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mattricesound commited on
Commit
af0842b
·
1 Parent(s): 634cc2a

Remove notebooks

Browse files
Files changed (4) hide show
  1. notebooks/Experiments.ipynb +0 -0
  2. notebooks/diffusion_test.ipynb +0 -0
  3. notebooks/egfx.ipynb +0 -603
  4. notebooks/guitar_generation_test.ipynb +0 -0
notebooks/Experiments.ipynb DELETED
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notebooks/diffusion_test.ipynb DELETED
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notebooks/egfx.ipynb DELETED
@@ -1,603 +0,0 @@
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- {
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- "cells": [
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- {
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- "cell_type": "code",
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- "execution_count": 28,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "import mirdata\n",
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- "from torch.utils.data import Dataset, DataLoader\n",
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- "import torchaudio\n",
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- "import torchaudio.transforms as T\n",
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- "import torch.nn.functional as F\n",
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- "from pathlib import Path\n",
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- "from typing import List\n",
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- "import torch\n"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 24,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "effect_type = [\"Phaser\"]\n",
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- "root=Path(\"./data/egfx\")\n",
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- "wet_files = []\n",
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- "dry_files = []\n",
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- "labels = []"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 18,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "for i, effect in enumerate(effect_type):\n",
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- " for pickup in Path(root / effect).iterdir():\n",
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- " wet_files += list(pickup.glob(\"*.wav\"))\n",
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- " dry_files += list(root.glob(f\"Clean/{pickup.name}/**/*.wav\"))\n",
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- " \n",
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- " labels += [i] * len(wet_files)\n"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 26,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "LENGTH = 2**18 # 12 seconds\n",
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- "ORIG_SR = 48000"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 27,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "class GuitarFXDataset(Dataset):\n",
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- " def __init__(\n",
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- " self,\n",
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- " root: str,\n",
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- " sample_rate: int,\n",
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- " length: int = LENGTH,\n",
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- " effect_type: List[str] = None,\n",
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- " ):\n",
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- " self.length = length\n",
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- " self.wet_files = []\n",
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- " self.dry_files = []\n",
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- " self.labels = []\n",
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- " self.root = Path(root)\n",
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- " if effect_type is None:\n",
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- " effect_type = [\n",
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- " d.name for d in self.root.iterdir() if d.is_dir() and d != \"Clean\"\n",
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- " ]\n",
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- " for i, effect in enumerate(effect_type):\n",
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- " for pickup in Path(self.root / effect).iterdir():\n",
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- " self.wet_files += sorted(list(pickup.glob(\"*.wav\")))\n",
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- " self.dry_files += sorted(\n",
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- " list(self.root.glob(f\"Clean/{pickup.name}/**/*.wav\"))\n",
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- " )\n",
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- " self.labels += [i] * len(self.wet_files)\n",
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- " print(\n",
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- " f\"Found {len(self.wet_files)} wet files and {len(self.dry_files)} dry files\"\n",
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- " )\n",
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- " self.resampler = T.Resample(ORIG_SR, sample_rate)\n",
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- "\n",
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- " def __len__(self):\n",
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- " return len(self.dry_files)\n",
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- "\n",
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- " def __getitem__(self, idx):\n",
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- " print(idx, self.wet_files[idx], self.dry_files[idx])\n",
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- " x, sr = torchaudio.load(self.wet_files[idx])\n",
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- " y, sr = torchaudio.load(self.dry_files[idx])\n",
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- " effect_label = self.labels[idx]\n",
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- "\n",
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- " resampled_x = self.resampler(x)\n",
