|
105 | 105 | }, |
106 | 106 | { |
107 | 107 | "cell_type": "code", |
108 | | - "execution_count": 63, |
| 108 | + "execution_count": 80, |
109 | 109 | "metadata": { |
110 | 110 | "dotnet_interactive": { |
111 | 111 | "language": "csharp" |
|
137 | 137 | " y += torch.randn(y.shape) * 0.01;\n", |
138 | 138 | "\n", |
139 | 139 | " // Make sure that the output isn't negative.\n", |
140 | | - " y += torch.where(y < 0.0, 0.01 * torch.randn(y.shape) + 0.01, torch.zeros(y.shape));\n", |
| 140 | + " //y += torch.where(y < 0.0, 0.01 * torch.randn(y.shape) + 0.01, torch.zeros(y.shape));\n", |
| 141 | + " y = y.relu_();\n", |
141 | 142 | "\n", |
142 | 143 | " // Save the data in two separate, binary files.\n", |
143 | 144 | " X.save(fileName + \".x\");\n", |
|
152 | 153 | }, |
153 | 154 | { |
154 | 155 | "cell_type": "code", |
155 | | - "execution_count": 64, |
| 156 | + "execution_count": 81, |
156 | 157 | "metadata": { |
157 | 158 | "dotnet_interactive": { |
158 | 159 | "language": "csharp" |
|
179 | 180 | }, |
180 | 181 | { |
181 | 182 | "cell_type": "code", |
182 | | - "execution_count": 65, |
| 183 | + "execution_count": 82, |
183 | 184 | "metadata": { |
184 | 185 | "dotnet_interactive": { |
185 | 186 | "language": "csharp" |
|
207 | 208 | }, |
208 | 209 | { |
209 | 210 | "cell_type": "code", |
210 | | - "execution_count": 66, |
| 211 | + "execution_count": 83, |
211 | 212 | "metadata": { |
212 | 213 | "dotnet_interactive": { |
213 | 214 | "language": "csharp" |
|
235 | 236 | }, |
236 | 237 | { |
237 | 238 | "cell_type": "code", |
238 | | - "execution_count": 67, |
| 239 | + "execution_count": 84, |
239 | 240 | "metadata": { |
240 | 241 | "dotnet_interactive": { |
241 | 242 | "language": "csharp" |
|
281 | 282 | }, |
282 | 283 | { |
283 | 284 | "cell_type": "code", |
284 | | - "execution_count": 68, |
| 285 | + "execution_count": 103, |
285 | 286 | "metadata": { |
286 | 287 | "dotnet_interactive": { |
287 | 288 | "language": "csharp" |
|
310 | 311 | }, |
311 | 312 | { |
312 | 313 | "cell_type": "code", |
313 | | - "execution_count": 69, |
| 314 | + "execution_count": 104, |
314 | 315 | "metadata": { |
315 | 316 | "dotnet_interactive": { |
316 | 317 | "language": "csharp" |
|
325 | 326 | "outputs": [], |
326 | 327 | "source": [ |
327 | 328 | "var learning_rate = 0.01f;\n", |
328 | | - "var optimizer = torch.optim.SGD(model.parameters(), learning_rate);" |
| 329 | + "var optimizer = torch.optim.Rprop(model.parameters(), learning_rate);" |
329 | 330 | ] |
330 | 331 | }, |
331 | 332 | { |
|
338 | 339 | }, |
339 | 340 | { |
340 | 341 | "cell_type": "code", |
341 | | - "execution_count": 78, |
| 342 | + "execution_count": 115, |
342 | 343 | "metadata": { |
343 | 344 | "dotnet_interactive": { |
344 | 345 | "language": "csharp" |
|
355 | 356 | "name": "stdout", |
356 | 357 | "output_type": "stream", |
357 | 358 | "text": [ |
358 | | - " initial loss = 0.0063750837\n", |
359 | | - " final loss = 0.007656585\n" |
| 359 | + " initial loss = 0.00047994562\n", |
| 360 | + " final loss = 0.0004698771\n" |
360 | 361 | ] |
361 | 362 | } |
362 | 363 | ], |
|
389 | 390 | }, |
390 | 391 | { |
391 | 392 | "cell_type": "code", |
392 | | - "execution_count": 79, |
| 393 | + "execution_count": 116, |
393 | 394 | "metadata": { |
394 | 395 | "dotnet_interactive": { |
395 | 396 | "language": "csharp" |
|
405 | 406 | { |
406 | 407 | "data": { |
407 | 408 | "text/html": [ |
408 | | - "<div class=\"dni-plaintext\"><pre>0.008805012</pre></div><style>\r\n", |
| 409 | + "<div class=\"dni-plaintext\"><pre>0.00061915093</pre></div><style>\r\n", |
409 | 410 | ".dni-code-hint {\r\n", |
410 | 411 | " font-style: italic;\r\n", |
411 | 412 | " overflow: hidden;\r\n", |
|
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