Difference between revisions of "Infrastructure/software/frameworks"
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[https://research.csc.fi/-/tensorflow TensorFlow] many versions, from 0.11 through 1.5.0; seemingly only installed for GPU nodes, though page provides instructions for user-level installation of CPU-only version. | [https://research.csc.fi/-/tensorflow TensorFlow] many versions, from 0.11 through 1.5.0; seemingly only installed for GPU nodes, though page provides instructions for user-level installation of CPU-only version. | ||
| − | [https://research.csc.fi/-/mlpython ML Bundle] Python 2.x and 3.x installations with multiple DL frameworks included, notably MxNet, PyTorch, Theano, and TensorFlow. No version information available for individual DL frameworks, and version scheme for the bundle at large seems to follow Python versions. Potentially troubling announcement that “packages in the Mlpython environments are updated periodically.” | + | [https://research.csc.fi/-/mlpython ML Bundle] Python 2.x and 3.x installations with multiple DL frameworks included, notably MxNet, PyTorch, Theano, and TensorFlow. No version information available for individual DL frameworks, and version scheme for the bundle at large seems to follow Python versions. Seemingly only available on GPU nodes. Potentially troubling announcement that “packages in the Mlpython environments are updated periodically.” |
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Revision as of 09:47, 6 March 2018
Background
General programming environment for so-called neural or deep learning (DL) are a prerequisite to much current NLP research, somewhat analogous to compilers or core libraries (like Boost or ICU). These frameworks are not in principle discipline-specific and will often be difficult to install in user space (i.e. without administrator privileges).
Taito
DyNet 2.0 and 2.0.1, apparently both for CPU and GPU nodes
TensorFlow many versions, from 0.11 through 1.5.0; seemingly only installed for GPU nodes, though page provides instructions for user-level installation of CPU-only version.
ML Bundle Python 2.x and 3.x installations with multiple DL frameworks included, notably MxNet, PyTorch, Theano, and TensorFlow. No version information available for individual DL frameworks, and version scheme for the bundle at large seems to follow Python versions. Seemingly only available on GPU nodes. Potentially troubling announcement that “packages in the Mlpython environments are updated periodically.”
