 -> python[version='>=3.7,<3.8.0a0'] -> vc[version='14.|9.']

Package tzdata conflicts for: kiwisolver=1.2.0 -> python[version='>=3.9,<3.10.0a0'] -> tzdata pyopenssl=19.1.0 -> python -> tzdata cycler=0.10.0 -> python -> tzdata pyqt -> python[version='>=3.9,<3.10.0a0'] -> tzdata requests=2.23.0 -> python -> tzdata mkl-service=2.3.0 -> python[version='>=3.9,<3.10.0a0'] -> tzdata pycparser=2.20 -> python -> tzdata dlib -> python[version='>=3.9,<3.10.0a0'] -> tzdata pyparsing=2.4.7 -> python -> tzdata python-dateutil=2.8.1 -> python -> tzdata sip -> python[version='>=3.9,<3.10.0a0'] -> tzdata pysocks=1.7.1 -> python[version='>=3.9,<3.10.0a0'] -> tzdata powershell_shortcut -> python -> tzdata idna=2.9 -> python -> tzdata olefile=0.46 -> python -> tzdata tornado=6.0.4 -> python[version='>=3.9,<3.10.0a0'] -> tzdata wincertstore -> python[version='>=3.9,<3.10.0a0'] -> tzdata pytz=2020.1 -> python -> tzdata wheel=0.34.2 -> python -> tzdata six=1.14.0 -> python -> tzdata pip=20.0.2 -> python -> tzdata cryptography=2.9.2 -> python[version='>=3.9,<3.10.0a0'] -> tzdata chardet=3.0.4 -> python[version='>=3.9,<3.10.0a0'] -> tzdata win_inet_pton -> python[version='>=3.9,<3.10.0a0'] -> tzdata certifi -> python[version='>=3.9,<3.10.0a0'] -> tzdata

Package six conflicts for: pyopenssl=19.1.0 -> cryptography[version='>=2.8'] -> six[version='>=1.4.1'] numpy-base=1.18.1 -> mkl-service[version='>=2,<3.0a0'] -> six scipy=1.4.1 -> mkl-service[version='>=2,<3.0a0'] -> six matplotlib-base=3.1.3 -> cycler[version='>=0.10'] -> six[version='>=1.5'] mkl_fft=1.0.15 -> mkl-service[version='>=2,<3.0a0'] -> six pyopenssl=19.1.0 -> six[version='>=1.5.2'] urllib3=1.25.8 -> cryptography[version='>=1.3.4'] -> six[version='>=1.4.1|>=1.5.2'] cryptography=2.9.2 -> six mkl_random=1.1.0 -> mkl-service[version='>=2,<3.0a0'] -> six mkl-service=2.3.0 -> six python-dateutil=2.8.1 -> six[version='>=1.5'] cycler=0.10.0 -> six pandas=1.0.3 -> python-dateutil[version='>=2.6.1'] -> six[version='>=1.5'] pytorch=1.5.0 -> mkl-service[version='>=2,<3.0a0'] -> six numpy=1.18.1 -> mkl-service[version='>=2,<3.0a0'] -> six

Package vs2010_runtime conflicts for: requests=2.23.0 -> python -> vs2010_runtime python-dateutil=2.8.1 -> python -> vs2010_runtime dlib -> python=3.4 -> vs2010_runtime olefile=0.46 -> python -> vs2010_runtime pyparsing=2.4.7 -> python -> vs2010_runtime sip -> python=3.4 -> vs2010_runtime wincertstore -> python=3.4 -> vs2010_runtime pytz=2020.1 -> python -> vs2010_runtime wheel=0.34.2 -> python -> vs2010_runtime pyopenssl=19.1.0 -> python -> vs2010_runtime chardet=3.0.4 -> python -> vs2010_runtime idna=2.9 -> python -> vs2010_runtime cycler=0.10.0 -> python -> vs2010_runtime powershell_shortcut -> python -> vs2010_runtime pip=20.0.2 -> python -> vs2010_runtime six=1.14.0 -> python -> vs2010_runtime pyqt -> python=3.4 -> vs2010_runtime certifi -> python=3.4 -> vs2010_runtime pycparser=2.20 -> python -> vs2010_runtime

Package libflang conflicts for: mkl_random=1.1.0 -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] blas=1.0 -> openblas -> libflang[version='>=5.0.0'] dlib -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] pytorch=1.5.0 -> numpy[version='>=1.11.3,<2.0a0'] -> libflang[version='>=5.0.0'] pandas=1.0.3 -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] torchvision=0.6.0 -> numpy[version='>=1.11'] -> libflang[version='>=5.0.0'] matplotlib-base=3.1.3 -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] mkl_fft=1.0.15 -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0'] scipy=1.4.1 -> numpy[version='>=1.14.6,<2.0a0'] -> libflang[version='>=5.0.0']

Package zstd conflicts for: libtiff=4.1.0 -> zstd[version='>=1.3.7,<1.3.8.0a0|>=1.4.4,<1.5.0a0|>=1.4|>=1.4.3,<1.5.0.0a0|>=1.4.4,<1.5.0.0a0|>=1.4.5,<1.5.0a0'] cmake -> zstd[version='>=1.4.5,<1.4.6.0a0'] pillow=7.1.2 -> libtiff[version='>=4.1.0,<5.0a0'] -> zstd[version='>=1.3.3,<1.3.4.0a0|>=1.3.7,<1.3.8.0a0|>=1.4.4,<1.5.0a0|>=1.4|>=1.4.3,<1.5.0.0a0|>=1.4.4,<1.5.0.0a0|>=1.4.5,<1.5.0a0|>=1.4.0,<1.5.0.0a0']

