\n",
"
\n",
"Figure 2: Conversion of sampled audio array to log-Mel spectrogram.\n",
"Left: sampled 1-dimensional audio signal. Right: corresponding log-Mel spectrogram. Figure source:\n",
"Google SpecAugment Blog.\n",
""
]
},
{
"cell_type": "markdown",
"id": "b2ef54d5-b946-4c1d-9fdc-adc5d01b46aa",
"metadata": {
"id": "b2ef54d5-b946-4c1d-9fdc-adc5d01b46aa"
},
"source": [
"We'll load the feature extractor from the pre-trained checkpoint with the default values:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "bc77d7bb-f9e2-47f5-b663-30f7a4321ce5",
"metadata": {
"id": "bc77d7bb-f9e2-47f5-b663-30f7a4321ce5"
},
"outputs": [],
"source": [
"from transformers import WhisperFeatureExtractor\n",
"\n",
"feature_extractor = WhisperFeatureExtractor.from_pretrained(\"openai/whisper-medium\")"
]
},
{
"cell_type": "markdown",
"id": "93748af7-b917-4ecf-a0c8-7d89077ff9cb",
"metadata": {
"id": "93748af7-b917-4ecf-a0c8-7d89077ff9cb"
},
"source": [
"### Load WhisperTokenizer"
]
},
{
"cell_type": "markdown",
"id": "2bc82609-a9fb-447a-a2af-99597c864029",
"metadata": {
"id": "2bc82609-a9fb-447a-a2af-99597c864029"
},
"source": [
"The Whisper model outputs a sequence of _token ids_. The tokenizer maps each of these token ids to their corresponding text string. For Hindi, we can load the pre-trained tokenizer and use it for fine-tuning without any further modifications. We simply have to \n",
"specify the target language and the task. These arguments inform the \n",
"tokenizer to prefix the language and task tokens to the start of encoded \n",
"label sequences:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "c7b07f9b-ae0e-4f89-98f0-0c50d432eab6",
"metadata": {
"id": "c7b07f9b-ae0e-4f89-98f0-0c50d432eab6",
"outputId": "5c004b44-86e7-4e00-88be-39e0af5eed69"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
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]
}
],
"source": [
"from transformers import WhisperTokenizer\n",
"\n",
"tokenizer = WhisperTokenizer.from_pretrained(\"openai/whisper-medium\", language=\"Malay\", task=\"transcribe\")"
]
},
{
"cell_type": "markdown",
"id": "d2ef23f3-f4a8-483a-a2dc-080a7496cb1b",
"metadata": {
"id": "d2ef23f3-f4a8-483a-a2dc-080a7496cb1b"
},
"source": [
"### Combine To Create A WhisperProcessor"
]
},
{
"cell_type": "markdown",
"id": "5ff67654-5a29-4bb8-a69d-0228946c6f8d",
"metadata": {
"id": "5ff67654-5a29-4bb8-a69d-0228946c6f8d"
},
"source": [
"To simplify using the feature extractor and tokenizer, we can _wrap_ \n",
"both into a single `WhisperProcessor` class. This processor object \n",
"inherits from the `WhisperFeatureExtractor` and `WhisperProcessor`, \n",
"and can be used on the audio inputs and model predictions as required. \n",
"In doing so, we only need to keep track of two objects during training: \n",
"the `processor` and the `model`:"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "77d9f0c5-8607-4642-a8ac-c3ab2e223ea6",
"metadata": {
"id": "77d9f0c5-8607-4642-a8ac-c3ab2e223ea6"
},
"outputs": [],
"source": [
"from transformers import WhisperProcessor\n",
"\n",
"processor = WhisperProcessor.from_pretrained(\"openai/whisper-medium\", language=\"Malay\", task=\"transcribe\")"
]
},
{
"cell_type": "markdown",
"id": "381acd09-0b0f-4d04-9eb3-f028ac0e5f2c",
"metadata": {
"id": "381acd09-0b0f-4d04-9eb3-f028ac0e5f2c"
},
"source": [
"### Prepare Data"
]
},
{
"cell_type": "markdown",
"id": "9649bf01-2e8a-45e5-8fca-441c13637b8f",
"metadata": {
"id": "9649bf01-2e8a-45e5-8fca-441c13637b8f"
},
"source": [
"Let's print the first example of the Common Voice dataset to see \n",
"what form the data is in:"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "6e6b0ec5-0c94-4e2c-ae24-c791be1b2255",
"metadata": {
"id": "6e6b0ec5-0c94-4e2c-ae24-c791be1b2255"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'audio': {'path': '14466102005240085063.wav', 'array': array([0. , 0. , 0. , ..., 0.0003528 , 0.00013924,\n",
" 0.00014025]), 'sampling_rate': 16000}, 'transcription': 'apabila anda telah selesa dengan pemformatan dan penyuntingan di web kemudian anda mungkin membina laman web sendiri'}\n"
]
}
],
"source": [
"print(fleurs[\"train\"][0])"
]
},
{
"cell_type": "markdown",
"id": "5a679f05-063d-41b3-9b58-4fc9c6ccf4fd",
"metadata": {
"id": "5a679f05-063d-41b3-9b58-4fc9c6ccf4fd"
},
"source": [
"Since \n",
"our input audio is sampled at 48kHz, we need to _downsample_ it to \n",
"16kHz prior to passing it to the Whisper feature extractor, 16kHz being the sampling rate expected by the Whisper model. \n",
"\n",
"We'll set the audio inputs to the correct sampling rate using dataset's \n",
"[`cast_column`](https://huggingface.co/docs/datasets/package_reference/main_classes.html?highlight=cast_column#datasets.DatasetDict.cast_column)\n",
"method. This operation does not change the audio in-place, \n",
"but rather signals to `datasets` to resample audio samples _on the fly_ the \n",
"first time that they are loaded:"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "f12e2e57-156f-417b-8cfb-69221cc198e8",
"metadata": {
"id": "f12e2e57-156f-417b-8cfb-69221cc198e8"
},
"outputs": [],
"source": [
"from datasets import Audio\n",
"\n",
"fleurs = fleurs.cast_column(\"audio\", Audio(sampling_rate=16000))"
]
},
{
"cell_type": "markdown",
"id": "00382a3e-abec-4cdd-a54c-d1aaa3ea4707",
"metadata": {
"id": "00382a3e-abec-4cdd-a54c-d1aaa3ea4707"
},
"source": [
"Re-loading the first audio sample in the Common Voice dataset will resample \n",
"it to the desired sampling rate:"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "87122d71-289a-466a-afcf-fa354b18946b",
"metadata": {
"id": "87122d71-289a-466a-afcf-fa354b18946b"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'audio': {'path': '14466102005240085063.wav', 'array': array([0. , 0. , 0. , ..., 0.0003528 , 0.00013924,\n",
" 0.00014025]), 'sampling_rate': 16000}, 'transcription': 'apabila anda telah selesa dengan pemformatan dan penyuntingan di web kemudian anda mungkin membina laman web sendiri'}\n"
]
}
],
"source": [
"print(fleurs[\"train\"][0])"
]
},
{
"cell_type": "markdown",
"id": "3df7378a-a4c0-45d7-8d07-defbd1062ab6",
"metadata": {},
"source": [
"We'll define our pre-processing strategy. We advise that you **do not** lower-case the transcriptions or remove punctuation unless mixing different datasets. This will enable you to fine-tune Whisper models that can predict punctuation and casing. Later, you will see how we can evaluate the predictions without punctuation or casing, so that the models benefit from the WER improvement obtained by normalising the transcriptions while still predicting fully formatted transcriptions."
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "d041650e-1c48-4439-87b3-5b6f4a514107",
"metadata": {},
"outputs": [],
"source": [
"from transformers.models.whisper.english_normalizer import BasicTextNormalizer\n",
"\n",
"do_lower_case = False\n",
"do_remove_punctuation = False\n",
"\n",
"normalizer = BasicTextNormalizer()"
]
},
{
"cell_type": "markdown",
"id": "89e12c2e-2f14-479b-987b-f0c75c881095",
"metadata": {},
"source": [
"Now we can write a function to prepare our data ready for the model:\n",
"1. We load and resample the audio data by calling `batch[\"audio\"]`. As explained above, π€ Datasets performs any necessary resampling operations on the fly.\n",
"2. We use the feature extractor to compute the log-Mel spectrogram input features from our 1-dimensional audio array.\n",
"3. We perform any optional pre-processing (lower-case or remove punctuation).\n",
"4. We encode the transcriptions to label ids through the use of the tokenizer."
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "c085911c-a10a-41ef-8874-306e0503e9bb",
"metadata": {},
"outputs": [],
"source": [
"def prepare_dataset(batch):\n",
" # load and (possibly) resample audio data to 16kHz\n",
" audio = batch[\"audio\"]\n",
"\n",
" # compute log-Mel input features from input audio array \n",
" batch[\"input_features\"] = processor.feature_extractor(audio[\"array\"], sampling_rate=audio[\"sampling_rate\"]).input_features[0]\n",
" # compute input length of audio sample in seconds\n",
" batch[\"input_length\"] = len(audio[\"array\"]) / audio[\"sampling_rate\"]\n",
" \n",
" # optional pre-processing steps\n",
" transcription = batch[\"transcription\"]\n",
" if do_lower_case:\n",
" transcription = transcription.lower()\n",
" if do_remove_punctuation:\n",
" transcription = normalizer(transcription).strip()\n",
" \n",
" # encode target text to label ids\n",
" batch[\"labels\"] = processor.tokenizer(transcription).input_ids\n",
" return batch"
]
},
{
"cell_type": "markdown",
"id": "8c960965-9fb6-466f-9dbd-c9d43e71d9d0",
"metadata": {
"id": "70b319fb-2439-4ef6-a70d-a47bf41c4a13"
},
"source": [
"We can apply the data preparation function to all of our training examples using dataset's `.map` method. The argument `num_proc` specifies how many CPU cores to use. Setting `num_proc` > 1 will enable multiprocessing. If the `.map` method hangs with multiprocessing, set `num_proc=1` and process the dataset sequentially."
