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52 | 52 | "name": "stdout",
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53 | 53 | "output_type": "stream",
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54 | 54 | "text": [
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55 |
| - "CPU times: user 65 µs, sys: 0 ns, total: 65 µs\n", |
56 |
| - "Wall time: 67.9 µs\n" |
| 55 | + "CPU times: user 56 µs, sys: 18 µs, total: 74 µs\n", |
| 56 | + "Wall time: 76.3 µs\n" |
57 | 57 | ]
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58 | 58 | }
|
59 | 59 | ],
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|
69 | 69 | " # sat_channels =('HRV', 'WV_062', 'WV_073'),\n",
|
70 | 70 | " nwp_base_path = f'gs://{NWP_BASE_PATH}',\n",
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71 | 71 | " pin_memory = True, #: Passed to DataLoader.\n",
|
72 |
| - " num_workers = 1, #: Passed to DataLoader.\n", |
| 72 | + " num_workers = 0, #: Passed to DataLoader.\n", |
73 | 73 | " prefetch_factor = 256, #: Passed to DataLoader.\n",
|
74 | 74 | " n_samples_per_timestep = 8, #: Passed to NowcastingDataset\n",
|
75 | 75 | ")"
|
|
94 | 94 | "text": [
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95 | 95 | "15 bad PV systems found and removed!\n",
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96 | 96 | "pv_power = 400.0 MB\n",
|
97 |
| - "CPU times: user 56.2 s, sys: 3.56 s, total: 59.8 s\n", |
98 |
| - "Wall time: 59.9 s\n" |
| 97 | + "CPU times: user 55.6 s, sys: 3.45 s, total: 59 s\n", |
| 98 | + "Wall time: 59.3 s\n" |
99 | 99 | ]
|
100 | 100 | }
|
101 | 101 | ],
|
|
124 | 124 | "/home/jack/miniconda3/envs/nowcasting_dataset/lib/python3.9/site-packages/pvlib/solarposition.py:368: FutureWarning: casting datetime64[ns] values to int64 with .astype(...) is deprecated and will raise in a future version. Use .view(...) instead.\n",
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125 | 125 | " unixtime = np.array(time.astype(np.int64)/10**9)\n",
|
126 | 126 | "/home/jack/miniconda3/envs/nowcasting_dataset/lib/python3.9/site-packages/pvlib/solarposition.py:368: FutureWarning: casting datetime64[ns] values to int64 with .astype(...) is deprecated and will raise in a future version. Use .view(...) instead.\n",
|
127 |
| - " unixtime = np.array(time.astype(np.int64)/10**9)\n" |
| 127 | + " unixtime = np.array(time.astype(np.int64)/10**9)\n", |
| 128 | + "/home/jack/dev/ocf/nowcasting_dataset/nowcasting_dataset/utils.py:20: FutureWarning: casting datetime64[ns] values to int64 with .astype(...) is deprecated and will raise in a future version. Use .view(...) instead.\n", |
| 129 | + " a = a.astype(int)\n", |
| 130 | + "DEBUG:nowcasting_dataset:Opening satellite data: gs://solar-pv-nowcasting-data/satellite/EUMETSAT/SEVIRI_RSS/OSGB36/all_zarr_int16_single_timestep.zarr\n", |
| 131 | + "DEBUG:nowcasting_dataset:Opening NWP data: gs://solar-pv-nowcasting-data/NWP/UK_Met_Office/UKV_zarr\n", |
| 132 | + "DEBUG:nowcasting_dataset:Opening satellite data: gs://solar-pv-nowcasting-data/satellite/EUMETSAT/SEVIRI_RSS/OSGB36/all_zarr_int16_single_timestep.zarr\n", |
| 133 | + "DEBUG:nowcasting_dataset:Opening NWP data: gs://solar-pv-nowcasting-data/NWP/UK_Met_Office/UKV_zarr\n" |
128 | 134 | ]
|
129 | 135 | },
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130 | 136 | {
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131 | 137 | "name": "stdout",
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132 | 138 | "output_type": "stream",
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133 | 139 | "text": [
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134 |
| - "CPU times: user 12.9 s, sys: 347 ms, total: 13.2 s\n", |
135 |
| - "Wall time: 15.4 s\n" |
136 |
| - ] |
137 |
| - }, |
138 |
| - { |
139 |
| - "name": "stderr", |
140 |
| - "output_type": "stream", |
141 |
| - "text": [ |
142 |