Package sqlite conflicts for: numpy-base=1.18.1 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.0,<4.0a0'] certifi -> python[version='>=3.9,<3.10.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.29.0,<4.0a0|>=3.30.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.28.0,<4.0a0|>=3.27.2,<4.0a0'] kiwisolver=1.2.0 -> python[version='>=3.9,<3.10.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.29.0,<4.0a0|>=3.30.1,<4.0a0|>=3.31.1,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.32.3,<4.0a0|>=3.28.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.0,<4.0a0'] urllib3=1.25.8 -> python[version='>=2.7,<2.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.1,<4.0a0|>=3.34.0,<4.0a0|>=3.33.0,<4.0a0|>=3.32.3,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.28.0,<4.0a0|>=3.29.0,<4.0a0'] pyparsing=2.4.7 -> python -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] win_inet_pton -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.0,<4.0a0'] pytz=2020.1 -> python -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] wheel=0.34.2 -> python -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] matplotlib=3.1.3 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.0,<4.0a0'] cffi=1.14.0 -> python[version='>=2.7,<2.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.1,<4.0a0|>=3.34.0,<4.0a0|>=3.33.0,<4.0a0|>=3.32.3,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.28.0,<4.0a0|>=3.29.0,<4.0a0'] mkl-service=2.3.0 -> python[version='>=3.8,<3.9.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.29.0,<4.0a0|>=3.30.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.28.0,<4.0a0|>=3.27.2,<4.0a0'] cycler=0.10.0 -> python -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] olefile=0.46 -> python -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] scipy=1.4.1 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.0,<4.0a0'] powershell_shortcut -> python -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] idna=2.9 -> python -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] chardet=3.0.4 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.0,<4.0a0'] qt -> sqlite[version='>=3.20.1,<4.0a0|>=3.22.0,<4.0a0|>=3.23.1,<4.0a0|>=3.24.0,<4.0a0|>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.29.0,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0'] mkl_fft=1.0.15 -> python[version='>=2.7,<2.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.1,<4.0a0|>=3.34.0,<4.0a0|>=3.33.0,<4.0a0|>=3.32.3,<4.0a0|>=3.28.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.30.0,<4.0a0'] wincertstore -> python[version='>=3.9,<3.10.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.29.0,<4.0a0|>=3.30.1,<4.0a0|>=3.31.1,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.32.3,<4.0a0|>=3.30.0,<4.0a0|>=3.28.0,<4.0a0|>=3.27.2,<4.0a0'] cryptography=2.9.2 -> python[version='>=3.8,<3.9.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] torchvision=0.6.0 -> python[version='>=3.8,<3.9.0a0'] -> sqlite[version='>=3.30.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0'] six=1.14.0 -> python -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] matplotlib-base=3.1.3 -> python[version='>=3.8,<3.9.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] pyqt -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.20.1,<4.0a0|>=3.22.0,<4.0a0|>=3.23.1,<4.0a0|>=3.24.0,<4.0a0|>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.0,<4.0a0'] ninja=1.9.0 -> python[version='>=3.8,<3.9.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] sip -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.0,<4.0a0'] pip=20.0.2 -> python -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] pycparser=2.20 -> python -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] requests=2.23.0 -> python -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] python=3.8.2 -> sqlite[version='>=3.30.1,<4.0a0|>=3.31.1,<4.0a0'] mkl_random=1.1.0 -> python[version='>=3.8,<3.9.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] tornado=6.0.4 -> python[version='>=3.8,<3.9.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.29.0,<4.0a0|>=3.30.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.28.0,<4.0a0|>=3.27.2,<4.0a0'] python-dateutil=2.8.1 -> python -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] pytorch=1.5.0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.0,<4.0a0'] numpy=1.18.1 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.0,<4.0a0'] pysocks=1.7.1 -> python[version='>=3.8,<3.9.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.29.0,<4.0a0|>=3.30.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.28.0,<4.0a0|>=3.27.2,<4.0a0'] pyopenssl=19.1.0 -> python -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.30.0,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] pillow=7.1.2 -> python[version='>=3.8,<3.9.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0'] pandas=1.0.3 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.0,<4.0a0'] setuptools=46.2.0 -> python[version='>=3.7,<3.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0|>=3.26.0,<4.0a0|>=3.28.0,<4.0a0|>=3.30.1,<4.0a0|>=3.32.3,<4.0a0|>=3.33.0,<4.0a0|>=3.34.0,<4.0a0|>=3.31.1,<4.0a0|>=3.29.0,<4.0a0|>=3.27.2,<4.0a0|>=3.30.0,<4.0a0']

Package blas conflicts for: scipy=1.4.1 -> blas==1.0=mkl pytorch=1.5.0 -> numpy[version='>=1.11.3,<2.0a0'] -> blas==1.1=openblas numpy=1.18.1 -> blas==1.0=mkl pytorch=1.5.0 -> blas[version='*|1.0',build=mkl] mkl_fft=1.0.15 -> numpy[version='>=1.14.6,<2.0a0'] -> blas[version='*|1.1',build='openblas|mkl'] numpy-base=1.18.1 -> blas==1.0=mkl torchvision=0.6.0 -> numpy[version='>=1.11'] -> blas[version='*|1.0|1.1',build='openblas|mkl|mkl'] pandas=1.0.3 -> numpy[version='>=1.14.6,<2.0a0'] -> blas[version='1.0|1.1',build='openblas|mkl'] mkl_random=1.1.0 -> mkl-service[version='>=2,<3.0a0'] -> blas[version='1.0|1.1',build='openblas|mkl'] matplotlib-base=3.1.3 -> numpy[version='>=1.14.6,<2.0a0'] -> blas[version='1.0|1.1',build='openblas|mkl'] scipy=1.4.1 -> numpy[version='>=1.14.6,<2.0a0'] -> blas==1.1=openblas numpy=1.18.1 -> mkl_fft -> blas=[build=mkl] mkl_random=1.1.0 -> blas=[build=mkl] mkl_fft=1.0.15 -> blas==1.0=mkl

Package olefile conflicts for: torchvision=0.6.0 -> pillow[version='>=4.1.1'] -> olefile pillow=7.1.2 -> olefile