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- " resampled_y = self.resampler(y)\n",
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- " # Pad or crop to length\n",
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- " if resampled_x.shape[-1] < self.length:\n",
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- " resampled_x = F.pad(resampled_x, (0, self.length - resampled_x.shape[1]))\n",
105
- " elif resampled_x.shape[-1] > self.length:\n",
106
- " resampled_x = resampled_x[:, : self.length]\n",
107
- " if resampled_y.shape[-1] < self.length:\n",
108
- " resampled_y = F.pad(resampled_y, (0, self.length - resampled_y.shape[1]))\n",
109
- " elif resampled_y.shape[-1] > self.length:\n",
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- " resampled_y = resampled_y[:, : self.length]\n",
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- " return (resampled_x, resampled_y, effect_label)\n"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 29,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "\n",
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- "SAMPLE_RATE = 22050\n",
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- "TRAIN_SPLIT = 0.8"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 32,
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- "metadata": {},
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- "outputs": [
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- {
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- "name": "stdout",
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- "output_type": "stream",
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- "text": [
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- "Found 690 wet files and 690 dry files\n"
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- ]
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- }
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- ],
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- "source": [
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- "guitfx = GuitarFXDataset(\n",
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- " root=\"./data/egfx\",\n",
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- " sample_rate=SAMPLE_RATE,\n",
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- " effect_type=[\"Phaser\"],\n",
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- ")"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 33,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "train_size = int(TRAIN_SPLIT * len(guitfx))\n",
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- "val_size = len(guitfx) - train_size\n",
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- "train_dataset, val_dataset = torch.utils.data.random_split(\n",
155
- " guitfx, [train_size, val_size]\n",
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- ")\n",
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- "val = DataLoader(val_dataset, batch_size=2)\n"
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- ]
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- },
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- {
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- "cell_type": "markdown",
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- "metadata": {},
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- "source": []
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 37,
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- "metadata": {},
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- "outputs": [
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- {
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- "name": "stdout",
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- "output_type": "stream",
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- "text": [
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- "[560, 150, 218, 404, 292, 509, 10, 315, 554, 6, 169, 116, 601, 309, 280, 510, 559, 197, 613, 424, 500, 460, 273, 467, 190, 534, 642, 112, 635, 283, 217, 7, 679, 526, 73, 102, 134, 263, 449, 142, 215, 154, 181, 378, 425, 278, 208, 58, 323, 210, 388, 363, 249, 57, 479, 79, 508, 429, 237, 390, 435, 62, 254, 528, 614, 311, 680, 61, 374, 668, 373, 594, 9, 677, 188, 2, 91, 633, 549, 257, 170, 183, 465, 502, 244, 664, 632, 356, 581, 145, 81, 85, 232, 250, 571, 118, 319, 308, 536, 592, 607, 566, 609, 302, 576, 354, 35, 493, 593, 437, 636, 495, 506, 153, 638, 164, 229, 456, 34, 518, 381, 322, 304, 565, 52, 499, 66, 39, 220, 38, 111, 454, 267, 98, 563, 585, 121, 391]\n"
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- ]
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- }
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- ],
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- "source": [
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- "print(val_dataset.indices)"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 38,
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- "metadata": {},
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- "outputs": [
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- {
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- "name": "stdout",
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- "output_type": "stream",
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- "text": [
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- "[tensor([[[0.0482, 0.0772, 0.0682, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0092, 0.0138, 0.0139, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[-0.0007, -0.0009, 0.0074, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[ 0.0007, 0.0036, 0.0064, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[0.0027, 0.0050, 0.0063, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0043, 0.0077, 0.0084, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0007, 0.0023, 0.0026, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0005, 0.0023, 0.0034, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[0.0008, 0.0017, 0.0056, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0008, 0.0016, 0.0016, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0007, 0.0022, 0.0028, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0003, 0.0009, 0.0011, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[ 