ja translation

translate_cache/transformers/compressive/experiment.ja.json

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+{
+ "<h1>Compressive Transformer Experiment</h1>\n<p>This is an annotated PyTorch experiment to train a compressive transformer model.</p>\n": "<h1>\u5727\u7e2e\u5909\u5727\u5668\u5b9f\u9a13</h1>\n<p>\u3053\u308c\u306f\u3001\u5727\u7e2e\u30c8\u30e9\u30f3\u30b9\u30e2\u30c7\u30eb\u3092\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3059\u308b\u305f\u3081\u306e\u6ce8\u91c8\u4ed8\u304d\u306e PyTorch \u5b9f\u9a13\u3067\u3059\u3002</p>\n",
+ "<h2>Auto regressive model</h2>\n": "<h2>\u81ea\u52d5\u56de\u5e30\u30e2\u30c7\u30eb</h2>\n",
+ "<h2>Configurations</h2>\n<p>The default configurations can and will be overridden when we start the experiment.</p>\n": "<h2>\u30b3\u30f3\u30d5\u30a3\u30ae\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3</h2>\n<p>\u30c7\u30d5\u30a9\u30eb\u30c8\u306e\u69cb\u6210\u306f\u3001\u5b9f\u9a13\u3092\u958b\u59cb\u3059\u308b\u3068\u304d\u306b\u4e0a\u66f8\u304d\u3067\u304d\u307e\u3059\u3002\u307e\u305f\u3001\u4eca\u5f8c\u5909\u66f4\u3059\u308b\u4e88\u5b9a\u3067\u3059\u3002</p>\n",
+ "<h3>Initialize the attention reconstruction loss</h3>\n": "<h3>\u6ce8\u610f\u529b\u518d\u69cb\u7bc9\u30ed\u30b9\u3092\u521d\u671f\u5316</h3>\n",
+ "<h3>Initialize the auto-regressive model</h3>\n": "<h3>\u81ea\u5df1\u56de\u5e30\u30e2\u30c7\u30eb\u3092\u521d\u671f\u5316</h3>\n",
+ "<h3>Run the experiment</h3>\n": "<h3>\u5b9f\u9a13\u3092\u5b9f\u884c\u3059\u308b</h3>\n",
+ "<h3>Sampling function to generate samples periodically while training</h3>\n": "<h3>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u4e2d\u306b\u5b9a\u671f\u7684\u306b\u30b5\u30f3\u30d7\u30eb\u3092\u751f\u6210\u3059\u308b\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u6a5f\u80fd</h3>\n",
+ "<h3>Training/validation step</h3>\n": "<h3>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0/\u691c\u8a3c\u30b9\u30c6\u30c3\u30d7</h3>\n",
+ "<p> </p>\n": "<p></p>\n",
+ "<p> Concatenate new memories and compress the oldest memories.</p>\n": "<p>\u65b0\u3057\u3044\u8a18\u61b6\u3092\u9023\u7d50\u3057\u3001\u6700\u3082\u53e4\u3044\u8a18\u61b6\u3092\u5727\u7e2e\u3057\u307e\u3059\u3002</p>\n",
+ "<p><span translate=no>_^_0_^_</span> </p>\n": "<p><span translate=no>_^_0_^_</span></p>\n",
+ "<p>A dictionary of configurations to override </p>\n": "<p>\u30aa\u30fc\u30d0\u30fc\u30e9\u30a4\u30c9\u3059\u308b\u8a2d\u5b9a\u306e\u8f9e\u66f8</p>\n",
+ "<p>A list to keep memories that need to be compressed for each layer. </p>\n": "<p>\u30ec\u30a4\u30e4\u30fc\u3054\u3068\u306b\u5727\u7e2e\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u30e1\u30e2\u30ea\u3092\u4fdd\u5b58\u3059\u308b\u305f\u3081\u306e\u30ea\u30b9\u30c8\u3002</p>\n",
