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| <div class="section" id="data-loading-api"> |
| <span id="data-loading-api"></span><h1>Data Loading API<a class="headerlink" href="#data-loading-api" title="Permalink to this headline">¶</a></h1> |
| <div class="section" id="overview"> |
| <span id="overview"></span><h2>Overview<a class="headerlink" href="#overview" title="Permalink to this headline">¶</a></h2> |
| <p>This document summarizes supported data formats and iterator APIs to read the |
| data including</p> |
| <table border="1" class="longtable docutils"> |
| <colgroup> |
| <col width="10%"/> |
| <col width="90%"/> |
| </colgroup> |
| <tbody valign="top"> |
| <tr class="row-odd"><td><a class="reference internal" href="#module-mxnet.io" title="mxnet.io"><code class="xref py py-obj docutils literal"><span class="pre">mxnet.io</span></code></a></td> |
| <td>Data iterators for common data formats.</td> |
| </tr> |
| <tr class="row-even"><td><a class="reference internal" href="#module-mxnet.recordio" title="mxnet.recordio"><code class="xref py py-obj docutils literal"><span class="pre">mxnet.recordio</span></code></a></td> |
| <td>Read and write for the RecordIO data format.</td> |
| </tr> |
| <tr class="row-odd"><td><a class="reference internal" href="../image/image.html#module-mxnet.image" title="mxnet.image"><code class="xref py py-obj docutils literal"><span class="pre">mxnet.image</span></code></a></td> |
| <td>Image Iterators and image augmentation functions</td> |
| </tr> |
| </tbody> |
| </table> |
| <p>First, let’s see how to write an iterator for a new data format. |
| The following iterator can be used to train a symbol whose input data variable has |
| name <code class="docutils literal"><span class="pre">data</span></code> and input label variable has name <code class="docutils literal"><span class="pre">softmax_label</span></code>. |
| The iterator also provides information about the batch, including the |
| shapes and name.</p> |
| <div class="highlight-python"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">nd_iter</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">NDArrayIter</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="p">{</span><span class="s1">'data'</span><span class="p">:</span><span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span><span class="mi">10</span><span class="p">))},</span> |
| <span class="gp">... </span> <span class="n">label</span><span class="o">=</span><span class="p">{</span><span class="s1">'softmax_label'</span><span class="p">:</span><span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">100</span><span class="p">,))},</span> |
| <span class="gp">... </span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">25</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="k">print</span><span class="p">(</span><span class="n">nd_iter</span><span class="o">.</span><span class="n">provide_data</span><span class="p">)</span> |
| <span class="go">[DataDesc[data,(25, 10L),<type 'numpy.float32'>,NCHW]]</span> |
| <span class="gp">>>> </span><span class="k">print</span><span class="p">(</span><span class="n">nd_iter</span><span class="o">.</span><span class="n">provide_label</span><span class="p">)</span> |
| <span class="go">[DataDesc[softmax_label,(25,),<type 'numpy.float32'>,NCHW]]</span> |
| </pre></div> |
| </div> |
| <p>Let’s see a complete example of how to use data iterator in model training.</p> |
| <div class="highlight-python"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">data</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'data'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">label</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">Variable</span><span class="p">(</span><span class="s1">'softmax_label'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">fullc</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">FullyConnected</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">num_hidden</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">loss</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">SoftmaxOutput</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">fullc</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">label</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">mod</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">mod</span><span class="o">.</span><span class="n">Module</span><span class="p">(</span><span class="n">loss</span><span class="p">,</span> <span class="n">data_names</span><span class="o">=</span><span class="p">[</span><span class="s1">'data'</span><span class="p">],</span> <span class="n">label_names</span><span class="o">=</span><span class="p">[</span><span class="s1">'softmax_label'</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">mod</span><span class="o">.</span><span class="n">bind</span><span class="p">(</span><span class="n">data_shapes</span><span class="o">=</span><span class="n">nd_iter</span><span class="o">.</span><span class="n">provide_data</span><span class="p">,</span> <span class="n">label_shapes</span><span class="o">=</span><span class="n">nd_iter</span><span class="o">.</span><span class="n">provide_label</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">mod</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">nd_iter</span><span class="p">,</span> <span class="n">num_epoch</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p>A detailed tutorial is available at |
| <a class="reference external" href="https://mxnet.incubator.apache.org/tutorials/basic/data.html">Iterators - Loading data</a>.</p> |
| </div> |
| <div class="section" id="data-iterators"> |
| <span id="data-iterators"></span><h2>Data iterators<a class="headerlink" href="#data-iterators" title="Permalink to this headline">¶</a></h2> |
| <table border="1" class="longtable docutils"> |
| <colgroup> |
| <col width="10%"/> |
| <col width="90%"/> |
| </colgroup> |
| <tbody valign="top"> |
| <tr class="row-odd"><td><a class="reference internal" href="#mxnet.io.NDArrayIter" title="mxnet.io.NDArrayIter"><code class="xref py py-obj docutils literal"><span class="pre">io.NDArrayIter</span></code></a></td> |
| <td>Returns an iterator for <code class="docutils literal"><span class="pre">mx.nd.NDArray</span></code>, <code class="docutils literal"><span class="pre">numpy.ndarray</span></code>, <code class="docutils literal"><span class="pre">h5py.Dataset</span></code> <code class="docutils literal"><span class="pre">mx.nd.sparse.CSRNDArray</span></code> or <code class="docutils literal"><span class="pre">scipy.sparse.csr_matrix</span></code>.</td> |
| </tr> |
| <tr class="row-even"><td><a class="reference internal" href="#mxnet.io.CSVIter" title="mxnet.io.CSVIter"><code class="xref py py-obj docutils literal"><span class="pre">io.CSVIter</span></code></a></td> |
| <td>b”Returns the CSV file iterator.nnIn this function, the <cite>data_shape</cite> parameter is used to set the shape of each line of the input data.nIf a row in an input file is <cite>1,2,3,4,5,6`</cite> and <cite>data_shape</cite> is (3,2), that rownwill be reshaped, yielding the array [[1,2],[3,4],[5,6]] of shape (3,2).nnBy default, the <cite>CSVIter</cite> has <cite>round_batch</cite> parameter set to <code class="docutils literal"><span class="pre">True</span></code>. So, if <cite>batch_size</cite>nis 3 and there are 4 total rows in CSV file, 2 more examplesnare consumed at the first round. If <cite>reset</cite> function is called after first round,nthe call is ignored and remaining examples are returned in the second round.nnIf one wants all the instances in the second round after calling <cite>reset</cite>, make surento set <cite>round_batch</cite> to False.nnIf <code class="docutils literal"><span class="pre">data_csv</span> <span class="pre">=</span> <span class="pre">'data/'</span></code> is set, then all the files in this directory will be read.nn``reset()`` is expected to be called only after a complete pass of data.nnExamples::nn // Contents of CSV file <code class="docutils literal"><span class="pre">data/data.csv</span></code>.n 1,2,3n 2,3,4n 3,4,5n 4,5,6nn // Creates a <cite>CSVIter</cite> with <cite>batch_size`=2 and default `round_batch`=True.n CSVIter = mx.io.CSVIter(data_csv = ‘data/data.csv’, data_shape = (3,),n batch_size = 2)nn // Two batches read from the above iterator are as follows:n [[ 1. 2. 3.]n [ 2. 3. 4.]]n [[ 3. 4. 5.]n [ 4. 5. 6.]]nn // Creates a `CSVIter</cite> with default <cite>round_batch</cite> set to True.n CSVIter = mx.io.CSVIter(data_csv = ‘data/data.csv’, data_shape = (3,),n batch_size = 3)nn // Two batches read from the above iterator in the first pass are as follows:n [[1. 2. 3.]n [2. 3. 4.]n [3. 4. 5.]]nn [[4. 5. 6.]n [1. 2. 3.]n [2. 3. 4.]]nn // Now, <cite>reset</cite> method is called.n CSVIter.reset()nn // Batch read from the above iterator in the second pass is as follows:n [[ 3. 4. 5.]n [ 4. 5. 6.]n [ 1. 2. 3.]]nn // Creates a <cite>CSVIter</cite> with <cite>round_batch`=False.n CSVIter = mx.io.CSVIter(data_csv = ‘data/data.csv’, data_shape = (3,),n batch_size = 3, round_batch=False)nn // Contents of two batches read from the above iterator in both passes, after callingn // `reset</cite> method before second pass, is as follows:n [[1. 2. 3.]n [2. 3. 4.]n [3. 4. 5.]]nn [[4. 5. 6.]n [2. 3. 4.]n [3. 4. 5.]]nnnnDefined in src/io/iter_csv.cc:L223”</td> |
| </tr> |
| <tr class="row-odd"><td><a class="reference internal" href="#mxnet.io.LibSVMIter" title="mxnet.io.LibSVMIter"><code class="xref py py-obj docutils literal"><span class="pre">io.LibSVMIter</span></code></a></td> |
| <td>b”Returns the LibSVM iterator which returns data with <cite>csr</cite>nstorage type. This iterator is experimental and should be used with care.nnThe input data is stored in a format similar to LibSVM file format, except that the <strong>indicesnare expected to be zero-based instead of one-based, and the column indices for each row arenexpected to be sorted in ascending order</strong>. Details of the LibSVM format are availablen`here. <<a class="reference external" href="https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/">https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/</a>>`_nnnThe <cite>data_shape</cite> parameter is used to set the shape of each line of the data.nThe dimension of both <cite>data_shape</cite> and <cite>label_shape</cite> are expected to be 1.nnThe <cite>data_libsvm</cite> parameter is used to set the path input LibSVM file.nWhen it is set to a directory, all the files in the directory will be read.nnWhen <cite>label_libsvm</cite> is set to <code class="docutils literal"><span class="pre">NULL</span></code>, both data and label are read from the file specifiednby <cite>data_libsvm</cite>. In this case, the data is stored in <cite>csr</cite> storage type, while the label is a 1Dndense array.nnThe <cite>LibSVMIter</cite> only support <cite>round_batch</cite> parameter set to <code class="docutils literal"><span class="pre">True</span></code>. Therefore, if <cite>batch_size</cite>nis 3 and there are 4 total rows in libsvm file, 2 more examples are consumed at the first round.nnWhen <cite>num_parts</cite> and <cite>part_index</cite> are provided, the data is split into <cite>num_parts</cite> partitions,nand the iterator only reads the <cite>part_index</cite>-th partition. However, the partitions are notnguaranteed to be even.nn``reset()`` is expected to be called only after a complete pass of data.nnExample::nn # Contents of libsvm file <code class="docutils literal"><span class="pre">data.t</span></code>.n 1.0 0:0.5 2:1.2n -2.0n -3.0 0:0.6 1:2.4 2:1.2n 4 2:-1.2nn # Creates a <cite>LibSVMIter</cite> with <cite>batch_size`=3.n >>> data_iter = mx.io.LibSVMIter(data_libsvm = ‘data.t’, data_shape = (3,), batch_size = 3)n # The data of the first batch is stored in csr storage typen >>> batch = data_iter.next()n >>> csr = batch.data[0]n <CSRNDArray 3x3 @cpu(0)>n >>> csr.asnumpy()n [[ 0.5 0. 1.2 ]n [ 0. 0. 0. ]n [ 0.6 2.4 1.2]]n # The label of first batchn >>> label = batch.label[0]n >>> labeln [ 1. -2. -3.]n <NDArray 3 @cpu(0)>nn >>> second_batch = data_iter.next()n # The data of the second batchn >>> second_batch.data[0].asnumpy()n [[ 0. 0. -1.2 ]n [ 0.5 0. 1.2 ]n [ 0. 0. 0. ]]n # The label of the second batchn >>> second_batch.label[0].asnumpy()n [ 4. 1. -2.]nn >>> data_iter.reset()n # To restart the iterator for the second pass of the datannWhen `label_libsvm</cite> is set to the path to another LibSVM file,ndata is read from <cite>data_libsvm</cite> and label from <cite>label_libsvm</cite>.nIn this case, both data and label are stored in the csr format.nIf the label column in the <cite>data_libsvm</cite> file is ignored.nnExample::nn # Contents of libsvm file <code class="docutils literal"><span class="pre">label.t</span></code>n 1.0n -2.0 0:0.125n -3.0 2:1.2n 4 1:1.0 2:-1.2nn # Creates a <cite>LibSVMIter</cite> with specified label filen >>> data_iter = mx.io.LibSVMIter(data_libsvm = ‘data.t’, data_shape = (3,),n label_libsvm = ‘label.t’, label_shape = (3,), batch_size = 3)nn # Both data and label are in csr storage typen >>> batch = data_iter.next()n >>> csr_data = batch.data[0]n <CSRNDArray 3x3 @cpu(0)>n >>> csr_data.asnumpy()n [[ 0.5 0. 1.2 ]n [ 0. 0. 0. ]n [ 0.6 2.4 1.2 ]]n >>> csr_label = batch.label[0]n <CSRNDArray 3x3 @cpu(0)>n >>> csr_label.asnumpy()n [[ 0. 0. 0. ]n [ 0.125 0. 0. ]n [ 0. 0. 1.2 ]]nnnnDefined in src/io/iter_libsvm.cc:L298”</td> |
| </tr> |
| <tr class="row-even"><td><a class="reference internal" href="#mxnet.io.ImageRecordIter" title="mxnet.io.ImageRecordIter"><code class="xref py py-obj docutils literal"><span class="pre">io.ImageRecordIter</span></code></a></td> |
| <td>b’Iterates on image RecordIO filesnnReads batches of images from .rec RecordIO files. One can use <code class="docutils literal"><span class="pre">im2rec.py</span></code> tooln(in tools/) to pack raw image files into RecordIO files. This iterator is lessnflexible to customization but is fast and has lot of language bindings. Toniterate over raw images directly use <code class="docutils literal"><span class="pre">ImageIter</span></code> instead (in Python).nnExample::nn data_iter = mx.io.ImageRecordIter(n path_imgrec=”./sample.rec”, # The target record file.n data_shape=(3, 227, 227), # Output data shape; 227x227 region will be cropped from the original image.n batch_size=4, # Number of items per batch.n resize=256 # Resize the shorter edge to 256 before cropping.n # You can specify more augmentation options. Use help(mx.io.ImageRecordIter) to see all the options.n )n # You can now use the data_iter to access batches of images.n batch = data_iter.next() # first batch.n images = batch.data[0] # This will contain 4 (=batch_size) images each of 3x227x227.n # process the imagesn ...n data_iter.reset() # To restart the iterator from the beginning.nnnnDefined in src/io/iter_image_recordio_2.cc:L748’</td> |
| </tr> |
| <tr class="row-odd"><td><a class="reference internal" href="#mxnet.io.ImageRecordUInt8Iter" title="mxnet.io.ImageRecordUInt8Iter"><code class="xref py py-obj docutils literal"><span class="pre">io.ImageRecordUInt8Iter</span></code></a></td> |
| <td>b’Iterating on image RecordIO filesnnThis iterator is identical to <code class="docutils literal"><span class="pre">ImageRecordIter</span></code> except for using <code class="docutils literal"><span class="pre">uint8</span></code> asnthe data type instead of <code class="docutils literal"><span class="pre">float</span></code>.nnnnDefined in src/io/iter_image_recordio_2.cc:L765’</td> |
| </tr> |
| <tr class="row-even"><td><a class="reference internal" href="#mxnet.io.MNISTIter" title="mxnet.io.MNISTIter"><code class="xref py py-obj docutils literal"><span class="pre">io.MNISTIter</span></code></a></td> |
| <td>b’Iterating on the MNIST dataset.nnOne can download the dataset from <a class="reference external" href="http://yann.lecun.com/exdb/mnist/nnnnDefined">http://yann.lecun.com/exdb/mnist/nnnnDefined</a> in src/io/iter_mnist.cc:L265’</td> |
| </tr> |
| <tr class="row-odd"><td><a class="reference internal" href="#mxnet.recordio.MXRecordIO" title="mxnet.recordio.MXRecordIO"><code class="xref py py-obj docutils literal"><span class="pre">recordio.MXRecordIO</span></code></a></td> |
| <td>Reads/writes <cite>RecordIO</cite> data format, supporting sequential read and write.</td> |
| </tr> |
| <tr class="row-even"><td><a class="reference internal" href="#mxnet.recordio.MXIndexedRecordIO" title="mxnet.recordio.MXIndexedRecordIO"><code class="xref py py-obj docutils literal"><span class="pre">recordio.MXIndexedRecordIO</span></code></a></td> |
| <td>Reads/writes <cite>RecordIO</cite> data format, supporting random access.</td> |
| </tr> |
| <tr class="row-odd"><td><a class="reference internal" href="../image/image.html#mxnet.image.ImageIter" title="mxnet.image.ImageIter"><code class="xref py py-obj docutils literal"><span class="pre">image.ImageIter</span></code></a></td> |
| <td>Image data iterator with a large number of augmentation choices.</td> |
| </tr> |
| <tr class="row-even"><td><a class="reference internal" href="../image/image.html#mxnet.image.ImageDetIter" title="mxnet.image.ImageDetIter"><code class="xref py py-obj docutils literal"><span class="pre">image.ImageDetIter</span></code></a></td> |
| <td>Image iterator with a large number of augmentation choices for detection.</td> |
| </tr> |
| </tbody> |
| </table> |
| </div> |
| <div class="section" id="helper-classes-and-functions"> |
| <span id="helper-classes-and-functions"></span><h2>Helper classes and functions<a class="headerlink" href="#helper-classes-and-functions" title="Permalink to this headline">¶</a></h2> |
| <p>Data structures and other iterators provided in the <code class="docutils literal"><span class="pre">mxnet.io</span></code> packages.</p> |
| <table border="1" class="longtable docutils"> |
| <colgroup> |
| <col width="10%"/> |
| <col width="90%"/> |
| </colgroup> |
| <tbody valign="top"> |
| <tr class="row-odd"><td><a class="reference internal" href="#mxnet.io.DataDesc" title="mxnet.io.DataDesc"><code class="xref py py-obj docutils literal"><span class="pre">io.DataDesc</span></code></a></td> |
| <td>DataDesc is used to store name, shape, type and layout information of the data or the label.</td> |
| </tr> |
| <tr class="row-even"><td><a class="reference internal" href="#mxnet.io.DataBatch" title="mxnet.io.DataBatch"><code class="xref py py-obj docutils literal"><span class="pre">io.DataBatch</span></code></a></td> |
| <td>A data batch.</td> |
| </tr> |
| <tr class="row-odd"><td><a class="reference internal" href="#mxnet.io.DataIter" title="mxnet.io.DataIter"><code class="xref py py-obj docutils literal"><span class="pre">io.DataIter</span></code></a></td> |
| <td>The base class for an MXNet data iterator.</td> |
| </tr> |
| <tr class="row-even"><td><a class="reference internal" href="#mxnet.io.ResizeIter" title="mxnet.io.ResizeIter"><code class="xref py py-obj docutils literal"><span class="pre">io.ResizeIter</span></code></a></td> |
