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Metatensor
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  • Metatensor’s goals
  • Installation
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    • Overview
    • Python API reference
      • TensorMap
      • TensorBlock
      • Labels
      • Serialization
      • Data arrays
      • Miscellaneous
    • C++ API reference
      • TensorMap
      • Labels
      • TensorBlock
      • Data arrays
      • Miscellaneous
    • C API reference
      • TensorMap
      • Labels
      • TensorBlock
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      • Miscellaneous
    • Rust API reference
    • Tutorials
      • First steps with metatensor
      • Handling sparsity
      • Managing gradients
    • Changelog
  • Operations
    • Operations and PyTorch
    • API reference
      • Creation operations
        • empty_like()
        • ones_like()
        • zeros_like()
        • random_like()
        • block_from_array()
      • Linear algebra
        • dot()
        • lstsq()
        • solve()
      • Logic function
        • allclose()
        • equal()
        • equal_metadata()
        • is_contiguous()
      • Manipulation operations
        • detach()
        • drop_blocks()
        • filter_blocks()
        • join()
        • make_contiguous()
        • 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()
      • Checks
    • Changelog
  • TorchScript backend
    • API reference
      • TensorMap
      • TensorBlock
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      • Serialization
      • TorchScript C++ API reference
        • TensorMap
        • TensorBlock
        • Labels
        • Miscellaneous
    • Changelog
  • Learning utilities
    • API reference
      • Data utilites
      • Neural Network
    • Tutorials
      • Datasets and data loaders
      • Using IndexedDataset
    • Changelog
  • Atomistic applications
    • Overview
    • API reference
      • Systems
      • Models
        • Exporting models
        • Information about models
      • Atomic Simulation Environment (ASE) integration
      • Serialization
      • C++ API reference
        • Systems
        • Models
    • Standard model outputs
      • Energy
      • Features
    • Simulation engines
      • ASE
      • Chemiscope
      • i-PI
      • LAMMPS
      • PLUMED
    • Tutorials
      • Exporting a model
      • Running Molecular Dynamics with ASE
      • Creating models that use neighbor lists
      • Profiling your models
  • Developer documentation
    • Getting started
    • Code organization
    • Version number management
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Tutorials¶

First steps with metatensor

First steps with metatensor

Handling sparsity

Handling sparsity

Managing gradients

Managing gradients

Download all examples in Python source code: core_python.zip

Download all examples in Jupyter notebooks: core_jupyter.zip

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