| - "/home/jack/dev/ocf/nowcasting_dataset/nowcasting_dataset/utils.py:20: FutureWarning: casting datetime64[ns] values to int64 with .astype(...) is deprecated and will raise in a future version. Use .view(...) instead.\n", |
143 |
| - " a = a.astype(int)\n" |
| 140 | + "CPU times: user 26.3 s, sys: 622 ms, total: 26.9 s\n", |
| 141 | + "Wall time: 33.8 s\n" |
144 | 142 | ]
|
145 | 143 | }
|
146 | 144 | ],
|
|
354 | 352 | "output_type": "stream",
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355 | 353 | "text": [
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356 | 354 | "/home/jack/miniconda3/envs/nowcasting_dataset/lib/python3.9/site-packages/pytorch_lightning/trainer/data_loading.py:102: UserWarning: The dataloader, val dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 16 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.\n",
|
357 |
| - " rank_zero_warn(\n", |
358 |
| - "DEBUG:nowcasting_dataset:Opening satellite data: gs://solar-pv-nowcasting-data/satellite/EUMETSAT/SEVIRI_RSS/OSGB36/all_zarr_int16_single_timestep.zarr\n", |
359 |
| - "DEBUG:nowcasting_dataset:Opening NWP data: gs://solar-pv-nowcasting-data/NWP/UK_Met_Office/UKV_zarr\n" |
| 355 | + " rank_zero_warn(\n" |
360 | 356 | ]
|
361 | 357 | },
|
362 | 358 | {
|
|
371 | 367 | "output_type": "stream",
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372 | 368 | "text": [
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373 | 369 | "/home/jack/miniconda3/envs/nowcasting_dataset/lib/python3.9/site-packages/pytorch_lightning/trainer/data_loading.py:102: UserWarning: The dataloader, train dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 16 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.\n",
|
374 |
| - " rank_zero_warn(\n", |
375 |
| - "DEBUG:nowcasting_dataset:Opening satellite data: gs://solar-pv-nowcasting-data/satellite/EUMETSAT/SEVIRI_RSS/OSGB36/all_zarr_int16_single_timestep.zarr\n", |
376 |
| - "[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)\n", |
377 |
| - "DEBUG:nowcasting_dataset:Opening NWP data: gs://solar-pv-nowcasting-data/NWP/UK_Met_Office/UKV_zarr\n" |
| 370 | + " rank_zero_warn(\n" |
378 | 371 | ]
|
379 | 372 | },
|
380 | 373 | {
|
381 | 374 | "name": "stdout",
|
382 | 375 | "output_type": "stream",
|
383 | 376 | "text": [
|
384 |
| - "Epoch 0: : 183it [13:31, 4.43s/it, loss=0.105, v_num=178] " |
| 377 | + "Epoch 0: : 209it [14:28, 4.16s/it, loss=0.0968, v_num=181]" |
385 | 378 | ]
|
386 | 379 | }
|
387 | 380 | ],
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392 | 385 | {
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393 | 386 | "cell_type": "code",
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394 | 387 | "execution_count": null,
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395 |
| - "id": "f2c4c66f-cdc5-4319-b7c8-0b7dddf438d5", |
396 |
| - "metadata": {}, |
397 |
| - "outputs": [], |
398 |
| - "source": [ |
399 |
| - "# torch.save(model.state_dict(), 'model_state_dict.pt')" |
400 |
| - ] |
401 |
| - }, |
402 |
| - { |
403 |
| - "cell_type": "code", |
404 |
| - "execution_count": null, |
405 |
| - "id": "54d607e2-f10e-4c07-88bf-492c0215c21e", |
406 |
| - "metadata": {}, |
407 |
| - "outputs": [], |
408 |
| - "source": [ |
409 |
| - "import pandas as pd" |
410 |
| - ] |
411 |
| - }, |
412 |
| - { |
413 |
| - "cell_type": "code", |
414 |
| - "execution_count": null, |
415 |
| - "id": "10119390-bdc1-4724-b5f8-1aa3877d5293", |
416 |
| - "metadata": {}, |
417 |
| - "outputs": [], |
418 |
| - "source": [ |
419 |
| - "pd.__version__" |
420 |
| - ] |
421 |
| - }, |
422 |
| - { |
423 |
| - "cell_type": "code", |
424 |
| - "execution_count": null, |
425 |
| - "id": "3e025240-b406-4add-9564-e27358f65d17", |
| 388 | + "id": "6813e0ec-0e7f-4cbb-87f3-51357f80362e", |
426 | 389 | "metadata": {},
|
427 | 390 | "outputs": [],
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428 | 391 | "source": []
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