| <td>Resize a data iterator to a given number of batches.</td> |
| </tr> |
| <tr class="row-odd"><td><a class="reference internal" href="#mxnet.io.PrefetchingIter" title="mxnet.io.PrefetchingIter"><code class="xref py py-obj docutils literal"><span class="pre">io.PrefetchingIter</span></code></a></td> |
| <td>Performs pre-fetch for other data iterators.</td> |
| </tr> |
| <tr class="row-even"><td><a class="reference internal" href="#mxnet.io.MXDataIter" title="mxnet.io.MXDataIter"><code class="xref py py-obj docutils literal"><span class="pre">io.MXDataIter</span></code></a></td> |
| <td>A python wrapper a C++ data iterator.</td> |
| </tr> |
| </tbody> |
| </table> |
| <p>Functions to read and write RecordIO files.</p> |
| <table border="1" class="longtable docutils"> |
| <colgroup> |
| <col width="10%"/> |
| <col width="90%"/> |
| </colgroup> |
| <tbody valign="top"> |
| <tr class="row-odd"><td><a class="reference internal" href="#mxnet.recordio.pack" title="mxnet.recordio.pack"><code class="xref py py-obj docutils literal"><span class="pre">recordio.pack</span></code></a></td> |
| <td>Pack a string into MXImageRecord.</td> |
| </tr> |
| <tr class="row-even"><td><a class="reference internal" href="#mxnet.recordio.unpack" title="mxnet.recordio.unpack"><code class="xref py py-obj docutils literal"><span class="pre">recordio.unpack</span></code></a></td> |
| <td>Unpack a MXImageRecord to string.</td> |
| </tr> |
| <tr class="row-odd"><td><a class="reference internal" href="#mxnet.recordio.unpack_img" title="mxnet.recordio.unpack_img"><code class="xref py py-obj docutils literal"><span class="pre">recordio.unpack_img</span></code></a></td> |
| <td>Unpack a MXImageRecord to image.</td> |
| </tr> |
| <tr class="row-even"><td><a class="reference internal" href="#mxnet.recordio.pack_img" title="mxnet.recordio.pack_img"><code class="xref py py-obj docutils literal"><span class="pre">recordio.pack_img</span></code></a></td> |
| <td>Pack an image into <code class="docutils literal"><span class="pre">MXImageRecord</span></code>.</td> |
| </tr> |
| </tbody> |
| </table> |
| </div> |
| <div class="section" id="develop-a-new-iterator"> |
| <span id="develop-a-new-iterator"></span><h2>Develop a new iterator<a class="headerlink" href="#develop-a-new-iterator" title="Permalink to this headline">¶</a></h2> |
| <p>Writing a new data iterator in Python is straightforward. Most MXNet |
| training/inference programs accept an iterable object with <code class="docutils literal"><span class="pre">provide_data</span></code> |
| and <code class="docutils literal"><span class="pre">provide_label</span></code> properties. |
| This <a class="reference external" href="https://mxnet.incubator.apache.org/tutorials/basic/data.html">tutorial</a> explains how to |
| write an iterator from scratch.</p> |
| <p>The following example demonstrates how to combine |
| multiple data iterators into a single one. It can be used for multiple |
| modality training such as image captioning, in which images are read by |
| <code class="docutils literal"><span class="pre">ImageRecordIter</span></code> while documents are read by <code class="docutils literal"><span class="pre">CSVIter</span></code></p> |
| <div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">class</span> <span class="nc">MultiIter</span><span class="p">:</span> |
| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">iter_list</span><span class="p">):</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">iters</span> <span class="o">=</span> <span class="n">iter_list</span> |
| <span class="k">def</span> <span class="nf">next</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="n">batches</span> <span class="o">=</span> <span class="p">[</span><span class="n">i</span><span class="o">.</span><span class="n">next</span><span class="p">()</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">iters</span><span class="p">]</span> |
| <span class="k">return</span> <span class="n">DataBatch</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="p">[</span><span class="o">*</span><span class="n">b</span><span class="o">.</span><span class="n">data</span> <span class="k">for</span> <span class="n">b</span> <span class="ow">in</span> <span class="n">batches</span><span class="p">],</span> |
| <span class="n">label</span><span class="o">=</span><span class="p">[</span><span class="o">*</span><span class="n">b</span><span class="o">.</span><span class="n">label</span> <span class="k">for</span> <span class="n">b</span> <span class="ow">in</span> <span class="n">batches</span><span class="p">])</span> |
| <span class="k">def</span> <span class="nf">reset</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">iters</span><span class="p">:</span> |
| <span class="n">i</span><span class="o">.</span><span class="n">reset</span><span class="p">()</span> |
| <span class="nd">@property</span> |
| <span class="k">def</span> <span class="nf">provide_data</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">return</span> <span class="p">[</span><span class="o">*</span><span class="n">i</span><span class="o">.</span><span class="n">provide_data</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">iters</span><span class="p">]</span> |
| <span class="nd">@property</span> |
| <span class="k">def</span> <span class="nf">provide_label</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">return</span> <span class="p">[</span><span class="o">*</span><span class="n">i</span><span class="o">.</span><span class="n">provide_label</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">iters</span><span class="p">]</span> |
| |
| <span class="nb">iter</span> <span class="o">=</span> <span class="n">MultiIter</span><span class="p">([</span><span class="n">mx</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">ImageRecordIter</span><span class="p">(</span><span class="s1">'image.rec'</span><span class="p">),</span> <span class="n">mx</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">CSVIter</span><span class="p">(</span><span class="s1">'txt.csv'</span><span class="p">)])</span> |
| </pre></div> |
| </div> |
| <p>Parsing and performing another pre-processing such as augmentation may be expensive. |
| If performance is critical, we can implement a data iterator in C++. Refer to |
| <a class="reference external" href="https://github.com/dmlc/mxnet/tree/master/src/io">src/io</a> for examples.</p> |
| <div class="section" id="change-batch-layout"> |
| <span id="change-batch-layout"></span><h3>Change batch layout<a class="headerlink" href="#change-batch-layout" title="Permalink to this headline">¶</a></h3> |
| <p>By default, the backend engine treats the first dimension of each data and label variable in data |
| iterators as the batch size (i.e. <code class="docutils literal"><span class="pre">NCHW</span></code> or <code class="docutils literal"><span class="pre">NT</span></code> layout). In order to override the axis for batch size, |
| the <code class="docutils literal"><span class="pre">provide_data</span></code> (and <code class="docutils literal"><span class="pre">provide_label</span></code> if there is label) properties should include the layouts. This |
| is especially useful in RNN since <code class="docutils literal"><span class="pre">TNC</span></code> layouts are often more efficient. For example:</p> |
| <div class="highlight-python"><div class="highlight"><pre><span></span><span class="nd">@property</span> |
| <span class="k">def</span> <span class="nf">provide_data</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="k">return</span> <span class="p">[</span><span class="n">DataDesc</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s1">'seq_var'</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="n">seq_length</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">),</span> <span class="n">layout</span><span class="o">=</span><span class="s1">'TN'</span><span class="p">)]</span> |
| </pre></div> |
| </div> |
| <p>The backend engine will recognize the index of <code class="docutils literal"><span class="pre">N</span></code> in the <code class="docutils literal"><span class="pre">layout</span></code> as the axis for batch size.</p> |
| </div> |
| </div> |
| <div class="section" id="api-reference"> |
| <span id="api-reference"></span><h2>API Reference<a class="headerlink" href="#api-reference" title="Permalink to this headline">¶</a></h2> |
| <script src="../../_static/js/auto_module_index.js" type="text/javascript"></script><span class="target" id="module-mxnet.io"></span><p>Data iterators for common data formats.</p> |
| <dl class="class"> |
| <dt id="mxnet.io.DataDesc"> |
| <em class="property">class </em><code class="descclassname">mxnet.io.</code><code class="descname">DataDesc</code><a class="reference internal" href="../../../_modules/mxnet/io.html#DataDesc"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.DataDesc" title="Permalink to this definition">¶</a></dt> |
| <dd><p>DataDesc is used to store name, shape, type and layout |
| information of the data or the label.</p> |
| <p>The <cite>layout</cite> describes how the axes in <cite>shape</cite> should be interpreted, |
| for example for image data setting <cite>layout=NCHW</cite> indicates |
| that the first axis is number of examples in the batch(N), |
| C is number of channels, H is the height and W is the width of the image.</p> |
| <p>For sequential data, by default <cite>layout</cite> is set to <code class="docutils literal"><span class="pre">NTC</span></code>, where |
| N is number of examples in the batch, T the temporal axis representing time |
| and C is the number of channels.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple"> |
| <li><strong>cls</strong> (<a class="reference internal" href="#mxnet.io.DataDesc" title="mxnet.io.DataDesc"><em>DataDesc</em></a>) – The class.</li> |
| <li><strong>name</strong> (<em>str</em>) – Data name.</li> |
| <li><strong>shape</strong> (<em>tuple of int</em>) – Data shape.</li> |
| <li><strong>dtype</strong> (<em>np.dtype</em><em>, </em><em>optional</em>) – Data type.</li> |
| <li><strong>layout</strong> (<em>str</em><em>, </em><em>optional</em>) – Data layout.</li> |
| </ul> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| <dl class="staticmethod"> |
| <dt id="mxnet.io.DataDesc.get_batch_axis"> |
| <em class="property">static </em><code class="descname">get_batch_axis</code><span class="sig-paren">(</span><em>layout</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#DataDesc.get_batch_axis"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.DataDesc.get_batch_axis" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Get the dimension that corresponds to the batch size.</p> |
| <p>When data parallelism is used, the data will be automatically split and |
| concatenated along the batch-size dimension. Axis can be -1, which means |
| the whole array will be copied for each data-parallelism device.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>layout</strong> (<em>str</em>) – layout string. For example, “NCHW”.</td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">An axis indicating the batch_size dimension.</td> |
| </tr> |
| <tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body">int</td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="staticmethod"> |
| <dt id="mxnet.io.DataDesc.get_list"> |
| <em class="property">static </em><code class="descname">get_list</code><span class="sig-paren">(</span><em>shapes</em>, <em>types</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#DataDesc.get_list"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.DataDesc.get_list" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Get DataDesc list from attribute lists.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple"> |
| <li><strong>shapes</strong> (<em>a tuple of</em><em> (</em><a class="reference internal" href="../gluon/gluon.html#mxnet.gluon.Block.name" title="mxnet.gluon.Block.name"><em>name</em></a><em>, </em><a class="reference internal" href="../ndarray/ndarray.html#mxnet.ndarray.NDArray.shape" title="mxnet.ndarray.NDArray.shape"><em>shape</em></a><em>)</em>) – </li> |
| <li><strong>types</strong> (<em>a tuple of</em><em> (</em><a class="reference internal" href="../gluon/gluon.html#mxnet.gluon.Block.name" title="mxnet.gluon.Block.name"><em>name</em></a><em>, </em><a class="reference internal" href="../kvstore/kvstore.html#mxnet.kvstore.KVStore.type" title="mxnet.kvstore.KVStore.type"><em>type</em></a><em>)</em>) – </li> |
| </ul> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| </dd></dl> |
| <dl class="class"> |
| <dt id="mxnet.io.DataBatch"> |
| <em class="property">class </em><code class="descclassname">mxnet.io.</code><code class="descname">DataBatch</code><span class="sig-paren">(</span><em>data</em>, <em>label=None</em>, <em>pad=None</em>, <em>index=None</em>, <em>bucket_key=None</em>, <em>provide_data=None</em>, <em>provide_label=None</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#DataBatch"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.DataBatch" title="Permalink to this definition">¶</a></dt> |
| <dd><p>A data batch.</p> |
| <p>MXNet’s data iterator returns a batch of data for each <cite>next</cite> call. |
| This data contains <cite>batch_size</cite> number of examples.</p> |
| <p>If the input data consists of images, then shape of these images depend on |
| the <cite>layout</cite> attribute of <cite>DataDesc</cite> object in <cite>provide_data</cite> parameter.</p> |
| <p>If <cite>layout</cite> is set to ‘NCHW’ then, images should be stored in a 4-D matrix |
| of shape <code class="docutils literal"><span class="pre">(batch_size,</span> <span class="pre">num_channel,</span> <span class="pre">height,</span> <span class="pre">width)</span></code>. |
| If <cite>layout</cite> is set to ‘NHWC’ then, images should be stored in a 4-D matrix |
| of shape <code class="docutils literal"><span class="pre">(batch_size,</span> <span class="pre">height,</span> <span class="pre">width,</span> <span class="pre">num_channel)</span></code>. |
| The channels are often in RGB order.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple"> |
| <li><strong>data</strong> (list of <cite>NDArray</cite>, each array containing <cite>batch_size</cite> examples.) – A list of input data.</li> |
| <li><strong>label</strong> (list of <cite>NDArray</cite>, each array often containing a 1-dimensional array. optional) – A list of input labels.</li> |
| <li><strong>pad</strong> (<em>int</em><em>, </em><em>optional</em>) – The number of examples padded at the end of a batch. It is used when the |
| total number of examples read is not divisible by the <cite>batch_size</cite>. |
| These extra padded examples are ignored in prediction.</li> |
| <li><strong>index</strong> (<em>numpy.array</em><em>, </em><em>optional</em>) – The example indices in this batch.</li> |
| <li><strong>bucket_key</strong> (<em>int</em><em>, </em><em>optional</em>) – The bucket key, used for bucketing module.</li> |
| <li><strong>provide_data</strong> (list of <cite>DataDesc</cite>, optional) – A list of <cite>DataDesc</cite> objects. <cite>DataDesc</cite> is used to store |
| name, shape, type and layout information of the data. |
| The <em>i</em>-th element describes the name and shape of <code class="docutils literal"><span class="pre">data[i]</span></code>.</li> |
| <li><strong>provide_label</strong> (list of <cite>DataDesc</cite>, optional) – A list of <cite>DataDesc</cite> objects. <cite>DataDesc</cite> is used to store |
| name, shape, type and layout information of the label. |
| The <em>i</em>-th element describes the name and shape of <code class="docutils literal"><span class="pre">label[i]</span></code>.</li> |
| </ul> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="class"> |
| <dt id="mxnet.io.DataIter"> |
| <em class="property">class </em><code class="descclassname">mxnet.io.</code><code class="descname">DataIter</code><span class="sig-paren">(</span><em>batch_size=0</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#DataIter"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.DataIter" title="Permalink to this definition">¶</a></dt> |
| <dd><p>The base class for an MXNet data iterator.</p> |
| <p>All I/O in MXNet is handled by specializations of this class. Data iterators |
| in MXNet are similar to standard-iterators in Python. On each call to <cite>next</cite> |
| they return a <cite>DataBatch</cite> which represents the next batch of data. When |
| there is no more data to return, it raises a <cite>StopIteration</cite> exception.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>batch_size</strong> (<em>int</em><em>, </em><em>optional</em>) – The batch size, namely the number of items in the batch.</td> |
| </tr> |
| </tbody> |
| </table> |
| <div class="admonition seealso"> |
| <p class="first admonition-title">See also</p> |
| <dl class="last docutils"> |
| <dt><a class="reference internal" href="#mxnet.io.NDArrayIter" title="mxnet.io.NDArrayIter"><code class="xref py py-class docutils literal"><span class="pre">NDArrayIter</span></code></a></dt> |
| <dd>Data-iterator for MXNet NDArray or numpy-ndarray objects.</dd> |
| <dt><a class="reference internal" href="#mxnet.io.CSVIter" title="mxnet.io.CSVIter"><code class="xref py py-class docutils literal"><span class="pre">CSVIter</span></code></a></dt> |
| <dd>Data-iterator for csv data.</dd> |
| <dt><a class="reference internal" href="#mxnet.io.LibSVMIter" title="mxnet.io.LibSVMIter"><code class="xref py py-class docutils literal"><span class="pre">LibSVMIter</span></code></a></dt> |
| <dd>Data-iterator for libsvm data.</dd> |
| <dt><code class="xref py py-class docutils literal"><span class="pre">ImageIter</span></code></dt> |
| <dd>Data-iterator for images.</dd> |
| </dl> |
| </div> |
| <dl class="method"> |
| <dt id="mxnet.io.DataIter.reset"> |
| <code class="descname">reset</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#DataIter.reset"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.DataIter.reset" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Reset the iterator to the begin of the data.</p> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.io.DataIter.next"> |
| <code class="descname">next</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#DataIter.next"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.DataIter.next" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Get next data batch from iterator.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">The data of next batch.</td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body"><a class="reference internal" href="#mxnet.io.DataBatch" title="mxnet.io.DataBatch">DataBatch</a></td> |
| </tr> |
| <tr class="field-odd field"><th class="field-name">Raises:</th><td class="field-body"><code class="xref py py-exc docutils literal"><span class="pre">StopIteration</span></code> – If the end of the data is reached.</td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.io.DataIter.iter_next"> |