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "7b73ab39-ffaf-4b9e-86e5-782963c6134b",
"metadata": {
"id": "7b73ab39-ffaf-4b9e-86e5-782963c6134b"
},
"outputs": [
{
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]
},
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"#1: 7%|ββββββββββββββ | 105/1495 [00:11<02:50, 8.13ex/s]\u001b[A\n",
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]
},
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]
},
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"#1: 19%|ββββββββββββββββββββββββββββββββββββββ | 288/1495 [00:29<01:20, 14.92ex/s]\u001b[A\n",
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"#1: 20%|βββββββββββββββββββββββββββββββββββββββ | 298/1495 [00:30<01:16, 15.58ex/s]\u001b[A\n",
"#0: 26%|ββββββββββββββββββββββββββββββββββββββββββββββββββ | 384/1496 [00:30<02:06, 8.78ex/s]\u001b[A\n",
"#1: 20%|βββββββββββββββββββββββββββββββββββββββ | 302/1495 [00:30<01:11, 16.68ex/s]\u001b[A\n",
"#0: 26%|ββββββββββββββββββββββββββββββββββββββββββββββββββ | 386/1496 [00:30<01:58, 9.36ex/s]\u001b[A\n",
"#0: 26%|ββββββββββββββββββββββββββββββββββββββββββββββββββ | 387/1496 [00:30<01:57, 9.41ex/s]\u001b[A\n",
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"#1: 21%|ββββββββββββββββββββββββββββββββββββββββ | 310/1495 [00:31<01:09, 16.97ex/s]\u001b[A\n",
"#0: 26%|βββββββββββββββββββββββββββββββββββββββββββββββββββ | 391/1496 [00:31<01:48, 10.20ex/s]\u001b[A\n",
"#0: 26%|βββββββββββββββββββββββββββββββββββββββββββββββββββ | 393/1496 [00:31<01:47, 10.30ex/s]\u001b[A\n"
]
},
{
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"output_type": "stream",
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"#1: 21%|βββββββββββββββββββββββββββββββββββββββββ | 316/1495 [00:31<01:10, 16.76ex/s]\u001b[A\n",
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"#0: 27%|βββββββββββββββββββββββββββββββββββββββββββββββββββββ | 409/1496 [00:32<01:45, 10.32ex/s]\u001b[A\n",
"#1: 23%|βββββββββββββββββββββββββββββββββββββββββββββ | 342/1495 [00:33<01:12, 15.99ex/s]\u001b[A\n",
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"#0: 28%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 413/1496 [00:33<01:42, 10.60ex/s]\u001b[A\n",
"#1: 23%|βββββββββββββββββββββββββββββββββββββββββββββ | 348/1495 [00:33<01:15, 15.16ex/s]\u001b[A\n",
"#0: 28%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 415/1496 [00:33<01:46, 10.15ex/s]\u001b[A\n",
"#0: 28%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 417/1496 [00:33<01:43, 10.47ex/s]\u001b[A\n",
"#0: 28%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 419/1496 [00:33<01:40, 10.72ex/s]\u001b[A\n",
"#1: 24%|ββββββββββββββββββββββββββββββββββββββββββββββ | 356/1495 [00:33<01:14, 15.27ex/s]\u001b[A\n",
"#0: 28%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 421/1496 [00:34<01:47, 9.98ex/s]\u001b[A\n",
"#1: 24%|βββββββββββββββββββββββββββββββββββββββββββββββ | 360/1495 [00:34<01:10, 16.07ex/s]\u001b[A\n",
"#0: 28%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 423/1496 [00:34<01:52, 9.50ex/s]\u001b[A\n",
"#0: 28%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 424/1496 [00:34<01:52, 9.51ex/s]\u001b[A\n",
"#1: 24%|ββββββββββββββββββββββββββββββββββββββββββββββββ | 366/1495 [00:34<01:09, 16.14ex/s]\u001b[A\n",
"#0: 28%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 426/1496 [00:34<01:52, 9.55ex/s]\u001b[A\n",
"#0: 29%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 428/1496 [00:34<01:45, 10.13ex/s]\u001b[A\n",
"#1: 25%|ββββββββββββββββββββββββββββββββββββββββββββββββ | 372/1495 [00:34<01:06, 16.92ex/s]\u001b[A\n",
"#0: 29%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 430/1496 [00:35<01:41, 10.54ex/s]\u001b[A\n",
"#0: 29%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 432/1496 [00:35<01:39, 10.74ex/s]\u001b[A\n",
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]
},
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"#0: 29%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 435/1496 [00:35<01:58, 8.94ex/s]\u001b[A\n",
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"#0: 29%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 441/1496 [00:36<01:57, 8.98ex/s]\u001b[A\n",
"#0: 30%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 445/1496 [00:36<01:45, 9.93ex/s]\u001b[A\n",
"#0: 30%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 447/1496 [00:36<01:45, 9.97ex/s]\u001b[A\n",
"#0: 30%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 449/1496 [00:37<01:41, 10.31ex/s]\u001b[A\n",
"#0: 30%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 451/1496 [00:37<01:43, 10.10ex/s]\u001b[A\n",
"#0: 30%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 453/1496 [00:37<01:40, 10.37ex/s]\u001b[A\n",
"#0: 30%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 455/1496 [00:37<01:43, 10.03ex/s]\u001b[A\n",
"#0: 31%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 457/1496 [00:37<01:41, 10.24ex/s]\u001b[A\n",
"#0: 31%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 459/1496 [00:38<01:39, 10.38ex/s]\u001b[A\n",
"#0: 31%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 461/1496 [00:38<01:40, 10.30ex/s]\u001b[A\n",
"#0: 31%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 463/1496 [00:38<01:37, 10.62ex/s]\u001b[A\n",
"#0: 31%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 465/1496 [00:38<01:38, 10.42ex/s]\u001b[A\n",
"#0: 31%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 467/1496 [00:38<01:36, 10.62ex/s]\u001b[A\n",
"#0: 31%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 469/1496 [00:38<01:34, 10.88ex/s]\u001b[A\n",
"#1: 28%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 417/1495 [00:39<01:48, 9.94ex/s]\u001b[A\n",
"#0: 32%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 473/1496 [00:39<01:34, 10.78ex/s]\u001b[A\n",
"#1: 28%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 420/1495 [00:39<01:48, 9.91ex/s]\u001b[A\n",
"#0: 32%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 475/1496 [00:39<01:37, 10.49ex/s]\u001b[A\n",
"#0: 32%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 479/1496 [00:39<01:34, 10.75ex/s]\u001b[A\n",
"#0: 32%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 481/1496 [00:40<01:33, 10.86ex/s]\u001b[A\n",
"#1: 29%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 428/1495 [00:40<01:40, 10.57ex/s]\u001b[A\n",
"#0: 32%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 483/1496 [00:40<01:32, 10.92ex/s]\u001b[A\n",
"#1: 29%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 432/1495 [00:40<01:21, 13.09ex/s]\u001b[A\n",
"#0: 32%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 485/1496 [00:40<01:34, 10.67ex/s]\u001b[A\n",
"#0: 33%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 487/1496 [00:40<01:35, 10.58ex/s]\u001b[A\n",
"#1: 29%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 438/1495 [00:40<01:12, 14.63ex/s]\u001b[A\n",
"#0: 33%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 489/1496 [00:40<01:34, 10.64ex/s]\u001b[A\n",
"#0: 33%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 491/1496 [00:41<01:34, 10.63ex/s]\u001b[A\n",
"#0: 33%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 493/1496 [00:41<01:35, 10.48ex/s]\u001b[A\n"
]
},
{
"name": "stderr",
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"text": [
"#0: 33%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 495/1496 [00:41<01:33, 10.74ex/s]\u001b[A\n",
"#0: 33%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 497/1496 [00:41<01:33, 10.68ex/s]\u001b[A\n",
"#0: 33%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 499/1496 [00:41<01:33, 10.64ex/s]\u001b[A\n",
"#0: 33%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 501/1496 [00:41<01:34, 10.55ex/s]\u001b[A\n",
"#0: 34%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 503/1496 [00:42<01:38, 10.10ex/s]\u001b[A\n",
"#0: 34%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 505/1496 [00:42<01:34, 10.44ex/s]\u001b[A\n",
"#0: 34%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 507/1496 [00:42<01:34, 10.45ex/s]\u001b[A\n",
"#0: 34%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 509/1496 [00:42<01:32, 10.71ex/s]\u001b[A\n",
"#0: 34%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 511/1496 [00:42<01:32, 10.70ex/s]\u001b[A\n",
"#0: 34%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 513/1496 [00:43<01:39, 9.86ex/s]\u001b[A\n",
"#0: 34%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 515/1496 [00:43<01:34, 10.33ex/s]\u001b[A\n",
"#0: 35%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 517/1496 [00:43<01:32, 10.60ex/s]\u001b[A\n",
"#0: 35%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 519/1496 [00:43<01:30, 10.78ex/s]\u001b[A\n",
"#0: 35%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 521/1496 [00:43<01:31, 10.64ex/s]\u001b[A\n",
"#0: 35%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 523/1496 [00:44<01:28, 10.95ex/s]\u001b[A\n",
"#0: 35%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 525/1496 [00:44<01:27, 11.07ex/s]\u001b[A\n",
"#0: 35%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 527/1496 [00:44<01:31, 10.55ex/s]\u001b[A\n",
"#0: 35%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 529/1496 [00:44<01:34, 10.27ex/s]\u001b[A\n",
"#0: 35%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 531/1496 [00:44<01:31, 10.52ex/s]\u001b[A\n",
"#0: 36%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 533/1496 [00:45<01:31, 10.50ex/s]\u001b[A\n",
"#0: 36%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 535/1496 [00:45<01:30, 10.58ex/s]\u001b[A\n",
"#0: 36%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 537/1496 [00:45<01:32, 10.37ex/s]\u001b[A\n",
"#0: 36%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 539/1496 [00:45<01:30, 10.62ex/s]\u001b[A\n",
"#0: 36%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 541/1496 [00:45<01:32, 10.32ex/s]\u001b[A\n",
"#0: 36%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 543/1496 [00:45<01:31, 10.36ex/s]\u001b[A\n",
"#0: 36%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 545/1496 [00:46<01:29, 10.66ex/s]\u001b[A\n",
"#0: 37%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 547/1496 [00:46<01:28, 10.70ex/s]\u001b[A\n",
"#0: 37%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 549/1496 [00:46<01:33, 10.18ex/s]\u001b[A\n",
"#0: 37%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 551/1496 [00:46<01:33, 10.16ex/s]\u001b[A\n",
"#0: 37%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 553/1496 [00:46<01:31, 10.34ex/s]\u001b[A\n",
"#0: 37%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 555/1496 [00:47<01:34, 9.98ex/s]\u001b[A\n",
"#0: 37%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 557/1496 [00:47<01:34, 9.96ex/s]\u001b[A\n",
"#0: 37%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 559/1496 [00:47<01:30, 10.31ex/s]\u001b[A\n"
]
},
{
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"output_type": "stream",
"text": [
"#0: 38%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 561/1496 [00:47<01:31, 10.17ex/s]\u001b[A\n",
"#0: 38%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 563/1496 [00:47<01:31, 10.21ex/s]\u001b[A\n",
"#0: 38%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 565/1496 [00:48<01:33, 9.97ex/s]\u001b[A\n",
"#0: 38%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 567/1496 [00:48<01:29, 10.43ex/s]\u001b[A\n",
"#0: 38%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 569/1496 [00:48<01:28, 10.42ex/s]\u001b[A\n",
"#0: 38%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 571/1496 [00:48<01:30, 10.28ex/s]\u001b[A\n",
"#0: 38%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 573/1496 [00:48<01:27, 10.59ex/s]\u001b[A\n",
"#0: 38%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 575/1496 [00:49<01:24, 10.88ex/s]\u001b[A\n",
"#0: 39%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 577/1496 [00:49<01:23, 10.94ex/s]\u001b[A\n",
"#0: 39%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 581/1496 [00:49<01:25, 10.69ex/s]\u001b[A\n",
"#0: 39%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 583/1496 [00:49<01:24, 10.85ex/s]\u001b[A\n",
"#0: 39%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 585/1496 [00:50<01:24, 10.73ex/s]\u001b[A\n",
"#0: 39%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 587/1496 [00:50<01:30, 10.10ex/s]\u001b[A\n",
"#0: 39%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 589/1496 [00:50<01:26, 10.50ex/s]\u001b[A\n",
"#0: 40%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 591/1496 [00:50<01:23, 10.82ex/s]\u001b[A\n",
"#1: 36%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 542/1495 [00:50<01:36, 9.92ex/s]\u001b[A\n",
"#0: 40%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 593/1496 [00:50<01:22, 10.92ex/s]\u001b[A\n",
"#0: 40%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 595/1496 [00:50<01:23, 10.77ex/s]\u001b[A\n",
"#0: 40%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 597/1496 [00:51<01:27, 10.32ex/s]\u001b[A\n",
"#0: 40%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 599/1496 [00:51<01:26, 10.33ex/s]\u001b[A\n",
"#0: 40%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 603/1496 [00:51<01:24, 10.62ex/s]\u001b[A\n",
"#1: 37%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 553/1495 [00:51<01:34, 9.92ex/s]\u001b[A\n",
"#0: 40%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 605/1496 [00:51<01:24, 10.57ex/s]\u001b[A\n",
"#0: 41%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 607/1496 [00:52<01:27, 10.22ex/s]\u001b[A\n",
"#0: 41%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 609/1496 [00:52<01:32, 9.58ex/s]\u001b[A\n",
"#0: 41%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 611/1496 [00:52<01:28, 9.98ex/s]\u001b[A\n",
"#0: 41%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 613/1496 [00:52<01:31, 9.70ex/s]\u001b[A\n",
"#0: 41%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 615/1496 [00:52<01:28, 9.93ex/s]\u001b[A\n",
"#0: 41%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 617/1496 [00:53<01:24, 10.34ex/s]\u001b[A\n",
"#0: 41%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 619/1496 [00:53<01:22, 10.60ex/s]\u001b[A\n",
"#0: 42%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 621/1496 [00:53<01:25, 10.26ex/s]\u001b[A\n",
"#0: 42%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 623/1496 [00:53<01:31, 9.51ex/s]\u001b[A\n",
"#0: 42%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 625/1496 [00:54<01:39, 8.77ex/s]\u001b[A\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"#0: 42%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 626/1496 [00:54<01:42, 8.45ex/s]\u001b[A\n",
"#0: 42%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 627/1496 [00:54<01:47, 8.09ex/s]\u001b[A\n",
"#0: 42%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 629/1496 [00:54<01:52, 7.67ex/s]\u001b[A\n",
"#0: 42%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 630/1496 [00:54<01:52, 7.71ex/s]\u001b[A\n",
"#0: 42%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 632/1496 [00:54<01:47, 8.01ex/s]\u001b[A\n",
"#0: 42%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 634/1496 [00:55<01:36, 8.96ex/s]\u001b[A\n",