Package mkl_fft conflicts for: matplotlib-base=3.1.3 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl_fft[version='>=1.0.14,<2.0a0|>=1.0.4|>=1.0.6,<2.0a0'] torchvision=0.6.0 -> numpy[version='>=1.11'] -> mkl_fft[version='>=1.0.14,<2.0a0|>=1.0.4|>=1.0.6,<2.0a0'] scipy=1.4.1 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl_fft[version='>=1.0.14,<2.0a0|>=1.0.4|>=1.0.6,<2.0a0'] mkl_random=1.1.0 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl_fft[version='>=1.0.14,<2.0a0|>=1.0.4|>=1.0.6,<2.0a0'] pytorch=1.5.0 -> numpy[version='>=1.11.3,<2.0a0'] -> mkl_fft[version='>=1.0.14,<2.0a0|>=1.0.4|>=1.0.6,<2.0a0'] numpy=1.18.1 -> mkl_fft pandas=1.0.3 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl_fft[version='>=1.0.14,<2.0a0|>=1.0.4|>=1.0.6,<2.0a0']

Package idna conflicts for: urllib3=1.25.8 -> idna[version='>=2.0.0'] urllib3=1.25.8 -> cryptography[version='>=1.3.4'] -> idna[version='>=2.1'] cryptography=2.9.2 -> idna requests=2.23.0 -> idna[version='>=2.5,<3'] pyopenssl=19.1.0 -> cryptography[version='>=2.8'] -> idna[version='>=2.1'] requests=2.23.0 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> idna[version='>=2.0.0']

Package xz conflicts for: libtiff=4.1.0 -> xz[version='>=5.2.4,<5.3.0a0|>=5.2.5,<5.3.0a0|>=5.2.5,<6.0a0|>=5.2.4,<6.0a0'] cmake -> zstd[version='>=1.4.5,<1.4.6.0a0'] -> xz[version='>=5.2.5,<5.3.0a0'] pillow=7.1.2 -> libtiff[version='>=4.1.0,<5.0a0'] -> xz[version='>=5.2.4,<5.3.0a0|>=5.2.5,<5.3.0a0|>=5.2.5,<6.0a0|>=5.2.4,<6.0a0'] cmake -> xz[version='5.2.*|>=5.2.5,<6.0a0'] zstd=1.3.7 -> xz[version='>=5.2.4,<5.3.0a0|>=5.2.4,<6.0a0']

Package icc_rt conflicts for: scipy=1.4.1 -> icc_rt[version='>=2019.0.0'] numpy=1.18.1 -> icc_rt[version='>=2019.0.0'] scipy=1.4.1 -> numpy[version='>=1.14.6,<2.0a0'] -> icc_rt[version='>=13.1.6|>=16.0.4'] pandas=1.0.3 -> numpy[version='>=1.14.6,<2.0a0'] -> icc_rt[version='>=13.1.6|>=2019.0.0|>=16.0.4'] pytorch=1.5.0 -> numpy[version='>=1.11.3,<2.0a0'] -> icc_rt[version='>=13.1.6|>=2019.0.0|>=16.0.4'] matplotlib-base=3.1.3 -> numpy[version='>=1.14.6,<2.0a0'] -> icc_rt[version='>=13.1.6|>=2019.0.0|>=16.0.4'] numpy-base=1.18.1 -> icc_rt[version='>=2019.0.0'] torchvision=0.6.0 -> numpy[version='>=1.11'] -> icc_rt[version='>=13.1.6|>=2019.0.0|>=16.0.4'] mkl_fft=1.0.15 -> numpy[version='>=1.14.6,<2.0a0'] -> icc_rt[version='>=13.1.6|>=2019.0.0|>=16.0.4'] dlib -> numpy[version='>=1.16.5,<2.0a0'] -> icc_rt[version='>=13.1.6|>=2019.0.0|>=16.0.4'] mkl_random=1.1.0 -> numpy[version='>=1.14.6,<2.0a0'] -> icc_rt[version='>=13.1.6|>=2019.0.0|>=16.0.4']

Package python-dateutil conflicts for: pandas=1.0.3 -> python-dateutil[version='>=2.6.1'] matplotlib-base=3.1.3 -> python-dateutil matplotlib=3.1.3 -> matplotlib-base==3.1.3=py37h2981e6d_0 -> python-dateutil

Package icu conflicts for: pyqt -> qt[version='>=5.12.9,<5.13.0a0'] -> icu[version='>=58.1,<59.0a0|>=64.2,<65.0a0|>=67.1,<68.0a0|>=68.1,<69.0a0|>=58.2,<59.0a0'] qt -> icu[version='>=58.1,<59.0a0|>=64.2,<65.0a0|>=67.1,<68.0a0|>=68.1,<69.0a0|>=58.2,<59.0a0']

Package intel-openmp conflicts for: mkl=2019.4 -> intel-openmp mkl_fft=1.0.15 -> mkl[version='>=2019.4,<2020.0a0'] -> intel-openmp scipy=1.4.1 -> mkl[version='>=2019.4,<2021.0a0'] -> intel-openmp mkl-service=2.3.0 -> mkl[version='>=2020.2,<2021.0a0'] -> intel-openmp mkl_random=1.1.0 -> mkl[version='>=2019.4,<2020.0a0'] -> intel-openmp numpy-base=1.18.1 -> mkl[version='>=2019.4,<2021.0a0'] -> intel-openmp blas=1.0 -> mkl -> intel-openmp pytorch=1.5.0 -> libmklml -> intel-openmp[version='2018.0.3.|2019.'] numpy=1.18.1 -> mkl[version='>=2019.4,<2021.0a0'] -> intel-openmp

Package enum34 conflicts for: urllib3=1.25.8 -> cryptography[version='>=1.3.4'] -> enum34 pyopenssl=19.1.0 -> cryptography[version='>=2.8'] -> enum34

Package cryptography conflicts for: pyopenssl=19.1.0 -> cryptography[version='>=2.8'] urllib3=1.25.8 -> pyopenssl[version='>=0.14'] -> cryptography[version='>=1.3|>=1.9|>=2.1.4|>=2.2.1|>=2.8|>=3.2'] urllib3=1.25.8 -> cryptography[version='>=1.3.4'] requests=2.23.0 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> cryptography[version='>=1.3.4']