| <code class="descname">iter_next</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#DataIter.iter_next"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.DataIter.iter_next" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Move to the next batch.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Whether the move is successful.</td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">boolean</td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.io.DataIter.getdata"> |
| <code class="descname">getdata</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#DataIter.getdata"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.DataIter.getdata" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Get data of current batch.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">The data of the current batch.</td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">list of NDArray</td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.io.DataIter.getlabel"> |
| <code class="descname">getlabel</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#DataIter.getlabel"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.DataIter.getlabel" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Get label of the current batch.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">The label of the current batch.</td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">list of NDArray</td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.io.DataIter.getindex"> |
| <code class="descname">getindex</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#DataIter.getindex"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.DataIter.getindex" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Get index of the current batch.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><strong>index</strong> – The indices of examples in the current batch.</td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">numpy.array</td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.io.DataIter.getpad"> |
| <code class="descname">getpad</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#DataIter.getpad"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.DataIter.getpad" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Get the number of padding examples in the current batch.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Number of padding examples in the current batch.</td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">int</td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| </dd></dl> |
| <dl class="class"> |
| <dt id="mxnet.io.ResizeIter"> |
| <em class="property">class </em><code class="descclassname">mxnet.io.</code><code class="descname">ResizeIter</code><span class="sig-paren">(</span><em>data_iter</em>, <em>size</em>, <em>reset_internal=True</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#ResizeIter"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.ResizeIter" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Resize a data iterator to a given number of batches.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple"> |
| <li><strong>data_iter</strong> (<a class="reference internal" href="#mxnet.io.DataIter" title="mxnet.io.DataIter"><em>DataIter</em></a>) – The data iterator to be resized.</li> |
| <li><strong>size</strong> (<em>int</em>) – The number of batches per epoch to resize to.</li> |
| <li><strong>reset_internal</strong> (<em>bool</em>) – Whether to reset internal iterator on ResizeIter.reset.</li> |
| </ul> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Examples</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">nd_iter</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">NDArrayIter</span><span class="p">(</span><span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span><span class="mi">10</span><span class="p">)),</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">25</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">resize_iter</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">ResizeIter</span><span class="p">(</span><span class="n">nd_iter</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="k">for</span> <span class="n">batch</span> <span class="ow">in</span> <span class="n">resize_iter</span><span class="p">:</span> |
| <span class="gp">... </span> <span class="nb">print</span><span class="p">(</span><span class="n">batch</span><span class="o">.</span><span class="n">data</span><span class="p">)</span> |
| <span class="go">[<NDArray 25x10 @cpu(0)>]</span> |
| <span class="go">[<NDArray 25x10 @cpu(0)>]</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| <dl class="class"> |
| <dt id="mxnet.io.PrefetchingIter"> |
| <em class="property">class </em><code class="descclassname">mxnet.io.</code><code class="descname">PrefetchingIter</code><span class="sig-paren">(</span><em>iters</em>, <em>rename_data=None</em>, <em>rename_label=None</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#PrefetchingIter"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.PrefetchingIter" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Performs pre-fetch for other data iterators.</p> |
| <p>This iterator will create another thread to perform <code class="docutils literal"><span class="pre">iter_next</span></code> and then |
| store the data in memory. It potentially accelerates the data read, at the |
| cost of more memory usage.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple"> |
| <li><strong>iters</strong> (<a class="reference internal" href="#mxnet.io.DataIter" title="mxnet.io.DataIter"><em>DataIter</em></a><em> or </em><em>list of DataIter</em>) – The data iterators to be pre-fetched.</li> |
| <li><strong>rename_data</strong> (<em>None</em><em> or </em><em>list of dict</em>) – The <em>i</em>-th element is a renaming map for the <em>i</em>-th iter, in the form of |
| {‘original_name’ : ‘new_name’}. Should have one entry for each entry |
| in iter[i].provide_data.</li> |
| <li><strong>rename_label</strong> (<em>None</em><em> or </em><em>list of dict</em>) – Similar to <code class="docutils literal"><span class="pre">rename_data</span></code>.</li> |
| </ul> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Examples</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">iter1</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">NDArrayIter</span><span class="p">({</span><span class="s1">'data'</span><span class="p">:</span><span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span><span class="mi">10</span><span class="p">))},</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">25</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">iter2</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">NDArrayIter</span><span class="p">({</span><span class="s1">'data'</span><span class="p">:</span><span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span><span class="mi">10</span><span class="p">))},</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">25</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">piter</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">PrefetchingIter</span><span class="p">([</span><span class="n">iter1</span><span class="p">,</span> <span class="n">iter2</span><span class="p">],</span> |
| <span class="gp">... </span> <span class="n">rename_data</span><span class="o">=</span><span class="p">[{</span><span class="s1">'data'</span><span class="p">:</span> <span class="s1">'data_1'</span><span class="p">},</span> <span class="p">{</span><span class="s1">'data'</span><span class="p">:</span> <span class="s1">'data_2'</span><span class="p">}])</span> |
| <span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">piter</span><span class="o">.</span><span class="n">provide_data</span><span class="p">)</span> |
| <span class="go">[DataDesc[data_1,(25, 10L),<type 'numpy.float32'>,NCHW],</span> |
| <span class="go"> DataDesc[data_2,(25, 10L),<type 'numpy.float32'>,NCHW]]</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| <dl class="class"> |
| <dt id="mxnet.io.NDArrayIter"> |
| <em class="property">class </em><code class="descclassname">mxnet.io.</code><code class="descname">NDArrayIter</code><span class="sig-paren">(</span><em>data</em>, <em>label=None</em>, <em>batch_size=1</em>, <em>shuffle=False</em>, <em>last_batch_handle='pad'</em>, <em>data_name='data'</em>, <em>label_name='softmax_label'</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#NDArrayIter"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.NDArrayIter" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns an iterator for <code class="docutils literal"><span class="pre">mx.nd.NDArray</span></code>, <code class="docutils literal"><span class="pre">numpy.ndarray</span></code>, <code class="docutils literal"><span class="pre">h5py.Dataset</span></code> |
| <code class="docutils literal"><span class="pre">mx.nd.sparse.CSRNDArray</span></code> or <code class="docutils literal"><span class="pre">scipy.sparse.csr_matrix</span></code>.</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">40</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">10</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">))</span> |
| <span class="gp">>>> </span><span class="n">labels</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">([</span><span class="mi">10</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">dataiter</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">NDArrayIter</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="kc">True</span><span class="p">,</span> <span class="n">last_batch_handle</span><span class="o">=</span><span class="s1">'discard'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="k">for</span> <span class="n">batch</span> <span class="ow">in</span> <span class="n">dataiter</span><span class="p">:</span> |
| <span class="gp">... </span> <span class="nb">print</span> <span class="n">batch</span><span class="o">.</span><span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">()</span> |
| <span class="gp">... </span> <span class="n">batch</span><span class="o">.</span><span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">shape</span> |
| <span class="gp">...</span> |
| <span class="go">[[[ 36. 37.]</span> |
| <span class="go"> [ 38. 39.]]</span> |
| <span class="go"> [[ 16. 17.]</span> |
| <span class="go"> [ 18. 19.]]</span> |
| <span class="go"> [[ 12. 13.]</span> |
| <span class="go"> [ 14. 15.]]]</span> |
| <span class="go">(3L, 2L, 2L)</span> |
| <span class="go">[[[ 32. 33.]</span> |
| <span class="go"> [ 34. 35.]]</span> |
| <span class="go"> [[ 4. 5.]</span> |
| <span class="go"> [ 6. 7.]]</span> |
| <span class="go"> [[ 24. 25.]</span> |
| <span class="go"> [ 26. 27.]]]</span> |
| <span class="go">(3L, 2L, 2L)</span> |
| <span class="go">[[[ 8. 9.]</span> |
| <span class="go"> [ 10. 11.]]</span> |
| <span class="go"> [[ 20. 21.]</span> |
| <span class="go"> [ 22. 23.]]</span> |
| <span class="go"> [[ 28. 29.]</span> |
| <span class="go"> [ 30. 31.]]]</span> |
| <span class="go">(3L, 2L, 2L)</span> |
| <span class="gp">>>> </span><span class="n">dataiter</span><span class="o">.</span><span class="n">provide_data</span> <span class="c1"># Returns a list of `DataDesc`</span> |
| <span class="go">[DataDesc[data,(3, 2L, 2L),<type 'numpy.float32'>,NCHW]]</span> |
| <span class="gp">>>> </span><span class="n">dataiter</span><span class="o">.</span><span class="n">provide_label</span> <span class="c1"># Returns a list of `DataDesc`</span> |
| <span class="go">[DataDesc[softmax_label,(3, 1L),<type 'numpy.float32'>,NCHW]]</span> |
| </pre></div> |
| </div> |
| <p>In the above example, data is shuffled as <cite>shuffle</cite> parameter is set to <cite>True</cite> |
| and remaining examples are discarded as <cite>last_batch_handle</cite> parameter is set to <cite>discard</cite>.</p> |
| <p>Usage of <cite>last_batch_handle</cite> parameter:</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">dataiter</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">NDArrayIter</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="kc">True</span><span class="p">,</span> <span class="n">last_batch_handle</span><span class="o">=</span><span class="s1">'pad'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">batchidx</span> <span class="o">=</span> <span class="mi">0</span> |
| <span class="gp">>>> </span><span class="k">for</span> <span class="n">batch</span> <span class="ow">in</span> <span class="n">dataiter</span><span class="p">:</span> |
| <span class="gp">... </span> <span class="n">batchidx</span> <span class="o">+=</span> <span class="mi">1</span> |
| <span class="gp">...</span> |
| <span class="gp">>>> </span><span class="n">batchidx</span> <span class="c1"># Padding added after the examples read are over. So, 10/3+1 batches are created.</span> |
| <span class="go">4</span> |
| <span class="gp">>>> </span><span class="n">dataiter</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">NDArrayIter</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="kc">True</span><span class="p">,</span> <span class="n">last_batch_handle</span><span class="o">=</span><span class="s1">'discard'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">batchidx</span> <span class="o">=</span> <span class="mi">0</span> |
| <span class="gp">>>> </span><span class="k">for</span> <span class="n">batch</span> <span class="ow">in</span> <span class="n">dataiter</span><span class="p">:</span> |
| <span class="gp">... </span> <span class="n">batchidx</span> <span class="o">+=</span> <span class="mi">1</span> |
| <span class="gp">...</span> |
| <span class="gp">>>> </span><span class="n">batchidx</span> <span class="c1"># Remaining examples are discarded. So, 10/3 batches are created.</span> |
| <span class="go">3</span> |
| </pre></div> |
| </div> |
| <p><cite>NDArrayIter</cite> also supports multiple input and labels.</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">data</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'data1'</span><span class="p">:</span><span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">)),</span> <span class="s1">'data2'</span><span class="p">:</span><span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">))}</span> |
| <span class="gp">>>> </span><span class="n">label</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'label1'</span><span class="p">:</span><span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">1</span><span class="p">)),</span> <span class="s1">'label2'</span><span class="p">:</span><span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span><span class="mi">1</span><span class="p">))}</span> |
| <span class="gp">>>> </span><span class="n">dataiter</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">NDArrayIter</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">label</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="kc">True</span><span class="p">,</span> <span class="n">last_batch_handle</span><span class="o">=</span><span class="s1">'discard'</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| <p><cite>NDArrayIter</cite> also supports <code class="docutils literal"><span class="pre">mx.nd.sparse.CSRNDArray</span></code> |
| with <cite>last_batch_handle</cite> set to <cite>discard</cite>.</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">csr_data</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">40</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">10</span><span class="p">,</span><span class="mi">4</span><span class="p">)))</span><span class="o">.</span><span class="n">tostype</span><span class="p">(</span><span class="s1">'csr'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">labels</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ones</span><span class="p">([</span><span class="mi">10</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span> |
| <span class="gp">>>> </span><span class="n">dataiter</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">NDArrayIter</span><span class="p">(</span><span class="n">csr_data</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">last_batch_handle</span><span class="o">=</span><span class="s1">'discard'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="p">[</span><span class="n">batch</span><span class="o">.</span><span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">batch</span> <span class="ow">in</span> <span class="n">dataiter</span><span class="p">]</span> |
| <span class="go">[</span> |
| <span class="go"><CSRNDArray 3x4 @cpu(0)>,</span> |
| <span class="go"><CSRNDArray 3x4 @cpu(0)>,</span> |
| <span class="go"><CSRNDArray 3x4 @cpu(0)>]</span> |
| </pre></div> |
| </div> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple"> |
| <li><strong>data</strong> (<a class="reference internal" href="../ndarray/ndarray.html#mxnet.ndarray.array" title="mxnet.ndarray.array"><em>array</em></a><em> or </em><em>list of array</em><em> or </em><em>dict of string to array</em>) – The input data.</li> |
| <li><strong>label</strong> (<a class="reference internal" href="../ndarray/ndarray.html#mxnet.ndarray.array" title="mxnet.ndarray.array"><em>array</em></a><em> or </em><em>list of array</em><em> or </em><em>dict of string to array</em><em>, </em><em>optional</em>) – The input label.</li> |
| <li><strong>batch_size</strong> (<em>int</em>) – Batch size of data.</li> |
| <li><strong>shuffle</strong> (<em>bool</em><em>, </em><em>optional</em>) – Whether to shuffle the data. |
| Only supported if no h5py.Dataset inputs are used.</li> |
| <li><strong>last_batch_handle</strong> (<em>str</em><em>, </em><em>optional</em>) – How to handle the last batch. This parameter can be ‘pad’, ‘discard’ or |
| ‘roll_over’. ‘roll_over’ is intended for training and can cause problems |
| if used for prediction.</li> |
| <li><strong>data_name</strong> (<em>str</em><em>, </em><em>optional</em>) – The data name.</li> |
| <li><strong>label_name</strong> (<em>str</em><em>, </em><em>optional</em>) – The label name.</li> |
| </ul> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| <dl class="attribute"> |
| <dt id="mxnet.io.NDArrayIter.provide_data"> |
| <code class="descname">provide_data</code><a class="headerlink" href="#mxnet.io.NDArrayIter.provide_data" title="Permalink to this definition">¶</a></dt> |
| <dd><p>The name and shape of data provided by this iterator.</p> |
| </dd></dl> |
| <dl class="attribute"> |
| <dt id="mxnet.io.NDArrayIter.provide_label"> |
| <code class="descname">provide_label</code><a class="headerlink" href="#mxnet.io.NDArrayIter.provide_label" title="Permalink to this definition">¶</a></dt> |
| <dd><p>The name and shape of label provided by this iterator.</p> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.io.NDArrayIter.hard_reset"> |
