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metatensor 0.1.1 documentation
metatensor 0.1.1 documentation

Content:

  • Getting started
    • Installing metatensor
    • Goals of this library
    • Core concepts
  • API reference
    • Python API reference
      • TensorMap
      • TensorBlock
      • Labels
      • Serialization
      • Data arrays
      • Miscelaneous
      • Changelog
    • Python operations reference
      • Checks
        • checks_enabled()
        • unsafe_enable_checks()
        • unsafe_disable_checks()
      • Creation operations
        • empty_like()
        • ones_like()
        • zeros_like()
        • random_like()
        • block_from_array()
      • Linear algebra
        • dot()
        • lstsq()
        • solve()
      • Logic function
        • allclose()
        • equal()
        • equal_metadata()
      • Manipulation operations
        • detach()
        • drop_blocks()
        • join()
        • manipulate dimension
        • one_hot()
        • remove_gradients()
        • requires_grad()
        • samples reduction
        • slice()
        • split()
      • Mathematical functions
        • abs()
        • add()
        • divide()
        • multiply()
        • pow()
        • subtract()
      • Set operations
        • unique_metadata()
        • sort()
      • Changelog
    • C++ API reference
      • TensorMap
      • Labels
      • TensorBlock
      • Data arrays
      • Miscelaneous
      • Changelog
    • C API reference
      • TensorMap
      • Labels
      • TensorBlock
      • Data arrays
      • Miscelaneous
      • Changelog
    • Rust API reference
    • TorchScript API reference
      • TensorMap
      • TensorBlock
      • Labels
      • Serialization
      • Changelog
      • TorchScript C++ API reference
        • TensorMap
        • TensorBlock
        • Labels
        • Miscellaneous
  • Atomistic Models
    • API reference
      • Systems
      • Models
      • Atomic Simulation Environment (ASE) integration
      • C++ API reference
        • Systems
        • Models
    • Standard model outputs
    • Tutorials
      • Exporting a model
      • Running Molecular Dynamics with ASE
  • Developer documentation
    • Getting started
    • Code organization
    • Version number management
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API reference#

The atomistic machine learning models capabilities of metatensor are part of the TorchScript API, and are installed when installing the TorchScript API.

These capabilities can be used from either Python or C++. The Python API is documented below, and is part of the metatensor.torch.atomistic module.

  • Systems
  • Models
  • Atomic Simulation Environment (ASE) integration

C++ API reference#

The C++ API can be accessed by including <metatensor/torch/atomistic.hpp>.

  • C++ API reference
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Copyright © 2024, Guillaume Fraux, Davide Tisi, Philip Loche, Joseph W. Abbott, Jigyasa Nigam, Chiheb Ben Mahmoud
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  • API reference
    • C++ API reference