+ "<p>A list to keep the memories that do not get compressed for each layer. </p>\n": "<p>\u30ec\u30a4\u30e4\u30fc\u3054\u3068\u306b\u5727\u7e2e\u3055\u308c\u306a\u3044\u30e1\u30e2\u30ea\u3092\u4fdd\u5b58\u3059\u308b\u305f\u3081\u306e\u30ea\u30b9\u30c8\u3002</p>\n",
+ "<p>Add a hook to log module outputs </p>\n": "<p>\u30e2\u30b8\u30e5\u30fc\u30eb\u51fa\u529b\u3092\u30ed\u30b0\u306b\u8a18\u9332\u3059\u308b\u30d5\u30c3\u30af\u3092\u8ffd\u52a0</p>\n",
+ "<p>Add attention reconstruction loss to loss </p>\n": "<p>\u640d\u5931\u306b\u6ce8\u610f\u518d\u69cb\u7bc9\u640d\u5931\u3092\u8ffd\u52a0</p>\n",
+ "<p>Add the prediction for logging </p>\n": "<p>\u30ed\u30ae\u30f3\u30b0\u7528\u306e\u4e88\u6e2c\u3092\u8ffd\u52a0</p>\n",
+ "<p>Add the prediction to prompt </p>\n": "<p>\u4e88\u6e2c\u3092\u30d7\u30ed\u30f3\u30d7\u30c8\u306b\u8ffd\u52a0</p>\n",
+ "<p>Attention Reconstruction Loss </p>\n": "<p>\u6ce8\u610f\u529b\u518d\u5efa\u30ed\u30b9</p>\n",
+ "<p>Calculate and log accuracy </p>\n": "<p>\u7cbe\u5ea6\u306e\u8a08\u7b97\u3068\u8a18\u9332</p>\n",
+ "<p>Calculate and log cross entropy loss </p>\n": "<p>\u30af\u30ed\u30b9\u30a8\u30f3\u30c8\u30ed\u30d4\u30fc\u640d\u5931\u306e\u8a08\u7b97\u3068\u8a18\u9332</p>\n",
+ "<p>Calculate attention reconstruction loss if memories were compressed in this step </p>\n": "<p>\u3053\u306e\u30b9\u30c6\u30c3\u30d7\u3067\u8a18\u61b6\u304c\u5727\u7e2e\u3055\u308c\u305f\u5834\u5408\u306e\u6ce8\u610f\u518d\u69cb\u6210\u640d\u5931\u3092\u8a08\u7b97\u3057\u307e\u3059\u3002</p>\n",
+ "<p>Calculate gradients </p>\n": "<p>\u52fe\u914d\u306e\u8a08\u7b97</p>\n",
+ "<p>Calculate the number of compressed memories to make <span translate=no>_^_0_^_</span>, where <span translate=no>_^_1_^_</span> is the number of memories we have and <span translate=no>_^_2_^_</span> is the maximum number of memories we maintain (<span translate=no>_^_3_^_</span>). </p>\n": "<p>\u4f5c\u6210\u3059\u308b\u5727\u7e2e\u30e1\u30e2\u30ea\u306e\u6570\u3092\u8a08\u7b97\u3057\u307e\u3059\u3002\u3053\u3053\u3067<span translate=no>_^_0_^_</span>\u3001<span translate=no>_^_1_^_</span>\u306f\u4fdd\u6301\u3059\u308b\u30e1\u30e2\u30ea\u306e\u6700\u5927\u6570\u3001<span translate=no>_^_2_^_</span>\u306f\u4fdd\u6301\u3059\u308b\u30e1\u30e2\u30ea\u306e\u6700\u5927\u6570 (<span translate=no>_^_3_^_</span>)\u3002</p>\n",
+ "<p>Clear the gradients </p>\n": "<p>\u30b0\u30e9\u30c7\u30fc\u30b7\u30e7\u30f3\u3092\u30af\u30ea\u30a2</p>\n",
+ "<p>Clip gradients </p>\n": "<p>\u30af\u30ea\u30c3\u30d7\u30b0\u30e9\u30c7\u30fc\u30b7\u30e7\u30f3</p>\n",
+ "<p>Collect memories to compress </p>\n": "<p>\u601d\u3044\u51fa\u3092\u96c6\u3081\u3066\u5727\u7e2e</p>\n",