"#0: 42%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 635/1496 [00:55<01:34, 9.14ex/s]\u001b[A\n",
"#0: 43%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 637/1496 [00:55<01:32, 9.33ex/s]\u001b[A\n",
"#0: 43%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 639/1496 [00:55<01:25, 10.07ex/s]\u001b[A\n",
"#0: 43%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 641/1496 [00:55<01:21, 10.47ex/s]\u001b[A\n",
"#0: 43%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 643/1496 [00:55<01:21, 10.50ex/s]\u001b[A\n",
"#0: 43%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 645/1496 [00:56<01:21, 10.46ex/s]\u001b[A\n",
"#0: 43%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 647/1496 [00:56<01:27, 9.73ex/s]\u001b[A\n",
"#0: 43%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 649/1496 [00:56<01:37, 8.73ex/s]\u001b[A\n",
"#0: 43%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 650/1496 [00:56<01:43, 8.16ex/s]\u001b[A\n",
"#0: 44%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 652/1496 [00:57<01:31, 9.23ex/s]\u001b[A\n",
"#0: 44%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 654/1496 [00:57<01:30, 9.33ex/s]\u001b[A\n",
"#0: 44%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 658/1496 [00:57<01:19, 10.52ex/s]\u001b[A\n",
"#1: 41%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 612/1495 [00:57<01:29, 9.91ex/s]\u001b[A\n",
"#0: 44%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 661/1496 [00:57<01:28, 9.40ex/s]\u001b[A\n",
"#0: 44%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 662/1496 [00:58<01:28, 9.45ex/s]\u001b[A\n",
"#0: 44%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 664/1496 [00:58<01:21, 10.18ex/s]\u001b[A\n",
"#0: 45%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 666/1496 [00:58<01:18, 10.63ex/s]\u001b[A\n",
"#0: 45%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 668/1496 [00:58<01:18, 10.60ex/s]\u001b[A\n",
"#0: 45%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 670/1496 [00:58<01:20, 10.30ex/s]\u001b[A\n",
"#0: 45%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 674/1496 [00:59<01:14, 11.02ex/s]\u001b[A\n",
"#0: 45%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 676/1496 [00:59<01:12, 11.29ex/s]\u001b[A\n",
"#0: 45%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 678/1496 [00:59<01:12, 11.21ex/s]\u001b[A\n",
"#1: 42%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 631/1495 [00:59<01:32, 9.37ex/s]\u001b[A\n",
"#0: 45%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 680/1496 [00:59<01:19, 10.29ex/s]\u001b[A\n",
"#0: 46%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 682/1496 [00:59<01:23, 9.74ex/s]\u001b[A\n",
"#0: 46%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 684/1496 [01:00<01:21, 9.93ex/s]\u001b[A\n",
"#1: 43%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 638/1495 [01:00<01:26, 9.91ex/s]\u001b[A\n"
]
},
{
"name": "stderr",
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"#0: 46%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 686/1496 [01:00<01:18, 10.31ex/s]\u001b[A\n",
"#0: 46%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 688/1496 [01:00<01:15, 10.69ex/s]\u001b[A\n",
"#1: 43%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 641/1495 [01:00<01:31, 9.28ex/s]\u001b[A\n",
"#0: 46%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 690/1496 [01:00<01:15, 10.73ex/s]\u001b[A\n",
"#0: 46%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 692/1496 [01:00<01:15, 10.66ex/s]\u001b[A\n",
"#1: 43%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 644/1495 [01:00<01:36, 8.78ex/s]\u001b[A\n",
"#0: 46%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 694/1496 [01:01<01:18, 10.24ex/s]\u001b[A\n",
"#1: 43%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 646/1495 [01:01<01:40, 8.46ex/s]\u001b[A\n",
"#0: 47%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 696/1496 [01:01<01:26, 9.20ex/s]\u001b[A\n",
"#0: 47%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 697/1496 [01:01<01:30, 8.86ex/s]\u001b[A\n",
"#0: 47%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 698/1496 [01:01<01:28, 9.01ex/s]\u001b[A\n",
"#0: 47%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 699/1496 [01:01<01:26, 9.17ex/s]\u001b[A\n",
"#0: 47%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 701/1496 [01:01<01:20, 9.90ex/s]\u001b[A\n",
"#0: 47%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 702/1496 [01:01<01:25, 9.26ex/s]\u001b[A\n",
"#0: 47%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 704/1496 [01:02<01:21, 9.73ex/s]\u001b[A\n",
"#0: 47%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 706/1496 [01:02<01:16, 10.31ex/s]\u001b[A\n",
"#0: 47%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 708/1496 [01:02<01:18, 10.04ex/s]\u001b[A\n",
"#0: 47%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 710/1496 [01:02<01:16, 10.29ex/s]\u001b[A\n",
"#1: 44%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 662/1495 [01:02<01:21, 10.24ex/s]\u001b[A\n",
"#0: 48%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 712/1496 [01:02<01:14, 10.51ex/s]\u001b[A\n",
"#0: 48%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 714/1496 [01:03<01:14, 10.51ex/s]\u001b[A\n",
"#1: 45%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 668/1495 [01:03<00:58, 14.14ex/s]\u001b[A\n",
"#0: 48%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 716/1496 [01:03<01:17, 10.12ex/s]\u001b[A\n",
"#1: 45%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 672/1495 [01:03<00:55, 14.79ex/s]\u001b[A\n",
"#0: 48%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 718/1496 [01:03<01:16, 10.18ex/s]\u001b[A\n",
"#0: 48%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 720/1496 [01:03<01:17, 10.04ex/s]\u001b[A\n",
"#1: 45%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 678/1495 [01:03<00:51, 15.86ex/s]\u001b[A\n",
"#0: 48%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 722/1496 [01:03<01:17, 9.94ex/s]\u001b[A\n",
"#1: 46%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 682/1495 [01:03<00:47, 17.02ex/s]\u001b[A\n",
"#0: 48%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 724/1496 [01:04<01:14, 10.31ex/s]\u001b[A\n",
"#0: 49%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 726/1496 [01:04<01:16, 10.07ex/s]\u001b[A\n",
"#1: 46%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 688/1495 [01:04<00:47, 16.82ex/s]\u001b[A\n",
"#0: 49%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 728/1496 [01:04<01:14, 10.26ex/s]\u001b[A\n"
]
},
{
"name": "stderr",
"output_type": "stream",
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"#1: 46%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 692/1495 [01:04<00:47, 17.08ex/s]\u001b[A\n",
"#0: 49%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 730/1496 [01:04<01:16, 10.04ex/s]\u001b[A\n",
"#0: 49%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 732/1496 [01:04<01:15, 10.14ex/s]\u001b[A\n",
"#1: 47%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 698/1495 [01:04<00:46, 17.05ex/s]\u001b[A\n",
"#0: 49%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 734/1496 [01:05<01:13, 10.31ex/s]\u001b[A\n",
"#1: 47%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 702/1495 [01:05<00:45, 17.27ex/s]\u001b[A\n",
"#0: 49%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 736/1496 [01:05<01:13, 10.30ex/s]\u001b[A\n",
"#1: 47%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 706/1495 [01:05<00:45, 17.28ex/s]\u001b[A\n",
"#0: 49%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 738/1496 [01:05<01:15, 10.02ex/s]\u001b[A\n",
"#0: 49%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 740/1496 [01:05<01:17, 9.71ex/s]\u001b[A\n",
"#1: 48%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 712/1495 [01:05<00:47, 16.59ex/s]\u001b[A\n",
"#0: 50%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 742/1496 [01:05<01:16, 9.87ex/s]\u001b[A\n",
"#0: 50%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 744/1496 [01:06<01:14, 10.11ex/s]\u001b[A\n",
"#1: 48%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 718/1495 [01:06<00:45, 17.05ex/s]\u001b[A\n",
"#0: 50%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 746/1496 [01:06<01:14, 10.10ex/s]\u001b[A\n",
"#1: 48%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 722/1495 [01:06<00:47, 16.38ex/s]\u001b[A\n",
"#0: 50%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 748/1496 [01:06<01:16, 9.82ex/s]\u001b[A\n",
"#0: 50%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 750/1496 [01:06<01:13, 10.13ex/s]\u001b[A\n",
"#1: 49%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 728/1495 [01:06<00:44, 17.09ex/s]\u001b[A\n",
"#0: 50%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 752/1496 [01:06<01:11, 10.37ex/s]\u001b[A\n",
"#1: 49%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 732/1495 [01:06<00:45, 16.60ex/s]\u001b[A\n",
"#0: 50%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 754/1496 [01:07<01:11, 10.36ex/s]\u001b[A\n",
"#0: 51%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 756/1496 [01:07<01:15, 9.83ex/s]\u001b[A\n",
"#0: 51%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 757/1496 [01:07<01:15, 9.77ex/s]\u001b[A\n",
"#1: 49%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 740/1495 [01:07<00:44, 17.02ex/s]\u001b[A\n",
"#0: 51%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 759/1496 [01:07<01:12, 10.12ex/s]\u001b[A\n",
"#1: 50%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 744/1495 [01:07<00:44, 17.02ex/s]\u001b[A\n",
"#0: 51%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 761/1496 [01:07<01:12, 10.11ex/s]\u001b[A\n",
"#0: 51%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 763/1496 [01:07<01:13, 9.96ex/s]\u001b[A\n",
"#1: 50%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 750/1495 [01:07<00:42, 17.39ex/s]\u001b[A\n",
"#0: 51%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 764/1496 [01:08<01:19, 9.23ex/s]\u001b[A\n",
"#0: 51%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 765/1496 [01:08<01:25, 8.52ex/s]\u001b[A\n",
"#0: 51%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 767/1496 [01:08<01:18, 9.23ex/s]\u001b[A\n"
]
},
{
"name": "stderr",
"output_type": "stream",
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"#1: 51%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 758/1495 [01:08<00:46, 15.92ex/s]\u001b[A\n",
"#0: 51%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 769/1496 [01:08<01:14, 9.77ex/s]\u001b[A\n",
"#0: 51%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 770/1496 [01:08<01:14, 9.73ex/s]\u001b[A\n",
"#0: 52%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 772/1496 [01:08<01:17, 9.32ex/s]\u001b[A\n",
"#0: 52%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 773/1496 [01:09<01:17, 9.29ex/s]\u001b[A\n",
"#1: 51%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 768/1495 [01:09<00:46, 15.66ex/s]\u001b[A\n",
"#0: 52%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 775/1496 [01:09<01:16, 9.46ex/s]\u001b[A\n",
"#0: 52%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 777/1496 [01:09<01:10, 10.21ex/s]\u001b[A\n",
"#0: 52%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 779/1496 [01:09<01:09, 10.30ex/s]\u001b[A\n",
"#1: 52%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 776/1495 [01:09<00:47, 15.03ex/s]\u001b[A\n",
"#0: 52%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 781/1496 [01:09<01:06, 10.68ex/s]\u001b[A\n",
"#1: 52%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 780/1495 [01:09<00:43, 16.48ex/s]\u001b[A\n",
"#0: 52%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 783/1496 [01:10<01:06, 10.80ex/s]\u001b[A\n",
"#1: 52%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 784/1495 [01:10<00:42, 16.61ex/s]\u001b[A\n",
"#0: 52%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 785/1496 [01:10<01:12, 9.85ex/s]\u001b[A\n",
"#0: 53%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 786/1496 [01:10<01:16, 9.22ex/s]\u001b[A\n",
"#0: 53%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 787/1496 [01:10<01:19, 8.87ex/s]\u001b[A\n",
"#0: 53%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 788/1496 [01:10<01:20, 8.74ex/s]\u001b[A\n",
"#1: 53%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 794/1495 [01:10<00:42, 16.58ex/s]\u001b[A\n",
"#0: 53%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 790/1496 [01:10<01:18, 9.01ex/s]\u001b[A\n",
"#0: 53%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 792/1496 [01:11<01:13, 9.59ex/s]\u001b[A\n",
"#1: 54%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 800/1495 [01:11<00:41, 16.62ex/s]\u001b[A\n",
"#0: 53%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 794/1496 [01:11<01:13, 9.61ex/s]\u001b[A\n",
"#1: 54%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 804/1495 [01:11<00:39, 17.41ex/s]\u001b[A\n",
"#0: 53%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 796/1496 [01:11<01:09, 10.06ex/s]\u001b[A\n",
"#0: 53%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 798/1496 [01:11<01:09, 10.09ex/s]\u001b[A\n",
"#1: 54%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 810/1495 [01:11<00:39, 17.13ex/s]\u001b[A\n",
"#0: 53%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 800/1496 [01:11<01:07, 10.37ex/s]\u001b[A\n",
"#1: 54%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 814/1495 [01:11<00:40, 16.61ex/s]\u001b[A\n",
"#0: 54%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 802/1496 [01:12<01:10, 9.89ex/s]\u001b[A\n",
"#0: 54%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 803/1496 [01:12<01:11, 9.70ex/s]\u001b[A\n",
"#0: 54%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 804/1496 [01:12<01:11, 9.62ex/s]\u001b[A\n",
"#0: 54%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 805/1496 [01:12<01:13, 9.35ex/s]\u001b[A\n"
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"#0: 54%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 807/1496 [01:12<01:17, 8.87ex/s]\u001b[A\n",
"#0: 54%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 809/1496 [01:12<01:09, 9.91ex/s]\u001b[A\n",
"#0: 54%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 810/1496 [01:12<01:12, 9.44ex/s]\u001b[A\n",
"#0: 54%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 812/1496 [01:13<01:09, 9.80ex/s]\u001b[A\n",
"#0: 55%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 816/1496 [01:13<01:05, 10.44ex/s]\u001b[A\n",
"#1: 56%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 834/1495 [01:13<01:01, 10.74ex/s]\u001b[A\n",
"#0: 55%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 818/1496 [01:13<01:02, 10.78ex/s]\u001b[A\n",
"#1: 56%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 838/1495 [01:13<00:49, 13.33ex/s]\u001b[A\n",
"#0: 55%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 820/1496 [01:13<01:05, 10.38ex/s]\u001b[A\n",
"#0: 55%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 822/1496 [01:14<01:05, 10.22ex/s]\u001b[A\n",
"#1: 56%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 844/1495 [01:14<00:40, 16.07ex/s]\u001b[A\n",
"#0: 55%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 824/1496 [01:14<01:03, 10.55ex/s]\u001b[A\n",