| <code class="descname">hard_reset</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#NDArrayIter.hard_reset"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.NDArrayIter.hard_reset" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Ignore roll over data and set to start.</p> |
| </dd></dl> |
| </dd></dl> |
| <dl class="class"> |
| <dt id="mxnet.io.MXDataIter"> |
| <em class="property">class </em><code class="descclassname">mxnet.io.</code><code class="descname">MXDataIter</code><span class="sig-paren">(</span><em>handle</em>, <em>data_name='data'</em>, <em>label_name='softmax_label'</em>, <em>**_</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/io.html#MXDataIter"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.io.MXDataIter" title="Permalink to this definition">¶</a></dt> |
| <dd><p>A python wrapper a C++ data iterator.</p> |
| <p>This iterator is the Python wrapper to all native C++ data iterators, such |
| as <cite>CSVIter</cite>, <cite>ImageRecordIter</cite>, <cite>MNISTIter</cite>, etc. When initializing |
| <cite>CSVIter</cite> for example, you will get an <cite>MXDataIter</cite> instance to use in your |
| Python code. Calls to <cite>next</cite>, <cite>reset</cite>, etc will be delegated to the |
| underlying C++ data iterators.</p> |
| <p>Usually you don’t need to interact with <cite>MXDataIter</cite> directly unless you are |
| implementing your own data iterators in C++. To do that, please refer to |
| examples under the <cite>src/io</cite> folder.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple"> |
| <li><strong>handle</strong> (<em>DataIterHandle</em><em>, </em><em>required</em>) – The handle to the underlying C++ Data Iterator.</li> |
| <li><strong>data_name</strong> (<em>str</em><em>, </em><em>optional</em>) – Data name. Default to “data”.</li> |
| <li><strong>label_name</strong> (<em>str</em><em>, </em><em>optional</em>) – Label name. Default to “softmax_label”.</li> |
| </ul> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| <div class="admonition seealso"> |
| <p class="first admonition-title">See also</p> |
| <p class="last">src/io : The underlying C++ data iterator implementation, e.g., <cite>CSVIter</cite>.</p> |
| </div> |
| </dd></dl> |
| <dl class="function"> |
| <dt id="mxnet.io.CSVIter"> |
| <code class="descclassname">mxnet.io.</code><code class="descname">CSVIter</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.io.CSVIter" title="Permalink to this definition">¶</a></dt> |
| <dd><p>b”Returns the CSV file iterator.nnIn this function, the <cite>data_shape</cite> parameter is used to set the shape of each line of the input data.nIf a row in an input file is <cite>1,2,3,4,5,6`</cite> and <cite>data_shape</cite> is (3,2), that rownwill be reshaped, yielding the array [[1,2],[3,4],[5,6]] of shape (3,2).nnBy default, the <cite>CSVIter</cite> has <cite>round_batch</cite> parameter set to <code class="docutils literal"><span class="pre">True</span></code>. So, if <cite>batch_size</cite>nis 3 and there are 4 total rows in CSV file, 2 more examplesnare consumed at the first round. If <cite>reset</cite> function is called after first round,nthe call is ignored and remaining examples are returned in the second round.nnIf one wants all the instances in the second round after calling <cite>reset</cite>, make surento set <cite>round_batch</cite> to False.nnIf <code class="docutils literal"><span class="pre">data_csv</span> <span class="pre">=</span> <span class="pre">'data/'</span></code> is set, then all the files in this directory will be read.nn``reset()`` is expected to be called only after a complete pass of data.nnExamples::nn // Contents of CSV file <code class="docutils literal"><span class="pre">data/data.csv</span></code>.n 1,2,3n 2,3,4n 3,4,5n 4,5,6nn // Creates a <cite>CSVIter</cite> with <cite>batch_size`=2 and default `round_batch`=True.n CSVIter = mx.io.CSVIter(data_csv = ‘data/data.csv’, data_shape = (3,),n batch_size = 2)nn // Two batches read from the above iterator are as follows:n [[ 1. 2. 3.]n [ 2. 3. 4.]]n [[ 3. 4. 5.]n [ 4. 5. 6.]]nn // Creates a `CSVIter</cite> with default <cite>round_batch</cite> set to True.n CSVIter = mx.io.CSVIter(data_csv = ‘data/data.csv’, data_shape = (3,),n batch_size = 3)nn // Two batches read from the above iterator in the first pass are as follows:n [[1. 2. 3.]n [2. 3. 4.]n [3. 4. 5.]]nn [[4. 5. 6.]n [1. 2. 3.]n [2. 3. 4.]]nn // Now, <cite>reset</cite> method is called.n CSVIter.reset()nn // Batch read from the above iterator in the second pass is as follows:n [[ 3. 4. 5.]n [ 4. 5. 6.]n [ 1. 2. 3.]]nn // Creates a <cite>CSVIter</cite> with <cite>round_batch`=False.n CSVIter = mx.io.CSVIter(data_csv = ‘data/data.csv’, data_shape = (3,),n batch_size = 3, round_batch=False)nn // Contents of two batches read from the above iterator in both passes, after callingn // `reset</cite> method before second pass, is as follows:n [[1. 2. 3.]n [2. 3. 4.]n [3. 4. 5.]]nn [[4. 5. 6.]n [2. 3. 4.]n [3. 4. 5.]]nnnnDefined in src/io/iter_csv.cc:L223”</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple"> |
| <li><strong>data_csv</strong> (<em>string</em><em>, </em><em>required</em>) – The input CSV file or a directory path.</li> |
| <li><strong>data_shape</strong> (<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) – The shape of one example.</li> |
| <li><strong>label_csv</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default='NULL'</em>) – The input CSV file or a directory path. If NULL, all labels will be returned as 0.</li> |
| <li><strong>label_shape</strong> (<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>1</em><em>]</em>) – The shape of one label.</li> |
| <li><strong>batch_size</strong> (<em>int</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>required</em>) – Batch size.</li> |
| <li><strong>round_batch</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Whether to use round robin to handle overflow batch or not.</li> |
| <li><strong>prefetch_buffer</strong> (<em>long</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=4</em>) – Maximum number of batches to prefetch.</li> |
| <li><strong>dtype</strong> (<em>{None</em><em>, </em><em>'float16'</em><em>, </em><em>'float32'</em><em>, </em><em>'float64'</em><em>, </em><em>'int32'</em><em>, </em><em>'uint8'}</em><em>,</em><em>optional</em><em>, </em><em>default='None'</em>) – Output data type. <code class="docutils literal"><span class="pre">None</span></code> means no change.</li> |
| </ul> |
| </td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">The result iterator.</p> |
| </td> |
| </tr> |
| <tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#mxnet.io.MXDataIter" title="mxnet.io.MXDataIter">MXDataIter</a></p> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="function"> |
| <dt id="mxnet.io.ImageDetRecordIter"> |
| <code class="descclassname">mxnet.io.</code><code class="descname">ImageDetRecordIter</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.io.ImageDetRecordIter" title="Permalink to this definition">¶</a></dt> |
| <dd><p>b’Create iterator for image detection dataset packed in recordio.’</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple"> |
| <li><strong>path_imglist</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Dataset Param: Path to image list.</li> |
| <li><strong>path_imgrec</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default='./data/imgrec.rec'</em>) – Dataset Param: Path to image record file.</li> |
| <li><strong>aug_seq</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default='det_aug_default'</em>) – Augmentation Param: the augmenter names to represent sequence of augmenters to be applied, seperated by comma. Additional keyword parameters will be seen by these augmenters. Make sure you don’t use normal augmenters for detection tasks.</li> |
| <li><strong>label_width</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Dataset Param: How many labels for an image, -1 for variable label size.</li> |
| <li><strong>data_shape</strong> (<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) – Dataset Param: Shape of each instance generated by the DataIter.</li> |
| <li><strong>preprocess_threads</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='4'</em>) – Backend Param: Number of thread to do preprocessing.</li> |
| <li><strong>verbose</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Auxiliary Param: Whether to output parser information.</li> |
| <li><strong>num_parts</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – partition the data into multiple parts</li> |
| <li><strong>part_index</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – the index of the part will read</li> |
| <li><strong>shuffle_chunk_size</strong> (<em>long</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – the size(MB) of the shuffle chunk, used with shuffle=True, it can enable global shuffling</li> |
| <li><strong>shuffle_chunk_seed</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – the seed for chunk shuffling</li> |
| <li><strong>label_pad_width</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – pad output label width if set larger than 0, -1 for auto estimate</li> |
| <li><strong>label_pad_value</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=-1</em>) – label padding value if enabled</li> |
| <li><strong>shuffle</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Whether to shuffle data.</li> |
| <li><strong>seed</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Augmentation Param: Random Seed.</li> |
| <li><strong>batch_size</strong> (<em>int</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>required</em>) – Batch size.</li> |
| <li><strong>round_batch</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Whether to use round robin to handle overflow batch or not.</li> |
| <li><strong>prefetch_buffer</strong> (<em>long</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=4</em>) – Maximum number of batches to prefetch.</li> |
| <li><strong>dtype</strong> (<em>{None</em><em>, </em><em>'float16'</em><em>, </em><em>'float32'</em><em>, </em><em>'float64'</em><em>, </em><em>'int32'</em><em>, </em><em>'uint8'}</em><em>,</em><em>optional</em><em>, </em><em>default='None'</em>) – Output data type. <code class="docutils literal"><span class="pre">None</span></code> means no change.</li> |
| <li><strong>resize</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Augmentation Param: scale shorter edge to size before applying other augmentations, -1 to disable.</li> |
| <li><strong>rand_crop_prob</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Probability of random cropping, <= 0 to disable</li> |
| <li><strong>min_crop_scales</strong> (<em>tuple of <float></em><em>, </em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>0</em><em>]</em>) – Augmentation Param: Min crop scales.</li> |
| <li><strong>max_crop_scales</strong> (<em>tuple of <float></em><em>, </em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>1</em><em>]</em>) – Augmentation Param: Max crop scales.</li> |
| <li><strong>min_crop_aspect_ratios</strong> (<em>tuple of <float></em><em>, </em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>1</em><em>]</em>) – Augmentation Param: Min crop aspect ratios.</li> |
| <li><strong>max_crop_aspect_ratios</strong> (<em>tuple of <float></em><em>, </em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>1</em><em>]</em>) – Augmentation Param: Max crop aspect ratios.</li> |
| <li><strong>min_crop_overlaps</strong> (<em>tuple of <float></em><em>, </em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>0</em><em>]</em>) – Augmentation Param: Minimum crop IOU between crop_box and ground-truths.</li> |
| <li><strong>max_crop_overlaps</strong> (<em>tuple of <float></em><em>, </em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>1</em><em>]</em>) – Augmentation Param: Maximum crop IOU between crop_box and ground-truth.</li> |
| <li><strong>min_crop_sample_coverages</strong> (<em>tuple of <float></em><em>, </em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>0</em><em>]</em>) – Augmentation Param: Minimum ratio of intersect/crop_area between crop box and ground-truths.</li> |
| <li><strong>max_crop_sample_coverages</strong> (<em>tuple of <float></em><em>, </em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>1</em><em>]</em>) – Augmentation Param: Maximum ratio of intersect/crop_area between crop box and ground-truths.</li> |
| <li><strong>min_crop_object_coverages</strong> (<em>tuple of <float></em><em>, </em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>0</em><em>]</em>) – Augmentation Param: Minimum ratio of intersect/gt_area between crop box and ground-truths.</li> |
| <li><strong>max_crop_object_coverages</strong> (<em>tuple of <float></em><em>, </em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>1</em><em>]</em>) – Augmentation Param: Maximum ratio of intersect/gt_area between crop box and ground-truths.</li> |
| <li><strong>num_crop_sampler</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – Augmentation Param: Number of crop samplers.</li> |
| <li><strong>crop_emit_mode</strong> (<em>{'center'</em><em>, </em><em>'overlap'}</em><em>,</em><em>optional</em><em>, </em><em>default='center'</em>) – Augmentation Param: Emition mode for invalid ground-truths after crop. center: emit if centroid of object is out of crop region; overlap: emit if overlap is less than emit_overlap_thresh.</li> |
| <li><strong>emit_overlap_thresh</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0.3</em>) – Augmentation Param: Emit overlap thresh for emit mode overlap only.</li> |
| <li><strong>max_crop_trials</strong> (<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>25</em><em>]</em>) – Augmentation Param: Skip cropping if fail crop trail count exceeds this number.</li> |
| <li><strong>rand_pad_prob</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Probability for random padding.</li> |
| <li><strong>max_pad_scale</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Augmentation Param: Maximum padding scale.</li> |
| <li><strong>max_random_hue</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Augmentation Param: Maximum random value of H channel in HSL color space.</li> |
| <li><strong>random_hue_prob</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Probability to apply random hue.</li> |
| <li><strong>max_random_saturation</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Augmentation Param: Maximum random value of S channel in HSL color space.</li> |
| <li><strong>random_saturation_prob</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Probability to apply random saturation.</li> |
| <li><strong>max_random_illumination</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Augmentation Param: Maximum random value of L channel in HSL color space.</li> |
| <li><strong>random_illumination_prob</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Probability to apply random illumination.</li> |
| <li><strong>max_random_contrast</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Maximum random value of delta contrast.</li> |
| <li><strong>random_contrast_prob</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Probability to apply random contrast.</li> |
| <li><strong>rand_mirror_prob</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Probability to apply horizontal flip aka. mirror.</li> |
| <li><strong>fill_value</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='127'</em>) – Augmentation Param: Filled color value while padding.</li> |
| <li><strong>inter_method</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – Augmentation Param: 0-NN 1-bilinear 2-cubic 3-area 4-lanczos4 9-auto 10-rand.</li> |
| <li><strong>resize_mode</strong> (<em>{'fit'</em><em>, </em><em>'force'</em><em>, </em><em>'shrink'}</em><em>,</em><em>optional</em><em>, </em><em>default='force'</em>) – Augmentation Param: How image data fit in data_shape. force: force reshape to data_shape regardless of aspect ratio; shrink: ensure each side fit in data_shape, preserve aspect ratio; fit: fit image to data_shape, preserve ratio, will upscale if applicable.</li> |
| <li><strong>mean_img</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Augmentation Param: Mean Image to be subtracted.</li> |
| <li><strong>mean_r</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Mean value on R channel.</li> |
| <li><strong>mean_g</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Mean value on G channel.</li> |
| <li><strong>mean_b</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Mean value on B channel.</li> |
| <li><strong>mean_a</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Mean value on Alpha channel.</li> |
| <li><strong>std_r</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Standard deviation on R channel.</li> |
| <li><strong>std_g</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Standard deviation on G channel.</li> |
| <li><strong>std_b</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Standard deviation on B channel.</li> |
| <li><strong>std_a</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Standard deviation on Alpha channel.</li> |
| <li><strong>scale</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Augmentation Param: Scale in color space.</li> |
| </ul> |
| </td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">The result iterator.</p> |
| </td> |
| </tr> |
| <tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#mxnet.io.MXDataIter" title="mxnet.io.MXDataIter">MXDataIter</a></p> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="function"> |
| <dt id="mxnet.io.ImageRecordIter"> |
| <code class="descclassname">mxnet.io.</code><code class="descname">ImageRecordIter</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.io.ImageRecordIter" title="Permalink to this definition">¶</a></dt> |
| <dd><p>b’Iterates on image RecordIO filesnnReads batches of images from .rec RecordIO files. One can use <code class="docutils literal"><span class="pre">im2rec.py</span></code> tooln(in tools/) to pack raw image files into RecordIO files. This iterator is lessnflexible to customization but is fast and has lot of language bindings. Toniterate over raw images directly use <code class="docutils literal"><span class="pre">ImageIter</span></code> instead (in Python).nnExample::nn data_iter = mx.io.ImageRecordIter(n path_imgrec=”./sample.rec”, # The target record file.n data_shape=(3, 227, 227), # Output data shape; 227x227 region will be cropped from the original image.n batch_size=4, # Number of items per batch.n resize=256 # Resize the shorter edge to 256 before cropping.n # You can specify more augmentation options. Use help(mx.io.ImageRecordIter) to see all the options.n )n # You can now use the data_iter to access batches of images.n batch = data_iter.next() # first batch.n images = batch.data[0] # This will contain 4 (=batch_size) images each of 3x227x227.n # process the imagesn ...n data_iter.reset() # To restart the iterator from the beginning.nnnnDefined in src/io/iter_image_recordio_2.cc:L748’</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple"> |