+ "<p>Collect output for printing </p>\n": "<p>\u5370\u5237\u7528\u306e\u51fa\u529b\u3092\u53ce\u96c6</p>\n",
+ "<p>Collect remaining memories </p>\n": "<p>\u6b8b\u308a\u306e\u601d\u3044\u51fa\u3092\u96c6\u3081\u3088\u3046</p>\n",
+ "<p>Compress the memories </p>\n": "<p>\u601d\u3044\u51fa\u3092\u5727\u7e2e</p>\n",
+ "<p>Compress the oldest memories if there are more memories than <span translate=no>_^_0_^_</span> </p>\n": "<p>\u3088\u308a\u591a\u304f\u306e\u30e1\u30e2\u30ea\u304c\u3042\u308b\u5834\u5408\u306f\u3001\u6700\u3082\u53e4\u3044\u30e1\u30e2\u30ea\u3092\u5727\u7e2e\u3057\u307e\u3059 <span translate=no>_^_0_^_</span></p>\n",
+ "<p>Compressed memory length </p>\n": "<p>\u5727\u7e2e\u30e1\u30e2\u30ea\u9577</p>\n",
+ "<p>Compression rate </p>\n": "<p>\u5727\u7e2e\u7387</p>\n",
+ "<p>Concatenate new memories with old memory </p>\n": "<p>\u65b0\u3057\u3044\u8a18\u61b6\u3068\u53e4\u3044\u8a18\u61b6\u3092\u3064\u306a\u3052\u308b</p>\n",
+ "<p>Concatenate newly compressed memories with old compressed memories </p>\n": "<p>\u65b0\u3057\u304f\u5727\u7e2e\u3055\u308c\u305f\u30e1\u30e2\u30ea\u3092\u53e4\u3044\u5727\u7e2e\u30e1\u30e2\u30ea\u3068\u9023\u7d50\u3059\u308b</p>\n",
+ "<p>Concatenate the masks if there is memory </p>\n": "<p>\u30e1\u30e2\u30ea\u304c\u3042\u308b\u5834\u5408\u306f\u30de\u30b9\u30af\u3092\u9023\u7d50\u3057\u3066\u304f\u3060\u3055\u3044</p>\n",
+ "<p>Create a subsequent mask for tokens </p>\n": "<p>\u30c8\u30fc\u30af\u30f3\u306e\u30de\u30b9\u30af\u3092\u5f8c\u304b\u3089\u4f5c\u6210</p>\n",
+ "<p>Create an all ones (full visibility) mask for memory </p>\n": "<p>\u30e1\u30e2\u30ea\u7528\u306e\u30aa\u30fc\u30eb\u30ef\u30f3 (\u30d5\u30eb\u30d3\u30b8\u30d3\u30ea\u30c6\u30a3) \u30de\u30b9\u30af\u3092\u4f5c\u6210</p>\n",
+ "<p>Create configs </p>\n": "<p>\u30b3\u30f3\u30d5\u30a3\u30b0\u306e\u4f5c\u6210</p>\n",
+ "<p>Create experiment </p>\n": "<p>\u5b9f\u9a13\u3092\u4f5c\u6210</p>\n",
+ "<p>Do not print the attention reconstruction loss in the terminal </p>\n": "<p>\u7aef\u672b\u306b\u6ce8\u610f\u518d\u69cb\u6210\u30ed\u30b9\u3092\u5370\u5237\u3057\u306a\u3044\u3067\u304f\u3060\u3055\u3044</p>\n",
+ "<p>Dropout probability </p>\n": "<p>\u8131\u843d\u78ba\u7387</p>\n",
+ "<p>Final layer </p>\n": "<p>\u6700\u7d42\u30ec\u30a4\u30e4\u30fc</p>\n",
+ "<p>Generate logits of the next token </p>\n": "<p>\u6b21\u306e\u30c8\u30fc\u30af\u30f3\u306e\u30ed\u30b8\u30c3\u30c8\u3092\u751f\u6210</p>\n",
+ "<p>Get attention reconstruction loss </p>\n": "<p>\u6ce8\u610f\u3092\u5411\u3051\u3066\u518d\u5efa\u30ed\u30b9</p>\n",
+ "<p>Get memories </p>\n": "<p>\u601d\u3044\u51fa\u3092\u30b2\u30c3\u30c8</p>\n",
