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<li class="toctree-l1"><a class="reference internal" href="installation.html">安装</a><ul>
<li class="toctree-l2"><a class="reference internal" href="installation.html#conda">从Conda安装</a></li>
<li class="toctree-l2"><a class="reference internal" href="installation.html#id2">从源码安装</a><ul>
<li class="toctree-l3"><a class="reference internal" href="installation.html#condasinga">由conda创建SINGA</a></li>
<li class="toctree-l3"><a class="reference internal" href="installation.html#ubuntusinga">使用本地工具在Ubuntu上创建SINGA</a></li>
<li class="toctree-l3"><a class="reference internal" href="installation.html#windowssinga">在Windows上编译SINGA</a></li>
<li class="toctree-l3"><a class="reference internal" href="installation.html#id3">更多编译选择</a><ul>
<li class="toctree-l4"><a class="reference internal" href="installation.html#use-modules">USE_MODULES</a></li>
<li class="toctree-l4"><a class="reference internal" href="installation.html#use-python">USE_PYTHON</a></li>
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<li class="toctree-l1"><a class="reference internal" href="software_stack.html">软件架构</a><ul>
<li class="toctree-l2"><a class="reference internal" href="software_stack.html#id2">核心</a></li>
<li class="toctree-l2"><a class="reference internal" href="software_stack.html#id3">模型</a></li>
<li class="toctree-l2"><a class="reference internal" href="software_stack.html#id4">输入输出</a></li>
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<li class="toctree-l1"><a class="reference internal" href="device.html">设备(Device)</a><ul>
<li class="toctree-l2"><a class="reference internal" href="device.html#id1">特定设备</a></li>
<li class="toctree-l2"><a class="reference internal" href="device.html#python-api">Python API</a><ul>
<li class="toctree-l3"><a class="reference internal" href="device.html#singa-device-create-cuda-gpus-num">singa.device.create_cuda_gpus(num)</a></li>
<li class="toctree-l3"><a class="reference internal" href="device.html#singa-device-create-cuda-gpus-on-device-ids">singa.device.create_cuda_gpus_on(device_ids)</a></li>
<li class="toctree-l3"><a class="reference internal" href="device.html#singa-device-get-default-device">singa.device.get_default_device()</a></li>
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<li class="toctree-l1"><a class="reference internal" href="tensor.html">张量(Tensor)</a><ul>
<li class="toctree-l2"><a class="reference internal" href="tensor.html#python-api">PYTHON API</a><ul>
<li class="toctree-l3"><a class="reference internal" href="tensor.html#class-singa-tensor-tensor-shape-none-device-none-dtype-0">class singa.tensor.Tensor(shape=None, device=None, dtype=0)</a><ul>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#t">T()</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#add-column-v">add_column(v)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#add-row-v">add_row(v)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#bernoulli-p">bernoulli(p)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#clone">clone()</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#copy">copy()</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#copy-data-t">copy_data(t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#copy-from-numpy-np-array-offset-0">copy_from_numpy(np_array, offset=0)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#deepcopy">deepcopy()</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#div-column-v">div_column(v)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#div-row-v">div_row(v)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#gaussian-mean-std">gaussian(mean, std)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#is-empty">is_empty()</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#is-transpose">is_transpose()</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#l1">l1()</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#l2">l2()</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#memsize">memsize()</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#mult-column-v">mult_column(v)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#mult-row-v">mult_row(v)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#ndim">ndim()</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#reset-like-t">reset_like(t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#set-value-x">set_value(x)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#size">size()</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#to-device-device">to_device(device)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#to-host">to_host()</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#uniform-low-high">uniform(low, high)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-abs-t">singa.tensor.abs(t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-add-lhs-rhs-ret-none">singa.tensor.add(lhs, rhs, ret=None)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-add-column-alpha-v-beta-m">singa.tensor.add_column(alpha, v, beta, M)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-add-row-alpha-v-beta-m">singa.tensor.add_row(alpha, v, beta, M)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-average-t-axis-none">singa.tensor.average(t, axis=None)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-axpy-alpha-x-y">singa.tensor.axpy(alpha, x, y)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-bernoulli-p-t">singa.tensor.bernoulli(p, t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-copy-data-to-from-dst-src-size-dst-offset-0-src-offset-0">singa.tensor.copy_data_to_from(dst, src, size, dst_offset=0, src_offset=0)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-div-lhs-rhs-ret-none">singa.tensor.div(lhs, rhs, ret=None)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-eltwise-mult-lhs-rhs-ret-none">singa.tensor.eltwise_mult(lhs, rhs, ret=None)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-exp-t">singa.tensor.exp(t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-from-numpy-np-array">singa.tensor.from_numpy(np_array)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-gaussian-mean-std-t">singa.tensor.gaussian(mean, std, t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-ge-t-x">singa.tensor.ge(t, x)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-gt-t-x">singa.tensor.gt(t, x)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-le-t-x">singa.tensor.le(t, x)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-lt-t-x">singa.tensor.lt(t, x)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-log-t">singa.tensor.log(t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-mult-a-b-c-none-alpha-1-0-beta-0-0">singa.tensor.mult(A, B, C=None, alpha=1.0, beta=0.0)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-pow-t-x-out-none">singa.tensor.pow(t, x, out=None)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-relu-t">singa.tensor.relu(t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-reshape-t-s">singa.tensor.reshape(t, s)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-sigmoid-t">singa.tensor.sigmoid(t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-sign-t">singa.tensor.sign(t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-sizeof-dtype">singa.tensor.sizeof(dtype)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-softmax-t-out-none">singa.tensor.softmax(t, out=None)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-sqrt-t">singa.tensor.sqrt(t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-square-t">singa.tensor.square(t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-sub-lhs-rhs-ret-none">singa.tensor.sub(lhs, rhs, ret=None)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-sum-t-axis-none">singa.tensor.sum(t, axis=None)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-sum-columns-m">singa.tensor.sum_columns(M)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-sum-rows-m">singa.tensor.sum_rows(M)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-tanh-t">singa.tensor.tanh(t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-to-host-t">singa.tensor.to_host(t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-to-numpy-t">singa.tensor.to_numpy(t)</a></li>
<li class="toctree-l4"><a class="reference internal" href="tensor.html#singa-tensor-uniform-low-high-t">singa.tensor.uniform(low, high, t)</a></li>
</ul>
</li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="layer.html">层(Layer)</a><ul>
<li class="toctree-l2"><a class="reference internal" href="layer.html#python-api">Python API</a><ul>
<li class="toctree-l3"><a class="reference internal" href="layer.html#singa-layer-engine-cudnn">singa.layer.engine = &#8216;cudnn&#8216;</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-layer-name-conf-none-kwargs">class singa.layer.Layer(name, conf=None, **kwargs)</a><ul>
<li class="toctree-l4"><a class="reference internal" href="layer.html#setup-in-shapes">setup(in_shapes)</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#caffe-layer">caffe_layer()</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#get-output-sample-shape">get_output_sample_shape()</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#param-names">param_names()</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#param-values">param_values()</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#forward-flag-x">forward(flag, x)</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#backward-flag-dy">backward(flag, dy)</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#to-device-device">to_device(device)</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-dummy-name-input-sample-shape-none">class singa.layer.Dummy(name, input_sample_shape=None)</a><ul>
<li class="toctree-l4"><a class="reference internal" href="layer.html#id1">forward(flag, x)</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#backward-falg-dy">backward(falg, dy)</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-conv2d-name-nb-kernels-kernel-3-stride-1-border-mode-same-cudnn-prefer-fatest-data-format-nchw-use-bias-true-w-specs-none-b-specs-none-pad-none-input-sample-shape-none">class singa.layer.Conv2D(name, nb_kernels, kernel=3, stride=1, border_mode=&#8216;same&#8216;, cudnn_prefer=&#8216;fatest&#8216;, data_format=&#8216;NCHW&#8216;, use_bias=True, W_specs=None, b_specs=None, pad=None, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-conv1d-name-nb-kernels-kernel-3-stride-1-border-mode-same-cudnn-prefer-fatest-use-bias-true-w-specs-init-xavier-b-specs-init-constant-value-0-pad-none-input-sample-shape-none">class singa.layer.Conv1D(name, nb_kernels, kernel=3, stride=1, border_mode=&#8216;same&#8216;, cudnn_prefer=&#8216;fatest&#8216;, use_bias=True, W_specs={&#8216;init&#8216;: &#8216;Xavier&#8216;}, b_specs={&#8216;init&#8216;: &#8216;Constant&#8216;, &#8216;value&#8216;: 0}, pad=None, input_sample_shape=None)</a><ul>
<li class="toctree-l4"><a class="reference internal" href="layer.html#id2">get_output_sample_shape()</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-pooling2d-name-mode-kernel-3-stride-2-border-mode-same-pad-none-data-format-nchw-input-sample-shape-none">class singa.layer.Pooling2D(name, mode, kernel=3, stride=2, border_mode=&#8216;same&#8216;, pad=None, data_format=&#8216;NCHW&#8216;, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-maxpooling2d-name-kernel-3-stride-2-border-mode-same-pad-none-data-format-nchw-input-sample-shape-none">class singa.layer.MaxPooling2D(name, kernel=3, stride=2, border_mode=&#8216;same&#8216;, pad=None, data_format=&#8216;NCHW&#8216;, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-avgpooling2d-name-kernel-3-stride-2-border-mode-same-pad-none-data-format-nchw-input-sample-shape-none">class singa.layer.AvgPooling2D(name, kernel=3, stride=2, border_mode=&#8216;same&#8216;, pad=None, data_format=&#8216;NCHW&#8216;, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-maxpooling1d-name-kernel-3-stride-2-border-mode-same-pad-none-data-format-nchw-input-sample-shape-none">class singa.layer.MaxPooling1D(name, kernel=3, stride=2, border_mode=&#8216;same&#8216;, pad=None, data_format=&#8216;NCHW&#8216;, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-avgpooling1d-name-kernel-3-stride-2-border-mode-same-pad-none-data-format-nchw-input-sample-shape-none">class singa.layer.AvgPooling1D(name, kernel=3, stride=2, border_mode=&#8216;same&#8216;, pad=None, data_format=&#8216;NCHW&#8216;, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-batchnormalization-name-momentum-0-9-beta-specs-none-gamma-specs-none-input-sample-shape-none">class singa.layer.BatchNormalization(name, momentum=0.9, beta_specs=None, gamma_specs=None, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-lrn-name-size-5-alpha-1-beta-0-75-mode-cross-channel-k-1-input-sample-shape-none">class singa.layer.LRN(name, size=5, alpha=1, beta=0.75, mode=&#8216;cross_channel&#8216;, k=1, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-dense-name-num-output-use-bias-true-w-specs-none-b-specs-none-w-transpose-false-input-sample-shape-none">class singa.layer.Dense(name, num_output, use_bias=True, W_specs=None, b_specs=None, W_transpose=False, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-dropout-name-p-0-5-input-sample-shape-none">class singa.layer.Dropout(name, p=0.5, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-activation-name-mode-relu-input-sample-shape-none">class singa.layer.Activation(name, mode=&#8216;relu&#8216;, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-softmax-name-axis-1-input-sample-shape-none">class singa.layer.Softmax(name, axis=1, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-flatten-name-axis-1-input-sample-shape-none">class singa.layer.Flatten(name, axis=1, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-merge-name-input-sample-shape-none">class singa.layer.Merge(name, input_sample_shape=None)</a><ul>
<li class="toctree-l4"><a class="reference internal" href="layer.html#setup-in-shape">setup(in_shape)</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#id3">get_output_sample_shape()</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#forward-flag-inputs">forward(flag, inputs)</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#backward-flag-grad">backward(flag, grad)</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-split-name-num-output-input-sample-shape-none">class singa.layer.Split(name, num_output, input_sample_shape=None)</a><ul>
<li class="toctree-l4"><a class="reference internal" href="layer.html#id4">setup(in_shape)</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#id5">get_output_sample_shape()</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#forward">forward()</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#backward">backward()</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-concat-name-axis-input-sample-shapes-none">class singa.layer.Concat(name, axis, input_sample_shapes=None)</a><ul>
<li class="toctree-l4"><a class="reference internal" href="layer.html#id6">forward(flag, inputs)</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#id7">backward(flag, dy)</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-slice-name-axis-slice-point-input-sample-shape-none">class singa.layer.Slice(name, axis, slice_point, input_sample_shape=None)</a><ul>
<li class="toctree-l4"><a class="reference internal" href="layer.html#id8">get_output_sample_shape()</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#id9">forward(flag, x)</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#backward-flag-grads">backward(flag, grads)</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-rnn-name-hidden-size-rnn-mode-lstm-dropout-0-0-num-stacks-1-input-mode-linear-bidirectional-false-param-specs-none-input-sample-shape-none">class singa.layer.RNN(name, hidden_size, rnn_mode=&#8216;lstm&#8216;, dropout=0.0, num_stacks=1, input_mode=&#8216;linear&#8216;, bidirectional=False, param_specs=None, input_sample_shape=None)</a><ul>
<li class="toctree-l4"><a class="reference internal" href="layer.html#id10">forward(flag, inputs)</a></li>
<li class="toctree-l4"><a class="reference internal" href="layer.html#id11">backward(flag, grad)</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-lstm-name-hidden-size-dropout-0-0-num-stacks-1-input-mode-linear-bidirectional-false-param-specs-none-input-sample-shape-none">class singa.layer.LSTM(name, hidden_size, dropout=0.0, num_stacks=1, input_mode=&#8216;linear&#8216;, bidirectional=False, param_specs=None, input_sample_shape=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="layer.html#class-singa-layer-gru-name-hidden-size-dropout-0-0-num-stacks-1-input-mode-linear-bidirectional-false-param-specs-none-input-sample-shape-none">class singa.layer.GRU(name, hidden_size, dropout=0.0, num_stacks=1, input_mode=&#8216;linear&#8216;, bidirectional=False, param_specs=None, input_sample_shape=None)</a><ul>
<li class="toctree-l4"><a class="reference internal" href="layer.html#singa-layer-get-layer-list">singa.layer.get_layer_list()</a></li>
</ul>
</li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="net.html">前馈网络</a><ul>
<li class="toctree-l2"><a class="reference internal" href="net.html#class-singa-net-feedforwardnet-loss-none-metric-none">class singa.net.FeedForwardNet(loss=None, metric=None)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="net.html#to-device-dev">to_device(dev)</a></li>
<li class="toctree-l3"><a class="reference internal" href="net.html#add-lyr-src-none">add(lyr, src=None)</a></li>
<li class="toctree-l3"><a class="reference internal" href="net.html#param-values">param_values()</a></li>
<li class="toctree-l3"><a class="reference internal" href="net.html#param-specs">param_specs()</a></li>
<li class="toctree-l3"><a class="reference internal" href="net.html#param-names">param_names()</a></li>
<li class="toctree-l3"><a class="reference internal" href="net.html#train-x-y">train(x, y)</a></li>
<li class="toctree-l3"><a class="reference internal" href="net.html#evaluate-x-y">evaluate(x, y)</a></li>
<li class="toctree-l3"><a class="reference internal" href="net.html#predict-x">predict(x)</a></li>
<li class="toctree-l3"><a class="reference internal" href="net.html#topo-sort-layers-src-of-layer">topo_sort(layers, src_of_layer)</a></li>
<li class="toctree-l3"><a class="reference internal" href="net.html#forward-flag-x-output">forward(flag, x, output=[])</a></li>
<li class="toctree-l3"><a class="reference internal" href="net.html#backward">backward()</a></li>
<li class="toctree-l3"><a class="reference internal" href="net.html#save-f-buffer-size-10-use-pickle-false">save(f, buffer_size=10, use_pickle=False)</a></li>
<li class="toctree-l3"><a class="reference internal" href="net.html#load-f-buffer-size-10-use-pickle-false">load(f, buffer_size=10, use_pickle=False)</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="initializer.html">初始化器(Initializer)</a><ul>
<li class="toctree-l2"><a class="reference internal" href="initializer.html#python-api">Python API</a><ul>
<li class="toctree-l3"><a class="reference internal" href="initializer.html#singa-initializer-uniform-t-fan-in-0-fan-out-0">singa.initializer.uniform(t, fan_in=0, fan_out=0)</a></li>
<li class="toctree-l3"><a class="reference internal" href="initializer.html#singa-initializer-gaussian-t-fan-in-0-fan-out-0">singa.initializer.gaussian(t, fan_in=0, fan_out=0)</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="loss.html">损失(Loss)</a><ul>
<li class="toctree-l2"><a class="reference internal" href="loss.html#class-singa-loss-loss">class singa.loss.Loss</a><ul>
<li class="toctree-l3"><a class="reference internal" href="loss.html#backward">backward()</a></li>
<li class="toctree-l3"><a class="reference internal" href="loss.html#evaluate-flag-x-y">evaluate(flag, x, y)</a></li>
<li class="toctree-l3"><a class="reference internal" href="loss.html#forward-flag-x-y">forward(flag, x, y)</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="loss.html#class-singa-loss-softmaxcrossentropy">class singa.loss.SoftmaxCrossEntropy</a></li>
<li class="toctree-l2"><a class="reference internal" href="loss.html#class-singa-loss-squarederror">class singa.loss.SquaredError</a><ul>
<li class="toctree-l3"><a class="reference internal" href="loss.html#id1">backward()</a></li>
<li class="toctree-l3"><a class="reference internal" href="loss.html#id2">evaluate(flag, x, y)</a></li>
<li class="toctree-l3"><a class="reference internal" href="loss.html#id3">forward(flag, x, y)</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="metric.html">度量(Metric)</a><ul>
<li class="toctree-l2"><a class="reference internal" href="metric.html#class-singa-metric-metric">class singa.metric.Metric</a><ul>
<li class="toctree-l3"><a class="reference internal" href="metric.html#forward-x-y">forward(x, y)</a></li>
<li class="toctree-l3"><a class="reference internal" href="metric.html#evaluate-x-y">evaluate(x, y)</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="metric.html#class-singa-metric-accuracy">class singa.metric.Accuracy</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="optimizer.html">优化器(Optimizer)</a><ul>
<li class="toctree-l2"><a class="reference internal" href="optimizer.html#class-singa-optimizer-optimizer-lr-none-momentum-none-weight-decay-none-regularizer-none-constraint-none">class singa.optimizer.Optimizer(lr=None, momentum=None, weight_decay=None, regularizer=None, constraint=None)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#register-name-specs">register(name, specs)</a></li>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#apply-regularizer-constraint-epoch-value-grad-name-none-step-1">apply_regularizer_constraint(epoch, value, grad, name=None, step=-1)</a></li>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#apply-with-lr-epoch-lr-grad-value-name-none-step-1">apply_with_lr(epoch, lr, grad, value, name=None, step=-1)</a></li>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#apply-epoch-grad-value-name-none-step-1">apply(epoch, grad, value, name=None, step=-1)</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="optimizer.html#class-singa-optimizer-sgd-lr-none-momentum-none-weight-decay-none-regularizer-none-constraint-none">class singa.optimizer.SGD(lr=None, momentum=None, weight_decay=None, regularizer=None, constraint=None)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#apply-with-lr-epoch-lr-grad-value-name-step-1">apply_with_lr(epoch, lr, grad, value, name, step=-1)</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="optimizer.html#class-singa-optimizer-nesterov-lr-none-momentum-0-9-weight-decay-none-regularizer-none-constraint-none">class singa.optimizer.Nesterov(lr=None, momentum=0.9, weight_decay=None, regularizer=None, constraint=None)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#id1">apply_with_lr(epoch, lr, grad, value, name, step=-1)</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="optimizer.html#class-singa-optimizer-rmsprop-rho-0-9-epsilon-1e-08-lr-none-weight-decay-none-regularizer-none-constraint-none">class singa.optimizer.RMSProp(rho=0.9, epsilon=1e-08, lr=None, weight_decay=None, regularizer=None, constraint=None)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#id2">apply_with_lr(epoch, lr, grad, value, name, step=-1)</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="optimizer.html#class-singa-optimizer-adagrad-epsilon-1e-08-lr-none-weight-decay-none-lr-gen-none-regularizer-none-constraint-none">class singa.optimizer.AdaGrad(epsilon=1e-08, lr=None, weight_decay=None, lr_gen=None, regularizer=None, constraint=None)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#id3">apply_with_lr(epoch, lr, grad, value, name, step=-1)</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="optimizer.html#class-singa-optimizer-adam-beta-1-0-9-beta-2-0-999-epsilon-1e-08-lr-none-weight-decay-none-regularizer-none-constraint-none">class singa.optimizer.Adam(beta_1=0.9, beta_2=0.999, epsilon=1e-08, lr=None, weight_decay=None, regularizer=None, constraint=None)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#id4">apply_with_lr(epoch, lr, grad, value, name, step=-1)</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="optimizer.html#class-singa-optimizer-regularizer">class singa.optimizer.Regularizer</a><ul>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#apply-epoch-value-grad-step-1">apply(epoch, value, grad, step=-1)</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="optimizer.html#class-singa-optimizer-cppregularizer-conf">class singa.optimizer.CppRegularizer(conf)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#id5">apply(epoch, value, grad, step=-1)</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="optimizer.html#class-singa-optimizer-l2regularizer-coefficient">class singa.optimizer.L2Regularizer(coefficient)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#id6">apply(epoch, value, grad, step=-1)</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="optimizer.html#class-singa-optimizer-constraint">class singa.optimizer.Constraint</a><ul>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#id7">apply(epoch, value, grad, step=-1)</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="optimizer.html#class-singa-optimizer-cppconstraint-conf">class singa.optimizer.CppConstraint(conf)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#id8">apply(epoch, value, grad, step=-1)</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="optimizer.html#class-singa-optimizer-l2constraint-threshold-none">class singa.optimizer.L2Constraint(threshold=None)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="optimizer.html#id9">apply(epoch, value, grad, step=-1)</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="data.html">数据(Data)</a><ul>
<li class="toctree-l2"><a class="reference internal" href="data.html#class-singa-data-imagebatchiter-img-list-file-batch-size-image-transform-shuffle-true-delimiter-image-folder-none-capacity-10">class singa.data.ImageBatchIter(img_list_file, batch_size, image_transform, shuffle=True, delimiter=&#8216; &#8216;, image_folder=None, capacity=10)</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="image_tool.html">图像工具</a><ul>
<li class="toctree-l2"><a class="reference internal" href="image_tool.html#class-singa-image-tool-imagetool">class singa.image_tool.ImageTool</a><ul>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#color-cast-offset-20-inplace-true">color_cast(offset=20, inplace=True)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#crop3-patch-num-case-1-inplace-true">crop3(patch, num_case=1, inplace=True)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#crop5-patch-num-case-1-inplace-true">crop5(patch, num_case=1, inplace=True)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#crop8-patch-num-case-1-inplace-true">crop8(patch, num_case=1, inplace=True)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#enhance-scale-0-2-inplace-true">enhance(scale=0.2, inplace=True)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#flip-num-case-1-inplace-true">flip(num_case=1, inplace=True)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#num-augmentation">num_augmentation()</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#random-crop-patch-inplace-true">random_crop(patch, inplace=True)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#resize-by-list-size-list-num-case-1-inplace-true">resize_by_list(size_list, num_case=1, inplace=True)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#resize-by-range-rng-inplace-true">resize_by_range(rng, inplace=True)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#rotate-by-list-angle-list-num-case-1-inplace-true">rotate_by_list(angle_list, num_case=1, inplace=True)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#rotate-by-range-rng-inplace-true">rotate_by_range(rng, inplace=True)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#singa-image-tool-color-cast-img-offset">singa.image_tool.color_cast(img, offset)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#singa-image-tool-crop-img-patch-position">singa.image_tool.crop(img, patch, position)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#singa-image-tool-crop-and-resize-img-patch-position">singa.image_tool.crop_and_resize(img, patch, position)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#singa-image-tool-enhance-img-scale">singa.image_tool.enhance(img, scale)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#singa-image-tool-load-img-path-grayscale-false">singa.image_tool.load_img(path, grayscale=False)</a></li>
<li class="toctree-l3"><a class="reference internal" href="image_tool.html#singa-image-tool-resize-img-small-size">singa.image_tool.resize(img, small_size)</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="snapshot.html">Snapshot</a><ul>
<li class="toctree-l2"><a class="reference internal" href="snapshot.html#class-singa-snapshot-snapshot-f-mode-buffer-size-10">class singa.snapshot.Snapshot(f, mode, buffer_size=10)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="snapshot.html#read">read()</a></li>
<li class="toctree-l3"><a class="reference internal" href="snapshot.html#write-param-name-param-val">write(param_name, param_val)</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="utils.html">Utils</a><ul>
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