{"cells":[{"metadata":{},"cell_type":"markdown","source":"## Reference:\n\n### 1) https://www.kaggle.com/akashravichandran/audiotag-eda\n\n### 2) https://www.kaggle.com/dude431/beginner-s-visualization-and-removing-uniformative\n\n### 3) https://www.kaggle.com/daisukelab/cnn-2d-basic-solution-powered-by-fast-ai"},{"metadata":{},"cell_type":"markdown","source":"## Import libraries"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\nimport os\nprint(os.listdir(\"../input\"))\n\nfrom tqdm import tqdm\nimport wave\nfrom scipy.io import wavfile\nimport seaborn as sns\nimport pandas as pd\nimport matplotlib.pyplot as plt\n%matplotlib inline\n\nimport librosa\nimport librosa.display\n\nfrom pathlib import Path\nfrom tqdm import tqdm_notebook\nimport path\nimport IPython\nfrom sklearn.preprocessing import minmax_scale\nimport warnings\nwarnings.filterwarnings(\"ignore\")\n\nfrom fastai import *\nfrom fastai.vision import *\nfrom fastai.vision.data import *\nimport random\n# Any results you write to the current directory are saved as output.","execution_count":79,"outputs":[{"output_type":"stream","text":"['test', 'train_noisy.csv', 'train_curated.csv', 'train_curated', 'sample_submission.csv', 'train_noisy']\n","name":"stdout"}]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","collapsed":true,"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":false},"cell_type":"markdown","source":"## Exploring the data"},{"metadata":{"trusted":true},"cell_type":"code","source":"noisy_df = pd.read_csv('../input/train_noisy.csv')\ncurated_df = pd.read_csv('../input/train_curated.csv')","execution_count":63,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"noisy_df","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### noisy_df contains all the sound files and the labels present in them."},{"metadata":{"trusted":true},"cell_type":"code","source":"noisy_df.shape","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"curated_df.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"curated_df.shape","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Function to play the .wav file"},{"metadata":{"trusted":true},"cell_type":"code","source":"IPython.display.Audio(\"../input/train_noisy/001f3501.wav\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sample = pd.read_csv('../input/sample_submission.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sample.head()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Distribution of categories"},{"metadata":{"trusted":true},"cell_type":"code","source":"plt.figure(figsize=(15,8))\n\n# Store the 30 highest present labels in the dataframe\naudio_type = curated_df[\"labels\"].value_counts().head(30)\nsns.barplot(audio_type.values, audio_type.index)\nfor i, v in enumerate(audio_type.values):\n    plt.text(0.8,i,v,color='k',fontsize=12)\nplt.xticks(rotation='vertical')\nplt.xlabel('Frequency')\nplt.ylabel('Label Name')\nplt.title(\"Top 30 labels with their frequencies in training data\")\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### We notice that labels Scissor, Gong and 4 more are the most common labels present"},{"metadata":{},"cell_type":"markdown","source":"## Analyze the audio lengths"},{"metadata":{"trusted":true},"cell_type":"code","source":"train_new = curated_df.sort_values('labels').reset_index()\n\n# Calculate the number of frames in an audio file\ntrain_new[\"nframes\"] = train_new[\"fname\"].apply(lambda f: wave.open(\"../input/train_curated/\" + f).getnframes())\n\ntrain_fname = train_new.head(1000)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_new[\"nframes\"].mean()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_new[\"nframes\"].max()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_new[\"nframes\"].min()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"_, ax = plt.subplots(figsize=(16, 4))\nsns.violinplot(ax=ax, x=\"labels\", y=\"nframes\", data=train_fname)\nplt.xticks(rotation=90)\nplt.title('Distribution of audio frames, per label', fontsize=16)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Frame length distribution"},{"metadata":{"trusted":true},"cell_type":"code","source":"path = \"../input/train_curated/\"\nfig, axes = plt.subplots(figsize=(16,5))\ntrain_new.nframes.hist(bins=100)\nplt.suptitle('Frame Length Distribution in Train Curated', ha='center', fontsize='large');","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### Most of the audio files are small and are in the range of 0-5 seconds time interval"},{"metadata":{},"cell_type":"markdown","source":"### Assessing the waveform of the audio files"},{"metadata":{"trusted":true},"cell_type":"code","source":"show_df = curated_df.sort_values('labels')\nlabels = show_df[\"labels\"].unique()\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"show_df.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"labels","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"len(labels)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"TRAIN_PATH = '../input/train_curated/'\ntrain_ids = next(os.walk(TRAIN_PATH))[2]\ntrain_ids[0]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"len(train_ids)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_ids","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"IPython.display.Audio(TRAIN_PATH + train_ids[0])\nIPython.display.Audio(TRAIN_PATH + train_ids[1])\nIPython.display.Audio(TRAIN_PATH + train_ids[2])\nIPython.display.Audio(TRAIN_PATH + train_ids[3])\nIPython.display.Audio(TRAIN_PATH + train_ids[4])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sample_rate, audio = wavfile.read(TRAIN_PATH + \"8a8110c2.wav\")\nplt.plot(audio);","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sample_rate, audio = wavfile.read(TRAIN_PATH + train_ids[1])\nplt.plot(audio);","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sample_rate, audio = wavfile.read(TRAIN_PATH + train_ids[2])\nplt.plot(audio);","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"sample_rate, audio = wavfile.read(TRAIN_PATH + train_ids[3])\nplt.plot(audio);","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### From the above plot of some of the audio files, we can infer that most of the important information is concentrated in a small part of the audio. This gives us the intuition that we need to normalize the audio and remove the other irrelevant part"},{"metadata":{},"cell_type":"markdown","source":"## Normalize the audio files"},{"metadata":{"trusted":true},"cell_type":"code","source":"def normalize_audio(audio):\n    audio = audio / max(np.abs(audio))\n    return audio","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def divide_audio(audio, resolution=100, window_duration=0.1, minimum_power=0.001, sample_rate=44100):\n    duration = len(audio)/sample_rate\n    