Package vs2008_runtime conflicts for: freetype=2.9.1 -> vc=9 -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] mkl-service=2.3.0 -> python[version='>=2.7,<2.8.0a0'] -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] pyqt -> python[version='>=2.7,<2.8.0a0'] -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] jpeg=9b -> vc=9 -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] icu -> vc==9 -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] python-dateutil=2.8.1 -> python -> vs2008_runtime certifi -> python[version='>=2.7,<2.8.0a0'] -> vs2008_runtime pyopenssl=19.1.0 -> python -> vs2008_runtime dlib -> python=2.7 -> vs2008_runtime cycler=0.10.0 -> python -> vs2008_runtime pytorch=1.5.0 -> ninja -> vs2008_runtime requests=2.23.0 -> python -> vs2008_runtime cffi=1.14.0 -> python[version='>=2.7,<2.8.0a0'] -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] pycparser=2.20 -> python -> vs2008_runtime zlib=1.2.11 -> vc[version='>=9,<10.0a0'] -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] openssl -> vc=9 -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] sip -> python[version='>=2.7,<2.8.0a0'] -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] six=1.14.0 -> python -> vs2008_runtime powershell_shortcut -> python -> vs2008_runtime win_inet_pton -> python[version='>=2.7,<2.8.0a0'] -> vs2008_runtime idna=2.9 -> python -> vs2008_runtime zstd=1.3.7 -> vc[version='>=9,<10.0a0'] -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] urllib3=1.25.8 -> python[version='>=2.7,<2.8.0a0'] -> vs2008_runtime wincertstore -> python[version='>=2.7,<2.8.0a0'] -> vs2008_runtime pyparsing=2.4.7 -> python -> vs2008_runtime pip=20.0.2 -> python -> vs2008_runtime mkl_fft=1.0.15 -> python[version='>=2.7,<2.8.0a0'] -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] olefile=0.46 -> python -> vs2008_runtime pysocks=1.7.1 -> python[version='>=2.7,<2.8.0a0'] -> vs2008_runtime ninja=1.9.0 -> python[version='>=2.7,<2.8.0a0'] -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] pytz=2020.1 -> python -> vs2008_runtime wheel=0.34.2 -> python -> vs2008_runtime vc -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] qt -> vc=9 -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] chardet=3.0.4 -> python[version='>=2.7,<2.8.0a0'] -> vs2008_runtime tk=8.6.8 -> vc=9 -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0'] libpng=1.6.37 -> vc=9 -> vs2008_runtime[version='>=9.0.30729.1,<10.0a0']

Package liblapacke conflicts for: mkl_random=1.1.0 -> blas=[build=mkl] -> liblapacke[version='3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.9.0',build='4_mkl|5_mkl|8_mkl|9_mkl|10_mkl|11_mkl|13_mkl|15_mkl|5_mkl|6_mkl|7_mkl|21_mkl|20_mkl|19_mkl|18_mkl|16_mkl|14_mkl|12_mkl|7_mkl|6_mkl'] pytorch=1.5.0 -> blas=[build=mkl] -> liblapacke[version='3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.8.0|3.9.0',build='4_mkl|5_mkl|8_mkl|9_mkl|10_mkl|11_mkl|13_mkl|15_mkl|5_mkl|6_mkl|7_mkl|21_mkl|20_mkl|19_mkl|18_mkl|16_mkl|14_mkl|12_mkl|7_mkl|6_mkl']

Package setuptools conflicts for: matplotlib=3.1.3 -> matplotlib-base==3.1.3=py37h2981e6d_0 -> setuptools wheel=0.34.2 -> setuptools zstd=1.3.7 -> lz4 -> setuptools pip=20.0.2 -> setuptools python=3.8.2 -> pip -> setuptools matplotlib-base=3.1.3 -> setuptools

Package cffi conflicts for: pytorch=1.5.0 -> cffi pyopenssl=19.1.0 -> cryptography[version='>=2.8'] -> cffi[version='!=1.11.3,>=1.8|>=1.8,!=1.11.3|>=1.8'] torchvision=0.6.0 -> pytorch==1.5.0 -> cffi urllib3=1.25.8 -> cryptography[version='>=1.3.4'] -> cffi[version='!=1.11.3,>=1.8|>=1.8,!=1.11.3|>=1.7|>=1.8'] cryptography=2.9.2 -> cffi

Package packaging conflicts for: pip=20.0.2 -> wheel -> packaging[version='>=20.2'] python=3.8.2 -> pip -> packaging

Package m2-gcc-libs conflicts for: m2-libreadline -> m2-ncurses -> m2-gcc-libs m2-ncurses -> m2-gcc-libs m2-libedit -> m2-ncurses -> m2-gcc-libs

Package lz4-c conflicts for: libtiff=4.1.0 -> zstd[version='>=1.4.5,<1.5.0a0'] -> lz4-c[version='>=1.8.3,<1.8.4.0a0|>=1.9.2,<1.10.0a0|>=1.9.2,<1.9.3.0a0|>=1.9.3,<1.9.4.0a0'] cmake -> zstd[version='>=1.4.5,<1.4.6.0a0'] -> lz4-c[version='>=1.9.2,<1.10.0a0|>=1.9.2,<1.9.3.0a0'] zstd=1.3.7 -> lz4 -> lz4-c[version='1.8.1.*|>=1.8.1.2,<1.8.2.0a0|>=1.8.3,<1.8.4.0a0|>=1.9.2,<1.9.3.0a0|>=1.9.3,<1.9.4.0a0|>=1.9.2,<1.10.0a0|>=1.8.1.2,<1.9.0a0']

Package mkl conflicts for: numpy=1.18.1 -> libblas[version='>=3.8.0,<4.0a0'] -> mkl[version='2019.1.*|2019.3|2019.4|2020.0|2020.1|2020.2|2020.4|>=2020.4,<2021.0a0|>=2020.2,<2021.0a0|>=2019.3,<2020.0a0|>=2019.0,<2020.0a0|>=2020.2,<2021.0a0|>=2019.4,<2020.0a0|>=2019.3,<2020.0a0|>=2019.3,<2021.0a0|>=2019.1,<2020.0a0|>=2019.1,<2021.0a0|>=2018.0.3,<2019.0a0|>=2020.0,<2021.0a0|>=2020.1,<2021.0a0',build='166|216|256|hb70f87d_311|256|245|203|203'] numpy=1.18.1 -> mkl[version='>=2019.4,<2021.0a0'] pytorch=1.5.0 -> mkl[version='2019.*|>=2019.4,<2021.0a0|>=2018'] scipy=1.4.1 -> blas==1.0=mkl -> mkl[version='>=2018.0.3,<2019.0a0|>=2019.1,<2021.0a0|>=2019.3,<2020.0a0|>=2019.4,<2020.0a0|>=2020.2,<2021.0a0|>=2019.3,<2021.0a0'] torchvision=0.6.0 -> numpy[version='>=1.11'] -> mkl[version='2019.*|>=2018.0.0,<2019.0a0|>=2018.0.1,<2019.0a0|>=2018.0.2,<2019.0a0|>=2018.0.3,<2019.0a0|>=2019.1,<2021.0a0|>=2019.3,<2021.0a0|>=2019.4,<2021.0a0|>=2019.4,<2020.0a0|>=2018'] scipy=1.4.1 -> mkl[version='>=2019.4,<2021.0a0'] mkl_fft=1.0.15 -> mkl[version='>=2019.4,<2020.0a0|>=2019.4,<2021.0a0'] mkl_fft=1.0.15 -> mkl-service[version='>=2,<3.0a0'] -> mkl[version='>=2018.0.0,<2019.0a0|>=2018.0.1,<2019.0a0|>=2018.0.2,<2019.0a0|>=2018.0.3,<2019.0a0|>=2019.1,<2021.0a0|>=2019.3,<2020.0a0|>=2020.2,<2021.0a0|>=2019.3,<2021.0a0'] mkl_random=1.1.0 -> mkl[version='>=2019.4,<2020.0a0|>=2019.4,<2021.0a0'] pytorch=1.5.0 -> blas==1.0=mkl -> mkl[version='>=2018.0.0,<2019.0a0|>=2018.0.1,<2019.0a0|>=2018.0.2,<2019.0a0|>=2018.0.3,<2019.0a0|>=2019.1,<2021.0a0|>=2019.3,<2020.0a0|>=2019.4,<2020.0a0|>=2020.2,<2021.0a0|>=2019.3,<2021.0a0'] mkl-service=2.3.0 -> mkl[version='>=2019.4,<2020.0a0|>=2020.2,<2021.0a0|>=2019.4,<2021.0a0'] pandas=1.0.3 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl[version='>=2018.0.3,<2019.0a0|>=2019.1,<2021.0a0|>=2019.3,<2021.0a0|>=2019.4,<2021.0a0|>=2019.4,<2020.0a0'] mkl_random=1.1.0 -> mkl-service[version='>=2,<3.0a0'] -> mkl[version='>=2018.0.0,<2019.0a0|>=2018.0.1,<2019.0a0|>=2018.0.2,<2019.0a0|>=2018.0.3,<2019.0a0|>=2019.1,<2021.0a0|>=2019.3,<2020.0a0|>=2020.2,<2021.0a0|>=2019.3,<2021.0a0'] numpy-base=1.18.1 -> mkl[version='>=2019.4,<2021.0a0'] matplotlib-base=3.1.3 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl[version='>=2018.0.3,<2019.0a0|>=2019.1,<2021.0a0|>=2019.3,<2021.0a0|>=2019.4,<2021.0a0|>=2019.4,<2020.0a0'] numpy-base=1.18.1 -> blas==1.0=mkl -> mkl[version='>=2019.3,<2020.0a0|>=2019.4,<2020.0a0|>=2020.2,<2021.0a0|>=2019.3,<2021.0a0'] blas=1.0 -> mkl

Package m2-msys2-runtime conflicts for: m2-ncurses -> m2-msys2-runtime m2-libedit -> m2-msys2-runtime m2-bash -> m2-msys2-runtime m2-gcc-libs -> m2-msys2-runtime m2-libreadline -> m2-ncurses -> m2-msys2-runtime

Package openblas conflicts for: matplotlib-base=3.1.3 -> numpy[version='>=1.14.6,<2.0a0'] -> openblas[version='>=0.2.20,<0.2.21.0a0|>=0.3.3,<0.3.4.0a0'] dlib -> numpy[version='>=1.14.6,<2.0a0'] -> openblas[version='>=0.2.20,<0.2.21.0a0|>=0.3.3,<0.3.4.0a0'] numpy=1.18.1 -> libblas[version='>=3.8.0,<4.0a0'] -> openblas[version='0.3.5.*|0.3.6|>=0.3.6,<0.3.7.0a0',build=h828a276_2] pytorch=1.5.0 -> numpy[version='>=1.11.3,<2.0a0'] -> openblas[version='0.2.20|0.2.20.*|>=0.2.20,<0.2.21.0a0|>=0.3.3,<0.3.4.0a0'] mkl_fft=1.0.15 -> numpy[version='>=1.14.6,<2.0a0'] -> openblas[version='0.2.20|0.2.20.*|>=0.2.20,<0.2.21.0a0|>=0.3.3,<0.3.4.0a0'] pandas=1.0.3 -> numpy[version='>=1.14.6,<2.0a0'] -> openblas[version='>=0.2.20,<0.2.21.0a0|>=0.3.3,<0.3.4.0a0'] blas=1.0 -> openblas mkl_random=1.1.0 -> numpy[version='>=1.14.6,<2.0a0'] -> openblas[version='0.2.20|0.2.20.*|>=0.2.20,<0.2.21.0a0|>=0.3.3,<0.3.4.0a0'] torchvision=0.6.0 -> numpy[version='>=1.11'] -> openblas[version='0.2.20|0.2.20.*|>=0.2.20,<0.2.21.0a0|>=0.3.3,<0.3.4.0a0'] scipy=1.4.1 -> numpy[version='>=1.14.6,<2.0a0'] -> openblas[version='>=0.2.20,<0.2.21.0a0|>=0.3.3,<0.3.4.0a0']