"#1: 57%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 848/1495 [01:14<00:40, 15.95ex/s]\u001b[A\n",
"#0: 55%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 826/1496 [01:14<01:03, 10.53ex/s]\u001b[A\n",
"#0: 55%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 828/1496 [01:14<01:05, 10.23ex/s]\u001b[A\n",
"#1: 57%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 854/1495 [01:14<00:37, 16.98ex/s]\u001b[A\n",
"#0: 55%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 830/1496 [01:14<01:11, 9.33ex/s]\u001b[A\n",
"#1: 57%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 858/1495 [01:14<00:38, 16.38ex/s]\u001b[A\n",
"#0: 56%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 832/1496 [01:15<01:09, 9.56ex/s]\u001b[A\n",
"#1: 58%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 862/1495 [01:15<00:38, 16.52ex/s]\u001b[A\n",
"#0: 56%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 834/1496 [01:15<01:06, 9.94ex/s]\u001b[A\n",
"#0: 56%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 836/1496 [01:15<01:03, 10.39ex/s]\u001b[A\n",
"#1: 58%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 868/1495 [01:15<00:35, 17.74ex/s]\u001b[A\n",
"#0: 56%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 838/1496 [01:15<01:03, 10.33ex/s]\u001b[A\n",
"#1: 58%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 872/1495 [01:15<00:33, 18.44ex/s]\u001b[A\n",
"#0: 56%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 840/1496 [01:15<01:01, 10.63ex/s]\u001b[A\n",
"#0: 56%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 842/1496 [01:16<01:03, 10.35ex/s]\u001b[A\n",
"#1: 59%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 878/1495 [01:16<00:35, 17.30ex/s]\u001b[A\n",
"#0: 56%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 844/1496 [01:16<01:01, 10.57ex/s]\u001b[A\n",
"#1: 59%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 882/1495 [01:16<00:34, 17.60ex/s]\u001b[A\n",
"#0: 57%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 846/1496 [01:16<01:03, 10.26ex/s]\u001b[A\n",
"#0: 57%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 848/1496 [01:16<01:01, 10.58ex/s]\u001b[A\n",
"#1: 59%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 888/1495 [01:16<00:34, 17.52ex/s]\u001b[A\n"
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"#0: 57%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 850/1496 [01:16<01:00, 10.62ex/s]\u001b[A\n",
"#0: 57%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 852/1496 [01:16<01:00, 10.67ex/s]\u001b[A\n",
"#1: 60%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 894/1495 [01:16<00:36, 16.54ex/s]\u001b[A\n",
"#0: 57%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 854/1496 [01:17<01:01, 10.51ex/s]\u001b[A\n",
"#1: 60%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 898/1495 [01:17<00:34, 17.17ex/s]\u001b[A\n",
"#0: 57%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 856/1496 [01:17<01:01, 10.48ex/s]\u001b[A\n",
"#0: 57%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 858/1496 [01:17<01:02, 10.25ex/s]\u001b[A\n",
"#1: 60%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 904/1495 [01:17<00:34, 17.06ex/s]\u001b[A\n",
"#0: 57%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 860/1496 [01:17<01:00, 10.57ex/s]\u001b[A\n",
"#0: 58%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 862/1496 [01:17<00:58, 10.88ex/s]\u001b[A\n",
"#1: 61%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 910/1495 [01:17<00:33, 17.33ex/s]\u001b[A\n",
"#0: 58%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 864/1496 [01:18<00:57, 10.95ex/s]\u001b[A\n",
"#1: 61%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 914/1495 [01:18<00:34, 16.67ex/s]\u001b[A\n",
"#0: 58%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 866/1496 [01:18<00:58, 10.78ex/s]\u001b[A\n",
"#1: 61%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 918/1495 [01:18<00:33, 17.14ex/s]\u001b[A\n",
"#0: 58%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 868/1496 [01:18<01:06, 9.37ex/s]\u001b[A\n",
"#0: 58%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 869/1496 [01:18<01:08, 9.11ex/s]\u001b[A\n",
"#0: 58%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 870/1496 [01:18<01:13, 8.55ex/s]\u001b[A\n",
"#0: 58%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 871/1496 [01:18<01:13, 8.52ex/s]\u001b[A\n",
"#0: 58%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 872/1496 [01:19<01:15, 8.27ex/s]\u001b[A\n",
"#0: 58%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 873/1496 [01:19<01:17, 8.07ex/s]\u001b[A\n",
"#0: 58%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 874/1496 [01:19<01:18, 7.92ex/s]\u001b[A\n",
"#0: 58%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 875/1496 [01:19<01:19, 7.84ex/s]\u001b[A\n",
"#0: 59%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 876/1496 [01:19<01:19, 7.77ex/s]\u001b[A\n",
"#0: 59%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 877/1496 [01:19<01:20, 7.73ex/s]\u001b[A\n",
"#0: 59%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 878/1496 [01:19<01:20, 7.71ex/s]\u001b[A\n",
"#0: 59%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 879/1496 [01:19<01:20, 7.68ex/s]\u001b[A\n",
"#0: 59%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 880/1496 [01:20<01:20, 7.67ex/s]\u001b[A\n",
"#0: 59%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 881/1496 [01:20<01:18, 7.86ex/s]\u001b[A\n",
"#1: 63%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 949/1495 [01:20<00:34, 16.04ex/s]\u001b[A\n",
"#0: 59%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 883/1496 [01:20<01:07, 9.09ex/s]\u001b[A\n",
"#0: 59%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 884/1496 [01:20<01:08, 8.91ex/s]\u001b[A\n",
"#0: 59%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 886/1496 [01:20<01:03, 9.65ex/s]\u001b[A\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"#1: 64%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 957/1495 [01:20<00:32, 16.63ex/s]\u001b[A\n",
"#0: 59%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 888/1496 [01:20<01:00, 10.07ex/s]\u001b[A\n",
"#0: 59%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 890/1496 [01:21<00:58, 10.36ex/s]\u001b[A\n",
"#1: 64%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 963/1495 [01:21<00:31, 16.77ex/s]\u001b[A\n",
"#0: 60%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 892/1496 [01:21<00:57, 10.45ex/s]\u001b[A\n",
"#1: 65%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 967/1495 [01:21<00:30, 17.05ex/s]\u001b[A\n",
"#0: 60%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 894/1496 [01:21<00:59, 10.12ex/s]\u001b[A\n",
"#0: 60%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 896/1496 [01:21<00:56, 10.55ex/s]\u001b[A\n",
"#1: 65%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 973/1495 [01:21<00:30, 16.99ex/s]\u001b[A\n",
"#0: 60%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 898/1496 [01:21<00:55, 10.78ex/s]\u001b[A\n",
"#1: 65%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 977/1495 [01:21<00:30, 16.91ex/s]\u001b[A\n",
"#0: 60%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 900/1496 [01:22<00:59, 10.06ex/s]\u001b[A\n",
"#0: 60%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 902/1496 [01:22<00:59, 10.06ex/s]\u001b[A\n",
"#1: 66%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 983/1495 [01:22<00:29, 17.27ex/s]\u001b[A\n",
"#0: 60%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 904/1496 [01:22<00:56, 10.42ex/s]\u001b[A\n",
"#1: 66%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 987/1495 [01:22<00:29, 17.41ex/s]\u001b[A\n",
"#0: 61%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 906/1496 [01:22<00:57, 10.20ex/s]\u001b[A\n",
"#0: 61%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 908/1496 [01:22<00:55, 10.56ex/s]\u001b[A\n",
"#1: 66%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 993/1495 [01:22<00:28, 17.91ex/s]\u001b[A\n",
"#0: 61%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 910/1496 [01:23<01:03, 9.26ex/s]\u001b[A\n",
"#0: 61%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 911/1496 [01:23<01:06, 8.81ex/s]\u001b[A\n",
"#0: 64%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 951/1496 [01:25<00:28, 19.27ex/s]\u001b[A\n",
"#0: 64%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 953/1496 [01:25<00:37, 14.42ex/s]\u001b[A\n",
"#0: 64%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 955/1496 [01:25<00:40, 13.43ex/s]\u001b[A\n",
"#0: 64%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 958/1496 [01:25<00:35, 15.03ex/s]\u001b[A\n",
"#0: 64%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 963/1496 [01:26<00:30, 17.37ex/s]\u001b[A\n",
"#0: 65%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 965/1496 [01:26<00:29, 17.78ex/s]\u001b[A\n",
"#0: 65%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 970/1496 [01:26<00:28, 18.64ex/s]\u001b[A\n",
"#0: 65%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 972/1496 [01:26<00:28, 18.51ex/s]\u001b[A\n",
"#0: 65%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 976/1496 [01:26<00:28, 18.36ex/s]\u001b[A\n",
"#0: 66%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 981/1496 [01:27<00:26, 19.32ex/s]\u001b[A\n",
"#0: 66%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 983/1496 [01:27<00:26, 19.01ex/s]\u001b[A\n",
"#0: 66%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 985/1496 [01:27<00:27, 18.91ex/s]\u001b[A\n"
]
},
{
"name": "stderr",
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"#0: 66%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 990/1496 [01:27<00:27, 18.53ex/s]\u001b[A\n",
"#0: 66%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 993/1496 [01:27<00:26, 19.20ex/s]\u001b[A\n",
"#0: 67%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 997/1496 [01:28<00:26, 18.77ex/s]\u001b[A\n",
"#0: 67%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 999/1496 [01:28<00:26, 18.65ex/s]\u001b[A\n",
"#1: 69%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1031/1495 [01:28<00:42, 11.03ex/s]\u001b[A\n",
"#1: 69%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1033/1495 [01:28<00:40, 11.33ex/s]\u001b[A\n",
"#1: 69%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1036/1495 [01:28<00:32, 13.98ex/s]\u001b[A\n",
"#1: 69%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1039/1495 [01:28<00:28, 15.87ex/s]\u001b[A\n",
"#1: 70%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1041/1495 [01:28<00:27, 16.33ex/s]\u001b[A\n",
"#1: 70%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1043/1495 [01:28<00:27, 16.60ex/s]\u001b[A\n",
"#1: 70%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1045/1495 [01:29<00:26, 17.22ex/s]\u001b[A\n",
"#1: 70%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1047/1495 [01:29<00:25, 17.25ex/s]\u001b[A\n",
"#1: 70%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1050/1495 [01:29<00:23, 18.56ex/s]\u001b[A\n",
"#1: 70%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1052/1495 [01:29<00:24, 18.42ex/s]\u001b[A\n",
"#1: 71%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1054/1495 [01:29<00:23, 18.46ex/s]\u001b[A\n",
"#1: 71%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1056/1495 [01:29<00:24, 18.09ex/s]\u001b[A\n",
"#1: 71%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1058/1495 [01:29<00:23, 18.49ex/s]\u001b[A\n",
"#1: 71%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1060/1495 [01:29<00:23, 18.64ex/s]\u001b[A\n",
"#1: 71%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1062/1495 [01:29<00:24, 17.72ex/s]\u001b[A\n",
"#1: 71%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1064/1495 [01:30<00:23, 18.06ex/s]\u001b[A\n",
"#1: 71%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1066/1495 [01:30<00:23, 18.26ex/s]\u001b[A\n",
"#1: 71%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1068/1495 [01:30<00:23, 18.46ex/s]\u001b[A\n",
"#1: 72%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1070/1495 [01:30<00:23, 18.34ex/s]\u001b[A\n",
"#1: 72%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1072/1495 [01:30<00:22, 18.54ex/s]\u001b[A\n",
"#0: 67%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1001/1496 [01:30<03:18, 2.49ex/s]\u001b[A\n",
"#0: 67%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1003/1496 [01:30<02:29, 3.30ex/s]\u001b[A\n",
"#0: 67%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1008/1496 [01:31<01:20, 6.08ex/s]\u001b[A\n",
"#0: 68%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1013/1496 [01:31<00:50, 9.57ex/s]\u001b[A\n",
"#0: 68%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1015/1496 [01:31<00:43, 11.12ex/s]\u001b[A\n",
"#0: 68%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1019/1496 [01:31<00:34, 13.93ex/s]\u001b[A\n",
"#0: 68%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1022/1496 [01:31<00:30, 15.77ex/s]\u001b[A\n",
"#0: 69%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1028/1496 [01:32<00:25, 18.49ex/s]\u001b[A\n",
"#0: 69%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1031/1496 [01:32<00:24, 19.33ex/s]\u001b[A\n"
]
},
{
"name": "stderr",
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"#1: 73%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1094/1495 [01:32<00:29, 13.61ex/s]\u001b[A\n",
"#0: 69%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1034/1496 [01:32<00:23, 19.64ex/s]\u001b[A\n",
"#0: 69%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1037/1496 [01:32<00:23, 19.88ex/s]\u001b[A\n",
"#0: 70%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1040/1496 [01:32<00:22, 20.39ex/s]\u001b[A\n",
"#0: 70%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1043/1496 [01:32<00:22, 20.22ex/s]\u001b[A\n",
"#0: 70%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1046/1496 [01:32<00:23, 19.52ex/s]\u001b[A\n",
"#0: 70%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1049/1496 [01:33<00:22, 19.44ex/s]\u001b[A\n",
"#0: 71%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1055/1496 [01:33<00:21, 20.22ex/s]\u001b[A\n",
"#0: 71%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1058/1496 [01:33<00:21, 20.06ex/s]\u001b[A\n",
"#0: 71%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1061/1496 [01:33<00:21, 19.91ex/s]\u001b[A\n",
"#0: 71%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1064/1496 [01:33<00:21, 20.49ex/s]\u001b[A\n",
"#0: 72%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1070/1496 [01:34<00:20, 20.39ex/s]\u001b[A\n",
"#0: 72%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1076/1496 [01:34<00:20, 20.24ex/s]\u001b[A\n",
"#0: 72%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1079/1496 [01:34<00:20, 20.51ex/s]\u001b[A\n",
"#0: 72%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1082/1496 [01:34<00:19, 20.81ex/s]\u001b[A\n",
"#0: 73%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1085/1496 [01:34<00:19, 21.04ex/s]\u001b[A\n",
"#0: 73%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1088/1496 [01:34<00:19, 21.18ex/s]\u001b[A\n",
"#0: 73%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1091/1496 [01:35<00:19, 20.58ex/s]\u001b[A\n",