| <li><strong>path_imglist</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Path to the image list (.lst) file. Generally created with tools/im2rec.py. Format (Tab separated): <index of record> <one or more labels> <relative path from root folder>.</li> |
| <li><strong>path_imgrec</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Path to the image RecordIO (.rec) file or a directory path. Created with tools/im2rec.py.</li> |
| <li><strong>path_imgidx</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Path to the image RecordIO index (.idx) file. Created with tools/im2rec.py.</li> |
| <li><strong>aug_seq</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default='aug_default'</em>) – The augmenter names to represent sequence of augmenters to be applied, seperated by comma. Additional keyword parameters will be seen by these augmenters.</li> |
| <li><strong>label_width</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – The number of labels per image.</li> |
| <li><strong>data_shape</strong> (<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) – The shape of one output image in (channels, height, width) format.</li> |
| <li><strong>preprocess_threads</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='4'</em>) – The number of threads to do preprocessing.</li> |
| <li><strong>verbose</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – If or not output verbose information.</li> |
| <li><strong>num_parts</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – Virtually partition the data into these many parts.</li> |
| <li><strong>part_index</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – The <em>i</em>-th virtual partition to be read.</li> |
| <li><strong>shuffle_chunk_size</strong> (<em>long</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – The data shuffle buffer size in MB. Only valid if shuffle is true.</li> |
| <li><strong>shuffle_chunk_seed</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – The random seed for shuffling</li> |
| <li><strong>shuffle</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Whether to shuffle data randomly or not.</li> |
| <li><strong>seed</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – The random seed.</li> |
| <li><strong>batch_size</strong> (<em>int</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>required</em>) – Batch size.</li> |
| <li><strong>round_batch</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Whether to use round robin to handle overflow batch or not.</li> |
| <li><strong>prefetch_buffer</strong> (<em>long</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=4</em>) – Maximum number of batches to prefetch.</li> |
| <li><strong>dtype</strong> (<em>{None</em><em>, </em><em>'float16'</em><em>, </em><em>'float32'</em><em>, </em><em>'float64'</em><em>, </em><em>'int32'</em><em>, </em><em>'uint8'}</em><em>,</em><em>optional</em><em>, </em><em>default='None'</em>) – Output data type. <code class="docutils literal"><span class="pre">None</span></code> means no change.</li> |
| <li><strong>resize</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Down scale the shorter edge to a new size before applying other augmentations.</li> |
| <li><strong>rand_crop</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – If or not randomly crop the image</li> |
| <li><strong>max_rotate_angle</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Rotate by a random degree in <code class="docutils literal"><span class="pre">[-v,</span> <span class="pre">v]</span></code></li> |
| <li><strong>max_aspect_ratio</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Change the aspect (namely width/height) to a random value in <code class="docutils literal"><span class="pre">[1</span> <span class="pre">-</span> <span class="pre">max_aspect_ratio,</span> <span class="pre">1</span> <span class="pre">+</span> <span class="pre">max_aspect_ratio]</span></code></li> |
| <li><strong>max_shear_ratio</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Apply a shear transformation (namely <code class="docutils literal"><span class="pre">(x,y)->(x+my,y)</span></code>) with <code class="docutils literal"><span class="pre">m</span></code> randomly chose from <code class="docutils literal"><span class="pre">[-max_shear_ratio,</span> <span class="pre">max_shear_ratio]</span></code></li> |
| <li><strong>max_crop_size</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Crop both width and height into a random size in <code class="docutils literal"><span class="pre">[min_crop_size,</span> <span class="pre">max_crop_size]</span></code></li> |
| <li><strong>min_crop_size</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Crop both width and height into a random size in <code class="docutils literal"><span class="pre">[min_crop_size,</span> <span class="pre">max_crop_size]</span></code></li> |
| <li><strong>max_random_scale</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Resize into <code class="docutils literal"><span class="pre">[width*s,</span> <span class="pre">height*s]</span></code> with <code class="docutils literal"><span class="pre">s</span></code> randomly chosen from <code class="docutils literal"><span class="pre">[min_random_scale,</span> <span class="pre">max_random_scale]</span></code></li> |
| <li><strong>min_random_scale</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Resize into <code class="docutils literal"><span class="pre">[width*s,</span> <span class="pre">height*s]</span></code> with <code class="docutils literal"><span class="pre">s</span></code> randomly chosen from <code class="docutils literal"><span class="pre">[min_random_scale,</span> <span class="pre">max_random_scale]</span></code></li> |
| <li><strong>max_img_size</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1e+10</em>) – Set the maximal width and height after all resize and rotate argumentation are applied</li> |
| <li><strong>min_img_size</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Set the minimal width and height after all resize and rotate argumentation are applied</li> |
| <li><strong>random_h</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Add a random value in <code class="docutils literal"><span class="pre">[-random_h,</span> <span class="pre">random_h]</span></code> to the H channel in HSL color space.</li> |
| <li><strong>random_s</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Add a random value in <code class="docutils literal"><span class="pre">[-random_s,</span> <span class="pre">random_s]</span></code> to the S channel in HSL color space.</li> |
| <li><strong>random_l</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Add a random value in <code class="docutils literal"><span class="pre">[-random_l,</span> <span class="pre">random_l]</span></code> to the L channel in HSL color space.</li> |
| <li><strong>rotate</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Rotate by an angle. If set, it overwrites the <code class="docutils literal"><span class="pre">max_rotate_angle</span></code> option.</li> |
| <li><strong>fill_value</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='255'</em>) – Set the padding pixes value into <code class="docutils literal"><span class="pre">fill_value</span></code>.</li> |
| <li><strong>inter_method</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – The interpolation method: 0-NN 1-bilinear 2-cubic 3-area 4-lanczos4 9-auto 10-rand.</li> |
| <li><strong>pad</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Change size from <code class="docutils literal"><span class="pre">[width,</span> <span class="pre">height]</span></code> into <code class="docutils literal"><span class="pre">[pad</span> <span class="pre">+</span> <span class="pre">width</span> <span class="pre">+</span> <span class="pre">pad,</span> <span class="pre">pad</span> <span class="pre">+</span> <span class="pre">height</span> <span class="pre">+</span> <span class="pre">pad]</span></code> by padding pixes</li> |
| <li><strong>mirror</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Whether to mirror the image or not. If true, images are flipped along the horizontal axis.</li> |
| <li><strong>rand_mirror</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Whether to randomly mirror images or not. If true, 50% of the images will be randomly mirrored (flipped along the horizontal axis)</li> |
| <li><strong>mean_img</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Filename of the mean image.</li> |
| <li><strong>mean_r</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – The mean value to be subtracted on the R channel</li> |
| <li><strong>mean_g</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – The mean value to be subtracted on the G channel</li> |
| <li><strong>mean_b</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – The mean value to be subtracted on the B channel</li> |
| <li><strong>mean_a</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – The mean value to be subtracted on the alpha channel</li> |
| <li><strong>std_r</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Augmentation Param: Standard deviation on R channel.</li> |
| <li><strong>std_g</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Augmentation Param: Standard deviation on G channel.</li> |
| <li><strong>std_b</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Augmentation Param: Standard deviation on B channel.</li> |
| <li><strong>std_a</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Augmentation Param: Standard deviation on Alpha channel.</li> |
| <li><strong>scale</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Multiply the image with a scale value.</li> |
| <li><strong>max_random_contrast</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Change the contrast with a value randomly chosen from <code class="docutils literal"><span class="pre">[-max_random_contrast,</span> <span class="pre">max_random_contrast]</span></code></li> |
| <li><strong>max_random_illumination</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Change the illumination with a value randomly chosen from <code class="docutils literal"><span class="pre">[-max_random_illumination,</span> <span class="pre">max_random_illumination]</span></code></li> |
| </ul> |
| </td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">The result iterator.</p> |
| </td> |
| </tr> |
| <tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#mxnet.io.MXDataIter" title="mxnet.io.MXDataIter">MXDataIter</a></p> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="function"> |
| <dt id="mxnet.io.ImageRecordIter_v1"> |
| <code class="descclassname">mxnet.io.</code><code class="descname">ImageRecordIter_v1</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.io.ImageRecordIter_v1" title="Permalink to this definition">¶</a></dt> |
| <dd><p>b’Iterating on image RecordIO filesnnRead images batches from RecordIO files with a rich of data augmentationnoptions.nnOne can use <code class="docutils literal"><span class="pre">tools/im2rec.py</span></code> to pack individual image files into RecordIOnfiles.nnnnDefined in src/io/iter_image_recordio.cc:L347’</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple"> |
| <li><strong>path_imglist</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Path to the image list (.lst) file. Generally created with tools/im2rec.py. Format (Tab separated): <index of record> <one or more labels> <relative path from root folder>.</li> |
| <li><strong>path_imgrec</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Path to the image RecordIO (.rec) file or a directory path. Created with tools/im2rec.py.</li> |
| <li><strong>path_imgidx</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Path to the image RecordIO index (.idx) file. Created with tools/im2rec.py.</li> |
| <li><strong>aug_seq</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default='aug_default'</em>) – The augmenter names to represent sequence of augmenters to be applied, seperated by comma. Additional keyword parameters will be seen by these augmenters.</li> |
| <li><strong>label_width</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – The number of labels per image.</li> |
| <li><strong>data_shape</strong> (<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) – The shape of one output image in (channels, height, width) format.</li> |
| <li><strong>preprocess_threads</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='4'</em>) – The number of threads to do preprocessing.</li> |
| <li><strong>verbose</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – If or not output verbose information.</li> |
| <li><strong>num_parts</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – Virtually partition the data into these many parts.</li> |
| <li><strong>part_index</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – The <em>i</em>-th virtual partition to be read.</li> |
| <li><strong>shuffle_chunk_size</strong> (<em>long</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – The data shuffle buffer size in MB. Only valid if shuffle is true.</li> |
| <li><strong>shuffle_chunk_seed</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – The random seed for shuffling</li> |
| <li><strong>shuffle</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Whether to shuffle data randomly or not.</li> |
| <li><strong>seed</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – The random seed.</li> |
| <li><strong>batch_size</strong> (<em>int</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>required</em>) – Batch size.</li> |
| <li><strong>round_batch</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Whether to use round robin to handle overflow batch or not.</li> |
| <li><strong>prefetch_buffer</strong> (<em>long</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=4</em>) – Maximum number of batches to prefetch.</li> |
| <li><strong>dtype</strong> (<em>{None</em><em>, </em><em>'float16'</em><em>, </em><em>'float32'</em><em>, </em><em>'float64'</em><em>, </em><em>'int32'</em><em>, </em><em>'uint8'}</em><em>,</em><em>optional</em><em>, </em><em>default='None'</em>) – Output data type. <code class="docutils literal"><span class="pre">None</span></code> means no change.</li> |
| <li><strong>resize</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Down scale the shorter edge to a new size before applying other augmentations.</li> |
| <li><strong>rand_crop</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – If or not randomly crop the image</li> |
| <li><strong>max_rotate_angle</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Rotate by a random degree in <code class="docutils literal"><span class="pre">[-v,</span> <span class="pre">v]</span></code></li> |
| <li><strong>max_aspect_ratio</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Change the aspect (namely width/height) to a random value in <code class="docutils literal"><span class="pre">[1</span> <span class="pre">-</span> <span class="pre">max_aspect_ratio,</span> <span class="pre">1</span> <span class="pre">+</span> <span class="pre">max_aspect_ratio]</span></code></li> |
| <li><strong>max_shear_ratio</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Apply a shear transformation (namely <code class="docutils literal"><span class="pre">(x,y)->(x+my,y)</span></code>) with <code class="docutils literal"><span class="pre">m</span></code> randomly chose from <code class="docutils literal"><span class="pre">[-max_shear_ratio,</span> <span class="pre">max_shear_ratio]</span></code></li> |
| <li><strong>max_crop_size</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Crop both width and height into a random size in <code class="docutils literal"><span class="pre">[min_crop_size,</span> <span class="pre">max_crop_size]</span></code></li> |
| <li><strong>min_crop_size</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Crop both width and height into a random size in <code class="docutils literal"><span class="pre">[min_crop_size,</span> <span class="pre">max_crop_size]</span></code></li> |
| <li><strong>max_random_scale</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Resize into <code class="docutils literal"><span class="pre">[width*s,</span> <span class="pre">height*s]</span></code> with <code class="docutils literal"><span class="pre">s</span></code> randomly chosen from <code class="docutils literal"><span class="pre">[min_random_scale,</span> <span class="pre">max_random_scale]</span></code></li> |
| <li><strong>min_random_scale</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Resize into <code class="docutils literal"><span class="pre">[width*s,</span> <span class="pre">height*s]</span></code> with <code class="docutils literal"><span class="pre">s</span></code> randomly chosen from <code class="docutils literal"><span class="pre">[min_random_scale,</span> <span class="pre">max_random_scale]</span></code></li> |
| <li><strong>max_img_size</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1e+10</em>) – Set the maximal width and height after all resize and rotate argumentation are applied</li> |
| <li><strong>min_img_size</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Set the minimal width and height after all resize and rotate argumentation are applied</li> |
| <li><strong>random_h</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Add a random value in <code class="docutils literal"><span class="pre">[-random_h,</span> <span class="pre">random_h]</span></code> to the H channel in HSL color space.</li> |
| <li><strong>random_s</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Add a random value in <code class="docutils literal"><span class="pre">[-random_s,</span> <span class="pre">random_s]</span></code> to the S channel in HSL color space.</li> |
| <li><strong>random_l</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Add a random value in <code class="docutils literal"><span class="pre">[-random_l,</span> <span class="pre">random_l]</span></code> to the L channel in HSL color space.</li> |
| <li><strong>rotate</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Rotate by an angle. If set, it overwrites the <code class="docutils literal"><span class="pre">max_rotate_angle</span></code> option.</li> |
| <li><strong>fill_value</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='255'</em>) – Set the padding pixes value into <code class="docutils literal"><span class="pre">fill_value</span></code>.</li> |
| <li><strong>inter_method</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – The interpolation method: 0-NN 1-bilinear 2-cubic 3-area 4-lanczos4 9-auto 10-rand.</li> |
| <li><strong>pad</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Change size from <code class="docutils literal"><span class="pre">[width,</span> <span class="pre">height]</span></code> into <code class="docutils literal"><span class="pre">[pad</span> <span class="pre">+</span> <span class="pre">width</span> <span class="pre">+</span> <span class="pre">pad,</span> <span class="pre">pad</span> <span class="pre">+</span> <span class="pre">height</span> <span class="pre">+</span> <span class="pre">pad]</span></code> by padding pixes</li> |