+ "<p>Get memory and compressed memory </p>\n": "<p>\u30e1\u30e2\u30ea\u3068\u5727\u7e2e\u30e1\u30e2\u30ea\u3092\u53d6\u5f97</p>\n",
+ "<p>Get the model output </p>\n": "<p>\u30e2\u30c7\u30eb\u51fa\u529b\u3092\u53d6\u5f97</p>\n",
+ "<p>Get the model prediction (greedy) </p>\n": "<p>\u30e2\u30c7\u30eb\u4e88\u6e2c\u3092\u53d6\u5f97 (\u6b32\u5f35\u308a)</p>\n",
+ "<p>If the configurations specify not to use memory </p>\n": "<p>\u69cb\u6210\u3067\u30e1\u30e2\u30ea\u3092\u4f7f\u7528\u3057\u306a\u3044\u3088\u3046\u6307\u5b9a\u3055\u308c\u3066\u3044\u308b\u5834\u5408</p>\n",
+ "<p>If there are no old compressed memories </p>\n": "<p>\u53e4\u3044\u5727\u7e2e\u30e1\u30e2\u30ea\u304c\u306a\u3044\u5834\u5408</p>\n",
+ "<p>Iterate through memories of each layer. </p>\n": "<p>\u5404\u30ec\u30a4\u30e4\u30fc\u306e\u30e1\u30e2\u30ea\u3092\u7e70\u308a\u8fd4\u3057\u51e6\u7406\u3057\u307e\u3059\u3002</p>\n",
+ "<p>Load configurations </p>\n": "<p>\u69cb\u6210\u3092\u30ed\u30fc\u30c9</p>\n",
+ "<p>Log the model parameters and gradients on last batch of every epoch </p>\n": "<p>\u5404\u30a8\u30dd\u30c3\u30af\u306e\u6700\u5f8c\u306e\u30d0\u30c3\u30c1\u3067\u30e2\u30c7\u30eb\u30d1\u30e9\u30e1\u30fc\u30bf\u3068\u52fe\u914d\u3092\u8a18\u9332\u3057\u307e\u3059</p>\n",
+ "<p>Masks </p>\n": "<p>\u30de\u30b9\u30af</p>\n",
+ "<p>Merge and compress memory </p>\n": "<p>\u30e1\u30e2\u30ea\u306e\u7d71\u5408\u3068\u5727\u7e2e</p>\n",
+ "<p>Move data to the device </p>\n": "<p>\u30c7\u30fc\u30bf\u3092\u30c7\u30d0\u30a4\u30b9\u306b\u79fb\u52d5</p>\n",
+ "<p>Move to device </p>\n": "<p>\u30c7\u30d0\u30a4\u30b9\u306b\u79fb\u52d5</p>\n",
+ "<p>No memories are compressed if the number of memories is less than <span translate=no>_^_0_^_</span> </p>\n": "<p>\u30e1\u30e2\u30ea\u306e\u6570\u304c\u4ee5\u4e0b\u306e\u5834\u5408\u3001\u30e1\u30e2\u30ea\u306f\u5727\u7e2e\u3055\u308c\u307e\u305b\u3093 <span translate=no>_^_0_^_</span></p>\n",
+ "<p>Number of attention heads </p>\n": "<p>\u30a2\u30c6\u30f3\u30b7\u30e7\u30f3\u30d8\u30c3\u30c9\u306e\u6570</p>\n",
+ "<p>Number of features in FFN hidden layer </p>\n": "<p>FFN \u96a0\u308c\u30ec\u30a4\u30e4\u30fc\u306e\u30d5\u30a3\u30fc\u30c1\u30e3\u6570</p>\n",
+ "<p>Number of memories to compress <span translate=no>_^_0_^_</span> </p>\n": "<p>\u5727\u7e2e\u3059\u308b\u30e1\u30e2\u30ea\u306e\u6570 <span translate=no>_^_0_^_</span></p>\n",
+ "<p>Number of memories to keep </p>\n": "<p>\u4fdd\u5b58\u3059\u308b\u30e1\u30e2\u30ea\u306e\u6570</p>\n",
+ "<p>Number of transformer layers </p>\n": "<p>\u5909\u5727\u5668\u5c64\u306e\u6570</p>\n",