0.0071, 0.0107, 0.0078, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[ 0.0043, 0.0011, -0.0055, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[-0.0004, -0.0014, -0.0022, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[ 0.0013, 0.0045, 0.0072, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[0.0022, 0.0036, 0.0059, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0431, 0.0687, 0.0638, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[ 0.0009, 0.0030, 0.0047, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.0001, -0.0012, -0.0022, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[ 0.0053, 0.0082, 0.0058, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.0035, -0.0036, -0.0021, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[ 0.0003, 0.0019, 0.0038, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.0003, -0.0029, -0.0058, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[ 0.0069, 0.0106, 0.0078, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.0035, -0.0040, -0.0034, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[ 0.0003, 0.0010, 0.0034, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.0020, -0.0076, -0.0117, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[ 0.0044, 0.0086, 0.0079, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.0016, -0.0022, -0.0014, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[-0.0006, -0.0020, -0.0020, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.0002, -0.0009, -0.0017, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[0.0027, 0.0027, 0.0002, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0033, 0.0048, 0.0028, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0008, 0.0035, 0.0059, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0002, 0.0006, 0.0011, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[ 0.0056, 0.0341, 0.0562, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.0009, -0.0013, -0.0002, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0021, 0.0092, 0.0056, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0007, 0.0021, 0.0023, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[ 0.0014, 0.0024, 0.0030, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.1450, -0.1390, -0.0209, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[ 2.6921e-04, 1.6453e-03, 2.7682e-03, ..., 0.0000e+00,\n",
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- " 0.0000e+00, 0.0000e+00]],\n",
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- "\n",
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- " [[-3.2024e-02, -1.9613e-01, -4.0412e-01, ..., 0.0000e+00,\n",
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- " 0.0000e+00, 0.0000e+00]]]), tensor([0, 0])]\n",
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- "[tensor([[[-0.0059, -0.0064, -0.0022, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.0039, -0.0046, -0.0021, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[-0.0002, -0.0021, -0.0037, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.0004, -0.0017, -0.0031, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[ 0.0086, 0.0122, 0.0111, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.0114, -0.0113, -0.0039, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[ 0.0004, 0.0043, 0.0085, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.0010, -0.0059, -0.0108, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[0.0069, 0.0105, 0.0097, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0069, 0.0100, 0.0067, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[1.4215e-04, 2.1199e-03, 5.7695e-03, ..., 0.0000e+00,\n",
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- " 0.0000e+00, 0.0000e+00]],\n",
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- "\n",
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- " [[9.1938e-05, 1.1531e-03, 2.8006e-03, ..., 0.0000e+00,\n",
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- " 0.0000e+00, 0.0000e+00]]]), tensor([0, 0])]\n",
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- "[tensor([[[0.0012, 0.0038, 0.0057, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0035, 0.0058, 0.0088, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0004, 0.0013, 0.0014, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0003, 0.0022, 0.0044, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[ 0.0011, 0.0023, 0.0030, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[-0.0033, -0.0038, -0.0007, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0003, 0.0023, 0.0041, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0005, 0.0038, 0.0079, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[ 0.0020, -0.0012, -0.0042, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[ 0.0035, 0.0056, 0.0063, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0013, 0.0048, 0.0063, ..., 0.0000, 0.0000, 0.0000]],\n",
278
- "\n",
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- " [[0.0005, 0.0026, 0.0049, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
280
- "[tensor([[[-0.0033, -0.0054, -0.0052, ..., 0.0000, 0.0000, 0.0000]],\n",
281
- "\n",
282
- " [[ 0.0031, 0.0057, 0.0069, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0021, 0.0064, 0.0081, ..., 0.0000, 0.0000, 0.0000]],\n",
283
- "\n",
284
- " [[0.0004, 0.0015, 0.0021, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
285
- "[tensor([[[-0.0023, -0.0059, -0.0074, ..., 0.0000, 0.0000, 0.0000]],\n",
286
- "\n",
287
- " [[ 0.0087, 0.0125, 0.0101, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[-0.0004, -0.0011, -0.0011, ..., 0.0000, 0.0000, 0.0000]],\n",
288
- "\n",
289
- " [[ 0.0019, 0.0071, 0.0113, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
290
- "[tensor([[[ 0.0046, 0.0039, -0.0007, ..., 0.0000, 0.0000, 0.0000]],\n",
291
- "\n",
292
- " [[ 0.0038, 0.0021, 0.0117, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0003, 0.0024, 0.0042, ..., 0.0000, 0.0000, 0.0000]],\n",
293
- "\n",
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- " [[0.0048, 0.0240, 0.0323, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
295
- "[tensor([[[ 0.0064, 0.0104, 0.0116, ..., 0.0000, 0.0000, 0.0000]],\n",
296
- "\n",
297
- " [[-0.0028, -0.0033, -0.0007, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0010, 0.0047, 0.0074, ..., 0.0000, 0.0000, 0.0000]],\n",
298