| <li><strong>mirror</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Whether to mirror the image or not. If true, images are flipped along the horizontal axis.</li> |
| <li><strong>rand_mirror</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Whether to randomly mirror images or not. If true, 50% of the images will be randomly mirrored (flipped along the horizontal axis)</li> |
| <li><strong>mean_img</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Filename of the mean image.</li> |
| <li><strong>mean_r</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – The mean value to be subtracted on the R channel</li> |
| <li><strong>mean_g</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – The mean value to be subtracted on the G channel</li> |
| <li><strong>mean_b</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – The mean value to be subtracted on the B channel</li> |
| <li><strong>mean_a</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – The mean value to be subtracted on the alpha channel</li> |
| <li><strong>std_r</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Augmentation Param: Standard deviation on R channel.</li> |
| <li><strong>std_g</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Augmentation Param: Standard deviation on G channel.</li> |
| <li><strong>std_b</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Augmentation Param: Standard deviation on B channel.</li> |
| <li><strong>std_a</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Augmentation Param: Standard deviation on Alpha channel.</li> |
| <li><strong>scale</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Multiply the image with a scale value.</li> |
| <li><strong>max_random_contrast</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Change the contrast with a value randomly chosen from <code class="docutils literal"><span class="pre">[-max_random_contrast,</span> <span class="pre">max_random_contrast]</span></code></li> |
| <li><strong>max_random_illumination</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Change the illumination with a value randomly chosen from <code class="docutils literal"><span class="pre">[-max_random_illumination,</span> <span class="pre">max_random_illumination]</span></code></li> |
| </ul> |
| </td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">The result iterator.</p> |
| </td> |
| </tr> |
| <tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#mxnet.io.MXDataIter" title="mxnet.io.MXDataIter">MXDataIter</a></p> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="function"> |
| <dt id="mxnet.io.ImageRecordUInt8Iter"> |
| <code class="descclassname">mxnet.io.</code><code class="descname">ImageRecordUInt8Iter</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.io.ImageRecordUInt8Iter" title="Permalink to this definition">¶</a></dt> |
| <dd><p>b’Iterating on image RecordIO filesnnThis iterator is identical to <code class="docutils literal"><span class="pre">ImageRecordIter</span></code> except for using <code class="docutils literal"><span class="pre">uint8</span></code> asnthe data type instead of <code class="docutils literal"><span class="pre">float</span></code>.nnnnDefined in src/io/iter_image_recordio_2.cc:L765’</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple"> |
| <li><strong>path_imglist</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Path to the image list (.lst) file. Generally created with tools/im2rec.py. Format (Tab separated): <index of record> <one or more labels> <relative path from root folder>.</li> |
| <li><strong>path_imgrec</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Path to the image RecordIO (.rec) file or a directory path. Created with tools/im2rec.py.</li> |
| <li><strong>path_imgidx</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Path to the image RecordIO index (.idx) file. Created with tools/im2rec.py.</li> |
| <li><strong>aug_seq</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default='aug_default'</em>) – The augmenter names to represent sequence of augmenters to be applied, seperated by comma. Additional keyword parameters will be seen by these augmenters.</li> |
| <li><strong>label_width</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – The number of labels per image.</li> |
| <li><strong>data_shape</strong> (<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) – The shape of one output image in (channels, height, width) format.</li> |
| <li><strong>preprocess_threads</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='4'</em>) – The number of threads to do preprocessing.</li> |
| <li><strong>verbose</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – If or not output verbose information.</li> |
| <li><strong>num_parts</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – Virtually partition the data into these many parts.</li> |
| <li><strong>part_index</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – The <em>i</em>-th virtual partition to be read.</li> |
| <li><strong>shuffle_chunk_size</strong> (<em>long</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – The data shuffle buffer size in MB. Only valid if shuffle is true.</li> |
| <li><strong>shuffle_chunk_seed</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – The random seed for shuffling</li> |
| <li><strong>shuffle</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Whether to shuffle data randomly or not.</li> |
| <li><strong>seed</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – The random seed.</li> |
| <li><strong>batch_size</strong> (<em>int</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>required</em>) – Batch size.</li> |
| <li><strong>round_batch</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Whether to use round robin to handle overflow batch or not.</li> |
| <li><strong>prefetch_buffer</strong> (<em>long</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=4</em>) – Maximum number of batches to prefetch.</li> |
| <li><strong>dtype</strong> (<em>{None</em><em>, </em><em>'float16'</em><em>, </em><em>'float32'</em><em>, </em><em>'float64'</em><em>, </em><em>'int32'</em><em>, </em><em>'uint8'}</em><em>,</em><em>optional</em><em>, </em><em>default='None'</em>) – Output data type. <code class="docutils literal"><span class="pre">None</span></code> means no change.</li> |
| <li><strong>resize</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Down scale the shorter edge to a new size before applying other augmentations.</li> |
| <li><strong>rand_crop</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – If or not randomly crop the image</li> |
| <li><strong>max_rotate_angle</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Rotate by a random degree in <code class="docutils literal"><span class="pre">[-v,</span> <span class="pre">v]</span></code></li> |
| <li><strong>max_aspect_ratio</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Change the aspect (namely width/height) to a random value in <code class="docutils literal"><span class="pre">[1</span> <span class="pre">-</span> <span class="pre">max_aspect_ratio,</span> <span class="pre">1</span> <span class="pre">+</span> <span class="pre">max_aspect_ratio]</span></code></li> |
| <li><strong>max_shear_ratio</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Apply a shear transformation (namely <code class="docutils literal"><span class="pre">(x,y)->(x+my,y)</span></code>) with <code class="docutils literal"><span class="pre">m</span></code> randomly chose from <code class="docutils literal"><span class="pre">[-max_shear_ratio,</span> <span class="pre">max_shear_ratio]</span></code></li> |
| <li><strong>max_crop_size</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Crop both width and height into a random size in <code class="docutils literal"><span class="pre">[min_crop_size,</span> <span class="pre">max_crop_size]</span></code></li> |
| <li><strong>min_crop_size</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Crop both width and height into a random size in <code class="docutils literal"><span class="pre">[min_crop_size,</span> <span class="pre">max_crop_size]</span></code></li> |
| <li><strong>max_random_scale</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Resize into <code class="docutils literal"><span class="pre">[width*s,</span> <span class="pre">height*s]</span></code> with <code class="docutils literal"><span class="pre">s</span></code> randomly chosen from <code class="docutils literal"><span class="pre">[min_random_scale,</span> <span class="pre">max_random_scale]</span></code></li> |
| <li><strong>min_random_scale</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Resize into <code class="docutils literal"><span class="pre">[width*s,</span> <span class="pre">height*s]</span></code> with <code class="docutils literal"><span class="pre">s</span></code> randomly chosen from <code class="docutils literal"><span class="pre">[min_random_scale,</span> <span class="pre">max_random_scale]</span></code></li> |
| <li><strong>max_img_size</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1e+10</em>) – Set the maximal width and height after all resize and rotate argumentation are applied</li> |
| <li><strong>min_img_size</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Set the minimal width and height after all resize and rotate argumentation are applied</li> |
| <li><strong>random_h</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Add a random value in <code class="docutils literal"><span class="pre">[-random_h,</span> <span class="pre">random_h]</span></code> to the H channel in HSL color space.</li> |
| <li><strong>random_s</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Add a random value in <code class="docutils literal"><span class="pre">[-random_s,</span> <span class="pre">random_s]</span></code> to the S channel in HSL color space.</li> |
| <li><strong>random_l</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Add a random value in <code class="docutils literal"><span class="pre">[-random_l,</span> <span class="pre">random_l]</span></code> to the L channel in HSL color space.</li> |
| <li><strong>rotate</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Rotate by an angle. If set, it overwrites the <code class="docutils literal"><span class="pre">max_rotate_angle</span></code> option.</li> |
| <li><strong>fill_value</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='255'</em>) – Set the padding pixes value into <code class="docutils literal"><span class="pre">fill_value</span></code>.</li> |
| <li><strong>inter_method</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – The interpolation method: 0-NN 1-bilinear 2-cubic 3-area 4-lanczos4 9-auto 10-rand.</li> |
| <li><strong>pad</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Change size from <code class="docutils literal"><span class="pre">[width,</span> <span class="pre">height]</span></code> into <code class="docutils literal"><span class="pre">[pad</span> <span class="pre">+</span> <span class="pre">width</span> <span class="pre">+</span> <span class="pre">pad,</span> <span class="pre">pad</span> <span class="pre">+</span> <span class="pre">height</span> <span class="pre">+</span> <span class="pre">pad]</span></code> by padding pixes</li> |
| </ul> |
| </td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">The result iterator.</p> |
| </td> |
| </tr> |
| <tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#mxnet.io.MXDataIter" title="mxnet.io.MXDataIter">MXDataIter</a></p> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="function"> |
| <dt id="mxnet.io.ImageRecordUInt8Iter_v1"> |
| <code class="descclassname">mxnet.io.</code><code class="descname">ImageRecordUInt8Iter_v1</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.io.ImageRecordUInt8Iter_v1" title="Permalink to this definition">¶</a></dt> |
| <dd><p>b’Iterating on image RecordIO filesnnThis iterator is identical to <code class="docutils literal"><span class="pre">ImageRecordIter</span></code> except for using <code class="docutils literal"><span class="pre">uint8</span></code> asnthe data type instead of <code class="docutils literal"><span class="pre">float</span></code>.nnnnDefined in src/io/iter_image_recordio.cc:L368’</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple"> |
| <li><strong>path_imglist</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Path to the image list (.lst) file. Generally created with tools/im2rec.py. Format (Tab separated): <index of record> <one or more labels> <relative path from root folder>.</li> |
| <li><strong>path_imgrec</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Path to the image RecordIO (.rec) file or a directory path. Created with tools/im2rec.py.</li> |
| <li><strong>path_imgidx</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default=''</em>) – Path to the image RecordIO index (.idx) file. Created with tools/im2rec.py.</li> |
| <li><strong>aug_seq</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default='aug_default'</em>) – The augmenter names to represent sequence of augmenters to be applied, seperated by comma. Additional keyword parameters will be seen by these augmenters.</li> |
| <li><strong>label_width</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – The number of labels per image.</li> |
| <li><strong>data_shape</strong> (<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) – The shape of one output image in (channels, height, width) format.</li> |
| <li><strong>preprocess_threads</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='4'</em>) – The number of threads to do preprocessing.</li> |
| <li><strong>verbose</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – If or not output verbose information.</li> |
| <li><strong>num_parts</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – Virtually partition the data into these many parts.</li> |
| <li><strong>part_index</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – The <em>i</em>-th virtual partition to be read.</li> |
| <li><strong>shuffle_chunk_size</strong> (<em>long</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – The data shuffle buffer size in MB. Only valid if shuffle is true.</li> |
| <li><strong>shuffle_chunk_seed</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – The random seed for shuffling</li> |
| <li><strong>shuffle</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Whether to shuffle data randomly or not.</li> |
| <li><strong>seed</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – The random seed.</li> |
| <li><strong>batch_size</strong> (<em>int</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>required</em>) – Batch size.</li> |
| <li><strong>round_batch</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Whether to use round robin to handle overflow batch or not.</li> |
| <li><strong>prefetch_buffer</strong> (<em>long</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=4</em>) – Maximum number of batches to prefetch.</li> |
| <li><strong>dtype</strong> (<em>{None</em><em>, </em><em>'float16'</em><em>, </em><em>'float32'</em><em>, </em><em>'float64'</em><em>, </em><em>'int32'</em><em>, </em><em>'uint8'}</em><em>,</em><em>optional</em><em>, </em><em>default='None'</em>) – Output data type. <code class="docutils literal"><span class="pre">None</span></code> means no change.</li> |
| <li><strong>resize</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Down scale the shorter edge to a new size before applying other augmentations.</li> |
| <li><strong>rand_crop</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – If or not randomly crop the image</li> |
| <li><strong>max_rotate_angle</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Rotate by a random degree in <code class="docutils literal"><span class="pre">[-v,</span> <span class="pre">v]</span></code></li> |
| <li><strong>max_aspect_ratio</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Change the aspect (namely width/height) to a random value in <code class="docutils literal"><span class="pre">[1</span> <span class="pre">-</span> <span class="pre">max_aspect_ratio,</span> <span class="pre">1</span> <span class="pre">+</span> <span class="pre">max_aspect_ratio]</span></code></li> |
| <li><strong>max_shear_ratio</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Apply a shear transformation (namely <code class="docutils literal"><span class="pre">(x,y)->(x+my,y)</span></code>) with <code class="docutils literal"><span class="pre">m</span></code> randomly chose from <code class="docutils literal"><span class="pre">[-max_shear_ratio,</span> <span class="pre">max_shear_ratio]</span></code></li> |
| <li><strong>max_crop_size</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Crop both width and height into a random size in <code class="docutils literal"><span class="pre">[min_crop_size,</span> <span class="pre">max_crop_size]</span></code></li> |
| <li><strong>min_crop_size</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Crop both width and height into a random size in <code class="docutils literal"><span class="pre">[min_crop_size,</span> <span class="pre">max_crop_size]</span></code></li> |
| <li><strong>max_random_scale</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Resize into <code class="docutils literal"><span class="pre">[width*s,</span> <span class="pre">height*s]</span></code> with <code class="docutils literal"><span class="pre">s</span></code> randomly chosen from <code class="docutils literal"><span class="pre">[min_random_scale,</span> <span class="pre">max_random_scale]</span></code></li> |
| <li><strong>min_random_scale</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Resize into <code class="docutils literal"><span class="pre">[width*s,</span> <span class="pre">height*s]</span></code> with <code class="docutils literal"><span class="pre">s</span></code> randomly chosen from <code class="docutils literal"><span class="pre">[min_random_scale,</span> <span class="pre">max_random_scale]</span></code></li> |
| <li><strong>max_img_size</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=1e+10</em>) – Set the maximal width and height after all resize and rotate argumentation are applied</li> |
| <li><strong>min_img_size</strong> (<em>float</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Set the minimal width and height after all resize and rotate argumentation are applied</li> |
| <li><strong>random_h</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Add a random value in <code class="docutils literal"><span class="pre">[-random_h,</span> <span class="pre">random_h]</span></code> to the H channel in HSL color space.</li> |
