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Recipes for creating Tensorflow conda packages.

In the defaults channel Tensorflow is provided via a number of packages. As of version 1.11.0, the library itself is provided by the tensorflow-base package. Different variants of this package are created for each platform from the tensorflow-base-cpu and tensorflow-base-gpu recipes.

Installing the tensorflow package using conda installs both the tensorflow library as well as tensorboard. The tensorboard recipe is used to create the tensorboard package.

The tensorflow metapackage package is created by the tensorflow recipe. The tensorflow metapackage depends on tensorboard, an exact build of tensorflow-base and the version of the _tflow_select package which matches the tensorflow-base variant.

The _tflow_select package, created from the _tflow_select recipe, establishes the priority of the variants using the version number. The variant with the highest version will be installed by default. The non-default variant can be installed using the tensorflow-mkl, tensorflow-eigen and tensorflow-gpu packages which are created from the tensorflow-variants recipe. Note that not some platforms do not support all variants.

Available Recipe:

  • tensorboard : Tensorboard.
  • tensorflow : Metapackage which installs tensorflow-base and tensorboard.
  • tensorflow-base-cpu : Eigen and MKL variants of the Tensorflow library.
  • tensorflow-base-gpu : GPU variant of the Tensorflow library.
  • tensorflow-variants : Recipe used to create tensorflow variant packages, e.g. tensorflow-mkl.
  • _tflow_select : Metapackage to establish priority in tensorflow-base packages.

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Tensorflow conda recipes

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