"#0: 73%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1094/1496 [01:35<00:19, 20.13ex/s]\u001b[A\n",
"#1: 75%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1126/1495 [01:35<00:48, 7.59ex/s]\u001b[A\n",
"#0: 73%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1099/1496 [01:35<00:19, 19.91ex/s]\u001b[A\n",
"#0: 74%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1102/1496 [01:35<00:19, 20.24ex/s]\u001b[A\n",
"#0: 74%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1105/1496 [01:35<00:19, 20.48ex/s]\u001b[A\n",
"#0: 74%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1108/1496 [01:35<00:18, 20.68ex/s]\u001b[A\n",
"#1: 76%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1131/1495 [01:36<00:49, 7.29ex/s]\u001b[A\n",
"#0: 74%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1114/1496 [01:36<00:18, 20.63ex/s]\u001b[A\n",
"#0: 75%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1117/1496 [01:36<00:18, 20.76ex/s]\u001b[A\n",
"#0: 75%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1120/1496 [01:36<00:18, 20.69ex/s]\u001b[A\n",
"#0: 75%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1123/1496 [01:36<00:17, 20.74ex/s]\u001b[A\n",
"#0: 75%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1129/1496 [01:37<00:17, 20.58ex/s]\u001b[A\n",
"#0: 76%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1132/1496 [01:37<00:17, 20.80ex/s]\u001b[A\n",
"#0: 76%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1138/1496 [01:37<00:16, 21.31ex/s]\u001b[A\n",
"#0: 76%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1141/1496 [01:37<00:16, 21.28ex/s]\u001b[A\n"
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{
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"#0: 76%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1144/1496 [01:37<00:16, 21.12ex/s]\u001b[A\n",
"#0: 77%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1150/1496 [01:37<00:16, 21.17ex/s]\u001b[A\n",
"#0: 77%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1153/1496 [01:38<00:16, 20.49ex/s]\u001b[A\n",
"#0: 77%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1156/1496 [01:38<00:16, 20.62ex/s]\u001b[A\n",
"#0: 77%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1159/1496 [01:38<00:16, 20.14ex/s]\u001b[A\n",
"#0: 78%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1162/1496 [01:38<00:16, 20.35ex/s]\u001b[A\n",
"#0: 78%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1165/1496 [01:38<00:16, 20.10ex/s]\u001b[A\n",
"#0: 78%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1168/1496 [01:38<00:16, 20.48ex/s]\u001b[A\n",
"#0: 78%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1171/1496 [01:39<00:15, 20.55ex/s]\u001b[A\n",
"#0: 78%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1174/1496 [01:39<00:15, 20.39ex/s]\u001b[A\n",
"#0: 79%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1177/1496 [01:39<00:15, 20.64ex/s]\u001b[A\n",
"#1: 78%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1162/1495 [01:39<00:41, 7.98ex/s]\u001b[A\n",
"#0: 79%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1183/1496 [01:39<00:14, 20.90ex/s]\u001b[A\n",
"#0: 79%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1186/1496 [01:39<00:14, 21.03ex/s]\u001b[A\n",
"#0: 79%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1189/1496 [01:39<00:14, 21.17ex/s]\u001b[A\n",
"#1: 78%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1168/1495 [01:39<00:32, 9.92ex/s]\u001b[A\n",
"#0: 80%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1192/1496 [01:40<00:16, 18.64ex/s]\u001b[A\n",
"#0: 80%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1194/1496 [01:40<00:18, 16.10ex/s]\u001b[A\n",
"#0: 80%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1196/1496 [01:40<00:20, 14.62ex/s]\u001b[A\n",
"#0: 80%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1200/1496 [01:40<00:22, 12.91ex/s]\u001b[A\n",
"#0: 80%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1202/1496 [01:40<00:23, 12.66ex/s]\u001b[A\n",
"#1: 79%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1178/1495 [01:40<00:35, 8.87ex/s]\u001b[A\n",
"#0: 80%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1204/1496 [01:41<00:26, 10.88ex/s]\u001b[A\n",
"#1: 79%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1180/1495 [01:41<00:38, 8.16ex/s]\u001b[A\n",
"#0: 81%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1206/1496 [01:41<00:28, 10.12ex/s]\u001b[A\n",
"#0: 81%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1208/1496 [01:41<00:27, 10.47ex/s]\u001b[A\n",
"#0: 81%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1210/1496 [01:41<00:26, 10.82ex/s]\u001b[A\n",
"#0: 81%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1212/1496 [01:41<00:25, 11.10ex/s]\u001b[A\n",
"#0: 81%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1214/1496 [01:42<00:25, 11.23ex/s]\u001b[A\n",
"#0: 81%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1216/1496 [01:42<00:24, 11.35ex/s]\u001b[A\n",
"#0: 81%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1218/1496 [01:42<00:24, 11.49ex/s]\u001b[A\n",
"#0: 82%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1220/1496 [01:42<00:23, 11.57ex/s]\u001b[A\n",
"#0: 82%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1222/1496 [01:42<00:23, 11.64ex/s]\u001b[A\n"
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"#0: 82%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1224/1496 [01:42<00:23, 11.59ex/s]\u001b[A\n",
"#0: 82%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1226/1496 [01:43<00:24, 11.19ex/s]\u001b[A\n",
"#0: 82%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1228/1496 [01:43<00:24, 11.13ex/s]\u001b[A\n",
"#0: 82%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1230/1496 [01:43<00:24, 11.07ex/s]\u001b[A\n",
"#0: 82%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1232/1496 [01:43<00:23, 11.28ex/s]\u001b[A\n",
"#0: 82%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1234/1496 [01:43<00:23, 11.35ex/s]\u001b[A\n",
"#0: 83%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1236/1496 [01:44<00:22, 11.44ex/s]\u001b[A\n",
"#0: 83%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1238/1496 [01:44<00:22, 11.49ex/s]\u001b[A\n",
"#0: 83%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1240/1496 [01:44<00:22, 11.59ex/s]\u001b[A\n",
"#0: 83%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1242/1496 [01:44<00:22, 11.54ex/s]\u001b[A\n",
"#0: 83%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1244/1496 [01:44<00:22, 11.41ex/s]\u001b[A\n",
"#0: 83%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1246/1496 [01:44<00:21, 11.42ex/s]\u001b[A\n",
"#0: 83%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1248/1496 [01:45<00:23, 10.57ex/s]\u001b[A\n",
"#0: 84%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1250/1496 [01:45<00:23, 10.44ex/s]\u001b[A\n",
"#0: 84%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1252/1496 [01:45<00:22, 10.79ex/s]\u001b[A\n",
"#0: 84%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1254/1496 [01:45<00:21, 11.05ex/s]\u001b[A\n",
"#0: 84%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1256/1496 [01:45<00:21, 11.23ex/s]\u001b[A\n",
"#0: 84%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1258/1496 [01:46<00:21, 11.32ex/s]\u001b[A\n",
"#0: 84%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1262/1496 [01:46<00:18, 12.77ex/s]\u001b[A\n",
"#0: 85%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1265/1496 [01:46<00:15, 15.27ex/s]\u001b[A\n",
"#0: 85%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1267/1496 [01:46<00:14, 16.18ex/s]\u001b[A\n",
"#0: 85%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1272/1496 [01:46<00:12, 18.14ex/s]\u001b[A\n",
"#0: 85%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1275/1496 [01:46<00:11, 19.02ex/s]\u001b[A\n",
"#0: 86%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1280/1496 [01:47<00:10, 19.84ex/s]\u001b[A\n",
"#0: 86%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1286/1496 [01:47<00:10, 20.89ex/s]\u001b[A\n",
"#0: 86%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1289/1496 [01:47<00:09, 20.98ex/s]\u001b[A\n",
"#0: 86%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1292/1496 [01:47<00:09, 21.00ex/s]\u001b[A\n",
"#0: 87%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1295/1496 [01:47<00:09, 21.09ex/s]\u001b[A\n",
"#0: 87%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1301/1496 [01:48<00:09, 20.97ex/s]\u001b[A\n",
"#0: 87%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1304/1496 [01:48<00:09, 20.94ex/s]\u001b[A\n",
"#0: 87%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1307/1496 [01:48<00:09, 20.72ex/s]\u001b[A\n",
"#0: 88%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1310/1496 [01:48<00:09, 20.66ex/s]\u001b[A\n",
"#0: 88%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1316/1496 [01:48<00:08, 21.08ex/s]\u001b[A\n"
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"#0: 88%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1319/1496 [01:49<00:08, 21.17ex/s]\u001b[A\n",
"#0: 88%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1322/1496 [01:49<00:08, 21.17ex/s]\u001b[A\n",
"#0: 89%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1328/1496 [01:49<00:07, 21.27ex/s]\u001b[A\n",
"#0: 89%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1331/1496 [01:49<00:07, 21.19ex/s]\u001b[A\n",
"#0: 89%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1334/1496 [01:49<00:07, 21.07ex/s]\u001b[A\n",
"#0: 89%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1337/1496 [01:49<00:07, 20.97ex/s]\u001b[A\n",
"#0: 90%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1343/1496 [01:50<00:07, 21.16ex/s]\u001b[A\n",
"#0: 90%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1346/1496 [01:50<00:07, 20.42ex/s]\u001b[A\n",
"#0: 90%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1349/1496 [01:50<00:07, 20.17ex/s]\u001b[A\n",
"#0: 90%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1352/1496 [01:50<00:07, 20.24ex/s]\u001b[A\n",
"#0: 91%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1358/1496 [01:50<00:06, 20.49ex/s]\u001b[A\n",
"#0: 91%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1361/1496 [01:51<00:06, 20.61ex/s]\u001b[A\n",
"#0: 91%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1364/1496 [01:51<00:06, 20.76ex/s]\u001b[A\n",
"#0: 91%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1367/1496 [01:51<00:06, 20.72ex/s]\u001b[A\n",
"#0: 92%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1370/1496 [01:51<00:06, 20.68ex/s]\u001b[A\n",
"#0: 92%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1376/1496 [01:51<00:05, 20.92ex/s]\u001b[A\n",
"#0: 92%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1379/1496 [01:51<00:05, 20.21ex/s]\u001b[A\n",
"#0: 92%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1382/1496 [01:52<00:05, 20.37ex/s]\u001b[A\n",
"#0: 93%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1388/1496 [01:52<00:05, 20.90ex/s]\u001b[A\n",
"#0: 93%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1391/1496 [01:52<00:05, 20.81ex/s]\u001b[A\n",
"#0: 93%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1394/1496 [01:52<00:04, 20.92ex/s]\u001b[A\n",
"#0: 94%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1400/1496 [01:52<00:04, 20.94ex/s]\u001b[A\n",
"#0: 94%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1403/1496 [01:53<00:04, 20.94ex/s]\u001b[A\n",
"#0: 94%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1406/1496 [01:53<00:04, 20.92ex/s]\u001b[A\n",
"#0: 94%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1409/1496 [01:53<00:04, 20.90ex/s]\u001b[A\n",
"#0: 94%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1412/1496 [01:53<00:04, 20.90ex/s]\u001b[A\n",
"#0: 95%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1418/1496 [01:53<00:03, 20.93ex/s]\u001b[A\n",
"#0: 95%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1421/1496 [01:53<00:03, 20.92ex/s]\u001b[A\n",
"#0: 95%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1424/1496 [01:54<00:03, 20.99ex/s]\u001b[A\n",
"#0: 96%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1430/1496 [01:54<00:03, 21.32ex/s]\u001b[A\n",
"#0: 96%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1433/1496 [01:54<00:02, 21.31ex/s]\u001b[A\n",
"#0: 96%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1436/1496 [01:54<00:02, 21.30ex/s]\u001b[A\n",
"#0: 96%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1442/1496 [01:54<00:02, 21.32ex/s]\u001b[A\n"
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"#0: 97%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1445/1496 [01:55<00:02, 21.28ex/s]\u001b[A\n",
"#0: 97%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1448/1496 [01:55<00:02, 21.16ex/s]\u001b[A\n",
"#0: 97%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1454/1496 [01:55<00:01, 21.32ex/s]\u001b[A\n",
"#0: 97%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1457/1496 [01:55<00:01, 21.40ex/s]\u001b[A\n",
"#0: 98%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1463/1496 [01:55<00:01, 21.22ex/s]\u001b[A\n",
"#0: 98%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1466/1496 [01:56<00:01, 21.19ex/s]\u001b[A\n",
"#0: 98%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1469/1496 [01:56<00:01, 21.21ex/s]\u001b[A\n",
"#0: 99%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1475/1496 [01:56<00:00, 21.20ex/s]\u001b[A\n",
"#0: 99%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1478/1496 [01:56<00:00, 20.89ex/s]\u001b[A\n",
"#0: 99%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1481/1496 [01:56<00:00, 20.86ex/s]\u001b[A\n",
"#0: 99%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1487/1496 [01:57<00:00, 20.78ex/s]\u001b[A\n",
"#0: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1490/1496 [01:57<00:00, 20.37ex/s]\u001b[A\n",
"#0: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1493/1496 [01:57<00:00, 20.55ex/s]\u001b[A\n",
"#0: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1496/1496 [01:57<00:00, 12.73ex/s]\u001b[A\n",
"\n",
"#1: 91%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1358/1495 [01:57<00:12, 10.84ex/s]\u001b[A\n",
"#1: 91%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1361/1495 [01:57<00:09, 13.64ex/s]\u001b[A\n",
"#1: 91%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1363/1495 [01:57<00:08, 14.91ex/s]\u001b[A\n",
"#1: 91%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1365/1495 [01:57<00:08, 15.91ex/s]\u001b[A\n",
"#1: 91%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1367/1495 [01:58<00:07, 16.51ex/s]\u001b[A\n",
"#1: 92%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1369/1495 [01:58<00:07, 17.05ex/s]\u001b[A\n",
"#1: 92%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1371/1495 [01:58<00:07, 17.64ex/s]\u001b[A\n",
"#1: 92%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1373/1495 [01:58<00:06, 17.52ex/s]\u001b[A\n",
"#1: 92%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1375/1495 [01:58<00:06, 17.94ex/s]\u001b[A\n",
"#1: 92%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1378/1495 [01:58<00:06, 19.15ex/s]\u001b[A\n",