iterations = int(duration * resolution)\n    step = int(sample_rate / resolution)\n    window_length = np.floor(sample_rate*window_duration)\n    audio_power = np.square(normalize_audio(audio))/ window_length\n    \n    start = np.array([])\n    stop = np.array([])\n    is_started = False\n    \n    for n in range(iterations):\n        power = np.sum(audio_power[n*step : int(n*step+ window_length)])\n        if not is_started and power > minimum_power:\n            start = np.append(start, n*step+window_length/2)\n            is_started = True\n        elif is_started and (power <= minimum_power or n == iterations-1):\n            stop = np.append(stop, n*step+window_length/2)\n            is_started = False\n    \n    if start.size == 0:\n        start = np.append(start, 0)\n        stop = np.append(stop, len(audio))\n        \n    start = start.astype(int)\n    stop = stop.astype(int)\n    return start, stop        ","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"start, stop =  divide_audio(audio)\nprint(start)\nprint(stop)\nplt.plot(audio[start[0]:stop[0]]);","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### According to Daisuke sama, we can convert our audio from the .wav file format to 2D matrix format to ease the processing using Deep Learning. We can convert it to MFCC format that is a good representation of audio data to perform processing on."},{"metadata":{"trusted":true},"cell_type":"code","source":"!mkdir work/\n!mkdir work/image","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"!ls work/image","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"!mkdir work/image/train_noisy","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"!mkdir work/image/train_curated","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"!mkdir work/image/test","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"DATA = Path('../input')\nCSV_TRN_CURATED = DATA/'train_curated.csv'\nCSV_TRN_NOISY = DATA/'train_noisy.csv'\nCSV_SUBMISSION = DATA/'sample_submission.csv'\nTRN_CURATED = DATA/'train_curated'\nTRN_NOISY = DATA/'train_noisy'\nTEST = DATA/'test'\n\nWORK = Path('work')\nIMG_TRN_CURATED = WORK/'image/trn_curated'\nIMG_TRN_NOISY = WORK/'image/train_noisy'\nIMG_TEST = WORK/'image/test'\nfor folder in [WORK, IMG_TRN_CURATED, IMG_TRN_NOISY, IMG_TEST]: \n    Path(folder).mkdir(exist_ok=True, parents=True)\n\ndf = pd.read_csv(CSV_TRN_CURATED)\ntest_df = pd.read_csv(CSV_SUBMISSION)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_df = pd.read_csv('../input/sample_submission.csv')","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Conversion to Mel-spectogram\n\n### [Reference](https://github.com/daisukelab/ml-sound-classifier) \n\n* Handle sampling rate 44.1kHz as is, no information loss.\n* Size of each file will be 128 x L, L is audio seconds x 128; [128, 256] if sound is 2s long.\n* Convert to Mel-spectrogram, not MFCC. We are handling general sound rather than human voice. https://en.wikipedia.org/wiki/Spectrogram"},{"metadata":{},"cell_type":"markdown","source":"### Perform preprocessing of audio signal before conversion to mel-spectogram"},{"metadata":{"trusted":true},"cell_type":"code","source":"def read_audio(conf, pathname, trim_long_data):\n    # Load an audio file as a floating point time series. Audio will be automatically resampled to the given rate.\n    # conf has different preprocessing techniques for audio\n    y, sr = librosa.load(pathname, sr=conf.sampling_rate)\n    \n    # Trim silence\n    if 0 < len(y):\n        y, _ = librosa.effects.trim(y)\n        \n    # Make it shorter than the required length\n    if len(y) > conf.samples:\n        if trim_long_data:\n            y = y[0:0 + conf.samples]\n    else:\n        # Add a blank padding to make all audio signals to one length\n        padding = conf.samples - len(y)\n        offset = padding // 2\n        y = np.pad(y, (offset, conf.samples - len(y) - offset), 'constant')\n    return y","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def audio_to_melspectogram(conf, audio):\n    # hop_length = number of samples between successive frames. \n    # n_fft = length of the Fast Fourier Transform window\n    # fmin = lowest frequency\n    # fmax = highest frequency\n    spectogram = librosa.feature.melspectrogram(audio, sr=conf.sampling_rate, n_mels=conf.n_mels, hop_length=conf.hop_length, n_fft=conf.n_fft, fmin=conf.fmin, fmax=conf.fmax)\n    # Convert a power spectogram to decibel units\n    spectogram = librosa.power_to_db(spectogram)\n    \n    spectogram = spectogram.astype(np.float32)\n    return spectogram","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def show_melspectogram(conf, mels, title=\"Log-frequency power spectogram\"):\n    librosa.display.specshow(mels, x_axis='time', y_axis='mel', sr=conf.sampling_rate, hop_length=conf.hop_length, fmin=conf.fmin, fmax=conf.fmax)\n    plt.colorbar(format='%+2.0f dB')\n    plt.title(title)\n    plt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def read_as_melspectrogram(conf, pathname, trim_long_data, debug_display=False):\n    x = read_audio(conf, pathname, trim_long_data)\n    mels = audio_to_melspectogram(conf, x)\n    if debug_display:\n        IPython.display.display(IPython.display.Audio(x, rate=conf.sampling_rate))\n        show_melspectogram(conf, mels)\n    return mels","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### Preprocessing settings "},{"metadata":{"trusted":true},"cell_type":"code","source":"class conf:\n    # Preprocessing settings\n    sampling_rate = 44100\n    duration = 2\n    hop_length = 347*duration # to make time steps 128\n    fmin = 20\n    fmax = sampling_rate // 2\n    n_mels = 128\n    n_fft = n_mels * 20\n    samples = sampling_rate * duration","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Making 2D mel-spectrogram data as 2D 3ch images\n\n### This helps in improving training"},{"metadata":{"trusted":true},"cell_type":"code","source":"def mono_to_color(X, mean=None, std=None, norm_max=None, norm_min=None, eps=1e-6):\n    \n    # Stack monocoloured X as [X, X, X] for 3-channel conversion\n    X = np.stack([X, X, X], axis=-1)\n    \n    mean = mean or X.mean()\n    std = std or X.std()\n    Xstd = (X - mean) / (std + eps)\n    _min, _max = Xstd.min(), Xstd.max()\n    norm_max = norm_max or _max\n    norm_min = norm_min or _min\n    \n    if (_max - _min) > eps:\n    # Scale to [0, 255]\n        V = Xstd\n        V[V < norm_min] = norm_min\n        V[V > norm_max] = norm_max\n        V = 255 * (V - norm_min) / (norm_max - norm_min)\n        V = V.astype(np.uint8)\n    else:\n        V = np.zeros_like(Xstd, dtype=np.uint8)\n    return V","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def convert_wav_to_image(df, source, img_dest):\n    X = []\n    for i, row in tqdm_notebook(df.iterrows()):\n        x = read_as_melspectrogram(conf, source/str(row.fname), trim_long_data=False)\n        x_color = mono_to_color(x)\n        X.append(x_color)\n    return X","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"X_train = convert_wav_to_image(df, source=TRN_CURATED, img_dest=IMG_TRN_CURATED)\nX_test = convert_wav_to_image(test_df, source=TEST, img_dest=IMG_TEST)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using fastai library to work on images"},{"metadata":{"trusted":true},"cell_type":"code","source":"CUR_X_FILES, CUR_X = list(curated_df.fname.values), X_train","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"CUR_X_FILES","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"### Perform random cropping of 1 second which will work as augmentation."