| <li><strong>random_s</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Add a random value in <code class="docutils literal"><span class="pre">[-random_s,</span> <span class="pre">random_s]</span></code> to the S channel in HSL color space.</li> |
| <li><strong>random_l</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Add a random value in <code class="docutils literal"><span class="pre">[-random_l,</span> <span class="pre">random_l]</span></code> to the L channel in HSL color space.</li> |
| <li><strong>rotate</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='-1'</em>) – Rotate by an angle. If set, it overwrites the <code class="docutils literal"><span class="pre">max_rotate_angle</span></code> option.</li> |
| <li><strong>fill_value</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='255'</em>) – Set the padding pixes value into <code class="docutils literal"><span class="pre">fill_value</span></code>.</li> |
| <li><strong>inter_method</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – The interpolation method: 0-NN 1-bilinear 2-cubic 3-area 4-lanczos4 9-auto 10-rand.</li> |
| <li><strong>pad</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Change size from <code class="docutils literal"><span class="pre">[width,</span> <span class="pre">height]</span></code> into <code class="docutils literal"><span class="pre">[pad</span> <span class="pre">+</span> <span class="pre">width</span> <span class="pre">+</span> <span class="pre">pad,</span> <span class="pre">pad</span> <span class="pre">+</span> <span class="pre">height</span> <span class="pre">+</span> <span class="pre">pad]</span></code> by padding pixes</li> |
| </ul> |
| </td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">The result iterator.</p> |
| </td> |
| </tr> |
| <tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#mxnet.io.MXDataIter" title="mxnet.io.MXDataIter">MXDataIter</a></p> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="function"> |
| <dt id="mxnet.io.LibSVMIter"> |
| <code class="descclassname">mxnet.io.</code><code class="descname">LibSVMIter</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.io.LibSVMIter" title="Permalink to this definition">¶</a></dt> |
| <dd><p>b”Returns the LibSVM iterator which returns data with <cite>csr</cite>nstorage type. This iterator is experimental and should be used with care.nnThe input data is stored in a format similar to LibSVM file format, except that the <strong>indicesnare expected to be zero-based instead of one-based, and the column indices for each row arenexpected to be sorted in ascending order</strong>. Details of the LibSVM format are availablen`here. <<a class="reference external" href="https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/">https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/</a>>`_nnnThe <cite>data_shape</cite> parameter is used to set the shape of each line of the data.nThe dimension of both <cite>data_shape</cite> and <cite>label_shape</cite> are expected to be 1.nnThe <cite>data_libsvm</cite> parameter is used to set the path input LibSVM file.nWhen it is set to a directory, all the files in the directory will be read.nnWhen <cite>label_libsvm</cite> is set to <code class="docutils literal"><span class="pre">NULL</span></code>, both data and label are read from the file specifiednby <cite>data_libsvm</cite>. In this case, the data is stored in <cite>csr</cite> storage type, while the label is a 1Dndense array.nnThe <cite>LibSVMIter</cite> only support <cite>round_batch</cite> parameter set to <code class="docutils literal"><span class="pre">True</span></code>. Therefore, if <cite>batch_size</cite>nis 3 and there are 4 total rows in libsvm file, 2 more examples are consumed at the first round.nnWhen <cite>num_parts</cite> and <cite>part_index</cite> are provided, the data is split into <cite>num_parts</cite> partitions,nand the iterator only reads the <cite>part_index</cite>-th partition. However, the partitions are notnguaranteed to be even.nn``reset()`` is expected to be called only after a complete pass of data.nnExample::nn # Contents of libsvm file <code class="docutils literal"><span class="pre">data.t</span></code>.n 1.0 0:0.5 2:1.2n -2.0n -3.0 0:0.6 1:2.4 2:1.2n 4 2:-1.2nn # Creates a <cite>LibSVMIter</cite> with <cite>batch_size`=3.n >>> data_iter = mx.io.LibSVMIter(data_libsvm = ‘data.t’, data_shape = (3,), batch_size = 3)n # The data of the first batch is stored in csr storage typen >>> batch = data_iter.next()n >>> csr = batch.data[0]n <CSRNDArray 3x3 @cpu(0)>n >>> csr.asnumpy()n [[ 0.5 0. 1.2 ]n [ 0. 0. 0. ]n [ 0.6 2.4 1.2]]n # The label of first batchn >>> label = batch.label[0]n >>> labeln [ 1. -2. -3.]n <NDArray 3 @cpu(0)>nn >>> second_batch = data_iter.next()n # The data of the second batchn >>> second_batch.data[0].asnumpy()n [[ 0. 0. -1.2 ]n [ 0.5 0. 1.2 ]n [ 0. 0. 0. ]]n # The label of the second batchn >>> second_batch.label[0].asnumpy()n [ 4. 1. -2.]nn >>> data_iter.reset()n # To restart the iterator for the second pass of the datannWhen `label_libsvm</cite> is set to the path to another LibSVM file,ndata is read from <cite>data_libsvm</cite> and label from <cite>label_libsvm</cite>.nIn this case, both data and label are stored in the csr format.nIf the label column in the <cite>data_libsvm</cite> file is ignored.nnExample::nn # Contents of libsvm file <code class="docutils literal"><span class="pre">label.t</span></code>n 1.0n -2.0 0:0.125n -3.0 2:1.2n 4 1:1.0 2:-1.2nn # Creates a <cite>LibSVMIter</cite> with specified label filen >>> data_iter = mx.io.LibSVMIter(data_libsvm = ‘data.t’, data_shape = (3,),n label_libsvm = ‘label.t’, label_shape = (3,), batch_size = 3)nn # Both data and label are in csr storage typen >>> batch = data_iter.next()n >>> csr_data = batch.data[0]n <CSRNDArray 3x3 @cpu(0)>n >>> csr_data.asnumpy()n [[ 0.5 0. 1.2 ]n [ 0. 0. 0. ]n [ 0.6 2.4 1.2 ]]n >>> csr_label = batch.label[0]n <CSRNDArray 3x3 @cpu(0)>n >>> csr_label.asnumpy()n [[ 0. 0. 0. ]n [ 0.125 0. 0. ]n [ 0. 0. 1.2 ]]nnnnDefined in src/io/iter_libsvm.cc:L298”</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple"> |
| <li><strong>data_libsvm</strong> (<em>string</em><em>, </em><em>required</em>) – The input zero-base indexed LibSVM data file or a directory path.</li> |
| <li><strong>data_shape</strong> (<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>required</em>) – The shape of one example.</li> |
| <li><strong>label_libsvm</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default='NULL'</em>) – The input LibSVM label file or a directory path. If NULL, all labels will be read from <code class="docutils literal"><span class="pre">data_libsvm</span></code>.</li> |
| <li><strong>label_shape</strong> (<em>Shape</em><em>(</em><em>tuple</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=</em><em>[</em><em>1</em><em>]</em>) – The shape of one label.</li> |
| <li><strong>num_parts</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – partition the data into multiple parts</li> |
| <li><strong>part_index</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – the index of the part will read</li> |
| <li><strong>batch_size</strong> (<em>int</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>required</em>) – Batch size.</li> |
| <li><strong>round_batch</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Whether to use round robin to handle overflow batch or not.</li> |
| <li><strong>prefetch_buffer</strong> (<em>long</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=4</em>) – Maximum number of batches to prefetch.</li> |
| <li><strong>dtype</strong> (<em>{None</em><em>, </em><em>'float16'</em><em>, </em><em>'float32'</em><em>, </em><em>'float64'</em><em>, </em><em>'int32'</em><em>, </em><em>'uint8'}</em><em>,</em><em>optional</em><em>, </em><em>default='None'</em>) – Output data type. <code class="docutils literal"><span class="pre">None</span></code> means no change.</li> |
| </ul> |
| </td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">The result iterator.</p> |
| </td> |
| </tr> |
| <tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#mxnet.io.MXDataIter" title="mxnet.io.MXDataIter">MXDataIter</a></p> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="function"> |
| <dt id="mxnet.io.MNISTIter"> |
| <code class="descclassname">mxnet.io.</code><code class="descname">MNISTIter</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#mxnet.io.MNISTIter" title="Permalink to this definition">¶</a></dt> |
| <dd><p>b’Iterating on the MNIST dataset.nnOne can download the dataset from <a class="reference external" href="http://yann.lecun.com/exdb/mnist/nnnnDefined">http://yann.lecun.com/exdb/mnist/nnnnDefined</a> in src/io/iter_mnist.cc:L265’</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple"> |
| <li><strong>image</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default='./train-images-idx3-ubyte'</em>) – Dataset Param: Mnist image path.</li> |
| <li><strong>label</strong> (<em>string</em><em>, </em><em>optional</em><em>, </em><em>default='./train-labels-idx1-ubyte'</em>) – Dataset Param: Mnist label path.</li> |
| <li><strong>batch_size</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='128'</em>) – Batch Param: Batch Size.</li> |
| <li><strong>shuffle</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=1</em>) – Augmentation Param: Whether to shuffle data.</li> |
| <li><strong>flat</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Augmentation Param: Whether to flat the data into 1D.</li> |
| <li><strong>seed</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – Augmentation Param: Random Seed.</li> |
| <li><strong>silent</strong> (<em>boolean</em><em>, </em><em>optional</em><em>, </em><em>default=0</em>) – Auxiliary Param: Whether to print out data info.</li> |
| <li><strong>num_parts</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='1'</em>) – partition the data into multiple parts</li> |
| <li><strong>part_index</strong> (<em>int</em><em>, </em><em>optional</em><em>, </em><em>default='0'</em>) – the index of the part will read</li> |
| <li><strong>prefetch_buffer</strong> (<em>long</em><em> (</em><em>non-negative</em><em>)</em><em>, </em><em>optional</em><em>, </em><em>default=4</em>) – Maximum number of batches to prefetch.</li> |
| <li><strong>dtype</strong> (<em>{None</em><em>, </em><em>'float16'</em><em>, </em><em>'float32'</em><em>, </em><em>'float64'</em><em>, </em><em>'int32'</em><em>, </em><em>'uint8'}</em><em>,</em><em>optional</em><em>, </em><em>default='None'</em>) – Output data type. <code class="docutils literal"><span class="pre">None</span></code> means no change.</li> |
| </ul> |
| </td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first">The result iterator.</p> |
| </td> |
| </tr> |
| <tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last"><a class="reference internal" href="#mxnet.io.MXDataIter" title="mxnet.io.MXDataIter">MXDataIter</a></p> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <span class="target" id="module-mxnet.recordio"></span><p>Read and write for the RecordIO data format.</p> |
| <dl class="class"> |
| <dt id="mxnet.recordio.MXRecordIO"> |
| <em class="property">class </em><code class="descclassname">mxnet.recordio.</code><code class="descname">MXRecordIO</code><span class="sig-paren">(</span><em>uri</em>, <em>flag</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#MXRecordIO"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.MXRecordIO" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Reads/writes <cite>RecordIO</cite> data format, supporting sequential read and write.</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">record</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">MXRecordIO</span><span class="p">(</span><span class="s1">'tmp.rec'</span><span class="p">,</span> <span class="s1">'w'</span><span class="p">)</span> |
| <span class="go"><mxnet.recordio.MXRecordIO object at 0x10ef40ed0></span> |
| <span class="gp">>>> </span><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">):</span> |
| <span class="gp">... </span> <span class="n">record</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="s1">'record_</span><span class="si">%d</span><span class="s1">'</span><span class="o">%</span><span class="n">i</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">record</span><span class="o">.</span><span class="n">close</span><span class="p">()</span> |
| <span class="gp">>>> </span><span class="n">record</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">MXRecordIO</span><span class="p">(</span><span class="s1">'tmp.rec'</span><span class="p">,</span> <span class="s1">'r'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">):</span> |
| <span class="gp">... </span> <span class="n">item</span> <span class="o">=</span> <span class="n">record</span><span class="o">.</span><span class="n">read</span><span class="p">()</span> |
| <span class="gp">... </span> <span class="nb">print</span><span class="p">(</span><span class="n">item</span><span class="p">)</span> |
| <span class="go">record_0</span> |
| <span class="go">record_1</span> |
| <span class="go">record_2</span> |
| <span class="go">record_3</span> |
| <span class="go">record_4</span> |
| <span class="gp">>>> </span><span class="n">record</span><span class="o">.</span><span class="n">close</span><span class="p">()</span> |
| </pre></div> |
| </div> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple"> |
| <li><strong>uri</strong> (<em>string</em>) – Path to the record file.</li> |
| <li><strong>flag</strong> (<em>string</em>) – ‘w’ for write or ‘r’ for read.</li> |
| </ul> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| <dl class="method"> |
| <dt id="mxnet.recordio.MXRecordIO.open"> |
| <code class="descname">open</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#MXRecordIO.open"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.MXRecordIO.open" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Opens the record file.</p> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.recordio.MXRecordIO.close"> |
| <code class="descname">close</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#MXRecordIO.close"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.MXRecordIO.close" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Closes the record file.</p> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.recordio.MXRecordIO.reset"> |
| <code class="descname">reset</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#MXRecordIO.reset"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.MXRecordIO.reset" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Resets the pointer to first item.</p> |
| <p>If the record is opened with ‘w’, this function will truncate the file to empty.</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">record</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">MXRecordIO</span><span class="p">(</span><span class="s1">'tmp.rec'</span><span class="p">,</span> <span class="s1">'r'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">2</span><span class="p">):</span> |
| <span class="gp">... </span> <span class="n">item</span> <span class="o">=</span> <span class="n">record</span><span class="o">.</span><span class="n">read</span><span class="p">()</span> |
| <span class="gp">... </span> <span class="nb">print</span><span class="p">(</span><span class="n">item</span><span class="p">)</span> |
| <span class="go">record_0</span> |
| <span class="go">record_1</span> |
| <span class="gp">>>> </span><span class="n">record</span><span class="o">.</span><span class="n">reset</span><span class="p">()</span> <span class="c1"># Pointer is reset.</span> |
| <span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">record</span><span class="o">.</span><span class="n">read</span><span class="p">())</span> <span class="c1"># Started reading from start again.</span> |
| <span class="go">record_0</span> |
| <span class="gp">>>> </span><span class="n">record</span><span class="o">.</span><span class="n">close</span><span class="p">()</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.recordio.MXRecordIO.write"> |
| <code class="descname">write</code><span class="sig-paren">(</span><em>buf</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#MXRecordIO.write"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.MXRecordIO.write" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Inserts a string buffer as a record.</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">record</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">MXRecordIO</span><span class="p">(</span><span class="s1">'tmp.rec'</span><span class="p">,</span> <span class="s1">'w'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">):</span> |
| <span class="gp">... </span> <span class="n">record</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="s1">'record_</span><span class="si">%d</span><span class="s1">'</span><span class="o">%</span><span class="n">i</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">record</span><span class="o">.</span><span class="n">close</span><span class="p">()</span> |
| </pre></div> |
| </div> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>buf</strong> (<em>string</em><em> (</em><em>python2</em><em>)</em><em>, </em><em>bytes</em><em> (</em><em>python3</em><em>)</em>) – Buffer to write.</td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.recordio.MXRecordIO.read"> |
| <code class="descname">read</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#MXRecordIO.read"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.MXRecordIO.read" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns record as a string.</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">record</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">MXRecordIO</span><span class="p">(</span><span class="s1">'tmp.rec'</span><span class="p">,</span> <span class="s1">'r'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">):</span> |
| <span class="gp">... </span> <span class="n">item</span> <span class="o">=</span> <span class="n">record</span><span class="o">.</span><span class="n">read</span><span class="p">()</span> |
| <span class="gp">... </span> <span class="nb">print</span><span class="p">(</span><span class="n">item</span><span class="p">)</span> |
| <span class="go">record_0</span> |
| <span class="go">record_1</span> |
| <span class="go">record_2</span> |
| <span class="go">record_3</span> |
| <span class="go">record_4</span> |
| <span class="gp">>>> </span><span class="n">record</span><span class="o">.</span><span class="n">close</span><span class="p">()</span> |
| </pre></div> |
| </div> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><strong>buf</strong> – Buffer read.</td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">string</td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| </dd></dl> |
| <dl class="class"> |
| <dt id="mxnet.recordio.MXIndexedRecordIO"> |