Package numpy conflicts for: matplotlib=3.1.3 -> matplotlib-base==3.1.3=py37h2981e6d_0 -> numpy[version='>=1.14.6,<2.0a0'] mkl_random=1.1.0 -> numpy[version='>=1.11.3,<2.0a0|>=1.14.6,<2.0a0'] scipy=1.4.1 -> numpy[version='>=1.14.6,<2.0a0'] pytorch=1.5.0 -> numpy[version='>=1.11|>=1.11.3,<2.0a0'] torchvision=0.6.0 -> numpy[version='>=1.11'] numpy-base=1.18.1 -> mkl-service[version='>=2,<3.0a0'] -> numpy[version='>=1.11.3,<2.0a0'] mkl_fft=1.0.15 -> numpy[version='>=1.11.3,<2.0a0|>=1.14.6,<2.0a0'] pandas=1.0.3 -> numpy[version='>=1.14.6,<2.0a0'] scipy=1.4.1 -> mkl-service[version='>=2,<3.0a0'] -> numpy[version='>=1.11.3,<2.0a0'] matplotlib-base=3.1.3 -> numpy[version='>=1.14.6,<2.0a0'] torchvision=0.6.0 -> pytorch==1.5.0 -> numpy[version='>=1.11.3,<2.0a0']

Package libpng conflicts for: qt -> libpng[version='>=1.6.32,<1.7.0a0|>=1.6.34,<1.7.0a0|>=1.6.35,<1.7.0a0|>=1.6.37,<1.7.0a0'] pillow=7.1.2 -> freetype[version='>=2.9.1,<3.0a0'] -> libpng[version='>=1.6.34,<1.7.0a0|>=1.6.35,<1.7.0a0|>=1.6.37,<1.7.0a0'] matplotlib=3.1.3 -> matplotlib-base==3.1.3=py37h2981e6d_0 -> libpng[version='>=1.6.37,<1.7.0a0'] pyqt -> qt[version='>=5.12.9,<5.13.0a0'] -> libpng[version='>=1.6.32,<1.7.0a0|>=1.6.34,<1.7.0a0|>=1.6.35,<1.7.0a0|>=1.6.37,<1.7.0a0'] freetype=2.9.1 -> libpng[version='>=1.6.34,<1.7.0a0|>=1.6.35,<1.7.0a0'] matplotlib-base=3.1.3 -> libpng[version='>=1.6.37,<1.7.0a0'] matplotlib-base=3.1.3 -> freetype[version='>=2.9.1,<3.0a0'] -> libpng[version='>=1.6.34,<1.7.0a0|>=1.6.35,<1.7.0a0']

Package win_inet_pton conflicts for: pysocks=1.7.1 -> win_inet_pton urllib3=1.25.8 -> pysocks[version='>=1.5.6,<2.0,!=1.5.7'] -> win_inet_pton

Package msys2-conda-epoch conflicts for: m2-bash -> msys2-conda-epoch[version='>=20160418'] m2-libreadline -> msys2-conda-epoch[version='>=20160418'] m2w64-gcc-libgfortran -> msys2-conda-epoch[version='>=20160418'] m2-gcc-libs -> msys2-conda-epoch[version='>=20160418'] m2-libedit -> msys2-conda-epoch[version='>=20160418'] m2w64-libwinpthread-git -> msys2-conda-epoch[version='>=20160418'] m2-msys2-runtime -> msys2-conda-epoch[version='>=20160418'] m2-libffi -> msys2-conda-epoch[version='>=20160418'] m2w64-gmp -> msys2-conda-epoch[version='>=20160418'] m2w64-gcc-libs-core -> msys2-conda-epoch[version='>=20160418'] m2-ncurses -> msys2-conda-epoch[version='>=20160418']

Package cycler conflicts for: matplotlib=3.1.3 -> matplotlib-base==3.1.3=py37h2981e6d_0 -> cycler[version='>=0.10'] matplotlib-base=3.1.3 -> cycler[version='>=0.10']

Package freetype conflicts for: torchvision=0.6.0 -> pillow[version='>=4.1.1'] -> freetype[version='2.7|2.7.|2.7|2.8.|2.8.1|2.8.1.*|>=2.10.4,<3.0a0|>=2.9.1,<3.0a0|>=2.8.1,<2.9.0a0|>=2.10.3,<3.0a0|>=2.8,<2.9.0a0'] matplotlib-base=3.1.3 -> freetype[version='>=2.9.1,<3.0a0'] matplotlib=3.1.3 -> matplotlib-base==3.1.3=py37h2981e6d_0 -> freetype[version='>=2.9.1,<3.0a0'] pillow=7.1.2 -> freetype[version='>=2.9.1,<3.0a0']

Package sip conflicts for: pyqt -> sip[version='4.18|4.18.|>=4.19.4,<=4.19.8|4.19.13.|>=4.19.13,<=4.19.14'] matplotlib=3.1.3 -> pyqt -> sip[version='4.18|4.18.|>=4.19.4,<=4.19.8|4.19.13.|>=4.19.13,<=4.19.14']

Package cudatoolkit conflicts for: pytorch=1.5.0 -> cudatoolkit[version='>=10.2,<10.3'] torchvision=0.6.0 -> cudatoolkit[version='>=10.2,<10.3']

Package certifi conflicts for: urllib3=1.25.8 -> certifi requests=2.23.0 -> certifi[version='>=2017.4.17'] wheel=0.34.2 -> setuptools -> certifi[version='>=2016.09|>=2016.9.26'] setuptools=46.2.0 -> certifi[version='>=2016.9.26'] requests=2.23.0 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> certifi matplotlib-base=3.1.3 -> setuptools -> certifi[version='>=2016.09|>=2016.9.26'] pip=20.0.2 -> setuptools -> certifi[version='>=2016.09|>=2016.9.26']

Package jpeg conflicts for: pillow=7.1.2 -> libtiff[version='>=4.1.0,<5.0a0'] -> jpeg[version='>=9d,<10a'] qt -> jpeg[version='>=9b,<10a|>=9c,<10a|>=9d,<10a'] pyqt -> qt[version='>=5.12.9,<5.13.0a0'] -> jpeg[version='>=9b,<10a|>=9c,<10a|>=9d,<10a'] libtiff=4.1.0 -> jpeg[version='>=9b,<10a|>=9c,<10a|>=9d,<10a'] torchvision=0.6.0 -> pillow[version='>=4.1.1'] -> jpeg[version='9.*|>=9c,<10a|>=9d,<10a|>=9b,<10a'] pillow=7.1.2 -> jpeg[version='>=9b,<10a|>=9c,<10a']

