diff --git a/application_documentation/trRosetta/trRosetta.md b/application_documentation/trRosetta/trRosetta.md index 6e189c5c9..c7e866e78 100644 --- a/application_documentation/trRosetta/trRosetta.md +++ b/application_documentation/trRosetta/trRosetta.md @@ -10,14 +10,14 @@ The trRosetta application uses the trRosetta neural network described in Yang _e ### Compilation requirements -The trRosetta application requires that Rosetta be linked against the Tensorflow C-API libraries. To compile with Tensorflow support: - -1. Download the Tensorflow 1.15 precompiled libraries for your operating system from one of the following. (Note that GPU versions require CUDA drivers; see https://www.tensorflow.org/install/lang_c for more information.) - * Linux/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-1.15.0.tar.gz - * Linux/GPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-1.15.0.tar.gz - * Windows/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-windows-x86_64-1.15.0.zip - * Windows/GPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-windows-x86_64-1.15.0.zip - * MacOS/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-darwin-x86_64-1.15.0.tar.gz +The trRosetta application requires that Rosetta be linked against the Tensorflow 2 C-API libraries, version 2.5.0 or higher. To compile with Tensorflow support: + +1. Download the Tensorflow 2.5.0 precompiled libraries for your operating system from one of the following. (Note that GPU versions require CUDA drivers; see https://www.tensorflow.org/install/lang_c for more information.) + * Linux/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-2.5.0.tar.gz + * Linux/GPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-2.5.0.tar.gz + * Windows/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-windows-x86_64-2.5.0.zip + * Windows/GPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-windows-x86_64-2.5.0.zip + * MacOS/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-darwin-x86_64-2.5.0.tar.gz * MacOS/GPU: None available. 2. Unzip/untar the archive into a suitable directory (~/mydir/ is used here as an example), and add the following environment variables: diff --git a/scripting_documentation/RosettaScripts/xsd/constraint_generator_trRosettaConstraintGenerator_type.md b/scripting_documentation/RosettaScripts/xsd/constraint_generator_trRosettaConstraintGenerator_type.md index 94a961b73..304815257 100644 --- a/scripting_documentation/RosettaScripts/xsd/constraint_generator_trRosettaConstraintGenerator_type.md +++ b/scripting_documentation/RosettaScripts/xsd/constraint_generator_trRosettaConstraintGenerator_type.md @@ -5,14 +5,14 @@ _Autogenerated Tag Syntax Documentation:_ --- The trRosettaConstraintGenerator takes as input a file containing a multiple sequence alignment, feeds this to the trRosetta neural network, and uses the output to generate distance and angle constraints between pairs of residues as described in Yang et al. (2020) Improved protein structure prediction using predicted interresidue orientations. Proc. Natl. Acad. Sci. USA 117(3):1496-503. https://doi.org/10.1073/pnas.1914677117. -The trRosettaConstraintGenerator requires compilation with Tensorflow support. To compile with Tensorflow support: +The trRosettaConstraintGenerator requires compilation with Tensorflow 2 support (version 2.5.0 or higher). To compile with Tensorflow support: -1. Download the Tensorflow 1.15 precompiled libraries for your operating system from one of the following. (Note that GPU versions require CUDA drivers; see https://www.tensorflow.org/install/lang_c for more information.) - Linux/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-1.15.0.tar.gz - Linux/GPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-1.15.0.tar.gz - Windows/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-windows-x86_64-1.15.0.zip - Windows/GPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-windows-x86_64-1.15.0.zip - MacOS/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-darwin-x86_64-1.15.0.tar.gz +1. Download the Tensorflow 2.5.0 precompiled libraries for your operating system from one of the following. (Note that GPU versions require CUDA drivers; see https://www.tensorflow.org/install/lang_c for more information.) + Linux/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-2.5.0.tar.gz + Linux/GPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-2.5.0.tar.gz + Windows/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-windows-x86_64-2.5.0.zip + Windows/GPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-windows-x86_64-2.5.0.zip + MacOS/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-darwin-x86_64-2.5.0.tar.gz MacOS/GPU: None available. 