| <em class="property">class </em><code class="descclassname">mxnet.recordio.</code><code class="descname">MXIndexedRecordIO</code><span class="sig-paren">(</span><em>idx_path</em>, <em>uri</em>, <em>flag</em>, <em>key_type=<class 'int'></em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#MXIndexedRecordIO"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.MXIndexedRecordIO" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Reads/writes <cite>RecordIO</cite> data format, supporting random access.</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">):</span> |
| <span class="gp">... </span> <span class="n">record</span><span class="o">.</span><span class="n">write_idx</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="s1">'record_</span><span class="si">%d</span><span class="s1">'</span><span class="o">%</span><span class="n">i</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">record</span><span class="o">.</span><span class="n">close</span><span class="p">()</span> |
| <span class="gp">>>> </span><span class="n">record</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">MXIndexedRecordIO</span><span class="p">(</span><span class="s1">'tmp.idx'</span><span class="p">,</span> <span class="s1">'tmp.rec'</span><span class="p">,</span> <span class="s1">'r'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">record</span><span class="o">.</span><span class="n">read_idx</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> |
| <span class="go">record_3</span> |
| </pre></div> |
| </div> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple"> |
| <li><strong>idx_path</strong> (<em>str</em>) – Path to the index file.</li> |
| <li><strong>uri</strong> (<em>str</em>) – Path to the record file. Only supports seekable file types.</li> |
| <li><strong>flag</strong> (<em>str</em>) – ‘w’ for write or ‘r’ for read.</li> |
| <li><strong>key_type</strong> (<a class="reference internal" href="../kvstore/kvstore.html#mxnet.kvstore.KVStore.type" title="mxnet.kvstore.KVStore.type"><em>type</em></a>) – Data type for keys.</li> |
| </ul> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| <dl class="method"> |
| <dt id="mxnet.recordio.MXIndexedRecordIO.close"> |
| <code class="descname">close</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#MXIndexedRecordIO.close"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.MXIndexedRecordIO.close" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Closes the record file.</p> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.recordio.MXIndexedRecordIO.seek"> |
| <code class="descname">seek</code><span class="sig-paren">(</span><em>idx</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#MXIndexedRecordIO.seek"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.MXIndexedRecordIO.seek" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Sets the current read pointer position.</p> |
| <p>This function is internally called by <cite>read_idx(idx)</cite> to find the current |
| reader pointer position. It doesn’t return anything.</p> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.recordio.MXIndexedRecordIO.tell"> |
| <code class="descname">tell</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#MXIndexedRecordIO.tell"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.MXIndexedRecordIO.tell" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns the current position of write head.</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">record</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">MXIndexedRecordIO</span><span class="p">(</span><span class="s1">'tmp.idx'</span><span class="p">,</span> <span class="s1">'tmp.rec'</span><span class="p">,</span> <span class="s1">'w'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">record</span><span class="o">.</span><span class="n">tell</span><span class="p">())</span> |
| <span class="go">0</span> |
| <span class="gp">>>> </span><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">):</span> |
| <span class="gp">... </span> <span class="n">record</span><span class="o">.</span><span class="n">write_idx</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="s1">'record_</span><span class="si">%d</span><span class="s1">'</span><span class="o">%</span><span class="n">i</span><span class="p">)</span> |
| <span class="gp">... </span> <span class="nb">print</span><span class="p">(</span><span class="n">record</span><span class="o">.</span><span class="n">tell</span><span class="p">())</span> |
| <span class="go">16</span> |
| <span class="go">32</span> |
| <span class="go">48</span> |
| <span class="go">64</span> |
| <span class="go">80</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.recordio.MXIndexedRecordIO.read_idx"> |
| <code class="descname">read_idx</code><span class="sig-paren">(</span><em>idx</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#MXIndexedRecordIO.read_idx"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.MXIndexedRecordIO.read_idx" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Returns the record at given index.</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">record</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">MXIndexedRecordIO</span><span class="p">(</span><span class="s1">'tmp.idx'</span><span class="p">,</span> <span class="s1">'tmp.rec'</span><span class="p">,</span> <span class="s1">'w'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">):</span> |
| <span class="gp">... </span> <span class="n">record</span><span class="o">.</span><span class="n">write_idx</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="s1">'record_</span><span class="si">%d</span><span class="s1">'</span><span class="o">%</span><span class="n">i</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">record</span><span class="o">.</span><span class="n">close</span><span class="p">()</span> |
| <span class="gp">>>> </span><span class="n">record</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">MXIndexedRecordIO</span><span class="p">(</span><span class="s1">'tmp.idx'</span><span class="p">,</span> <span class="s1">'tmp.rec'</span><span class="p">,</span> <span class="s1">'r'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">record</span><span class="o">.</span><span class="n">read_idx</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span> |
| <span class="go">record_3</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| <dl class="method"> |
| <dt id="mxnet.recordio.MXIndexedRecordIO.write_idx"> |
| <code class="descname">write_idx</code><span class="sig-paren">(</span><em>idx</em>, <em>buf</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#MXIndexedRecordIO.write_idx"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.MXIndexedRecordIO.write_idx" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Inserts input record at given index.</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">):</span> |
| <span class="gp">... </span> <span class="n">record</span><span class="o">.</span><span class="n">write_idx</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="s1">'record_</span><span class="si">%d</span><span class="s1">'</span><span class="o">%</span><span class="n">i</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">record</span><span class="o">.</span><span class="n">close</span><span class="p">()</span> |
| </pre></div> |
| </div> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple"> |
| <li><strong>idx</strong> (<em>int</em>) – Index of a file.</li> |
| <li><strong>buf</strong> – Record to write.</li> |
| </ul> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| </dd></dl> |
| </dd></dl> |
| <dl class="attribute"> |
| <dt id="mxnet.recordio.IRHeader"> |
| <code class="descclassname">mxnet.recordio.</code><code class="descname">IRHeader</code><a class="headerlink" href="#mxnet.recordio.IRHeader" title="Permalink to this definition">¶</a></dt> |
| <dd><p>An alias for HEADER. Used to store metadata (e.g. labels) accompanying a record. |
| See mxnet.recordio.pack and mxnet.recordio.pack_img for example uses.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple"> |
| <li><strong>flag</strong> (<em>int</em>) – Available for convenience, can be set arbitrarily.</li> |
| <li><strong>label</strong> (<em>float</em><em> or </em><em>an array of float</em>) – Typically used to store label(s) for a record.</li> |
| <li><strong>id</strong> (<em>int</em>) – Usually a unique id representing record.</li> |
| <li><strong>id2</strong> (<em>int</em>) – Higher order bits of the unique id, should be set to 0 (in most cases).</li> |
| </ul> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| <p>alias of <code class="xref py py-class docutils literal"><span class="pre">HEADER</span></code></p> |
| </dd></dl> |
| <dl class="function"> |
| <dt id="mxnet.recordio.pack"> |
| <code class="descclassname">mxnet.recordio.</code><code class="descname">pack</code><span class="sig-paren">(</span><em>header</em>, <em>s</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#pack"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.pack" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Pack a string into MXImageRecord.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple"> |
| <li><strong>header</strong> (<a class="reference internal" href="#mxnet.recordio.IRHeader" title="mxnet.recordio.IRHeader"><em>IRHeader</em></a>) – Header of the image record. |
| <code class="docutils literal"><span class="pre">header.label</span></code> can be a number or an array. See more detail in <code class="docutils literal"><span class="pre">IRHeader</span></code>.</li> |
| <li><strong>s</strong> (<em>str</em>) – Raw image string to be packed.</li> |
| </ul> |
| </td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first"><strong>s</strong> – The packed string.</p> |
| </td> |
| </tr> |
| <tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">str</p> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Examples</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">label</span> <span class="o">=</span> <span class="mi">4</span> <span class="c1"># label can also be a 1-D array, for example: label = [1,2,3]</span> |
| <span class="gp">>>> </span><span class="nb">id</span> <span class="o">=</span> <span class="mi">2574</span> |
| <span class="gp">>>> </span><span class="n">header</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">IRHeader</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">label</span><span class="p">,</span> <span class="nb">id</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="s1">'r'</span><span class="p">)</span> <span class="k">as</span> <span class="n">file</span><span class="p">:</span> |
| <span class="gp">... </span> <span class="n">s</span> <span class="o">=</span> <span class="n">file</span><span class="o">.</span><span class="n">read</span><span class="p">()</span> |
| <span class="gp">>>> </span><span class="n">packed_s</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">pack</span><span class="p">(</span><span class="n">header</span><span class="p">,</span> <span class="n">s</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| <dl class="function"> |
| <dt id="mxnet.recordio.unpack"> |
| <code class="descclassname">mxnet.recordio.</code><code class="descname">unpack</code><span class="sig-paren">(</span><em>s</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#unpack"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.unpack" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Unpack a MXImageRecord to string.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>s</strong> (<em>str</em>) – String buffer from <code class="docutils literal"><span class="pre">MXRecordIO.read</span></code>.</td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><ul class="simple"> |
| <li><strong>header</strong> (<em>IRHeader</em>) – Header of the image record.</li> |
| <li><strong>s</strong> (<em>str</em>) – Unpacked string.</li> |
| </ul> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Examples</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">record</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">MXRecordIO</span><span class="p">(</span><span class="s1">'test.rec'</span><span class="p">,</span> <span class="s1">'r'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">item</span> <span class="o">=</span> <span class="n">record</span><span class="o">.</span><span class="n">read</span><span class="p">()</span> |
| <span class="gp">>>> </span><span class="n">header</span><span class="p">,</span> <span class="n">s</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">unpack</span><span class="p">(</span><span class="n">item</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">header</span> |
| <span class="go">HEADER(flag=0, label=14.0, id=20129312, id2=0)</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| <dl class="function"> |
| <dt id="mxnet.recordio.unpack_img"> |
| <code class="descclassname">mxnet.recordio.</code><code class="descname">unpack_img</code><span class="sig-paren">(</span><em>s</em>, <em>iscolor=-1</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#unpack_img"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.unpack_img" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Unpack a MXImageRecord to image.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple"> |
| <li><strong>s</strong> (<em>str</em>) – String buffer from <code class="docutils literal"><span class="pre">MXRecordIO.read</span></code>.</li> |
| <li><strong>iscolor</strong> (<em>int</em>) – Image format option for <code class="docutils literal"><span class="pre">cv2.imdecode</span></code>.</li> |
| </ul> |
| </td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"><ul class="simple"> |
| <li><strong>header</strong> (<em>IRHeader</em>) – Header of the image record.</li> |
| <li><strong>img</strong> (<em>numpy.ndarray</em>) – Unpacked image.</li> |
| </ul> |
| </p> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Examples</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">record</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">MXRecordIO</span><span class="p">(</span><span class="s1">'test.rec'</span><span class="p">,</span> <span class="s1">'r'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">item</span> <span class="o">=</span> <span class="n">record</span><span class="o">.</span><span class="n">read</span><span class="p">()</span> |
| <span class="gp">>>> </span><span class="n">header</span><span class="p">,</span> <span class="n">img</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">unpack_img</span><span class="p">(</span><span class="n">item</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">header</span> |
| <span class="go">HEADER(flag=0, label=14.0, id=20129312, id2=0)</span> |
| <span class="gp">>>> </span><span class="n">img</span> |
| <span class="go">array([[[ 23, 27, 45],</span> |
| <span class="go"> [ 28, 32, 50],</span> |
| <span class="go"> ...,</span> |
| <span class="go"> [ 36, 40, 59],</span> |
| <span class="go"> [ 35, 39, 58]],</span> |
| <span class="go"> ...,</span> |
| <span class="go"> [[ 91, 92, 113],</span> |
| <span class="go"> [ 97, 98, 119],</span> |
| <span class="go"> ...,</span> |
| <span class="go"> [168, 169, 167],</span> |
| <span class="go"> [166, 167, 165]]], dtype=uint8)</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
| <dl class="function"> |
| <dt id="mxnet.recordio.pack_img"> |
| <code class="descclassname">mxnet.recordio.</code><code class="descname">pack_img</code><span class="sig-paren">(</span><em>header</em>, <em>img</em>, <em>quality=95</em>, <em>img_fmt='.jpg'</em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/mxnet/recordio.html#pack_img"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mxnet.recordio.pack_img" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Pack an image into <code class="docutils literal"><span class="pre">MXImageRecord</span></code>.</p> |
| <table class="docutils field-list" frame="void" rules="none"> |
| <col class="field-name"/> |
| <col class="field-body"/> |
| <tbody valign="top"> |
| <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple"> |
| <li><strong>header</strong> (<a class="reference internal" href="#mxnet.recordio.IRHeader" title="mxnet.recordio.IRHeader"><em>IRHeader</em></a>) – Header of the image record. |
| <code class="docutils literal"><span class="pre">header.label</span></code> can be a number or an array. See more detail in <code class="docutils literal"><span class="pre">IRHeader</span></code>.</li> |
| <li><strong>img</strong> (<em>numpy.ndarray</em>) – Image to be packed.</li> |
| <li><strong>quality</strong> (<em>int</em>) – Quality for JPEG encoding in range 1-100, or compression for PNG encoding in range 1-9.</li> |
| <li><strong>img_fmt</strong> (<em>str</em>) – Encoding of the image (.jpg for JPEG, .png for PNG).</li> |
| </ul> |
| </td> |
| </tr> |
| <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first"><strong>s</strong> – The packed string.</p> |
| </td> |
| </tr> |
| <tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">str</p> |
| </td> |
| </tr> |
| </tbody> |
| </table> |
| <p class="rubric">Examples</p> |
| <div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">label</span> <span class="o">=</span> <span class="mi">4</span> <span class="c1"># label can also be a 1-D array, for example: label = [1,2,3]</span> |
| <span class="gp">>>> </span><span class="nb">id</span> <span class="o">=</span> <span class="mi">2574</span> |
| <span class="gp">>>> </span><span class="n">header</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">IRHeader</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">label</span><span class="p">,</span> <span class="nb">id</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">img</span> <span class="o">=</span> <span class="n">cv2</span><span class="o">.</span><span class="n">imread</span><span class="p">(</span><span class="s1">'test.jpg'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">packed_s</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">recordio</span><span class="o">.</span><span class="n">pack_img</span><span class="p">(</span><span class="n">header</span><span class="p">,</span> <span class="n">img</span><span class="p">)</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
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| <li><a class="reference internal" href="#">Data Loading API</a><ul> |
| <li><a class="reference internal" href="#overview">Overview</a></li> |
| <li><a class="reference internal" href="#data-iterators">Data iterators</a></li> |
| <li><a class="reference internal" href="#helper-classes-and-functions">Helper classes and functions</a></li> |
| <li><a class="reference internal" href="#develop-a-new-iterator">Develop a new iterator</a><ul> |
| <li><a class="reference internal" href="#change-batch-layout">Change batch layout</a></li> |
| </ul> |
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| <li><a class="reference internal" href="#api-reference">API Reference</a></li> |
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