},{"metadata":{"trusted":true},"cell_type":"code","source":"def open_fat2019_image(fn, convert_mode, after_open)->Image:\n    idx = CUR_X_FILES.index(fn.split('/')[-1])\n    x = PIL.Image.fromarray(CUR_X[idx])\n    \n    # Perform a random cropping\n    time_dim, base_dim = x.size\n    crop_x = random.randint(0, time_dim - base_dim)\n    x = x.crop([crop_x, 0, crop_x + base_dim, base_dim])\n    \n    # Standardize\n    return Image(pil2tensor(x, np.float32).div_(255))\n\nvision.data.open_image = open_fat2019_image","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Multi-label classification\n\n### Using: \n\n### [FastAI](https://nbviewer.jupyter.org/github/fastai/course-v3/blob/master/nbs/dl1/lesson3-planet.ipynb)\n\n###        [lwrap metric code](https://colab.research.google.com/drive/1AgPdhSp7ttY18O3fEoHOQKlt_3HJDLi8)"},{"metadata":{"trusted":true},"cell_type":"code","source":"def _one_sample_positive_class_precisions(scores, truth):\n    \"\"\"Calculate precisions for each true class for a single sample.\n\n    Args:\n      scores: np.array of (num_classes,) giving the individual classifier scores.\n      truth: np.array of (num_classes,) bools indicating which classes are true.\n\n    Returns:\n      pos_class_indices: np.array of indices of the true classes for this sample.\n      pos_class_precisions: np.array of precisions corresponding to each of those\n        classes.\n    \"\"\"\n    num_classes = scores.shape[0]\n    pos_class_indices = np.flatnonzero(truth > 0)\n    # Only calculate precisions if there are some true classes.\n    if not len(pos_class_indices):\n        return pos_class_indices, np.zeros(0)\n    # Retrieval list of classes for this sample.\n    retrieved_classes = np.argsort(scores)[::-1]\n    # class_rankings[top_scoring_class_index] == 0 etc.\n    class_rankings = np.zeros(num_classes, dtype=np.int)\n    class_rankings[retrieved_classes] = range(num_classes)\n    # Which of these is a true label?\n    retrieved_class_true = np.zeros(num_classes, dtype=np.bool)\n    retrieved_class_true[class_rankings[pos_class_indices]] = True\n    # Num hits for every truncated retrieval list.\n    retrieved_cumulative_hits = np.cumsum(retrieved_class_true)\n    # Precision of retrieval list truncated at each hit, in order of pos_labels.\n    precision_at_hits = (\n            retrieved_cumulative_hits[class_rankings[pos_class_indices]] /\n            (1 + class_rankings[pos_class_indices].astype(np.float)))\n    return pos_class_indices, precision_at_hits","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# All-in-one calculation of per-class lwlrap.\n\ndef calculate_per_class_lwlrap(truth, scores):\n  \"\"\"Calculate label-weighted label-ranking average precision.\n  \n  Arguments:\n    truth: np.array of (num_samples, num_classes) giving boolean ground-truth\n      of presence of that class in that sample.\n    scores: np.array of (num_samples, num_classes) giving the classifier-under-\n      test's real-valued score for each class for each sample.\n  \n  Returns:\n    per_class_lwlrap: np.array of (num_classes,) giving the lwlrap for each \n      class.\n    weight_per_class: np.array of (num_classes,) giving the prior of each \n      class within the truth labels.  Then the overall unbalanced lwlrap is \n      simply np.sum(per_class_lwlrap * weight_per_class)\n  \"\"\"\n  assert truth.shape == scores.shape\n  num_samples, num_classes = scores.shape\n  # Space to store a distinct precision value for each class on each sample.\n  # Only the classes that are true for each sample will be filled in.\n  precisions_for_samples_by_classes = np.zeros((num_samples, num_classes))\n  for sample_num in range(num_samples):\n    pos_class_indices, precision_at_hits = (\n      _one_sample_positive_class_precisions(scores[sample_num, :], \n                                            truth[sample_num, :]))\n    precisions_for_samples_by_classes[sample_num, pos_class_indices] = (\n        precision_at_hits)\n  labels_per_class = np.sum(truth > 0, axis=0)\n  weight_per_class = labels_per_class / float(np.sum(labels_per_class))\n  # Form average of each column, i.e. all the precisions assigned to labels in\n  # a particular class.\n  per_class_lwlrap = (np.sum(precisions_for_samples_by_classes, axis=0) / \n                      np.maximum(1, labels_per_class))\n  # overall_lwlrap = simple average of all the actual per-class, per-sample precisions\n  #                = np.sum(precisions_for_samples_by_classes) / np.sum(precisions_for_samples_by_classes > 0)\n  #           also = weighted mean of per-class lwlraps, weighted by class label prior across samples\n  #                = np.sum(per_class_lwlrap * weight_per_class)\n  return per_class_lwlrap, weight_per_class","execution_count":64,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Wrapper for fast.ai library\ndef lwlrap(scores, truth, **kwargs):\n    score, weight = calculate_per_class_lwlrap(to_np(truth), to_np(scores))\n    return torch.Tensor([(score * weight).sum()])","execution_count":65,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"tfms = get_transforms(do_flip=True, max_rotate=0, max_lighting=0.1, max_zoom=0, max_warp=0.)\nsrc = (ImageList.from_csv(WORK/'image', Path('../../')/CSV_TRN_CURATED, folder='trn_curated')\n       .split_by_rand_pct(0.2)\n       .label_from_df(label_delim=',')\n)\ndata = (src.transform(tfms, size=128)\n        .databunch(bs=64).normalize(imagenet_stats)\n)","execution_count":66,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data.show_batch(2)","execution_count":67,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 576x576 with 4 Axes>","image/png":"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\n"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"### Use cnn_learner method from fastai.vision library to create a learner object that will be used on the spectograms above. We are trying to find the best learning rate that fits the model here."