+ "<p>Only feed the last character to model in next iteration, rest will go in as memories </p>\n": "<p>\u6b21\u306e\u30a4\u30c6\u30ec\u30fc\u30b7\u30e7\u30f3\u3067\u306f\u6700\u5f8c\u306e\u6587\u5b57\u3060\u3051\u3092\u30e2\u30c7\u30eb\u306b\u30d5\u30a3\u30fc\u30c9\u3057\u3001\u6b8b\u308a\u306f\u30e1\u30e2\u30ea\u3068\u3057\u3066\u6b8b\u308a\u307e\u3059</p>\n",
+ "<p>Print the sampled output </p>\n": "<p>\u30b5\u30f3\u30d7\u30eb\u51fa\u529b\u3092\u5370\u5237\u3059\u308b</p>\n",
+ "<p>Return memories and the memories that were compressed. Memories that were compressed are needed for the reconstruction loss computation. </p>\n": "<p>\u30e1\u30e2\u30ea\u3068\u5727\u7e2e\u3055\u308c\u305f\u30e1\u30e2\u30ea\u3092\u8fd4\u3057\u307e\u3059\u3002\u518d\u69cb\u6210\u640d\u5931\u306e\u8a08\u7b97\u306b\u306f\u3001\u5727\u7e2e\u3055\u308c\u305f\u30e1\u30e2\u30ea\u304c\u5fc5\u8981\u3067\u3059</p>\u3002\n",
+ "<p>Run it through the transformer </p>\n": "<p>\u5909\u5727\u5668\u306b\u901a\u3057\u3066\u304f\u3060\u3055\u3044</p>\n",
+ "<p>Run the model </p>\n": "<p>\u30e2\u30c7\u30eb\u3092\u5b9f\u884c</p>\n",
+ "<p>Sample 25 tokens </p>\n": "<p>25\u30c8\u30fc\u30af\u30f3\u306e\u30b5\u30f3\u30d7\u30eb</p>\n",
+ "<p>Save the tracked metrics </p>\n": "<p>\u8ffd\u8de1\u3057\u305f\u30e1\u30c8\u30ea\u30af\u30b9\u3092\u4fdd\u5b58\u3059\u308b</p>\n",
+ "<p>Set models for saving and loading </p>\n": "<p>\u4fdd\u5b58\u304a\u3088\u3073\u8aad\u307f\u8fbc\u307f\u7528\u306e\u30e2\u30c7\u30eb\u3092\u8a2d\u5b9a\u3059\u308b</p>\n",
+ "<p>Set tracker configurations </p>\n": "<p>\u30c8\u30e9\u30c3\u30ab\u30fc\u69cb\u6210\u3092\u8a2d\u5b9a</p>\n",
+ "<p>Split the memories at <span translate=no>_^_0_^_</span> </p>\n": "<p>\u601d\u3044\u51fa\u3092\u5206\u3051\u3066 <span translate=no>_^_0_^_</span></p>\n",
+ "<p>Start the experiment </p>\n": "<p>\u5b9f\u9a13\u3092\u59cb\u3081\u308b</p>\n",
+ "<p>Starting prompt </p>\n": "<p>\u8d77\u52d5\u30d7\u30ed\u30f3\u30d7\u30c8</p>\n",
+ "<p>State module to maintain memories when switching between training and validation </p>\n": "<p>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3068\u691c\u8a3c\u3092\u5207\u308a\u66ff\u3048\u308b\u3068\u304d\u306b\u30e1\u30e2\u30ea\u3092\u7dad\u6301\u3059\u308b\u30b9\u30c6\u30fc\u30c8\u30e2\u30b8\u30e5\u30fc\u30eb</p>\n",
+ "<p>Take optimizer step </p>\n": "<p>\u6700\u9069\u5316\u306e\u4e00\u6b69\u3092\u8e0f\u307f\u51fa\u3059</p>\n",
+ "<p>This will keep the accuracy metric stats and memories separate for training and validation. </p>\n": "<p>\u3053\u308c\u306b\u3088\u308a\u3001\u7cbe\u5ea6\u30e1\u30c8\u30ea\u30c3\u30af\u306e\u7d71\u8a08\u60c5\u5831\u3068\u30e1\u30e2\u30ea\u304c\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3068\u691c\u8a3c\u7528\u306b\u5225\u3005\u306b\u4fdd\u6301\u3055\u308c\u307e\u3059\u3002</p>\n",