"#1: 92%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1380/1495 [01:58<00:07, 16.15ex/s]\u001b[A\n",
"#1: 93%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1383/1495 [01:58<00:06, 17.83ex/s]\u001b[A\n",
"#1: 93%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1385/1495 [01:59<00:05, 18.34ex/s]\u001b[A\n",
"#1: 93%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1388/1495 [01:59<00:05, 19.54ex/s]\u001b[A\n",
"#1: 93%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1391/1495 [01:59<00:05, 20.42ex/s]\u001b[A\n",
"#1: 93%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1394/1495 [01:59<00:04, 20.97ex/s]\u001b[A\n",
"#1: 93%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1397/1495 [01:59<00:04, 21.31ex/s]\u001b[A\n",
"#1: 94%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1400/1495 [01:59<00:04, 21.62ex/s]\u001b[A\n",
"#1: 94%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1403/1495 [01:59<00:04, 21.82ex/s]\u001b[A\n"
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"#1: 94%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1406/1495 [02:00<00:04, 21.86ex/s]\u001b[A\n",
"#1: 94%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1409/1495 [02:00<00:03, 21.92ex/s]\u001b[A\n",
"#1: 94%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1412/1495 [02:00<00:03, 21.80ex/s]\u001b[A\n",
"#1: 95%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1415/1495 [02:00<00:03, 22.01ex/s]\u001b[A\n",
"#1: 95%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1418/1495 [02:00<00:03, 22.03ex/s]\u001b[A\n",
"#1: 95%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1421/1495 [02:00<00:03, 22.11ex/s]\u001b[A\n",
"#1: 95%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1424/1495 [02:00<00:03, 22.20ex/s]\u001b[A\n",
"#1: 95%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1427/1495 [02:00<00:03, 22.24ex/s]\u001b[A\n",
"#1: 96%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1430/1495 [02:01<00:02, 22.20ex/s]\u001b[A\n",
"#1: 96%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1433/1495 [02:01<00:02, 22.21ex/s]\u001b[A\n",
"#1: 96%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1436/1495 [02:01<00:02, 22.15ex/s]\u001b[A\n",
"#1: 96%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1439/1495 [02:01<00:02, 22.21ex/s]\u001b[A\n",
"#1: 96%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1442/1495 [02:01<00:02, 22.19ex/s]\u001b[A\n",
"#1: 97%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1445/1495 [02:01<00:02, 22.11ex/s]\u001b[A\n",
"#1: 97%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1448/1495 [02:01<00:02, 22.07ex/s]\u001b[A\n",
"#1: 97%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1451/1495 [02:02<00:01, 22.05ex/s]\u001b[A\n",
"#1: 97%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1454/1495 [02:02<00:01, 22.11ex/s]\u001b[A\n",
"#1: 97%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1457/1495 [02:02<00:01, 21.99ex/s]\u001b[A\n",
"#1: 98%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1460/1495 [02:02<00:01, 22.02ex/s]\u001b[A\n",
"#1: 98%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1463/1495 [02:02<00:01, 21.93ex/s]\u001b[A\n",
"#1: 98%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1466/1495 [02:02<00:01, 22.08ex/s]\u001b[A\n",
"#1: 98%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1469/1495 [02:02<00:01, 22.06ex/s]\u001b[A\n",
"#1: 98%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1472/1495 [02:02<00:01, 22.21ex/s]\u001b[A\n",
"#1: 99%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1475/1495 [02:03<00:00, 22.17ex/s]\u001b[A\n",
"#1: 99%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1478/1495 [02:03<00:00, 22.12ex/s]\u001b[A\n",
"#1: 99%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1481/1495 [02:03<00:00, 22.11ex/s]\u001b[A\n",
"#1: 99%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1484/1495 [02:03<00:00, 22.19ex/s]\u001b[A\n",
"#1: 99%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 1487/1495 [02:03<00:00, 22.16ex/s]\u001b[A\n",
"#1: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1490/1495 [02:03<00:00, 22.11ex/s]\u001b[A\n",
"#1: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 1495/1495 [02:04<00:00, 12.05ex/s]\u001b[A\n",
"#0: 0%| | 0/375 [00:00, ?ex/s]\n",
"#0: 0%|β | 1/375 [00:00<05:09, 1.21ex/s]\u001b[A\n",
"#0: 1%|β | 2/375 [00:00<02:30, 2.48ex/s]\u001b[A\n",
"#0: 1%|ββ | 4/375 [00:01<01:17, 4.77ex/s]\u001b[A\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"#1: 2%|ββββ | 6/374 [00:01<00:51, 7.18ex/s]\u001b[A\n",
"#0: 2%|ββββ | 6/375 [00:01<00:56, 6.53ex/s]\u001b[A\n",
"#0: 2%|ββββ | 7/375 [00:01<00:53, 6.83ex/s]\u001b[A\n",
"#0: 2%|βββββ | 9/375 [00:01<00:44, 8.20ex/s]\u001b[A\n",
"#0: 3%|ββββββ | 10/375 [00:01<00:43, 8.44ex/s]\u001b[A\n",
"#1: 4%|βββββββββ | 16/374 [00:01<00:24, 14.51ex/s]\u001b[A\n",
"#0: 3%|βββββββ | 12/375 [00:01<00:38, 9.31ex/s]\u001b[A\n",
"#0: 4%|ββββββββ | 14/375 [00:02<00:37, 9.65ex/s]\u001b[A\n",
"#1: 6%|ββββββββββββ | 23/374 [00:02<00:20, 17.04ex/s]\u001b[A\n",
"#0: 4%|βββββββββ | 16/375 [00:02<00:39, 9.13ex/s]\u001b[A\n",
"#0: 5%|βββββββββ | 17/375 [00:02<00:39, 8.99ex/s]\u001b[A\n",
"#0: 5%|ββββββββββ | 18/375 [00:02<00:41, 8.59ex/s]\u001b[A\n",
"#0: 5%|ββββββββββ | 19/375 [00:02<00:43, 8.28ex/s]\u001b[A\n",
"#1: 9%|ββββββββββββββββββ | 33/374 [00:02<00:20, 16.47ex/s]\u001b[A\n",
"#0: 6%|βββββββββββ | 21/375 [00:02<00:45, 7.74ex/s]\u001b[A\n",
"#0: 6%|ββββββββββββ | 23/375 [00:03<00:44, 7.85ex/s]\u001b[A\n",
"#0: 7%|βββββββββββββ | 25/375 [00:03<00:38, 9.15ex/s]\u001b[A\n",
"#0: 7%|ββββββββββββββ | 27/375 [00:03<00:36, 9.60ex/s]\u001b[A\n",
"#0: 8%|βββββββββββββββ | 29/375 [00:03<00:33, 10.32ex/s]\u001b[A\n",
"#0: 8%|ββββββββββββββββ | 31/375 [00:03<00:32, 10.68ex/s]\u001b[A\n",
"#0: 9%|ββββββββββββββββββ | 33/375 [00:04<00:31, 10.74ex/s]\u001b[A\n",
"#0: 10%|ββββββββββββββββββββ | 37/375 [00:04<00:31, 10.70ex/s]\u001b[A\n",
"#0: 10%|βββββββββββββββββββββ | 39/375 [00:04<00:32, 10.39ex/s]\u001b[A\n",
"#1: 14%|ββββββββββββββββββββββββββββ | 53/374 [00:04<00:35, 9.15ex/s]\u001b[A\n",
"#0: 11%|ββββββββββββββββββββββ | 41/375 [00:05<00:36, 9.04ex/s]\u001b[A\n",
"#0: 11%|βββββββββββββββββββββββ | 43/375 [00:05<00:34, 9.56ex/s]\u001b[A\n",
"#1: 15%|ββββββββββββββββββββββββββββββ | 56/374 [00:05<00:38, 8.20ex/s]\u001b[A\n",
"#0: 12%|ββββββββββββββββββββββββ | 45/375 [00:05<00:33, 9.87ex/s]\u001b[A\n",
"#0: 13%|βββββββββββββββββββββββββ | 47/375 [00:05<00:31, 10.42ex/s]\u001b[A\n",
"#0: 14%|βββββββββββββββββββββββββββ | 51/375 [00:05<00:24, 13.34ex/s]\u001b[A\n",
"#0: 14%|ββββββββββββββββββββββββββββ | 54/375 [00:05<00:20, 15.59ex/s]\u001b[A\n",
"#0: 15%|ββββββββββββββββββββββββββββββ | 57/375 [00:06<00:19, 16.72ex/s]\u001b[A\n",
"#0: 16%|βββββββββββββββββββββββββββββββ | 59/375 [00:06<00:18, 17.03ex/s]\u001b[A\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"#0: 16%|ββββββββββββββββββββββββββββββββ | 61/375 [00:06<00:18, 17.20ex/s]\u001b[A\n",
"#0: 17%|βββββββββββββββββββββββββββββββββ | 63/375 [00:06<00:18, 17.07ex/s]\u001b[A\n",
"#0: 17%|ββββββββββββββββββββββββββββββββββ | 65/375 [00:06<00:17, 17.27ex/s]\u001b[A\n",
"#0: 18%|ββββββββββββββββββββββββββββββββββββ | 69/375 [00:06<00:18, 16.65ex/s]\u001b[A\n",
"#0: 19%|βββββββββββββββββββββββββββββββββββββ | 71/375 [00:06<00:18, 16.75ex/s]\u001b[A\n",
"#0: 20%|βββββββββββββββββββββββββββββββββββββββ | 74/375 [00:07<00:17, 17.46ex/s]\u001b[A\n",
"#0: 21%|ββββββββββββββββββββββββββββββββββββββββ | 77/375 [00:07<00:16, 18.57ex/s]\u001b[A\n",
"#0: 21%|βββββββββββββββββββββββββββββββββββββββββ | 79/375 [00:07<00:15, 18.52ex/s]\u001b[A\n",
"#0: 22%|ββββββββββββββββββββββββββββββββββββββββββ | 81/375 [00:07<00:16, 17.84ex/s]\u001b[A\n",
"#0: 22%|ββββββββββββββββββββββββββββββββββββββββββββ | 83/375 [00:07<00:16, 18.11ex/s]\u001b[A\n",
"#0: 23%|βββββββββββββββββββββββββββββββββββββββββββββ | 85/375 [00:07<00:16, 17.30ex/s]\u001b[A\n",
"#0: 23%|ββββββββββββββββββββββββββββββββββββββββββββββ | 87/375 [00:07<00:16, 17.57ex/s]\u001b[A\n",
"#0: 24%|ββββββββββββββββββββββββββββββββββββββββββββββββ | 91/375 [00:07<00:15, 18.37ex/s]\u001b[A\n",
"#0: 25%|βββββββββββββββββββββββββββββββββββββββββββββββββ | 93/375 [00:08<00:15, 18.36ex/s]\u001b[A\n",
"#0: 25%|ββββββββββββββββββββββββββββββββββββββββββββββββββ | 95/375 [00:08<00:19, 14.44ex/s]\u001b[A\n",
"#0: 26%|βββββββββββββββββββββββββββββββββββββββββββββββββββ | 97/375 [00:08<00:21, 13.08ex/s]\u001b[A\n",
"#0: 26%|ββββββββββββββββββββββββββββββββββββββββββββββββββββ | 99/375 [00:08<00:22, 12.24ex/s]\u001b[A\n",
"#0: 27%|βββββββββββββββββββββββββββββββββββββββββββββββββββββ | 101/375 [00:08<00:24, 10.98ex/s]\u001b[A\n",
"#0: 27%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 103/375 [00:09<00:25, 10.50ex/s]\u001b[A\n",
"#0: 28%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 105/375 [00:09<00:25, 10.54ex/s]\u001b[A\n",
"#0: 29%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 107/375 [00:09<00:25, 10.58ex/s]\u001b[A\n",
"#0: 29%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 109/375 [00:09<00:26, 10.04ex/s]\u001b[A\n",
"#0: 30%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 111/375 [00:09<00:26, 10.04ex/s]\u001b[A\n",
"#0: 30%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 113/375 [00:10<00:25, 10.44ex/s]\u001b[A\n",
"#0: 31%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 115/375 [00:10<00:24, 10.68ex/s]\u001b[A\n",
"#0: 31%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 117/375 [00:10<00:25, 10.12ex/s]\u001b[A\n",
"#0: 32%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 119/375 [00:10<00:25, 10.12ex/s]\u001b[A\n",
"#0: 32%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 121/375 [00:10<00:24, 10.51ex/s]\u001b[A\n",
"#0: 33%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 123/375 [00:11<00:24, 10.12ex/s]\u001b[A\n",
"#0: 33%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 125/375 [00:11<00:23, 10.54ex/s]\u001b[A\n",
"#0: 34%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 127/375 [00:11<00:22, 10.84ex/s]\u001b[A\n",
"#0: 34%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 129/375 [00:11<00:23, 10.68ex/s]\u001b[A\n",
"#0: 35%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 131/375 [00:11<00:23, 10.28ex/s]\u001b[A\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"#0: 35%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 133/375 [00:12<00:23, 10.18ex/s]\u001b[A\n",
"#0: 36%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 135/375 [00:12<00:24, 9.97ex/s]\u001b[A\n",
"#0: 37%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 139/375 [00:12<00:19, 11.82ex/s]\u001b[A\n",
"#0: 38%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 144/375 [00:12<00:14, 15.41ex/s]\u001b[A\n",
"#0: 39%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 146/375 [00:12<00:14, 15.92ex/s]\u001b[A\n",
"#0: 40%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 150/375 [00:13<00:13, 17.05ex/s]\u001b[A\n",
"#0: 42%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 156/375 [00:13<00:11, 19.45ex/s]\u001b[A\n",
"#0: 42%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 159/375 [00:13<00:11, 18.60ex/s]\u001b[A\n",
"#0: 43%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 161/375 [00:13<00:11, 18.49ex/s]\u001b[A\n",
"#0: 44%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 164/375 [00:13<00:11, 19.07ex/s]\u001b[A\n",
"#0: 44%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 166/375 [00:13<00:11, 18.81ex/s]\u001b[A\n",
"#0: 45%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 170/375 [00:14<00:11, 18.53ex/s]\u001b[A\n",
"#0: 46%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 172/375 [00:14<00:11, 18.33ex/s]\u001b[A\n",
"#0: 46%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 174/375 [00:14<00:11, 17.85ex/s]\u001b[A\n",
"#0: 47%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 176/375 [00:14<00:10, 18.40ex/s]\u001b[A\n",
"#0: 47%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 178/375 [00:14<00:10, 17.92ex/s]\u001b[A\n",
"#0: 48%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 181/375 [00:14<00:10, 18.80ex/s]\u001b[A\n",
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{
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"#0: 76%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 286/375 [00:20<00:05, 16.99ex/s]\u001b[A\n",
"#0: 77%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 288/375 [00:20<00:05, 17.36ex/s]\u001b[A\n",
"#0: 77%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 290/375 [00:20<00:04, 17.56ex/s]\u001b[A\n",
"#0: 78%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 292/375 [00:20<00:04, 17.98ex/s]\u001b[A\n",
"#0: 79%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 295/375 [00:21<00:04, 18.58ex/s]\u001b[A\n",
"#0: 80%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 299/375 [00:21<00:04, 17.44ex/s]\u001b[A\n",
"#0: 81%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 302/375 [00:21<00:03, 18.74ex/s]\u001b[A\n"
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"#0: 82%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 306/375 [00:21<00:03, 17.95ex/s]\u001b[A\n",
"#0: 83%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 311/375 [00:21<00:03, 18.85ex/s]\u001b[A\n",
"#0: 83%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 313/375 [00:22<00:03, 18.77ex/s]\u001b[A\n",
"#0: 84%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 315/375 [00:22<00:03, 18.36ex/s]\u001b[A\n",
"#0: 85%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 317/375 [00:22<00:03, 17.87ex/s]\u001b[A\n",
"#0: 85%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 320/375 [00:22<00:03, 18.00ex/s]\u001b[A\n",
"#0: 87%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 325/375 [00:22<00:02, 18.91ex/s]\u001b[A\n",
"#0: 87%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 327/375 [00:22<00:02, 18.81ex/s]\u001b[A\n",
"#0: 88%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 329/375 [00:23<00:02, 16.01ex/s]\u001b[A\n",
"#0: 88%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 331/375 [00:23<00:03, 11.84ex/s]\u001b[A\n",
"#0: 89%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 333/375 [00:23<00:04, 9.88ex/s]\u001b[A\n",
"#0: 89%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 335/375 [00:23<00:03, 11.48ex/s]\u001b[A\n",
"#0: 90%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 337/375 [00:23<00:03, 12.57ex/s]\u001b[A\n",
"#0: 91%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 341/375 [00:24<00:02, 15.36ex/s]\u001b[A\n",
"#1: 62%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 232/374 [00:24<00:17, 8.26ex/s]\u001b[A\n",
"#0: 92%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 344/375 [00:24<00:01, 16.35ex/s]\u001b[A\n",
"#0: 93%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 348/375 [00:24<00:01, 16.82ex/s]\u001b[A\n",
"#0: 94%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 351/375 [00:24<00:01, 17.90ex/s]\u001b[A\n",
"#0: 94%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 353/375 [00:24<00:01, 17.90ex/s]\u001b[A\n",
"#0: 95%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 355/375 [00:24<00:01, 18.12ex/s]\u001b[A\n",