- "\n",
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- " [[0.0005, 0.0013, 0.0009, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
300
- "[tensor([[[0.0042, 0.0073, 0.0064, ..., 0.0000, 0.0000, 0.0000]],\n",
301
- "\n",
302
- " [[0.0015, 0.0029, 0.0041, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0007, 0.0026, 0.0033, ..., 0.0000, 0.0000, 0.0000]],\n",
303
- "\n",
304
- " [[0.0004, 0.0016, 0.0026, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
305
- "[tensor([[[-0.0016, -0.0054, -0.0048, ..., 0.0000, 0.0000, 0.0000]],\n",
306
- "\n",
307
- " [[ 0.0113, 0.0209, 0.0223, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[ 0.0014, 0.0034, 0.0026, ..., 0.0000, 0.0000, 0.0000]],\n",
308
- "\n",
309
- " [[-0.0004, -0.0024, -0.0011, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
310
- "[tensor([[[ 0.0064, 0.0108, 0.0107, ..., 0.0000, 0.0000, 0.0000]],\n",
311
- "\n",
312
- " [[-0.0007, -0.0040, -0.0083, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0005, 0.0018, 0.0035, ..., 0.0000, 0.0000, 0.0000]],\n",
313
- "\n",
314
- " [[0.0002, 0.0008, 0.0012, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
315
- "[tensor([[[ 0.0071, 0.0064, -0.0008, ..., 0.0000, 0.0000, 0.0000]],\n",
316
- "\n",
317
- " [[ 0.0024, 0.0039, 0.0042, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0018, 0.0064, 0.0094, ..., 0.0000, 0.0000, 0.0000]],\n",
318
- "\n",
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- " [[0.0001, 0.0008, 0.0019, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
320
- "[tensor([[[0.0075, 0.0099, 0.0065, ..., 0.0000, 0.0000, 0.0000]],\n",
321
- "\n",
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- " [[0.0008, 0.0010, 0.0005, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0007, 0.0032, 0.0058, ..., 0.0000, 0.0000, 0.0000]],\n",
323
- "\n",
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- " [[0.0006, 0.0023, 0.0029, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
325
- "[tensor([[[-0.0024, -0.0027, -0.0021, ..., 0.0000, 0.0000, 0.0000]],\n",
326
- "\n",
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- " [[ 0.0096, 0.0151, 0.0139, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[-0.0003, -0.0012, -0.0023, ..., 0.0000, 0.0000, 0.0000]],\n",
328
- "\n",
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- " [[-0.0001, -0.0010, -0.0015, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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- "[tensor([[[0.0012, 0.0027, 0.0036, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
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- " [[0.0030, 0.0039, 0.0039, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[ 0.0005, 0.0015, 0.0021, ..., 0.0000, 0.0000, 0.0000]],\n",
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- "\n",
334
- " [[-0.0003, -0.0010, -0.0016, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
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375
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383
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384
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385
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386
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395
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400
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401
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403
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404
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405
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406
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407
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408
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410
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411
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413
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414
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415
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417
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418
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419
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420
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422
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423
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424
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425
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426
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427
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428
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429
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430
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431
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432
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433
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434
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435
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436
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437
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438
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439
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440
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441
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442
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443
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444
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445
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446
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447
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448
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449
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450
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451
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452
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453
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454
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455
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456
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457
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458
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459
