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:caption: Usage
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:maxdepth: 1
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quick_start
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unified_memory
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using_streams
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usage/quick_start
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usage/unified_memory
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usage/using_streams
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usage/numpy
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.. toctree::
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:caption: Examples
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.. _indexing:
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Indexing Arrays
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===============
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.. currentmodule:: mlx.core
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For the most part, indexing an MLX :obj:`array` works the same as indexing a
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NumPy :obj:`numpy.ndarray`. See the `NumPy documentation
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<https://numpy.org/doc/stable/user/basics.indexing.html>`_ for more details on
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how that works
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@ -1,59 +0,0 @@
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mlx.nn.Module
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=============
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.. currentmodule:: mlx.nn
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.. autoclass:: Module
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.. automethod:: __init__
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.. rubric:: Methods
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.. autosummary::
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~Module.__init__
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~Module.apply
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~Module.apply_to_modules
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~Module.children
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~Module.clear
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~Module.copy
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~Module.eval
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~Module.filter_and_map
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~Module.freeze
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~Module.fromkeys
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~Module.get
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~Module.is_module
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~Module.items
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~Module.keys
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~Module.leaf_modules
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~Module.load_weights
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~Module.modules
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~Module.named_modules
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~Module.parameters
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~Module.pop
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~Module.popitem
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~Module.save_weights
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~Module.setdefault
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~Module.train
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~Module.trainable_parameter_filter
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~Module.trainable_parameters
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~Module.unfreeze
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~Module.update
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~Module.update_modules
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~Module.valid_child_filter
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~Module.valid_parameter_filter
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~Module.values
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.. rubric:: Attributes
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.. autosummary::
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~Module.training
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@ -1,8 +0,0 @@
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mlx.nn.losses.smooth\_l1\_loss
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==============================
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.. currentmodule:: mlx.nn.losses
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.. autoclass:: smooth_l1_loss
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103
docs/build/html/_sources/usage/numpy.rst
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docs/build/html/_sources/usage/numpy.rst
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@ -0,0 +1,103 @@
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.. _numpy:
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Conversion to NumPy and Other Frameworks
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========================================
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MLX array implements the `Python Buffer Protocol <https://docs.python.org/3/c-api/buffer.html>`_.
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Let's convert an array to NumPy and back.
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.. code-block:: python
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import mlx.core as mx
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import numpy as np
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a = mx.arange(3)
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b = np.array(a) # copy of a
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c = mx.array(b) # copy of b
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.. note::
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Since NumPy does not support ``bfloat16`` arrays, you will need to convert to ``float16`` or ``float32`` first:
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``np.array(a.astype(mx.float32))``.
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Otherwise, you will receive an error like: ``Item size 2 for PEP 3118 buffer format string does not match the dtype V item size 0.``
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By default, NumPy copies data to a new array. This can be prevented by creating an array view:
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.. code-block:: python
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a = mx.arange(3)
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a_view = np.array(a, copy=False)
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print(a_view.flags.owndata) # False
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a_view[0] = 1
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print(a[0].item()) # 1
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A NumPy array view is a normal NumPy array, except that it does not own its memory.
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This means writing to the view is reflected in the original array.
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While this is quite powerful to prevent copying arrays, it should be noted that external changes to the memory of arrays cannot be reflected in gradients.
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Let's demonstrate this in an example:
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.. code-block:: python
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def f(x):
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x_view = np.array(x, copy=False)
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x_view[:] *= x_view # modify memory without telling mx
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return x.sum()
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x = mx.array([3.0])
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y, df = mx.value_and_grad(f)(x)
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print("f(x) = x² =", y.item()) # 9.0
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print("f'(x) = 2x !=", df.item()) # 1.0
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The function ``f`` indirectly modifies the array ``x`` through a memory view.
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However, this modification is not reflected in the gradient, as seen in the last line outputting ``1.0``,
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representing the gradient of the sum operation alone.
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The squaring of ``x`` occurs externally to MLX, meaning that no gradient is incorporated.
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It's important to note that a similar issue arises during array conversion and copying.
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For instance, a function defined as ``mx.array(np.array(x)**2).sum()`` would also result in an incorrect gradient,
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even though no in-place operations on MLX memory are executed.
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PyTorch
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-------
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PyTorch supports the buffer protocol, but it requires an explicit :obj:`memoryview`.
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.. code-block:: python
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import mlx.core as mx
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import torch
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a = mx.arange(3)
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b = torch.tensor(memoryview(a))
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c = mx.array(b.numpy())
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Conversion from PyTorch tensors back to arrays must be done via intermediate NumPy arrays with ``numpy()``.
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JAX
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---
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JAX fully supports the buffer protocol.
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.. code-block:: python
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import mlx.core as mx
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import jax.numpy as jnp
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a = mx.arange(3)
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b = jnp.array(a)
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c = mx.array(b)
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TensorFlow
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----------
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TensorFlow supports the buffer protocol, but it requires an explicit :obj:`memoryview`.