"#0: 95%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 358/375 [00:24<00:00, 19.01ex/s]\u001b[A\n",
"#0: 96%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 360/375 [00:25<00:00, 18.90ex/s]\u001b[A\n",
"#0: 97%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 362/375 [00:25<00:00, 17.63ex/s]\u001b[A\n",
"#0: 98%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 366/375 [00:25<00:00, 18.61ex/s]\u001b[A\n",
"#0: 98%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 368/375 [00:25<00:00, 18.96ex/s]\u001b[A\n",
"#0: 99%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 370/375 [00:25<00:00, 17.90ex/s]\u001b[A\n",
"#0: 99%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 373/375 [00:25<00:00, 18.53ex/s]\u001b[A\n",
"#0: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 375/375 [00:25<00:00, 14.50ex/s]\u001b[A\n",
"\n",
"#1: 67%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 249/374 [00:25<00:14, 8.64ex/s]\u001b[A\n",
"#1: 67%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 250/374 [00:26<00:14, 8.78ex/s]\u001b[A\n",
"#1: 68%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 253/374 [00:26<00:09, 12.73ex/s]\u001b[A\n",
"#1: 68%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 255/374 [00:26<00:08, 14.26ex/s]\u001b[A\n",
"#1: 69%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 257/374 [00:26<00:07, 15.14ex/s]\u001b[A\n"
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"#1: 69%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 259/374 [00:26<00:07, 14.82ex/s]\u001b[A\n",
"#1: 70%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 261/374 [00:26<00:07, 15.01ex/s]\u001b[A\n",
"#1: 70%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 263/374 [00:26<00:07, 15.26ex/s]\u001b[A\n",
"#1: 71%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 265/374 [00:26<00:06, 16.40ex/s]\u001b[A\n",
"#1: 71%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 267/374 [00:27<00:06, 16.10ex/s]\u001b[A\n",
"#1: 72%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 270/374 [00:27<00:05, 17.75ex/s]\u001b[A\n",
"#1: 73%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 272/374 [00:27<00:05, 18.01ex/s]\u001b[A\n",
"#1: 73%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 274/374 [00:27<00:05, 18.11ex/s]\u001b[A\n",
"#1: 74%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 277/374 [00:27<00:05, 17.54ex/s]\u001b[A\n",
"#1: 75%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 279/374 [00:27<00:05, 17.78ex/s]\u001b[A\n",
"#1: 75%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 282/374 [00:27<00:04, 19.12ex/s]\u001b[A\n",
"#1: 76%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 284/374 [00:27<00:04, 18.83ex/s]\u001b[A\n",
"#1: 76%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 286/374 [00:28<00:04, 18.76ex/s]\u001b[A\n",
"#1: 77%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 288/374 [00:28<00:04, 18.71ex/s]\u001b[A\n",
"#1: 78%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 290/374 [00:28<00:04, 18.66ex/s]\u001b[A\n",
"#1: 78%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 293/374 [00:28<00:04, 19.72ex/s]\u001b[A\n",
"#1: 79%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 295/374 [00:28<00:04, 19.12ex/s]\u001b[A\n",
"#1: 79%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 297/374 [00:28<00:04, 17.49ex/s]\u001b[A\n",
"#1: 80%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 299/374 [00:28<00:04, 17.67ex/s]\u001b[A\n",
"#1: 81%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 302/374 [00:28<00:03, 19.26ex/s]\u001b[A\n",
"#1: 81%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 304/374 [00:28<00:03, 19.19ex/s]\u001b[A\n",
"#1: 82%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 306/374 [00:29<00:03, 18.66ex/s]\u001b[A\n",
"#1: 82%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 308/374 [00:29<00:03, 18.98ex/s]\u001b[A\n",
"#1: 83%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 310/374 [00:29<00:03, 18.51ex/s]\u001b[A\n",
"#1: 84%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 313/374 [00:29<00:03, 19.83ex/s]\u001b[A\n",
"#1: 84%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 315/374 [00:29<00:03, 19.63ex/s]\u001b[A\n",
"#1: 85%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 317/374 [00:29<00:03, 18.95ex/s]\u001b[A\n",
"#1: 85%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 319/374 [00:29<00:02, 18.70ex/s]\u001b[A\n",
"#1: 86%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 321/374 [00:29<00:02, 18.59ex/s]\u001b[A\n",
"#1: 87%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 324/374 [00:30<00:02, 19.54ex/s]\u001b[A\n",
"#1: 87%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 326/374 [00:30<00:02, 17.99ex/s]\u001b[A\n",
"#1: 88%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 329/374 [00:30<00:02, 18.96ex/s]\u001b[A\n",
"#1: 89%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 331/374 [00:30<00:02, 18.95ex/s]\u001b[A\n"
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"#1: 89%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 333/374 [00:30<00:02, 18.85ex/s]\u001b[A\n",
"#1: 90%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 335/374 [00:30<00:02, 17.74ex/s]\u001b[A\n",
"#1: 90%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 338/374 [00:30<00:01, 18.88ex/s]\u001b[A\n",
"#1: 91%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 340/374 [00:30<00:01, 19.12ex/s]\u001b[A\n",
"#1: 91%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 342/374 [00:30<00:01, 19.12ex/s]\u001b[A\n",
"#1: 92%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 344/374 [00:31<00:01, 18.99ex/s]\u001b[A\n",
"#1: 93%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 346/374 [00:31<00:01, 18.85ex/s]\u001b[A\n",
"#1: 93%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 348/374 [00:31<00:01, 18.70ex/s]\u001b[A\n",
"#1: 94%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 350/374 [00:31<00:01, 18.89ex/s]\u001b[A\n",
"#1: 94%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 352/374 [00:31<00:01, 18.53ex/s]\u001b[A\n",
"#1: 95%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 354/374 [00:31<00:01, 18.75ex/s]\u001b[A\n",
"#1: 95%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 356/374 [00:31<00:00, 18.52ex/s]\u001b[A\n",
"#1: 96%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 358/374 [00:31<00:00, 18.61ex/s]\u001b[A\n",
"#1: 96%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 360/374 [00:31<00:00, 18.53ex/s]\u001b[A\n",
"#1: 97%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 362/374 [00:32<00:00, 18.50ex/s]\u001b[A\n",
"#1: 97%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 364/374 [00:32<00:00, 18.09ex/s]\u001b[A\n",
"#1: 98%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 367/374 [00:32<00:00, 19.23ex/s]\u001b[A\n",
"#1: 99%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 369/374 [00:32<00:00, 18.57ex/s]\u001b[A\n",
"#1: 99%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ | 371/374 [00:32<00:00, 17.77ex/s]\u001b[A\n",
"#1: 100%|ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 374/374 [00:32<00:00, 11.44ex/s]\u001b[A\n"
]
}
],
"source": [
"fleurs = fleurs.map(prepare_dataset, remove_columns=fleurs.column_names[\"train\"], num_proc=2)"
]
},
{
"cell_type": "markdown",
"id": "54ce0fdb-7218-4a4d-b175-383980fec0df",
"metadata": {},
"source": [
"Finally, we filter any training data with audio samples longer than 30s. These samples would otherwise be truncated by the Whisper feature-extractor which could affect the stability of training. We define a function that returns `True` for samples that are less than 30s, and `False` for those that are longer:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "01cb25ef-4bb0-4325-9461-f59198acadf6",
"metadata": {},
"outputs": [],
"source": [
"max_input_length = 30.0\n",
"\n",
"def is_audio_in_length_range(length):\n",
" return length < max_input_length"
]
},
{
"cell_type": "markdown",
"id": "30e676a8-7ca8-4850-8c5d-5b2b00d13fba",
"metadata": {},
"source": [
"We apply our filter function to all samples of our training dataset through π€ Datasets' `.filter` method:"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "333f7f6e-6053-4d3b-8924-c733c79b82ac",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 3/3 [00:00<00:00, 515.00ba/s]\n"
]
}
],
"source": [
"fleurs[\"train\"] = fleurs[\"train\"].filter(\n",
" is_audio_in_length_range,\n",
" input_columns=[\"input_length\"],\n",
")"
]
},
{
"cell_type": "markdown",
"id": "263a5a58-0239-4a25-b0df-c625fc9c5810",
"metadata": {
"id": "263a5a58-0239-4a25-b0df-c625fc9c5810"
},
"source": [
"## Training and Evaluation"
]
},
{
"cell_type": "markdown",
"id": "a693e768-c5a6-453f-89a1-b601dcf7daf7",
"metadata": {
"id": "a693e768-c5a6-453f-89a1-b601dcf7daf7"
},
"source": [
"Now that we've prepared our data, we're ready to dive into the training pipeline. \n",
"The [π€ Trainer](https://huggingface.co/transformers/master/main_classes/trainer.html?highlight=trainer)\n",
"will do much of the heavy lifting for us. All we have to do is:\n",
"\n",
"- Define a data collator: the data collator takes our pre-processed data and prepares PyTorch tensors ready for the model.\n",
"\n",
"- Evaluation metrics: during evaluation, we want to evaluate the model using the [word error rate (WER)](https://huggingface.co/metrics/wer) metric. We need to define a `compute_metrics` function that handles this computation.\n",
"\n",
"- Load a pre-trained checkpoint: we need to load a pre-trained checkpoint and configure it correctly for training.\n",
"\n",
"- Define the training configuration: this will be used by the π€ Trainer to define the training schedule.\n",
"\n",
"Once we've fine-tuned the model, we will evaluate it on the test data to verify that we have correctly trained it \n",
"to transcribe speech in Hindi."
]
},
{
"cell_type": "markdown",
"id": "8d230e6d-624c-400a-bbf5-fa660881df25",
"metadata": {
"id": "8d230e6d-624c-400a-bbf5-fa660881df25"
},
"source": [
"### Define a Data Collator"
]
},
{
"cell_type": "markdown",
"id": "04def221-0637-4a69-b242-d3f0c1d0ee78",
"metadata": {
"id": "04def221-0637-4a69-b242-d3f0c1d0ee78"
},
"source": [
"The data collator for a sequence-to-sequence speech model is unique in the sense that it \n",
"treats the `input_features` and `labels` independently: the `input_features` must be \n",
"handled by the feature extractor and the `labels` by the tokenizer.\n",
"\n",
"The `input_features` are already padded to 30s and converted to a log-Mel spectrogram \n",
"of fixed dimension by action of the feature extractor, so all we have to do is convert the `input_features`\n",
"to batched PyTorch tensors. We do this using the feature extractor's `.pad` method with `return_tensors=pt`.\n",
"\n",
"The `labels` on the other hand are un-padded. We first pad the sequences\n",
"to the maximum length in the batch using the tokenizer's `.pad` method. The padding tokens \n",
"are then replaced by `-100` so that these tokens are **not** taken into account when \n",
"computing the loss. We then cut the BOS token from the start of the label sequence as we \n",
"append it later during training.\n",
"\n",
"We can leverage the `WhisperProcessor` we defined earlier to perform both the \n",
"feature extractor and the tokenizer operations:"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "8326221e-ec13-4731-bb4e-51e5fc1486c5",
"metadata": {
"id": "8326221e-ec13-4731-bb4e-51e5fc1486c5"
},
"outputs": [],
"source": [
"import torch\n",
"\n",
"from dataclasses import dataclass\n",
"from typing import Any, Dict, List, Union\n",
"\n",
"@dataclass\n",
"class DataCollatorSpeechSeq2SeqWithPadding:\n",
" processor: Any\n",
"\n",
" def __call__(self, features: List[Dict[str, Union[List[int], torch.Tensor]]]) -> Dict[str, torch.Tensor]:\n",
" # split inputs and labels since they have to be of different lengths and need different padding methods\n",
" # first treat the audio inputs by simply returning torch tensors\n",
" input_features = [{\"input_features\": feature[\"input_features\"]} for feature in features]\n",
" batch = self.processor.feature_extractor.pad(input_features, return_tensors=\"pt\")\n",
"\n",
" # get the tokenized label sequences\n",
" label_features = [{\"input_ids\": feature[\"labels\"]} for feature in features]\n",
" # pad the labels to max length\n",
" labels_batch = self.processor.tokenizer.pad(label_features, return_tensors=\"pt\")\n",
"\n",
" # replace padding with -100 to ignore loss correctly\n",
" labels = labels_batch[\"input_ids\"].masked_fill(labels_batch.attention_mask.ne(1), -100)\n",
"\n",
" # if bos token is appended in previous tokenization step,\n",
" # cut bos token here as it's append later anyways\n",
" if (labels[:, 0] == self.processor.tokenizer.bos_token_id).all().cpu().item():\n",
" labels = labels[:, 1:]\n",
"\n",
" batch[\"labels\"] = labels\n",
"\n",
" return batch"
]
},
{
"cell_type": "markdown",
"id": "3cae7dbf-8a50-456e-a3a8-7fd005390f86",
"metadata": {
"id": "3cae7dbf-8a50-456e-a3a8-7fd005390f86"
},
"source": [
"Let's initialise the data collator we've just defined:"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "fc834702-c0d3-4a96-b101-7b87be32bf42",
"metadata": {
"id": "fc834702-c0d3-4a96-b101-7b87be32bf42"
},
"outputs": [],
"source": [
"data_collator = DataCollatorSpeechSeq2SeqWithPadding(processor=processor)"
]
},
{
"cell_type": "markdown",
"id": "d62bb2ab-750a-45e7-82e9-61d6f4805698",
"metadata": {
"id": "d62bb2ab-750a-45e7-82e9-61d6f4805698"
},
"source": [
"### Evaluation Metrics"
]
},
{
"cell_type": "markdown",
"id": "66fee1a7-a44c-461e-b047-c3917221572e",
"metadata": {
"id": "66fee1a7-a44c-461e-b047-c3917221572e"
},
"source": [
"We'll use the word error rate (WER) metric, the 'de-facto' metric for assessing \n",
"ASR systems. For more information, refer to the WER [docs](https://huggingface.co/metrics/wer). We'll load the WER metric from π€ Evaluate:"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "b22b4011-f31f-4b57-b684-c52332f92890",
"metadata": {
"id": "b22b4011-f31f-4b57-b684-c52332f92890"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Downloading builder script: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 4.49k/4.49k [00:00<00:00, 7.77MB/s]\n"
]
}
],
"source": [
"import evaluate\n",
"\n",
"metric = evaluate.load(\"wer\")"
]
},
{
"cell_type": "markdown",
"id": "4f32cab6-31f0-4cb9-af4c-40ba0f5fc508",
"metadata": {
"id": "4f32cab6-31f0-4cb9-af4c-40ba0f5fc508"
},
"source": [
"We then simply have to define a function that takes our model \n",
"predictions and returns the WER metric. This function, called\n",
"`compute_metrics`, first replaces `-100` with the `pad_token_id`\n",
"in the `label_ids` (undoing the step we applied in the \n",
"data collator to ignore padded tokens correctly in the loss).\n",
"It then decodes the predicted and label ids to strings. Finally,\n",
"it computes the WER between the predictions and reference labels. \n",
"Here, we have the option of evaluating with the 'normalised' transcriptions \n",
"and predictions. We recommend you set this to `True` to benefit from the WER \n",
"improvement obtained by normalising the transcriptions."
