Comments (2)
conda is more explicit:
$ conda install tensorflow=1.9
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
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.
failed
UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:
Specifications:
- tensorflow=1.9 -> python[version='2.7.*|3.5.*|3.6.*']
- tensorflow=1.9 -> python[version='>=2.7,<2.8.0a0|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0']
Your python: python=3.7
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 each other:
Package certifi conflicts for:
tensorflow=1.9 -> python=2.7 -> pip -> setuptools -> certifi[version='>=2016.09|>=2016.9.26']
python=3.7 -> pip -> setuptools -> certifi[version='>=2016.09|>=2016.9.26']
Package ca-certificates conflicts for:
tensorflow=1.9 -> python=2.7 -> ca-certificates
python=3.7 -> openssl[version='>=1.1.1b,<1.1.2a'] -> ca-certificates
Package pip conflicts for:
python=3.7 -> pip
tensorflow=1.9 -> python=2.7 -> pip
Package wheel conflicts for:
python=3.7 -> pip -> wheel
tensorflow=1.9 -> python=2.7 -> pip -> wheel
Package setuptools conflicts for:
tensorflow=1.9 -> python=2.7 -> pip -> setuptools
python=3.7 -> pip -> setuptools
from trailmap.
Thank you for bring this issue up. You indeed need to use Python 3.6 if you use tensorflow 1.9.
I will update the readme page later this week with a detailed tested version of pip install.
Please let me know if you have anymore issues.
from trailmap.
Related Issues (14)
- Labeling method HOT 2
- HDF5 file with pre-trained model weights in Github repo is corrupt HOT 7
- Blas SGEMM launch failed when predicting with GPU HOT 5
- `get_dir` gets thrown off by created `seg-` folder HOT 7
- A few questions HOT 1
- Hi, your work is good, and where can I find your training dataset? HOT 4
- Error during inference HOT 3
- Threshold and cells HOT 12
- Cuda / Cudnn
- Inconsistent environment
- note though that in contrast to your instructions I do not have h5py version 2.1 HOT 4
- VisibleDeprecationWarning for segment_brain.py HOT 1
- Model weights cannot be downloaded (`This repository is over its data quota`) HOT 1
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from trailmap.