},{"metadata":{"trusted":true},"cell_type":"code","source":"learn = cnn_learner(data, models.resnet18, pretrained=False, metrics=[lwlrap])\nlearn.unfreeze()\n\nlearn.lr_find();\nlearn.recorder.plot();","execution_count":68,"outputs":[{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":""},"metadata":{}},{"output_type":"stream","text":"LR Finder is complete, type {learner_name}.recorder.plot() to see the graph.\n","name":"stdout"},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"iVBORw0KGgoAAAANSUhEUgAAAYsAAAEKCAYAAADjDHn2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAIABJREFUeJzt3Xl83NV97//XZxbt1mbJm2y8G2NsMCAMCRCgBOKEBELTUNNfbghp4CYNabPctEnza5KSpUl6uUmz3LaQQJayJCFNC9SBUAIJO7YxNth4wzZe8IZkWZYsaUYzn/vHfGUGIWlkW7No9H4+Ht+H57vN93MszXx0zvl+zzF3R0REZCihfAcgIiKFT8lCREQyUrIQEZGMlCxERCQjJQsREclIyUJERDJSshARkYyULEREJCMlCxERySiS7wBGSkNDg8+YMSPfYYiIjCqrVq16zd0bMx1XNMlixowZrFy5Mt9hiIiMKmb2ynCOUzOUiIhkpGQhIiIZKVmIiEhGShYiIpKRkoWIiGSkZCEiIhkpWYiISEZF85zFiYonkhzu7qW9K05HTy815VEax5VSFg0DkEg6e9u72dl6hH3t3cQTTiKZpDfpJJJOrDdJLJEk3uuEQzChuoxJ1WVMqiljfGUJlaURSiMhzOzo+3XGejnc3UtXLEFPb4Ke3iSx3iTl0TC1FVFqK0qoLoscPcfdSTqEjKPbRERyYcwni/2Hu7nwW4/SFU8MuH9cWYTqsij7D6cSxIkIGVSWREi60xkb+HoDnRMyI+FO33TpIYOSSIiScIjykjATxpUxuSa1NFSVknToTSaJJxx3JxoOEQ2HKImEiIYNM3v9fZNOVzxBVyzBkViCWCJBIulBMnTCIaOiJEx5NExZNEx3PEHbkThtXTEOdcWpKo3QUFXK+KoSGqpKqSyNHD2+PBomGgkRDhnRUIhoxKgui1JdHqWyJKyEJzKKjPlkUV0W5QPnnnT0S6y6PEJ5NEJ7V5wDHT0cONzDoa44k2rKmFZXwUn1FUyqKaM0+BLsW/q+vKPhEPFEkn3t3exr72FvezcHO2MciSU4Euulo6cXwxhXFmFcWYSq0gjlJWFKI2FKoyFKwyGOxBK0dcVpOxKj7UicpKe+tEOWWuKJVC2mJ576gt9/uIftLZ08tbWFw929AJhBNBTCjKO1n6GYQUU0TGk0TCRkREJGOGwkEqlkciSWqvmURELUVUSpLS+hujzCq23drN11iJbOWMZrpAuHjPrKEmY1VDJ7QhVzGquY2ViZqo1Vl1FbEVUyESkg5n5ify0XiubmZtdwHxDrTR5NYOlStYVUkvEkJN1JuhMyC5JVKOOXczLp2CBNYMmk09YVp7On9w01lUTS6U0m6U04sUSSw91xDnWllgOHe3j5QCdb9ndwqCv+hvcrCYeorYimknCQiPsSZW9QlqrSCJNryphUU87kmjIax5VSX1lCQ1UJ9ZWl1JRHGVcWIRpW15zIYMxslbs3ZzpuzNcsik1JZOAvxlQCCR/tgzkeodDgySQU1BTqK0uO+X3dndc6YrzS0sm+9p6gVtZN25E4sUTyaH9QX5NaJBwiGjLau3vZ297FC7sP8VpHbND3rygJU12W6oOaWF3KhOoyJgZNdxOD5rtJNWVUl0WPOXaRsULJQvLOzGgcV0rjuNLjfo+e3gQtHTFaO2O81tFDa2eqT6XvpoVDQbPi7rZuntvRRmvnm5NLbUWUk+ormFZfwbS6CqbUljE5qLU01ZaraUzGNCULKQqlkTBTasuZUls+rON7ehPsD/qU9h7q5tW2LnYePMKO1i7Wv9rOb9ftfdMNDeXRMFNqy5hSW8708RUsaqphYVMN8yaOU1OXFD0lCxmTSiPhVA2ivmLA/cmk81pnD3vautlzqIvdbd3saevi1eD1f65+lX97egeQavpb1FTDubPqOXfWeM6aXkdFiT5aUlzUwS1yHJJJ55XWI7yw+xBrd7axasdB1u46RCLpRELGoqk1NE+vo3lGPc3T6xhfdfxNbCLZNNwObiULkRHS2dPLylcO8vTWFlZub2XNzkPEEkkAZjVWcs7MepbMrGfJzPE0DbO5TCTblCxE8qw7nuDF3YdYsf0gK7e38uz21qPPwUytK+fcWeODpZ6pdQM3h4lkm26dFcmzsmg41Qw1ox6YTSLpbNx7mGe3tfDMtlYefmkf96zaBaSSxzkzxx/t9xisL0UkX1SzEMmTZNLZtP8wT73cwjNbW3lmWwsHj6QeTjxlcjXvPm0yly+azIyGyjxHKsVMzVAio0wy6Wze38Fjmw/wmxf3suqVgwAsbKpm2dkncdUZTVSWqjFARpaShcgot7uti9+8sId/f2436/e0U1Ua4X1nNvGBc6czd+K4fIcnRULJQqRIuDvP7WjjZ09tZ/kLe4klksyZUMVlCyZy6YKJnD61dsihWESGomQhUoRe6+jhvjWv8tD6fTyzrZVE0plSU8a1b53BNeecpPGt5JgpWYgUubYjMR7ZuJ9frtzFky+3UFkSZtmSk7juvBm6FVeGTclCZAx5cfchfvjYVu5buweAdy2azPUXzOS0qbV5jkwKnZKFyBj0alsXP35yO3c+s4OOnl6WzKznYxfN5qJ5jRoxVwakZCEyhh3ujvPzFTu5/Ynt7G7r4i2zxvOFy09hYVNNvkOTAjPcZJHVcZXNbKmZbTSzLWb2uQH2n2Rmj5jZajNba2bvStv3+eC8jWb2jmzGKVJsxpVF+cgFs3j0sxfx91ecysZ9h3n39x7nk3evZndbV77Dk1EoazULMwsDm4BLgV3ACuAad1+fdswtwGp3/2czWwAsd/cZweu7gCXAFOC/gXnunhjseqpZiAyuvTvOvzz6Mj96fBvRcIivvPdUrjpjar7DkgJQCDWLJcAWd9/q7jHgbuDKfsc4UB28rgFeDV5fCdzt7j3uvg3YEryfiByH6rIof710Pv/96QuZP2kcn/r5Gv7q7tW0d8cznyxCdpNFE7AzbX1XsC3dl4EPmNkuYDnwiWM4V0SO0bT6Cu6+4Vw+c+k87l+7h3d+57Gjw4qIDCXfc0FeA/zY3acC7wJ+ZmbDjsnMbjCzlWa28sCBA1kLUqSYRMIhPnHJXO756FuIhI1ltzzFL1fuzHyijGnZTBa7gWlp61ODben+HPgFgLs/BZQBDcM8F3e/xd2b3b25sbFxBEMXKX5nnFTHvR8/n3Nmjuez96zla/+1nkSyOO6OlJGXzWSxAphrZjPNrARYBtzb75gdwCUAZnYKqWRxIDhumZmVmtlMYC7wbBZjFRmTaiqi3H7d2Vz7lunc+tg2PvKTFRxWP4YMIGvJwt17gRuBB4GXgF+4+zozu8nMrggO+wxwvZmtIXX304c8ZR2pGsd64AHg40PdCSUixy8aDvH3Vy7kq+9dyB82v8YHfvSsOr7lTfRQnogc9dD6fXzs31Zx2tQafvrn51Cl+TOKXiHcOisio8ylCyby/T87gzW7DnHd7c/S2dOb75CkQChZiMgbLF04me8uO4PndrTx4R+v4EhMCUOULERkAJefNpn/c/XprNjeyqd+/jxJ3SVVsHLVlaBkISIDunJxE1+4fAEPrtvHdx7enO9wZBDX/XgF7/vnJ7N+HfVeicigPnzeDDbsaee7D2/m5InjuPy0yfkOSfrpiiWI5GBaXdUsRGRQZsZXr1rIWdPr+Mwvn+fF3YfyHZL00x1PUF4Szvp1lCxEZEilkTD/8oGzqKso4YafrqSloyffIUmarniC8qiShYgUgMZxpdz6wWYOdPTwrQc25jscSaNkISIFZWFTDde+ZQa/WLVTzVEFpCuWpEzNUCJSSD5xyVxqy6N85f71ObtlU4bWrZqFiBSamvIon77sZJ7Z1sqD6/blO5wxz93VDCUihemas6cxb2IVX1/+Ej29Gt8zn+IJJ5F03Q0lIoUnEg7xd+9ewI7WI/z4ie35DmdM64qnknWZahYiUogumNvIJfMn8L3fbeE13UqbN91BslAzlIgUrM+/6xQ6Y7386PFt+Q5lzOqKBcmiJPtf5UoWInJc5kyo4vJFk/npk9tpOxLLdzhjUpdqFiIyGnz84jl0xhL8+Mnt+Q5lTFKfhYiMCqdMrubtp0zk9ie206GJknKuO6aahYiMEjf+0RwOdcX5t6dfyXcoY87RZijdOisihW7xtFoumNvADx/berTDVXJDfRYiMqrcePEcXuuIcfeKHfkOZUzpS87qsxCRUeGcWeM5e0Yd//r7rcR6k/kOZ8zoVjOUiIw2H71wNnvbu3lk4/58hzJmqBlKREadC+c10lBVwn+s3p3vUMaMrliqFqdmKBEZNSLhEO85fQoPv7SfQ0fi+Q5nTOiKJyiJhAhrDm4RGU2uOqOJWCLJf72wJ9+hjAm5mssClCxEZAQtaqphdmOlmqJypCumZCEio5CZ8cdnTuXZ7a3sbD2S73CKXlc8kZM7oUDJQkRG2BWnTwHgP59X7SLbuuKJnHRug5KFiIywafUVLJlZz7+v3q15urMs1WeRm69xJQsRGXF/fEYTWw90snbXoXyHUtS6YmqGEpFR7J2LJlMSCfFrdXRnVZfuhhKR0aymPMrbT5nAfWtepTeh4T+yRX0WIjLqXb5oCi2dMVbvbMt3KEWru1hunTWzpWa20cy2mNnnBtj/bTN7Plg2mVlb2r5E2r57sxmniIy8C+Y1EAkZv9ugsaKyJZe3zkay9cZmFgZ+AFwK7AJWmNm97r6+7xh3/1Ta8Z8Azkh7iy53X5yt+EQku6rLopw9o55HNuznb5bOz3c4RalY+iyWAFvcfau7x4C7gSuHOP4a4K4sxiMiOfZH8yewYe9hdrd15TuUopNMOt3xZFH0WTQBO9PWdwXb3sTMpgMzgd+lbS4zs5Vm9rSZvXeQ824Ijll54MCBkYpbREbIxfMnAPCImqJGXE8wb8hYu3V2GXCPu6fPyTjd3ZuBPwO+Y2az+5/k7re4e7O7Nzc2NuYqVhEZptmNlZxUX6F+iyzI5VwWkN1ksRuYlrY+Ndg2kGX0a4Jy993Bv1uBR3ljf4aIjAJmxh/Nn8CTL792dFY3GRnFlCxWAHPNbKaZlZBKCG+6q8nM5gN1wFNp2+rMrDR43QCcB6zvf66IFL6L50+gO57kqZdb8h1KUTk6//Zob4Zy917gRuBB4CXgF+6+zsxuMrMr0g5dBtztbxxE5hRgpZmtAR4BvpF+F5WIjB7nzKynPBpWU9QI685xzSJrt84CuPtyYHm/bV/st/7lAc57EliUzdhEJDfKomHOm9PA7zbs5yZ3zLI/q9tYUEzNUCIiAFxyygR2t3WxeX9HvkMpGn3NUOUlGnVWRIrExSenbqFVU9TI6atZFMNzFiIiAEyqKWPB5GolixGU6z4LJQsRyYmL5zey6pWDHO6O5zuUovB6M5SShYgUkfPnNJJIOs9ua813KEVBHdwiUpTOnF5LWTTE41tey3coRUF9FiJSlEojYZbMHM8TShYjojuWwAxKI7obSkSKzPlzxrNpXwf727vzHcqo1zc8ea6eW1GyEJGcOW9OAwBPvKzaxYnK5VwWoGQhIjl0yqRq6itLeGyzksWJ6orlbi4LULIQkRwKhYy3zk71W7xxODg5Vt05nFIVlCxEJMfOn9PAvvYeXj6goT9OhJqhRKSo9fVbPK6mqBPSFVOyEJEiNq2+gunjK3h8i+a3OBFd8UTO5rIAJQsRyYPz5jTw9NYWehPJfIcyanXHE5RHc/cVrmQhIjl3/pwGOnp6WbPrUL5DGbXUZyEiRe8ts8Zjhp7mPgFdMd0NJSJFrq6yhIVTatTJfQK64onCe87CzGabWWnw+iIz+0szq81uaCJSzM6b08DqnQfp7OnNdyijUneBNkP9CkiY2RzgFmAacGfWohKRonf+nAbiCQ1ZfjziiSTxhBdkski6ey9wFfA9d/8sMDl7YYlIsWueUUdJREOWH4+js+QVYJ9F3MyuAa4F7g+2RbMTkoiMBWXRMGfPqFMn93HI9VwWMPxkcR3wFuBr7r7NzGYCP8teWCIyFpw/p5ENew+z/7CGLD8W3bHU8ykF1wzl7uvd/S/d/S4zqwPGufs3sxybiBS584OhP57U09zHpKtQm6HM7FEzqzazeuA54FYz+z/ZDU1Eit2CKdXUVkTVb3GMcj3/Ngy/GarG3duBPwZ+6u7nAG/PXlgiMhaEgyHLH9+sIcuPRVescPssImY2Gbia1zu4RURO2PlzGtnb3s3LBzrzHcqoUch3Q90EPAi87O4rzGwWsDl7YYnIWNHXb6G7ooavYJuh3P2X