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "23959a70-22d0-4ffe-9fa1-72b61e75bb52",
"metadata": {
"id": "23959a70-22d0-4ffe-9fa1-72b61e75bb52"
},
"outputs": [],
"source": [
"#Β evaluate with the 'normalised' WER\n",
"do_normalize_eval = True\n",
"\n",
"def compute_metrics(pred):\n",
" pred_ids = pred.predictions\n",
" label_ids = pred.label_ids\n",
"\n",
" # replace -100 with the pad_token_id\n",
" label_ids[label_ids == -100] = processor.tokenizer.pad_token_id\n",
"\n",
" # we do not want to group tokens when computing the metrics\n",
" pred_str = processor.tokenizer.batch_decode(pred_ids, skip_special_tokens=True)\n",
" label_str = processor.tokenizer.batch_decode(label_ids, skip_special_tokens=True)\n",
"\n",
" if do_normalize_eval:\n",
" pred_str = [normalizer(pred) for pred in pred_str]\n",
" label_str = [normalizer(label) for label in label_str]\n",
"\n",
" wer = 100 * metric.compute(predictions=pred_str, references=label_str)\n",
"\n",
" return {\"wer\": wer}"
]
},
{
"cell_type": "markdown",
"id": "daf2a825-6d9f-4a23-b145-c37c0039075b",
"metadata": {
"id": "daf2a825-6d9f-4a23-b145-c37c0039075b"
},
"source": [
"###Β Load a Pre-Trained Checkpoint"
]
},
{
"cell_type": "markdown",
"id": "437a97fa-4864-476b-8abc-f28b8166cfa5",
"metadata": {
"id": "437a97fa-4864-476b-8abc-f28b8166cfa5"
},
"source": [
"Now let's load the pre-trained Whisper `small` checkpoint. Again, this \n",
"is trivial through use of π€ Transformers!"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "5a10cc4b-07ec-4ebd-ac1d-7c601023594f",
"metadata": {
"id": "5a10cc4b-07ec-4ebd-ac1d-7c601023594f"
},
"outputs": [],
"source": [
"from transformers import WhisperForConditionalGeneration\n",
"\n",
"model = WhisperForConditionalGeneration.from_pretrained(\"openai/whisper-medium\")"
]
},
{
"cell_type": "markdown",
"id": "a15ead5f-2277-4a39-937b-585c2497b2df",
"metadata": {
"id": "a15ead5f-2277-4a39-937b-585c2497b2df"
},
"source": [
"Override generation arguments - no tokens are forced as decoder outputs (see [`forced_decoder_ids`](https://huggingface.co/docs/transformers/main_classes/text_generation#transformers.generation_utils.GenerationMixin.generate.forced_decoder_ids)), no tokens are suppressed during generation (see [`suppress_tokens`](https://huggingface.co/docs/transformers/main_classes/text_generation#transformers.generation_utils.GenerationMixin.generate.suppress_tokens)). Set `use_cache` to False since we're using gradient checkpointing, and the two are incompatible:"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "62038ba3-88ed-4fce-84db-338f50dcd04f",
"metadata": {
"id": "62038ba3-88ed-4fce-84db-338f50dcd04f"
},
"outputs": [],
"source": [
"model.config.forced_decoder_ids = None\n",
"model.config.suppress_tokens = []\n",
"model.config.use_cache = False"
]
},
{
"cell_type": "markdown",
"id": "2178dea4-80ca-47b6-b6ea-ba1915c90c06",
"metadata": {
"id": "2178dea4-80ca-47b6-b6ea-ba1915c90c06"
},
"source": [
"### Define the Training Configuration"
]
},
{
"cell_type": "markdown",
"id": "c21af1e9-0188-4134-ac82-defc7bdcc436",
"metadata": {
"id": "c21af1e9-0188-4134-ac82-defc7bdcc436"
},
"source": [
"In the final step, we define all the parameters related to training. For more detail on the training arguments, refer to the Seq2SeqTrainingArguments [docs](https://huggingface.co/docs/transformers/main_classes/trainer#transformers.Seq2SeqTrainingArguments)."
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "0ae3e9af-97b7-4aa0-ae85-20b23b5bcb3a",
"metadata": {
"id": "0ae3e9af-97b7-4aa0-ae85-20b23b5bcb3a"
},
"outputs": [],
"source": [
"from transformers import Seq2SeqTrainingArguments\n",
"\n",
"training_args = Seq2SeqTrainingArguments(\n",
" output_dir=\"./\",\n",
" per_device_train_batch_size=32,\n",
" gradient_accumulation_steps=1, # increase by 2x for every 2x decrease in batch size\n",
" learning_rate=1e-5,\n",
" warmup_steps=500,\n",
" max_steps=5000,\n",
" gradient_checkpointing=True,\n",
" fp16=True,\n",
" evaluation_strategy=\"steps\",\n",
" per_device_eval_batch_size=16,\n",
" predict_with_generate=True,\n",
" generation_max_length=225,\n",
" save_steps=1000,\n",
" eval_steps=1000,\n",
" logging_steps=25,\n",
" report_to=[\"tensorboard\"],\n",
" load_best_model_at_end=True,\n",
" metric_for_best_model=\"wer\",\n",
" greater_is_better=False,\n",
" push_to_hub=True,\n",
")"
]
},
{
"cell_type": "markdown",
"id": "b3a944d8-3112-4552-82a0-be25988b3857",
"metadata": {
"id": "b3a944d8-3112-4552-82a0-be25988b3857"
},
"source": [
"**Note**: if one does not want to upload the model checkpoints to the Hub, \n",
"set `push_to_hub=False`."
]
},
{
"cell_type": "markdown",
"id": "bac29114-d226-4f54-97cf-8718c9f94e1e",
"metadata": {
"id": "bac29114-d226-4f54-97cf-8718c9f94e1e"
},
"source": [
"We can forward the training arguments to the π€ Trainer along with our model,\n",
"dataset, data collator and `compute_metrics` function:"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "d546d7fe-0543-479a-b708-2ebabec19493",
"metadata": {
"id": "d546d7fe-0543-479a-b708-2ebabec19493"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/ubuntu/whisper-medium-ms/./ is already a clone of https://huggingface.co/Scrya/whisper-medium-ms. Make sure you pull the latest changes with `repo.git_pull()`.\n",
"max_steps is given, it will override any value given in num_train_epochs\n",
"Using cuda_amp half precision backend\n"
]
}
],
"source": [
"from transformers import Seq2SeqTrainer\n",
"\n",
"trainer = Seq2SeqTrainer(\n",
" args=training_args,\n",
" model=model,\n",
" train_dataset=fleurs[\"train\"],\n",
" eval_dataset=fleurs[\"test\"],\n",
" data_collator=data_collator,\n",
" compute_metrics=compute_metrics,\n",
" tokenizer=processor.feature_extractor,\n",
")"
]
},
{
"cell_type": "markdown",
"id": "uOrRhDGtN5S4",
"metadata": {
"id": "uOrRhDGtN5S4"
},
"source": [
"We'll save the processor object once before starting training. Since the processor is not trainable, it won't change over the course of training:"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "-2zQwMfEOBJq",
"metadata": {
"id": "-2zQwMfEOBJq"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Feature extractor saved in ./preprocessor_config.json\n",
"tokenizer config file saved in ./tokenizer_config.json\n",
"Special tokens file saved in ./special_tokens_map.json\n",
"added tokens file saved in ./added_tokens.json\n"
]
}
],
"source": [
"processor.save_pretrained(training_args.output_dir)"
]
},
{
"cell_type": "markdown",
"id": "7f404cf9-4345-468c-8196-4bd101d9bd51",
"metadata": {
"id": "7f404cf9-4345-468c-8196-4bd101d9bd51"
},
"source": [
"### Training"
]
},
{
"cell_type": "markdown",
"id": "5e8b8d56-5a70-4f68-bd2e-f0752d0bd112",
"metadata": {
"id": "5e8b8d56-5a70-4f68-bd2e-f0752d0bd112"
},
"source": [
"Training will take approximately 5-10 hours depending on your GPU. The peak GPU memory for the given training configuration is approximately 36GB. \n",
"Depending on your GPU, it is possible that you will encounter a CUDA `\"out-of-memory\"` error when you launch training. \n",
"In this case, you can reduce the `per_device_train_batch_size` incrementally by factors of 2 \n",
"and employ [`gradient_accumulation_steps`](https://huggingface.co/docs/transformers/main_classes/trainer#transformers.Seq2SeqTrainingArguments.gradient_accumulation_steps)\n",
"to compensate.\n",
"\n",
"To launch training, simply execute:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ee8b7b8e-1c9a-4d77-9137-1778a629e6de",
"metadata": {
"id": "ee8b7b8e-1c9a-4d77-9137-1778a629e6de",
"scrolled": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"The following columns in the training set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message.\n",
"/home/ubuntu/hf_env/lib/python3.8/site-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n",
" warnings.warn(\n",
"***** Running training *****\n",
" Num examples = 2985\n",
" Num Epochs = 54\n",
" Instantaneous batch size per device = 32\n",
" Total train batch size (w. parallel, distributed & accumulation) = 32\n",
" Gradient Accumulation steps = 1\n",
" Total optimization steps = 5000\n",
" Number of trainable parameters = 763857920\n"
]
},
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
"
\n",
" [1028/5000 2:10:54 < 8:26:47, 0.13 it/s, Epoch 10.93/54]\n",
"
\n",
" \n",
" \n",
" \n",
" Step | \n",
" Training Loss | \n",
" Validation Loss | \n",
" Wer | \n",
"
\n",
" \n",
" \n",
" \n",
" 1000 | \n",
" 0.002400 | \n",
" 0.243783 | \n",
" 10.344360 | \n",
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""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message.\n",
"***** Running Evaluation *****\n",
" Num examples = 749\n",
" Batch size = 16\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"/home/ubuntu/hf_env/lib/python3.8/site-packages/transformers/generation/utils.py:1134: UserWarning: You have modified the pretrained model configuration to control generation. This is a deprecated strategy to control generation and will be removed soon, in a future version. Please use a generation configuration file (see https://huggingface.co/docs/transformers/main_classes/text_generation)\n",
" warnings.warn(\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Generate config GenerationConfig {\n",
" \"begin_suppress_tokens\": [\n",
" 220,\n",
" 50257\n",
" ],\n",
" \"bos_token_id\": 50257,\n",
" \"decoder_start_token_id\": 50258,\n",
" \"eos_token_id\": 50257,\n",
" \"max_length\": 448,\n",
" \"pad_token_id\": 50257,\n",
" \"suppress_tokens\": [],\n",
" \"transformers_version\": \"4.26.0.dev0\",\n",
" \"use_cache\": false\n",
"}\n",
"\n",
"Saving model checkpoint to ./checkpoint-1000\n",
"Configuration saved in ./checkpoint-1000/config.json\n",
"Model weights saved in ./checkpoint-1000/pytorch_model.bin\n",
"Feature extractor saved in ./checkpoint-1000/preprocessor_config.json\n",
"Feature extractor saved in ./preprocessor_config.json\n"
]
}
],
"source": [
"trainer.train()"
]
},
{
"cell_type": "markdown",
"id": "810ced54-7187-4a06-b2fe-ba6dcca94dc3",
"metadata": {
"id": "810ced54-7187-4a06-b2fe-ba6dcca94dc3"
},
"source": [
"We can label our checkpoint with the `whisper-event` tag on push by setting the appropriate key-word arguments (kwargs):"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c704f91e-241b-48c9-b8e0-f0da396a9663",
"metadata": {
"id": "c704f91e-241b-48c9-b8e0-f0da396a9663"
},
"outputs": [],
"source": [
"kwargs = {\n",
" \"dataset_tags\": \"google/fleurs\",\n",
" \"dataset\": \"FLEURS\", # a 'pretty' name for the training dataset\n",
" \"language\": \"ms\",\n",
" \"model_name\": \"Whisper Medium MS - FLEURS\", # a 'pretty' name for your model\n",
" \"finetuned_from\": \"openai/whisper-medium\",\n",
" \"tasks\": \"automatic-speech-recognition\",\n",
" \"tags\": \"whisper-event\",\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "090d676a-f944-4297-a938-a40eda0b2b68",
"metadata": {
"id": "090d676a-f944-4297-a938-a40eda0b2b68"
},
"source": [
"The training results can now be uploaded to the Hub. To do so, execute the `push_to_hub` command and save the preprocessor object we created:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d7030622-caf7-4039-939b-6195cdaa2585",
"metadata": {
"id": "d7030622-caf7-4039-939b-6195cdaa2585"
},
"outputs": [],
"source": [
"trainer.push_to_hub(**kwargs)"
]
},
{
"cell_type": "markdown",
"id": "ca743fbd-602c-48d4-ba8d-a2fe60af64ba",
"metadata": {
"id": "ca743fbd-602c-48d4-ba8d-a2fe60af64ba"
},
"source": [
"## Closing Remarks"
]
},
{
"cell_type": "markdown",
"id": "7f737783-2870-4e35-aa11-86a42d7d997a",
"metadata": {
"id": "7f737783-2870-4e35-aa11-86a42d7d997a"
},
"source": [
"In this blog, we covered a step-by-step guide on fine-tuning Whisper for multilingual ASR \n",
"using π€ Datasets, Transformers and the Hugging Face Hub. For more details on the Whisper model, the Common Voice dataset and the theory behind fine-tuning, refere to the accompanying [blog post](https://huggingface.co/blog/fine-tune-whisper). If you're interested in fine-tuning other \n",
"Transformers models, both for English and multilingual ASR, be sure to check out the \n",
"examples scripts at [examples/pytorch/speech-recognition](https://github.com/huggingface/transformers/tree/main/examples/pytorch/speech-recognition)."
]
}
],
"metadata": {
"colab": {
"include_colab_link": true,
"provenance": []
},
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}