+ "<p>Token embedding module </p>\n": "<p>\u30c8\u30fc\u30af\u30f3\u57cb\u3081\u8fbc\u307f\u30e2\u30b8\u30e5\u30fc\u30eb</p>\n",
+ "<p>Token embedding size </p>\n": "<p>\u30c8\u30fc\u30af\u30f3\u306e\u57cb\u3081\u8fbc\u307f\u30b5\u30a4\u30ba</p>\n",
+ "<p>Token embeddings </p>\n": "<p>\u30c8\u30fc\u30af\u30f3\u306e\u57cb\u3081\u8fbc\u307f</p>\n",
+ "<p>Tokenize the prompt </p>\n": "<p>\u30d7\u30ed\u30f3\u30d7\u30c8\u3092\u30c8\u30fc\u30af\u30f3\u5316</p>\n",
+ "<p>Total length of the memory and compressed memory (for masks) </p>\n": "<p>\u30e1\u30e2\u30ea\u3068\u5727\u7e2e\u30e1\u30e2\u30ea\u306e\u5408\u8a08\u9577 (\u30de\u30b9\u30af\u7528)</p>\n",
+ "<p>Track attention reconstruction loss </p>\n": "<p>\u30c8\u30e9\u30c3\u30af\u30fb\u30a2\u30c6\u30f3\u30b7\u30e7\u30f3\u30fb\u30ea\u30b3\u30f3\u30b9\u30c8\u30e9\u30af\u30b7\u30e7\u30f3\u30fb\u30ed\u30b9</p>\n",
+ "<p>Train the model </p>\n": "<p>\u30e2\u30c7\u30eb\u306e\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0</p>\n",
+ "<p>Transformer </p>\n": "<p>\u5909\u5727\u5668</p>\n",
+ "<p>Truncate old memories </p>\n": "<p>\u53e4\u3044\u601d\u3044\u51fa\u3092\u5207\u308a\u6368\u3066\u308b</p>\n",
+ "<p>Update and compress memory </p>\n": "<p>\u30e1\u30e2\u30ea\u306e\u66f4\u65b0\u3068\u5727\u7e2e</p>\n",
+ "<p>Update global step (number of tokens processed) when in training mode </p>\n": "<p>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u30e2\u30fc\u30c9\u6642\u306b\u30b0\u30ed\u30fc\u30d0\u30eb\u30b9\u30c6\u30c3\u30d7 (\u51e6\u7406\u3055\u308c\u305f\u30c8\u30fc\u30af\u30f3\u306e\u6570) \u3092\u66f4\u65b0</p>\n",
+ "<p>Update memories </p>\n": "<p>\u30e1\u30e2\u30ea\u30fc\u3092\u66f4\u65b0</p>\n",
+ "<p>Update the memories </p>\n": "<p>\u601d\u3044\u51fa\u3092\u66f4\u65b0</p>\n",
+ "<p>Use only the subsequent mask otherwise </p>\n": "<p>\u305d\u308c\u4ee5\u5916\u306e\u5834\u5408\u306f\u3001\u5f8c\u7d9a\u306e\u30de\u30b9\u30af\u306e\u307f\u3092\u4f7f\u7528\u3057\u3066\u304f\u3060\u3055\u3044</p>\n",
+ "<p>Whether to capture model outputs </p>\n": "<p>\u30e2\u30c7\u30eb\u51fa\u529b\u3092\u30ad\u30e3\u30d7\u30c1\u30e3\u3059\u308b\u304b\u3069\u3046\u304b</p>\n",
+ "<p>memory </p>\n": "<p>\u8a18\u61b6</p>\n",
+ "Compressive Transformer Experiment": "\u5727\u7e2e\u5909\u5727\u5668\u5b9f\u9a13",
+ "This experiment trains a compressive transformer model on tiny Shakespeare dataset.": "\u3053\u306e\u5b9f\u9a13\u3067\u306f\u3001\u5c0f\u3055\u306a\u30b7\u30a7\u30a4\u30af\u30b9\u30d4\u30a2\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3067\u5727\u7e2e\u30c8\u30e9\u30f3\u30b9\u30d5\u30a9\u30fc\u30de\u30fc\u30e2\u30c7\u30eb\u3092\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u3057\u307e\u3059\u3002"
+}