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.. code-block:: python
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import mlx.core as mx
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import tensorflow as tf
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a = mx.arange(3)
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b = tf.constant(memoryview(a))
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c = mx.array(b)
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7
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</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
|
||||
<ul class="nav bd-sidenav">
|
||||
<li class="toctree-l1"><a class="reference internal" href="../quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/numpy.html">Conversion to NumPy and Other Frameworks</a></li>
|
||||
</ul>
|
||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Examples</span></p>
|
||||
<ul class="nav bd-sidenav">
|
||||
|
||||
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</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
|
||||
<ul class="nav bd-sidenav">
|
||||
<li class="toctree-l1"><a class="reference internal" href="../quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/numpy.html">Conversion to NumPy and Other Frameworks</a></li>
|
||||
</ul>
|
||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Examples</span></p>
|
||||
<ul class="nav bd-sidenav">
|
||||
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||||
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||||
<link rel="index" title="Index" href="../genindex.html" />
|
||||
<link rel="search" title="Search" href="../search.html" />
|
||||
<link rel="next" title="Multi-Layer Perceptron" href="mlp.html" />
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||||
<link rel="prev" title="Using Streams" href="../using_streams.html" />
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<link rel="prev" title="Conversion to NumPy and Other Frameworks" href="../usage/numpy.html" />
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<meta name="viewport" content="width=device-width, initial-scale=1"/>
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<meta name="docsearch:language" content="en"/>
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</head>
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||||
@ -147,9 +147,10 @@
|
||||
</ul>
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||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
|
||||
<ul class="nav bd-sidenav">
|
||||
<li class="toctree-l1"><a class="reference internal" href="../quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/numpy.html">Conversion to NumPy and Other Frameworks</a></li>
|
||||
</ul>
|
||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Examples</span></p>
|
||||
<ul class="current nav bd-sidenav">
|
||||
@ -705,12 +706,12 @@ examples are available in the MLX GitHub repo.</p>
|
||||
|
||||
<div class="prev-next-area">
|
||||
<a class="left-prev"
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href="../using_streams.html"
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href="../usage/numpy.html"
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title="previous page">
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<i class="fa-solid fa-angle-left"></i>
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<div class="prev-next-info">
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<p class="prev-next-subtitle">previous</p>
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||||
<p class="prev-next-title">Using Streams</p>
|
||||
<p class="prev-next-title">Conversion to NumPy and Other Frameworks</p>
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||||
</div>
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||||
</a>
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||||
<a class="right-next"
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||||
|
||||
@ -147,9 +147,10 @@
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</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
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||||
<ul class="nav bd-sidenav">
|
||||
<li class="toctree-l1"><a class="reference internal" href="../quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/numpy.html">Conversion to NumPy and Other Frameworks</a></li>
|
||||
</ul>
|
||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Examples</span></p>
|
||||
<ul class="current nav bd-sidenav">
|
||||
|
||||
7
docs/build/html/examples/mlp.html
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</ul>
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||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
|
||||
<ul class="nav bd-sidenav">
|
||||
<li class="toctree-l1"><a class="reference internal" href="../quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="../usage/numpy.html">Conversion to NumPy and Other Frameworks</a></li>
|
||||
</ul>
|
||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Examples</span></p>
|
||||
<ul class="current nav bd-sidenav">
|
||||
|
||||
7
docs/build/html/genindex.html
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docs/build/html/genindex.html
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</ul>
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||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
|
||||
<ul class="nav bd-sidenav">
|
||||
<li class="toctree-l1"><a class="reference internal" href="quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="usage/quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="usage/unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="usage/using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="usage/numpy.html">Conversion to NumPy and Other Frameworks</a></li>
|
||||
</ul>
|
||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Examples</span></p>
|
||||
<ul class="nav bd-sidenav">
|
||||
|
||||
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</ul>
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||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
|
||||
<ul class="nav bd-sidenav">
|
||||
<li class="toctree-l1"><a class="reference internal" href="quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="usage/quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="usage/unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="usage/using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="usage/numpy.html">Conversion to NumPy and Other Frameworks</a></li>
|
||||
</ul>
|
||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Examples</span></p>
|
||||
<ul class="nav bd-sidenav">
|
||||
@ -662,9 +663,10 @@ are the CPU and GPU.</p>
|
||||
<div class="toctree-wrapper compound">
|
||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
|
||||
<ul>
|
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<li class="toctree-l1"><a class="reference internal" href="quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="usage/quick_start.html">Quick Start Guide</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="usage/unified_memory.html">Unified Memory</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="usage/using_streams.html">Using Streams</a></li>
|
||||
<li class="toctree-l1"><a class="reference internal" href="usage/numpy.html">Conversion to NumPy and Other Frameworks</a></li>
|
||||
</ul>
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</div>
|
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<div class="toctree-wrapper compound">
|
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<!DOCTYPE html>
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<html lang="en" data-content_root="" >
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<head>
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<meta charset="utf-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
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<title>Indexing Arrays — MLX 0.0.6 documentation</title>