7n6au38sWN/q7u/LbmgiMhacNL6CafXlmmr1GPQ1QxVcsjCzqWb2azPbHyy/MrOp2Q5ORMaG8+c0asjyY3D0OYuSwhui/HbgXmBKsNwXbBMROWEasvzYdBdqMxTQ6O63u3tvsPwYaMxiXCIyhrxldmrIco1COzyFfDdUi5l9wMzCwfIBQE/RiMiIqK8s4dQp1Ty2+UC+QxkVuuIJomEjGi68ZqgPk7ptdi+wB/gT4ENZiklExqAL5zWyemcbh7ri+Q6l4OV6LgsY/t1Qr7j7Fe7e6O4T3P29QMa7ocxsqZltNLMtZva5AfZ/28yeD5ZNZtaWtu9aM9scLNceU6lEZNS56OQJJJKuW2iHIddzWcCJzZT36aF2mlkY+AHwTmABcI2ZLUg/xt0/5e6L3X0x8D3g34Nz64EvAecAS4AvBWNSiUiROmNaLePKIjy6cX++Qyl4uZ5SFU4sWViG/UuALcEzGTHgbuDKIY6/BrgreP0O4CF3b3X3g8BDwNITiFVEClwkHOKCuQ38ftMBDf2RQdcoq1lk+mk2ATvT1ncF297EzKYDM4HfHcu5ZnaDma00s5UHDqhjTGS0u2jeBPa19/DSnsP5DqWgdcWThdVnYWaHzax9gOUwqectRsoy4B53TxzLSe5+i7s3u3tzY6Pu5BUZ7S48OfU5/v0m/fE3lO5YgdUs3H2cu1cPsIxz90iG995Naq7uPlODbQNZxutNUMd6rogUiYnVZZwyuVr9Fhl0xUdXn0UmK4C5ZjbTzEpIJYR7+x9kZvOBOuCptM0PApeZWV3QsX1ZsE1EitxFJzey6pWDHO7WLbSDGW19FkNy917gRlJf8i8Bv3D3dWZ2k5ldkXboMuBuT+vRcvdW4CukEs4K4KZgm4gUuQvnNdKrW2iH1BXL/XMWmZqSToi7LweW99v2xX7rXx7k3NuA27IWnIgUpLOm1zGuNMLvNx1g6cLJ+Q6nIHXHE5TncBBByG4zlIjIMYuGQ5w3p4FHN+oW2sEUVTOUiMjxuujkRvYc6mbTvo58h1Jw3F3JQkQEXr+FVndFvVlPbxJ3KCuiu6FERI7L5Jpy5k8ax8MblCz6y8dcFqBkISIF6rIFE1m5vZWWjp58h1JQ8jH/NihZiEiBuuzUSSQd1S76OTr/tpqhRETg1CnVNNWW89t1e/MdSkE5Ov+2ahYiImBmXLpgIn/Y/BqdPb35DqdgqM9CRKSfd5w6iVhvUtOtpumKJQE1Q4mIHHX2jDpqK6I8uG5fvkMpGOrgFhHpJxIOccn8iTz80j7iiWS+wykI6rMQERnAZadOpL27l2e3aSxRSM1lAWqGEhF5g7fNbaQsGuJB3RUFqBlKRGRA5SVh3ja3kd+u26eBBVGyEBEZ1GWnTmJvezcv7D6U71Dyru+hvNKIhigXEXmDS+ZPIBwyHnhRTVHd8QRl0RChkOX0ukoWIlLw6ipLeOvs8dy/ds+Yb4rKx/DkoGQhIqPEe06fwo7WI6zdNbabojp7lCxERAb1jlMnEQ0b9615Nd+h5FXbkRi1FSU5v66ShYiMCjXlUS6cN4H71+4hmRy7TVGtR2KMr1KyEBEZ1HtOn8ze9m5WbB+7D+i1dsaor1SyEBEZ1KULJlIeDXPf2rHbFNXaEaNOzVAiIoOrKIlwySkTWP7CXnrH4FhRsd4kh3t6Ga+ahYjI0N5z+hRaO2M8+XJLvkPJuYNHYkDqVuJcU7IQkVHlwnmNjCuNjMm7olo6UslCNQsRkQzKomEuO3USD6zbS09vIt/h5FRfzUId3CIiw3DF4ikc7u7l9xvH1gx6LZ1KFiIiw/bW2eNpqCrlnlW78h1KTh1UshARGb5oOMT7zmri4Q372d/ene9wcqalM4YZeoJbRGS4lp19Eomkc89zY6d20drZQ215lHCOR5wFJQsRGaVmNlRyzsx6fr5i55gZifZgZzwvTVCgZCEio9iyJdN4peUIT28dG8N/tHT2KFmIiByrdy6czLiyCD9fsSPfoeREvsaFgiwnCzNbamYbzWyLmX1ukGOuNrP1ZrbOzO5M254ws+eD5d5sxikio1NZNMxVZzSx/MW9HDoSz3c4WdfaGae+sjQv185asjCzMPAD4J3AAuAaM1vQ75i5wOeB89z9VOCTabu73H1xsFyRrThFZHT707OnEetN8h/P7853KFmVTDoHj8Sor4zm5frZrFksAba4+1Z3jwF3A1f2O+Z64AfufhDA3fdnMR4RKUKnTqlhUVMNdz27o6g7ug9395JIevHVLIAmYGfa+q5gW7p5wDwze8LMnjazpWn7ysxsZbD9vVmMU0RGuT89exob9h5mTRFPudrS2QNQlDWL4YgAc4GLgGuAW82sNtg33d2bgT8DvmNms/ufbGY3BAll5YEDY+uxfxF53ZWLp1BVGuH2J7blO5SsaT369Hbx1Sx2A9PS1qcG29LtAu5197i7bwM2kUoeuPvu4N+twKPAGf0v4O63uHuzuzc3NjaOfAlEZFQYVxZl2dnTuH/tHna3deU7nKzoSxb5GHEWspssVgBzzWymmZUAy4D+dzX9B6laBWbWQKpZaquZ1ZlZadr284D1WYxVREa5686fCcCPi7R20Zcs8jGXBWQxWbh7L3Aj8CDwEvALd19nZjeZWd/dTQ8CLWa2HngE+Ky7twCnACvNbE2w/RvurmQhIoNqqi3n8kWTuevZnbR3F99ttK1H8luziGTzzd19ObC837Yvpr124NPBkn7Mk8CibMYmIsXn+gtmce+aV/n5szu5/m2z8h3OiGrtiFFREqYsGs7L9fPdwS0iMmIWTa3h3Fn13PbENuJFNkd3a2eMujyMNttHyUJEisoNb5vFnkPd/NfaPfkOZUS1HokxvkrJQkRkRFw0bwKzGyu59bGtRfWQnmoWIiIjKBQyrr9gFutebefRTcXz/FVLRyxvndugZCEiReiqM5s4qb6CbyzfQCJZHLWL1LhQShYiIiOmNBLmc++cz8Z9h/nlyp2ZTyhw3fEER2KJvD1jAUoWIlKk3rlwEmdNr+PmhzbR2dOb73BOSL6f3gYlCxEpUmbGFy4/hQOHe/jX37+c73BOSL6f3gYlCxEpYmeeVMe7T5vMLY9tZc+h0TtmVItqFiIi2fU3S+eTTMLNv92U71CO28GjI84qWYiIZMW0+gquO28Gv3puF09ueS3f4RyXFiULEZHs+8tL5jK7sYob71rNq6NwCPPWzh7CIaO6LD8TH4GShYiMAZWlEf71f5xFrDfJx+54jp7eRL5DOiatnXHqKkoIhSxvMShZiMiYMLuxiv/9/tNZs7ONL987umY8aO3sydt0qn2ULERkzFi6cBJ/cdFs7np2Bz9fsSPf4Qzbwc54XvsrQMlCRMaYz1x2MhfMbeDv/mMdj2zcn+9whqWls0fJQkQkl8Ih4/vXnMnciVX8z5+t4tFRkDBaO/M7LhQoWYjIGFRTEeWOj5zD3AlV3PCzVfy+gEenTSSdtq449ZWleY1DyUJExqTaihLu+Mg5zGms4vqfrizYhNF2JIY71Feog1tEJC/ekDB+spIHXiy82fX6xoWqr1LNQkQkb+oqS7jz+nNY2FTNX9zxHHc+U1h3SRXCiLOgZCEiEtQwzuXCeY387a9f4HsPby6YKVmPjjibxylVQclCRASA8pIwt3ywmavOaOLmhzZx0/3rCyJhtB4JahZV+U0WkbxeXUSkgETDIW5+/+nUVkS5/YnthMz4/y8/BbP8DbPR0pFKFrV57uBWshARSRMKGV989wLc4UePb6MkEuKv33FyXhKGu/PAi3s5eeI4SiPhnF8/nZKFiEg/ZsaX3rOAWCLJPz/6MqWREJ98+7ycx/HU1hbW72nnm+9blPNr96dkISIyADPjq1cuJNab5Dv/vZloOMTHL56T0xh+9Ng2xleWcOXippxedyBKFiIigwiFjG++7zTiiST/+OBGwiHjoxfOzsm1Xz7QwcMb9vPJt8+lLJrfJihQshARGVI4ZNz8/tNJOnzjNxsw4H/mIGHcFvSXfODc6Vm/1nAoWYiIZBAJh/j21afj7vzDbzYQMuP6t83K2vVaO2P86rld/PEZTTTk+cntPkoWIiLDEAmH+M6fLsaBry1/id6k89ELZ2XlLqk7n3mF7niSD58/c8Tf+3gpWYiIDFMkHOKf/nQxITO++cAG9h/u5u8uXzCi05329Cb4yVOvcOG8RuZNHDdi73uilCxERI5BX8JorCrltie2sb+9h5uvPn3EOqH/c/WrHDjcw0euLpxaBShZiIgcs1DI+OJ7FjCltoyv/tdLHOjo4dYPNlNTfmJPWXfHE/zTw5s5bWoN589pGKFoR0ZWx4Yys6VmttHMtpjZ5wY55mozW29m68zszrTt15rZ5mC5Nptxiogcj49cMIvvXnMGq3cc5MY7nyOZPLGxpO54Zge727r4m6Xz8zrEyECyVrMwszDwA+BSYBewwszudff1acfMBT4PnOfuB81sQrC9HvgS0Aw4sCo492C24hUROR5XnD6Fju5e/vbXL3DbE9v4yAXHd5fU4e44P3hkCxfMbeC8AqtVQHZrFkuALe6+1d1jwN3Alf2OuR74QV8ScPe+yXDfATzk7q3BvoeApVmMVUTkuF2zZBqXLpjItx7YyLpXD71p/7727owj2N762DZaO2N89h0nZyvME5LNZNEE7Exb3xVsSzcPmGdmT5jZ02a29BjOFREpCGapJ71rK6L81d3P0xVLANDS0cOnf/E853z9YW68czXd8cSA57/W0cMPH9vK5Ysmc9rU2lyGPmz57uCOAHOBi4CpwB/MbNgjZpnZDcANACeddFI24hMRGZbVBKHZAAAKAUlEQVT6yhJuvvp0/sePnuVry9ezcEoN//CbDRyJ9fKuRZNY/uIeXj3Uxa0fbH7Tg3bf/90WenqTfPqy3A9WOFzZTBa7gWlp61ODbel2Ac+4exzYZmabSCWP3aQSSPq5j/a/gLvfAtwC0NzcnP9ZSkRkTLtgbiPXXzCTWx/bBsCSmfV8/aqFzJkwjgde3Msnf76aq/7vE9z+obOZUF3Gi7sO8fyuNu545hWubp7K7MaqPJdgcJatmaDMLAJsAi4h9eW/Avgzd1+XdsxS4Bp3v9bMGoDVwGKCTm3gzODQ54Cz3L11sOs1Nzf7ypUrs1IWEZHh6ulNcNN961k8rZY/OWvqG+5qen5nGx/5yQrau3qJJZJHt8+fNI6ffHgJE6vLch6vma1y9+ZMx2WtZuHuvWZ2I/AgEAZuc/d1ZnYTsNLd7w32XWZm64EE8Fl3bwkK8BVSCQbgpqEShYhIoSiNhPnaVQO3pi+eVsuv/+I8bvnDViZWl7Joai2nNdVQV5nfKVOHI2s1i1xTzUJE5NgNt2aR1YfyRESkOChZiIhIRkoWIiKSkZKFiIhkpGQhIiIZKVmIiEhGShYiIpKRkoWIiGRUNA/lmdkB4JUBdtUA/ccM7r8tfX2g133/NgCvHWeIA8Ux3GMylWGw8gx0TDbLMNT+of7P+69nep2PMozE71H66+MtQzZ/j/qvD/VZgMIsw3DKU2if5+GuZ+uzMN3dGzMe7e5FvQC3ZNqWvj7Q67R/V45kHMM9JlMZBivPIGXJWhmG2j/U//lwfgb5LsNI/B6NRBmy+Xs0zLjTtxVcGYZTnkL7PA93Pdefhf7LWGiGum8Y2+7L8Hqg9xiJOIZ7TKYyDFaeoY45HpneY6j9Q/2f918fzuvjdbxlGInfo+FcP5Ns/h71Xy+mz0L660Irw3DXc/1ZeIOiaYbKBTNb6cMYQ6WQqQyFQWXIv9EeP+S2DGOhZjGSbsl3ACNAZSgMKkP+jfb4IYdlUM1CREQyUs1CREQyGrPJwsxuM7P9ZvbicZx7lpm9YGZbzOy7ljYVlpl9wsw2mNk6M/vWyEb9pjhGvAxm9mUz221mzwfLu0Y+8jfEkZWfQ7D/M2bmwSyMWZOln8NXzGxt8DP4rZlNGfnIj8aQjfj/MfgcrDWzX5tZ7chH/oY4slGG9wef46SZZa1f4ERiH+T9rjWzzcFybdr2IT8vGR3vbVejfQHeRmra1heP49xngXMBA34DvDPYfjHw30BpsD5hFJbhy8D/Gs0/h2DfNFIzMb4CNIy2MgDVacf8JfAvoyz+y4BI8PqbwDdH4c/gFOBk4FGgudBiD+Ka0W9bPbA1+LcueF03VDmHu4zZmoW7/wF4w1StZjbbzB4ws1Vm9piZze9/nplNJvVBftpTP4GfAu8Ndn8M+Ia79wTX2D8Ky5BTWSzDt4G/JjWfe1Zlowzu3p52aCVZLEeW4v+tu/cGhz4NTM1W/Fksw0vuvjGbcZ9I7IN4B/CQu7e6+0HgIWDpSHzmx2yyGMQtwCfc/SzgfwH/d4BjmoBdaeu7gm0A84ALzOwZM/u9mZ2d1WgHdqJlALgxaD64zczqshfqoE6oDGZ2JbDb3ddkO9AhnPDPwcy+ZmY7gf8P+GIWYx3ISPwe9fkwqb9kc20ky5Brw4l9IE3AzrT1vvKccDkjx3JwMTOzKuCtwC/TmvJKj/FtIqSqf+cCZwO/MLNZQSbPuhEqwz8DXyH1l+xXgJtJfdhz4kTLYGYVwN+SagbJixH6OeDuXwC+YGafB24EvjRiQQ5hpOIP3usLQC9wx8hEN+zrjlgZcm2o2M3sOuCvgm1zgOVmFgO2uftV2YxLyeJ1IaDN3RenbzSzMLAqWL2X1JdpepV6KrA7eL0L+PcgOTxrZklSY7ccyGbgaU64DO6+L+28W4H7sxnwAE60DLOBmcCa4IM2FXjOzJa4+94