2. Unzip/untar the archive into a suitable directory (~/mydir/ is used here as an example), and add the following environment variables: diff --git a/scripting_documentation/RosettaScripts/xsd/filter_FragmentScoreFilter_type.md b/scripting_documentation/RosettaScripts/xsd/filter_FragmentScoreFilter_type.md index cf17faf3b..c4110da47 100644 --- a/scripting_documentation/RosettaScripts/xsd/filter_FragmentScoreFilter_type.md +++ b/scripting_documentation/RosettaScripts/xsd/filter_FragmentScoreFilter_type.md @@ -13,7 +13,7 @@ Filter based on any score that can be calculated in fragment_picker. outputs_name="(pose &string;)" csblast="(&string;)" blast_pgp="(&string;)" placeholder_seqs="(&string;)" sparks-x="(&string;)" sparks-x_query="(&string;)" psipred="(&string;)" - vall_path="(/scratch/benchmark/W.hojo-1/rosetta.Hojo-1/master/main/database//sampling/vall.jul19.2011.gz &string;)" + vall_path="(/home/vmulligan/rosetta_devcopy_local2/Rosetta/main/database//sampling/vall.jul19.2011.gz &string;)" frags_scoring_config="(&string;)" n_frags="(200 &non_negative_integer;)" n_candidates="(1000 &non_negative_integer;)" print_to_pdb="(false &xs:boolean;)" diff --git a/scripting_documentation/RosettaScripts/xsd/mover_trRosettaProtocol_type.md b/scripting_documentation/RosettaScripts/xsd/mover_trRosettaProtocol_type.md index febc4e32e..9e5c44bcb 100644 --- a/scripting_documentation/RosettaScripts/xsd/mover_trRosettaProtocol_type.md +++ b/scripting_documentation/RosettaScripts/xsd/mover_trRosettaProtocol_type.md @@ -5,14 +5,14 @@ _Autogenerated Tag Syntax Documentation:_ --- Implements the full trRosetta protocol, as described in Yang et al. (2020) Improved protein structure prediction using predicted interresidue orientations. Proc. Natl. Acad. Sci. USA 117(3):1496-503. https://doi.org/10.1073/pnas.1914677117. This mover takes as input a multiple sequence alignment, runs the trRosetta neural network, generates distance and angle constraints between pairs of residues, and carries out energy-minimization to produce a structure. Note that this mover deletes and replaces the input structure. If a native structure is provided, the mover tags the output structure with the RMSD to native. -The trRosettaProtocol mover requires compilation with Tensorflow support. To compile with Tensorflow support: +The trRosettaProtocol mover requires compilation with Tensorflow 2 support (version 2.5.0 or higher). To compile with Tensorflow support: -1. Download the Tensorflow 1.15 precompiled libraries for your operating system from one of the following. (Note that GPU versions require CUDA drivers; see https://www.tensorflow.org/install/lang_c for more information.) - Linux/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-1.15.0.tar.gz - Linux/GPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-1.15.0.tar.gz - Windows/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-windows-x86_64-1.15.0.zip - Windows/GPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-windows-x86_64-1.15.0.zip - MacOS/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-darwin-x86_64-1.15.0.tar.gz +1. Download the Tensorflow 2.5.0 precompiled libraries for your operating system from one of the following. (Note that GPU versions require CUDA drivers; see https://www.tensorflow.org/install/lang_c for more information.) + Linux/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-2.5.0.tar.gz + Linux/GPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-2.5.0.tar.gz + Windows/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-windows-x86_64-2.5.0.zip + Windows/GPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-windows-x86_64-2.5.0.zip + MacOS/CPU: https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-darwin-x86_64-2.5.0.tar.gz MacOS/GPU: None available. 2. Unzip/untar the archive into a suitable directory (~/mydir/ is used here as an example), and add the following environment variables: