MNIST-TP-200

Not a large MNIST model with 200 parameters, accuracy: 0.8353000283241272 loss: 0.5836790204048157

<div class="display_data output-id-1"><div class="output_subarea output_html rendered_html"><pre style="white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace"><span style="font-weight: bold">Model: "MNIST_model"</span> </pre> </div></div><div class="display_data output-id-2"><div class="output_subarea output_html rendered_html"><pre style="white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓ ┃<span style="font-weight: bold"> Layer (type) </span>┃<span style="font-weight: bold"> Output Shape </span>┃<span style="font-weight: bold"> Param # </span>┃ ┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩ │ input_layer_8 (<span style="color: #0087ff; text-decoration-color: #0087ff">InputLayer</span>) │ (<span style="color: #00d7ff; text-decoration-color: #00d7ff">None</span>, <span style="color: #00af00; text-decoration-color: #00af00">28</span>, <span style="color: #00af00; text-decoration-color: #00af00">28</span>) │ <span style="color: #00af00; text-decoration-color: #00af00">0</span> │ ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ │ reshape_16 (<span style="color: #0087ff; text-decoration-color: #0087ff">Reshape</span>) │ (<span style="color: #00d7ff; text-decoration-color: #00d7ff">None</span>, <span style="color: #00af00; text-decoration-color: #00af00">28</span>, <span style="color: #00af00; text-decoration-color: #00af00">28</span>, <span style="color: #00af00; text-decoration-color: #00af00">1</span>) │ <span style="color: #00af00; text-decoration-color: #00af00">0</span> │ ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ │ depthwise_conv2d_32 │ (<span style="color: #00d7ff; text-decoration-color: #00d7ff">None</span>, <span style="color: #00af00; text-decoration-color: #00af00">13</span>, <span style="color: #00af00; text-decoration-color: #00af00">13</span>, <span style="color: #00af00; text-decoration-color: #00af00">5</span>) │ <span style="color: #00af00; text-decoration-color: #00af00">50</span> │ │ (<span style="color: #0087ff; text-decoration-color: #0087ff">DepthwiseConv2D</span>) │ │ │ ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ │ depthwise_conv2d_33 │ (<span style="color: #00d7ff; text-decoration-color: #00d7ff">None</span>, <span style="color: #00af00; text-decoration-color: #00af00">6</span>, <span style="color: #00af00; text-decoration-color: #00af00">6</span>, <span style="color: #00af00; text-decoration-color: #00af00">5</span>) │ <span style="color: #00af00; text-decoration-color: #00af00">50</span> │ │ (<span style="color: #0087ff; text-decoration-color: #0087ff">DepthwiseConv2D</span>) │ │ │ ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ │ depthwise_conv2d_34 │ (<span style="color: #00d7ff; text-decoration-color: #00d7ff">None</span>, <span style="color: #00af00; text-decoration-color: #00af00">2</span>, <span style="color: #00af00; text-decoration-color: #00af00">2</span>, <span style="color: #00af00; text-decoration-color: #00af00">5</span>) │ <span style="color: #00af00; text-decoration-color: #00af00">50</span> │ │ (<span style="color: #0087ff; text-decoration-color: #0087ff">DepthwiseConv2D</span>) │ │ │ ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ │ depthwise_conv2d_35 │ (<span style="color: #00d7ff; text-decoration-color: #00d7ff">None</span>, <span style="color: #00af00; text-decoration-color: #00af00">1</span>, <span style="color: #00af00; text-decoration-color: #00af00">1</span>, <span style="color: #00af00; text-decoration-color: #00af00">10</span>) │ <span style="color: #00af00; text-decoration-color: #00af00">50</span> │ │ (<span style="color: #0087ff; text-decoration-color: #0087ff">DepthwiseConv2D</span>) │ │ │ ├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤ │ reshape_17 (<span style="color: #0087ff; text-decoration-color: #0087ff">Reshape</span>) │ (<span style="color: #00d7ff; text-decoration-color: #00d7ff">None</span>, <span style="color: #00af00; text-decoration-color: #00af00">10</span>) │ <span style="color: #00af00; text-decoration-color: #00af00">0</span> │ └──────────────────────────────────────┴─────────────────────────────┴─────────────────┘ </pre> </div></div><div class="display_data output-id-3"><div class="output_subarea output_html rendered_html"><pre style="white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace"><span style="font-weight: bold"> Total params: </span><span style="color: #00af00; text-decoration-color: #00af00">200</span> (800.00 B) </pre> </div></div><div class="display_data output-id-4"><div class="output_subarea output_html rendered_html"><pre style="white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace"><span style="font-weight: bold"> Trainable params: </span><span style="color: #00af00; text-decoration-color: #00af00">200</span> (800.00 B) </pre> </div></div><div class="display_data output-id-5"><div class="output_subarea output_html rendered_html"><pre style="white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace"><span style="font-weight: bold"> Non-trainable params: </span><span style="color: #00af00; text-decoration-color: #00af00">0</span> (0.00 B) </pre> </div></div>