Package m2w64-gcc-libs conflicts for: numpy=1.18.1 -> libblas[version='>=3.8.0,<4.0a0'] -> m2w64-gcc-libs mkl_random=1.1.0 -> blas=[build=mkl] -> m2w64-gcc-libs pytorch=1.5.0 -> blas=[build=mkl] -> m2w64-gcc-libs m2w64-gcc-libgfortran -> m2w64-gcc-libs

Package ninja conflicts for: pytorch=1.5.0 -> ninja torchvision=0.6.0 -> pytorch==1.5.0 -> ninja

Package mkl-service conflicts for: scipy=1.4.1 -> mkl-service[version='>=2,<3.0a0'] numpy=1.18.1 -> mkl-service[version='>=2,<3.0a0'] matplotlib-base=3.1.3 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl-service[version='>=2,<3.0a0'] numpy-base=1.18.1 -> mkl-service[version='>=2,<3.0a0'] pytorch=1.5.0 -> mkl-service[version='>=2,<3.0a0'] pandas=1.0.3 -> numpy[version='>=1.14.6,<2.0a0'] -> mkl-service[version='>=2,<3.0a0'] torchvision=0.6.0 -> numpy[version='>=1.11'] -> mkl-service[version='>=2,<3.0a0'] mkl_fft=1.0.15 -> mkl-service[version='>=2,<3.0a0'] mkl_random=1.1.0 -> mkl-service[version='>=2,<3.0a0']

Package libclang conflicts for: pyqt -> qt[version='>=5.12.9,<5.13.0a0'] -> libclang[version='>=10.0.1,<11.0a0|>=11.0.0,<12.0a0|>=9.0.0,<10.0a0'] qt -> libclang[version='>=10.0.1,<11.0a0|>=11.0.0,<12.0a0|>=9.0.0,<10.0a0|>=8.0.0,<9.0a0']

Package tornado conflicts for: matplotlib-base=3.1.3 -> tornado matplotlib=3.1.3 -> matplotlib-base==3.1.3=py37h2981e6d_0 -> tornado

Package pyparsing conflicts for: matplotlib-base=3.1.3 -> pyparsing matplotlib=3.1.3 -> matplotlib-base==3.1.3=py37h2981e6d_0 -> pyparsing

Package wincertstore conflicts for: wheel=0.34.2 -> setuptools -> wincertstore[version='>=0.2'] setuptools=46.2.0 -> wincertstore[version='>=0.2'] pip=20.0.2 -> setuptools -> wincertstore[version='>=0.2'] matplotlib-base=3.1.3 -> setuptools -> wincertstore[version='>=0.2']

Package kiwisolver conflicts for: matplotlib-base=3.1.3 -> kiwisolver matplotlib=3.1.3 -> matplotlib-base==3.1.3=py37h2981e6d_0 -> kiwisolver

Package pycparser conflicts for: cffi=1.14.0 -> pycparser cryptography=2.9.2 -> cffi -> pycparser pytorch=1.5.0 -> cffi -> pycparser

Package pysocks conflicts for: urllib3=1.25.8 -> pysocks[version='>=1.5.6,<2.0,!=1.5.7'] requests=2.23.0 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> pysocks[version='>=1.5.6,<2.0,!=1.5.7']

Package libopenblas conflicts for: numpy=1.18.1 -> libblas[version='>=3.8.0,<4.0a0'] -> libopenblas[version='0.3.10|0.3.12|0.3.9|0.3.8|0.3.7|0.3.7|0.3.6',build='h29e5d5d_0|hcfe7411_0|hc8a65f3_0|pthreads_h1662909_0|pthreads_h1662909_1|hcfe7411_0|h29e5d5d_1|h29e5d5d_6'] blas=1.0 -> openblas -> libopenblas[version='0.3.10|0.3.10|0.3.10|0.3.10|0.3.10|0.3.10|0.3.12|0.3.12|0.3.13|0.3.9|0.3.8|0.3.7|0.3.7|0.3.7|0.3.7|0.3.7|0.3.7|0.3.7|0.3.7|0.3.6|0.3.6|0.3.6|0.3.6',build='h29e5d5d_3|h29e5d5d_4|h29e5d5d_6|h29e5d5d_0|h29e5d5d_2|hcfe7411_4|hcfe7411_6|hcfe7411_7|hc8a65f3_0|pthreads_h1662909_1|pthreads_h1662909_2|pthreads_h1662909_5|pthreads_h1662909_0|pthreads_h1662909_1|pthreads_hc469a61_0|pthreads_h1662909_4|pthreads_h1662909_3|hcfe7411_0|hcfe7411_0|hcfe7411_5|h29e5d5d_3|h29e5d5d_1|h29e5d5d_5']

Package pypy3.6 conflicts for: cryptography=2.9.2 -> cffi -> pypy3.6[version='7.3.0.|7.3.1.|7.3.2.|7.3.3.'] pytorch=1.5.0 -> cffi -> pypy3.6[version='7.3.0.|7.3.1.|7.3.2.|7.3.3.'] cffi=1.14.0 -> pypy3.6=7.3.1

Package vs2013_runtime conflicts for: cmake -> vs2013_runtime pytorch=1.5.0 -> libmklml -> vs2013_runtime

Package tk conflicts for: pillow=7.1.2 -> tk[version='>=8.6.10,<8.7.0a0|>=8.6.8,<8.7.0a0'] torchvision=0.6.0 -> pillow[version='>=4.1.1'] -> tk[version='8.6.*|>=8.6.10,<8.7.0a0|>=8.6.9,<8.7.0a0|>=8.6.8,<8.7.0a0|>=8.6.7,<8.7.0a0']

Package wheel conflicts for: python=3.8.2 -> pip -> wheel pip=20.0.2 -> wheel

Package lz4 conflicts for: zstd=1.3.7 -> lz4 libtiff=4.1.0 -> zstd[version='>=1.3.7,<1.3.8.0a0'] -> lz4