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461
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462
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463
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464
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465
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466
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467
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468
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469
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470
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471
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472
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473
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474
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475
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476
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477
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478
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479
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480
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481
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482
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483
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484
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485
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486
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487
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488
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489
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490
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491
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492
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493
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494
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495
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496
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497
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498
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499
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500
- "\n",
501
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502
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503
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504
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505
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506
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507
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508
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509
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510
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511
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512
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513
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514
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515
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516
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517
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518
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519
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520
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521
- "\n",
522
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523
- " 0.0000e+00, 0.0000e+00]]]), tensor([[[8.0004e-05, 1.0549e-03, 2.6432e-03, ..., 0.0000e+00,\n",
524
- " 0.0000e+00, 0.0000e+00]],\n",
525
- "\n",
526
- " [[7.4739e-05, 1.3412e-04, 1.7083e-04, ..., 0.0000e+00,\n",
527
- " 0.0000e+00, 0.0000e+00]]]), tensor([0, 0])]\n",
528
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529
- "\n",
530
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531
- "\n",
532
- " [[-0.0001, -0.0019, -0.0042, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
533
- "[tensor([[[ 0.0006, 0.0013, 0.0020, ..., 0.0000, 0.0000, 0.0000]],\n",
534
- "\n",
535
- " [[-0.0153, -0.0197, -0.0135, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[7.0598e-04, 3.5944e-03, 4.8469e-03, ..., 0.0000e+00,\n",
536
- " 0.0000e+00, 0.0000e+00]],\n",
537
- "\n",
538
- " [[5.7171e-05, 3.5541e-04, 3.9973e-04, ..., 0.0000e+00,\n",
539
- " 0.0000e+00, 0.0000e+00]]]), tensor([0, 0])]\n",
540
- "[tensor([[[0.0013, 0.0020, 0.0025, ..., 0.0000, 0.0000, 0.0000]],\n",
541
- "\n",
542
- " [[0.0120, 0.0202, 0.0220, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0006, 0.0025, 0.0037, ..., 0.0000, 0.0000, 0.0000]],\n",
543
- "\n",
544
- " [[0.0004, 0.0027, 0.0058, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
545
- "[tensor([[[0.0029, 0.0039, 0.0064, ..., 0.0000, 0.0000, 0.0000]],\n",
546
- "\n",
547
- " [[0.0015, 0.0025, 0.0030, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0004, 0.0048, 0.0087, ..., 0.0000, 0.0000, 0.0000]],\n",
548
- "\n",
549
- " [[0.0003, 0.0012, 0.0022, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
550
- "[tensor([[[0.0034, 0.0093, 0.0100, ..., 0.0000, 0.0000, 0.0000]],\n",
551
- "\n",
552
- " [[0.0007, 0.0014, 0.0018, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[-0.0008, -0.0035, -0.0042, ..., 0.0000, 0.0000, 0.0000]],\n",
553
- "\n",
554
- " [[ 0.0003, 0.0016, 0.0028, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n",
555
- "[tensor([[[0.0022, 0.0047, 0.0062, ..., 0.0000, 0.0000, 0.0000]],\n",
556
- "\n",
557
- " [[0.0082, 0.0121, 0.0115, ..., 0.0000, 0.0000, 0.0000]]]), tensor([[[0.0013, 0.0045, 0.0062, ..., 0.0000, 0.0000, 0.0000]],\n",
558
- "\n",
559
- " [[0.0015, 0.0091, 0.0154, ..., 0.0000, 0.0000, 0.0000]]]), tensor([0, 0])]\n"
560
- ]
561
- }
562
- ],
563
- "source": [
564
- "for v in val:\n",
565
- " print(v)"
566
- ]
567
- },
568
- {
569
- "cell_type": "code",
570
- "execution_count": null,
571
- "metadata": {},
572
- "outputs": [],
573
- "source": []
574
- }
575
- ],
576
- "metadata": {
577
- "kernelspec": {
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- "display_name": "env",
579
- "language": "python",
580
- "name": "python3"
581
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582
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The diff for this file is too large to render. See raw diff