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<script data-cfasync="false">
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document.documentElement.dataset.mode = localStorage.getItem("mode") || "";
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document.documentElement.dataset.theme = localStorage.getItem("theme") || "light";
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@ -634,7 +635,7 @@ document.write(`
|
||||
<h1>mlx.core.eye<a class="headerlink" href="#mlx-core-eye" title="Permalink to this heading">#</a></h1>
|
||||
<dl class="py function">
|
||||
<dt class="sig sig-object py" id="mlx.core.eye">
|
||||
<span class="sig-prename descclassname"><span class="pre">mlx.core.</span></span><span class="sig-name descname"><span class="pre">eye</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">m</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="mlx.core.Dtype.html#mlx.core.Dtype" title="mlx.core.Dtype"><span class="pre">Dtype</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stream</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="mlx.core.Stream.html#mlx.core.Stream" title="mlx.core.Stream"><span class="pre">Stream</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="mlx.core.Device.html#mlx.core.Device" title="mlx.core.Device"><span class="pre">Device</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="mlx.core.array.html#mlx.core.array" title="mlx.core.array"><span class="pre">array</span></a></span></span><a class="headerlink" href="#mlx.core.eye" title="Permalink to this definition">#</a></dt>
|
||||
<span class="sig-prename descclassname"><span class="pre">mlx.core.</span></span><span class="sig-name descname"><span class="pre">eye</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">m</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="mlx.core.Dtype.html#mlx.core.Dtype" title="mlx.core.Dtype"><span class="pre">Dtype</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">float32</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">stream</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="mlx.core.Stream.html#mlx.core.Stream" title="mlx.core.Stream"><span class="pre">Stream</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="mlx.core.Device.html#mlx.core.Device" title="mlx.core.Device"><span class="pre">Device</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="mlx.core.array.html#mlx.core.array" title="mlx.core.array"><span class="pre">array</span></a></span></span><a class="headerlink" href="#mlx.core.eye" title="Permalink to this definition">#</a></dt>
|
||||
<dd><p>Create an identity matrix or a general diagonal matrix.</p>
|
||||
<dl class="field-list simple">
|
||||
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
|
||||
|
||||
@ -147,9 +147,10 @@
|
||||
</ul>
|
||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
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||||
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|
||||
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||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Examples</span></p>
|
||||
<ul class="nav bd-sidenav">
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||||
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||||
@ -147,9 +147,10 @@
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||||
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@ -147,9 +147,10 @@
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<li class="toctree-l1"><a class="reference internal" href="../../using_streams.html">Using Streams</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../../usage/quick_start.html">Quick Start Guide</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../../usage/unified_memory.html">Unified Memory</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../../usage/using_streams.html">Using Streams</a></li>
|
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<li class="toctree-l1"><a class="reference internal" href="../../usage/numpy.html">Conversion to NumPy and Other Frameworks</a></li>
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</ul>
|
||||
<p aria-level="2" class="caption" role="heading"><span class="caption-text">Examples</span></p>
|
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<ul class="nav bd-sidenav">
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@ -147,9 +147,10 @@
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</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
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<li class="toctree-l1"><a class="reference internal" href="../../quick_start.html">Quick Start Guide</a></li>
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@ -147,9 +147,10 @@
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
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||||
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<li class="toctree-l1"><a class="reference internal" href="../../unified_memory.html">Unified Memory</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../using_streams.html">Using Streams</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../usage/quick_start.html">Quick Start Guide</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../usage/unified_memory.html">Unified Memory</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../usage/using_streams.html">Using Streams</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../usage/numpy.html">Conversion to NumPy and Other Frameworks</a></li>
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||||
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||||
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||||
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||||
@ -147,9 +147,10 @@
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||||
</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
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||||
<ul class="nav bd-sidenav">
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<li class="toctree-l1"><a class="reference internal" href="../../quick_start.html">Quick Start Guide</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../../unified_memory.html">Unified Memory</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../using_streams.html">Using Streams</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../usage/quick_start.html">Quick Start Guide</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../usage/unified_memory.html">Unified Memory</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../usage/using_streams.html">Using Streams</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../usage/numpy.html">Conversion to NumPy and Other Frameworks</a></li>
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||||
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||||
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|
||||
<ul class="nav bd-sidenav">
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||||
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||||
@ -147,9 +147,10 @@
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||||
</ul>
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<p aria-level="2" class="caption" role="heading"><span class="caption-text">Usage</span></p>
|
||||
<ul class="nav bd-sidenav">
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<li class="toctree-l1"><a class="reference internal" href="../../quick_start.html">Quick Start Guide</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../using_streams.html">Using Streams</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../usage/quick_start.html">Quick Start Guide</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../usage/unified_memory.html">Unified Memory</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../usage/using_streams.html">Using Streams</a></li>
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||||
<li class="toctree-l1"><a class="reference internal" href="../../usage/numpy.html">Conversion to NumPy and Other Frameworks</a></li>
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