Package qt conflicts for: matplotlib=3.1.3 -> pyqt -> qt[version='4.8.|5.6.|5.9.*|>=5.12.5,<5.13.0a0|>=5.12.9,<5.13.0a0|>=5.9.7,<5.10.0a0|>=5.6.2,<5.7.0a0|>=5.9.6,<5.10.0a0|>=5.9.4,<5.10.0a0'] pyqt -> qt[version='4.8.|5.6.|5.9.*|>=5.12.5,<5.13.0a0|>=5.12.9,<5.13.0a0|>=5.9.7,<5.10.0a0|>=5.6.2,<5.7.0a0|>=5.9.6,<5.10.0a0|>=5.9.4,<5.10.0a0']

Package m2w64-gmp conflicts for: m2w64-gcc-libs-core -> m2w64-gmp m2w64-gcc-libgfortran -> m2w64-gcc-libs-core -> m2w64-gmp

Package m2-ncurses conflicts for: m2-libedit -> m2-ncurses m2-libreadline -> m2-ncurses

Package m2w64-libwinpthread-git conflicts for: m2w64-gcc-libs-core -> m2w64-libwinpthread-git m2w64-gcc-libgfortran -> m2w64-gcc-libs-core -> m2w64-libwinpthread-git

Package libtiff conflicts for: pillow=7.1.2 -> libtiff[version='>=4.0.10,<5.0a0|>=4.1.0,<5.0a0'] torchvision=0.6.0 -> pillow[version='>=4.1.1'] -> libtiff[version='4.0.*|>=4.0.10,<5.0a0|>=4.1.0,<5.0a0|>=4.0.9,<5.0a0|>=4.0.8,<4.0.10|>=4.0.3,<4.0.8|>=4.0.8,<5.0a0']

Package pyopenssl conflicts for: requests=2.23.0 -> urllib3[version='>=1.21.1,<1.26,!=1.25.0,!=1.25.1'] -> pyopenssl[version='>=0.14'] urllib3=1.25.8 -> pyopenssl[version='>=0.14']

END CONFLICTS TRYING TO INSTALL DLIB INTO ENVIRONMENT DIRECTLY

I hope this information makes solving this issue possible. Let me know if you need something specific to help. Thanks for reading this!

Cannot run align_face.

(pulse) root@e2bbc3333453:/home/pulse# python align_face.py
Downloading Shape Predictor
Downloading https://drive.google.com/uc?id=1huhv8PYpNNKbGCLOaYUjOgR1pY5pmbJx ............ failed
Traceback (most recent call last):
  File "align_face.py", line 34, in <module>
    f=open_url("https://drive.google.com/uc?id=1huhv8PYpNNKbGCLOaYUjOgR1pY5pmbJx", cache_dir=cache_dir, return_path=True)
  File "/home/pulse/drive.py", line 66, in open_url
    raise IOError("Google Drive quota exceeded")
OSError: Google Drive quota exceeded

Probably sharing a new link would fix this.

About another matter, maybe it would be best to warn people to put their input images as png. It took me a while to understand why my images weren't processed when runnin "python run.py'.

run.py and PULSE.py attempt to download files from Google drive every time they are executed. This leads to OSError: Google Drive quota exceeded quite fast. Checking the cache directory first for synthesis.pt, mapping.pt or shape_predictor_68_face_landmarks.dat reduces server queries and also reduces initialization time.

Little remark: While automatic downloading approaches failed every time, I was able to copy the URL into my browser and download all the files manually as a workaround.

If I try to use the pre-trained model I get this error

RuntimeError: CUDA out of memory. Tried to allocate 64.00 MiB (GPU 0; 1.95 GiB total capacity; 1.19 GiB already allocated; 57.31 MiB free; 1.25 GiB reserved in total by PyTorch)

My graphic card is a NVIDIA GeForce GTX 750 Ti with 2 GB of VRAM: is there a configuration that allows to use the model with this amount of VRAM ?

I have deleted the hash after the names and even tried removing the specified version, but it still says package not found.

(C:\ProgramData\Anaconda3) Z:\pulse>conda env create -n pulse -f pulse.yml
Collecting package metadata (repodata.json): done
Solving environment: failed

ResolvePackageNotFound:
  - libcxx
  - readline
  - libedit
  - libgfortran
  - ncurses

Microsoft Windows [Version 10.0.19044.1645] conda 4.11.0

Error reporting process: ############################### Loading Synthesis Network Traceback (most recent call last): File "/home/kfn/anaconda3/envs/pulse/lib/python3.8/site-packages/spyder_kernels/py3compat.py", line 356, in compat_exec exec(code, globals, locals) File "/home/kfn/comparison model/pulser/run.py", line 79, in for j,(HR,LR) in enumerate(model(ref_im,**kwargs)): File "/home/kfn/anaconda3/envs/pulse/lib/python3.8/site-packages/torch/nn/modules/module.py", line 550, in call result = self.forward(*input, **kwargs) File "/home/kfn/anaconda3/envs/pulse/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 156, in forward return self.gather(outputs, self.output_device) File "/home/kfn/anaconda3/envs/pulse/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 168, in gather return gather(outputs, output_device, dim=self.dim) File "/home/kfn/anaconda3/envs/pulse/lib/python3.8/site-packages/torch/nn/parallel/scatter_gather.py", line 68, in gather res = gather_map(outputs) File "/home/kfn/anaconda3/envs/pulse/lib/python3.8/site-packages/torch/nn/parallel/scatter_gather.py", line 63, in gather_map return type(out)(map(gather_map, zip(*outputs))) TypeError: cannot create 'generator' instances. ###################### Hope to receive to reply as soon as possible, Thanks a lot.

As the title says.

I'm looking for a nice "image-enhancing" library that given an image and a target resolution could create an enhanced version of this image (having the new resolution).

I wish to use it on Android, and I don't think Python can be used so easily for Android. If I'm wrong, please let me know how to do it on Android.

Hi any advice would be appreciated:

[tibero@acer pulse-master]$ conda create -f pulse.yml
WARNING: A directory already exists at the target location '/usr' but it is not a conda environment. Continue creating environment (y/[n])? y

CondaValueError: either -n NAME or -p PREFIX option required, try "conda create -h" for more details