sx95nJH6X0t0BLCdHyYIRit/MPgS8G7gkV38wpRnpn0EuDRg7gLvfDtwOYGaPAh9y9+1ph+wGLkpbn0qqb2M3J1rObHXajIYFmEFapxLwJPD+4LUBpw9yXv+OoncF2z8K3BS8nkeqOmijrAyT0475FHD3aPs59DtmO1nu4M7Sz2Fu2jGfAO4ZZfEvBdYDjdn+v8/27xFZ7uA+3tgZvIN7G6nO7brgdf1wypkxxlz9IAttAe4C9gBxUjWCPyf1F+kDwJrgF/2Lg5zbDLwIvAx8n9cfbiwB/i3Y9xzwR6OwDD8DXgDWkvrLa/JoK0O/Y7aT/buhsvFz+FWwfS2pMXyaRln8W0j9sfR8sGTtbq4sluGq4L16gH3Ag4UUOwMki2D7h4P//y3AdcfyeRlq0RPcIiKSke6GEhGRjJQsREQkIyULERHJSMlCREQyUrIQEZGMlCykqJlZR46v90MzWzBC75Ww1KizL5rZfZlGbjWzWjP7i5G4tkh/unVWipqZdbh71Qi+X8RfHyAvq9JjN7OfAJvc/WtDHD8DuN/dF+YiPhlbVLOQMcfMGs3sV2a2IljOC7YvMbOnzGy1mT1pZicH2z9kZvea2e+Ah83sIjN71MzusdScDXf0zQ0QbG8OXncEgwGuMbOnzWxisH12sP6CmX11mLWfp3h9oMQqM3vYzJ4L3uPK4JhvALOD2sg/Bsd+NijjWjP7+xH8b5QxRslCxqJ/Ar7t7mcD7wN+GGzfAFzg7meQGuX162nnnAn8ibtfGKyfAXwSWADMAs4b4DqVwNPufjrwB+D6tOv/k7sv4o0jgQ4oGM/oElJP1AN0A1e5+5mk5lC5OUhWnwNedvfF7v5ZM7sMmAssARYDZ5nZ2zJdT2QgGkhQxqK3AwvSRvSsDkb6rAF+YmZzSY26G0075yF3T59z4Fl33wVgZs+TGtvn8X7XifH6QIyrgEuD12/h9bkE7gT+9yBxlgfv3QS8RGpuAkiN7fP14Is/GeyfOMD5lwXL6mC9ilTy+MMg1xMZlJKFjEUh4Fx3707faGbfBx5x96uC9v9H03Z39nuPnrTXCQb+LMX99U7BwY4ZSpe7Lw6GXX8Q+DjwXVLzWzQCZ7l73My2A2UDnG/AP7j7vx7jdUXeRM1QMhb9ltRIrgCYWd9Q0DW8Pmzzh7J4/adJNX8BLMt0sLsfITW16mfMLEIqzv1BorgYmB4cehgYl3bqg8CHg1oTZtZkZhNGqAwyxihZSLGrMLNdacunSX3xNgedvutJDS0P8C3gH8xsNdmtdX8S+LSZrSU1gc2hTCe4+2pSI9BeQ2p+i2YzewH4IKm+Fty9BXgiuNX2H939t6SauZ4Kjr2HNyYTkWHTrbMiORY0K3W5u5vZMuAad78y03ki+aQ+C5HcOwv4fnAHUxs5nLZW5HipZiEiIhmpz0JERDJSshARkYyULEREJCMlCxERyUjJQkREMlKyEBGRjP4fegl+p6N7avYAAAAASUVORK5CYII=\n"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"### We check for different values for learning rate, the most plausible value that helps in model fitting"},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.fit_one_cycle(5, 1e-1)\nlearn.fit_one_cycle(10, 1e-2)","execution_count":69,"outputs":[{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: left;\">\n      <th>epoch</th>\n      <th>train_loss</th>\n      <th>valid_loss</th>\n      <th>lwlrap</th>\n      <th>time</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <td>0</td>\n      <td>0.201582</td>\n      <td>0.081113</td>\n      <td>0.095991</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>1</td>\n      <td>0.108429</td>\n      <td>0.083185</td>\n      <td>0.130152</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>2</td>\n      <td>0.085876</td>\n      <td>0.073305</td>\n      <td>0.164370</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>3</td>\n      <td>0.074956</td>\n      <td>0.067097</td>\n      <td>0.206753</td>\n      <td>00:07</td>\n    </tr>\n    <tr>\n      <td>4</td>\n      <td>0.068081</td>\n      <td>0.062653</td>\n      <td>0.286865</td>\n      <td>00:06</td>\n    </tr>\n  </tbody>\n</table>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: left;\">\n      <th>epoch</th>\n      <th>train_loss</th>\n      <th>valid_loss</th>\n      <th>lwlrap</th>\n      <th>time</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <td>0</td>\n      <td>0.063640</td>\n      <td>0.062158</td>\n      <td>0.307880</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>1</td>\n      <td>0.063535</td>\n      <td>0.063192</td>\n      <td>0.286583</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>2</td>\n      <td>0.063523</td>\n      <td>0.061708</td>\n      <td>0.298675</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>3</td>\n      <td>0.062919</td>\n      <td>0.061523</td>\n      <td>0.304185</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>4</td>\n      <td>0.061199</td>\n      <td>0.060133</td>\n      <td>0.335900</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>5</td>\n      <td>0.059085</td>\n      <td>0.056732</td>\n      <td>0.367521</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>6</td>\n      <td>0.056874</td>\n      <td>0.057343</td>\n      <td>0.378845</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>7</td>\n      <td>0.055202</td>\n      <td>0.075317</td>\n      <td>0.444712</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>8</td>\n      <td>0.053723</td>\n      <td>0.056097</td>\n      <td>0.457561</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>9</td>\n      <td>0.052419</td>\n      <td>0.051366</td>\n      <td>0.470008</td>\n      <td>00:05</td>\n    </tr>\n  </tbody>\n</table>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"### We can observe that with more epochs, the train_loss decreases and the lwlrap increases. We will test for different ranges of values to find which set of values are the most suitable in fitting the CNN."},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.lr_find(); learn.recorder.plot()","execution_count":70,"outputs":[{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":""},"metadata":{}},{"output_type":"stream","text":"LR Finder is complete, type {learner_name}.recorder.plot() to see the graph.\n","name":"stdout"},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.fit_one_cycle(20, 3e-3)","execution_count":71,"outputs":[{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: left;\">\n      <th>epoch</th>\n      <th>train_loss</th>\n      <th>valid_loss</th>\n      <th>lwlrap</th>\n      <th>time</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <td>0</td>\n      <td>0.051873</td>\n      <td>0.050972</td>\n      <td>0.474893</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>1</td>\n      <td>0.051627</td>\n      <td>0.051145</td>\n      <td>0.463718</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>2</td>\n      <td>0.050993</td>\n      <td>0.052181</td>\n      <td>0.445176</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>3</td>\n      <td>0.051010</td>\n      <td>0.100620</td>\n      <td>0.456688</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>4</td>\n      <td>0.050657</td>\n      <td>0.050571</td>\n      <td>0.464714</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>5</td>\n      <td>0.050080</td>\n      <td>0.062263</td>\n      <td>0.454669</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>6</td>\n      <td>0.049101</td>\n      <td>0.048809</td>\n      <td>0.497651</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>7</td>\n      <td>0.047899</td>\n      <td>0.108080</td>\n      <td>0.501707</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>8</td>\n      <td>0.047142</td>\n      <td>0.045166</td>\n      <td>0.552453</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>9</td>\n      <td>0.045796</td>\n      <td>0.074573</td>\n      <td>0.544577</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>10</td>\n      <td>0.043998</td>\n      <td>0.044443</td>\n      <td>0.565180</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>11</td>\n      <td>0.042659</td>\n      <td>0.042520</td>\n      <td>0.590335</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>12</td>\n      <td>0.041343</td>\n      <td>0.044903</td>\n      <td>0.604797</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>13</td>\n      <td>0.040180</td>\n      <td>0.041084</td>\n      <td>0.596881</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>14</td>\n      <td>0.038293</td>\n      <td>0.040429</td>\n      <td>0.614679</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>15</td>\n      <td>0.037505</td>\n      <td>0.039428</td>\n      <td>0.628134</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>16</td>\n      <td>0.036542</td>\n      <td>0.038696</td>\n      <td>0.637064</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>17</td>\n      <td>0.035908</td>\n      <td>0.042047</td>\n      <td>0.625560</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>18</td>\n      <td>0.035589</td>\n      <td>0.039224</td>\n      <td>0.633307</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>19</td>\n      <td>0.035517</td>\n      <td>0.040182</td>\n      <td>0.629453</td>\n      <td>00:05</td>\n    </tr>\n  </tbody>\n</table>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.lr_find(); learn.recorder.plot()","execution_count":72,"outputs":[{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":""},"metadata":{}},{"output_type":"stream","text":"LR Finder is complete, type {learner_name}.recorder.plot() to see the graph.\n","name":"stdout"},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 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\n"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.fit_one_cycle(20, 1e-3)","execution_count":73,"outputs":[{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: left;\">\n      <th>epoch</th>\n      <th>train_loss</th>\n      <th>valid_loss</th>\n      <th>lwlrap</th>\n      <th>time</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <td>0</td>\n      <td>0.035530</td>\n      <td>0.039726</td>\n      <td>0.642899</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>1</td>\n      <td>0.035078</td>\n      <td>0.039200</td>\n      <td>0.639756</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>2</td>\n      <td>0.034994</td>\n      <td>0.039246</td>\n      <td>0.636912</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>3</td>\n      <td>0.035439</td>\n      <td>0.039502</td>\n      <td>0.636931</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>4</td>\n      <td>0.035133</td>\n      <td>0.039666</td>\n      <td>0.634491</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>5</td>\n      <td>0.035131</td>\n      <td>0.039829</td>\n      <td>0.634816</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>6</td>\n      <td>0.034575</td>\n      <td>0.039982</td>\n      <td>0.632692</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>7</td>\n      <td>0.033924</td>\n      <td>0.045757</td>\n      <td>0.620884</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>8</td>\n      <td>0.033420</td>\n      <td>0.038445</td>\n      <td>0.644875</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>9</td>\n      <td>0.033393</td>\n      <td>0.039132</td>\n      <td>0.645004</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>10</td>\n      <td>0.032529</td>\n      <td>0.054534</td>\n      <td>0.645029</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>11</td>\n      <td>0.031645</td>\n      <td>0.047677</td>\n      <td>0.649244</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>12</td>\n      <td>0.031282</td>\n      <td>0.042128</td>\n      <td>0.654376</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>13</td>\n      <td>0.030353</td>\n      <td>0.035985</td>\n      <td>0.668461</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>14</td>\n      <td>0.030018</td>\n      <td>0.045135</td>\n      <td>0.663740</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>15</td>\n      <td>0.029580</td>\n      <td>0.036914</td>\n      <td>0.669859</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>16</td>\n      <td>0.029287</td>\n      <td>0.040584</td>\n      <td>0.663737</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>17</td>\n      <td>0.028808</td>\n      <td>0.035643</td>\n      <td>0.675787</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>18</td>\n      <td>0.028744</td>\n      <td>0.049977</td>\n      <td>0.671082</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>19</td>\n      <td>0.029068</td>\n      <td>0.038664</td>\n      <td>0.678306</td>\n      <td>00:06</td>\n    </tr>\n  </tbody>\n</table>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.lr_find(); learn.recorder.plot()","execution_count":74,"outputs":[{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":""},"metadata":{}},{"output_type":"stream","text":"LR Finder is complete, type {learner_name}.recorder.plot() to see the graph.\n","name":"stdout"},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 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\n"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.fit_one_cycle(50, slice(1e-3, 3e-3))","execution_count":75,"outputs":[{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: left;\">\n      <th>epoch</th>\n      <th>train_loss</th>\n      <th>valid_loss</th>\n      <th>lwlrap</th>\n      <th>time</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <td>0</td>\n      <td>0.028287</td>\n      <td>0.036092</td>\n      <td>0.689257</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>1</td>\n      <td>0.028539</td>\n      <td>0.035683</td>\n      <td>0.673221</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>2</td>\n      <td>0.028495</td>\n      <td>0.036044</td>\n      <td>0.676667</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>3</td>\n      <td>0.028339</td>\n      <td>0.037222</td>\n      <td>0.676526</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>4</td>\n      <td>0.028428</td>\n      <td>0.035822</td>\n      <td>0.672935</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>5</td>\n      <td>0.028256</td>\n      <td>0.036362</td>\n      <td>0.679709</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>6</td>\n      <td>0.028572</td>\n      <td>0.037216</td>\n      <td>0.681607</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>7</td>\n      <td>0.028688</td>\n      <td>0.055815</td>\n      <td>0.662765</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>8</td>\n      <td>0.028332</td>\n      <td>0.037204</td>\n      <td>0.658666</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>9</td>\n      <td>0.028616</td>\n      <td>0.038504</td>\n      <td>0.669101</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>10</td>\n      <td>0.028397</td>\n      <td>0.037542</td>\n      <td>0.670058</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>11</td>\n      <td>0.027808</td>\n      <td>0.035922</td>\n      <td>0.677306</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>12</td>\n      <td>0.027813</td>\n      <td>0.040944</td>\n      <td>0.654413</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>13</td>\n      <td>0.027899</td>\n      <td>0.038768</td>\n      <td>0.658314</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>14</td>\n      <td>0.026837</td>\n      <td>0.037989</td>\n      <td>0.661774</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>15</td>\n      <td>0.026542</td>\n      <td>0.037120</td>\n      <td>0.669658</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>16</td>\n      <td>0.027049</td>\n      <td>0.057516</td>\n      <td>0.679422</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>17</td>\n      <td>0.025865</td>\n      <td>0.037199</td>\n      <td>0.676295</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>18</td>\n      <td>0.024800</td>\n      <td>0.036588</td>\n      <td>0.687230</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>19</td>\n      <td>0.024383</td>\n      <td>0.038680</td>\n      <td>0.680638</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>20</td>\n      <td>0.023351</td>\n      <td>0.038827</td>\n      <td>0.669730</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>21</td>\n      <td>0.023475</td>\n      <td>0.179776</td>\n      <td>0.686961</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>22</td>\n      <td>0.022229</td>\n      <td>0.036673</td>\n      <td>0.684352</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>23</td>\n      <td>0.021407</td>\n      <td>0.037124</td>\n      <td>0.681272</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>24</td>\n      <td>0.021117</td>\n      <td>0.051110</td>\n      <td>0.698674</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>25</td>\n      <td>0.020658</td>\n      <td>0.035810</td>\n      <td>0.697423</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>26</td>\n      <td>0.019858</td>\n      <td>0.034987</td>\n      <td>0.713379</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>27</td>\n      <td>0.019296</td>\n      <td>0.041382</td>\n      <td>0.699095</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>28</td>\n      <td>0.018568</td>\n      <td>0.035491</td>\n      <td>0.717657</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>29</td>\n      <td>0.018282</td>\n      <td>0.036351</td>\n      <td>0.709056</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>30</td>\n      <td>0.017688</td>\n      <td>0.039208</td>\n      <td>0.687023</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>31</td>\n      <td>0.017092</td>\n      <td>0.038122</td>\n      <td>0.713196</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>32</td>\n      <td>0.016740</td>\n      <td>0.037993</td>\n      <td>0.700593</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>33</td>\n      <td>0.015858</td>\n      <td>0.036950</td>\n      <td>0.713441</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>34</td>\n      <td>0.015618</td>\n      <td>0.037040</td>\n      <td>0.710688</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>35</td>\n      <td>0.014948</td>\n      <td>0.035844</td>\n      <td>0.733552</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>36</td>\n      <td>0.014603</td>\n      <td>0.051018</td>\n      <td>0.714475</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>37</td>\n      <td>0.013971</td>\n      <td>0.036487</td>\n      <td>0.717295</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>38</td>\n      <td>0.013449</td>\n      <td>0.037938</td>\n      <td>0.712229</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>39</td>\n      <td>0.013522</td>\n      <td>0.038381</td>\n      <td>0.717509</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>40</td>\n      <td>0.013112</td>\n      <td>0.036391</td>\n      <td>0.719115</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>41</td>\n      <td>0.012555</td>\n      <td>0.036444</td>\n      <td>0.722084</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>42</td>\n      <td>0.012485</td>\n      <td>0.036779</td>\n      <td>0.723948</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>43</td>\n      <td>0.012285</td>\n      <td>0.037822</td>\n      <td>0.721510</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>44</td>\n      <td>0.012087</td>\n      <td>0.036847</td>\n      <td>0.726098</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>45</td>\n      <td>0.011965</td>\n      <td>0.036553</td>\n      <td>0.731710</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>46</td>\n      <td>0.011827</td>\n      <td>0.035987</td>\n      <td>0.732226</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>47</td>\n      <td>0.011730</td>\n      <td>0.037345</td>\n      <td>0.720904</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>48</td>\n      <td>0.011701</td>\n      <td>0.036889</td>\n      <td>0.724420</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>49</td>\n      <td>0.011295</td>\n      <td>0.036519</td>\n      <td>0.725755</td>\n      <td>00:05</td>\n    </tr>\n  </tbody>\n</table>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.fit_one_cycle(10, slice(1e-4, 1e-3))","execution_count":76,"outputs":[{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: left;\">\n      <th>epoch</th>\n      <th>train_loss</th>\n      <th>valid_loss</th>\n      <th>lwlrap</th>\n      <th>time</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <td>0</td>\n      <td>0.011692</td>\n      <td>0.037372</td>\n      <td>0.717386</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>1</td>\n      <td>0.011538</td>\n      <td>0.038012</td>\n      <td>0.727155</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>2</td>\n      <td>0.011889</td>\n      <td>0.036912</td>\n      <td>0.721933</td>\n      <td>00:06</td>\n    </tr>\n    <tr>\n      <td>3</td>\n      <td>0.011805</td>\n      <td>0.038350</td>\n      <td>0.719961</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>4</td>\n      <td>0.011636</td>\n      <td>0.038521</td>\n      <td>0.717311</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>5</td>\n      <td>0.011327</td>\n      <td>0.037635</td>\n      <td>0.723888</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>6</td>\n      <td>0.011273</td>\n      <td>0.039795</td>\n      <td>0.713023</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>7</td>\n      <td>0.011025</td>\n      <td>0.038661</td>\n      <td>0.722394</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>8</td>\n      <td>0.011252</td>\n      <td>0.038327</td>\n      <td>0.728244</td>\n      <td>00:05</td>\n    </tr>\n    <tr>\n      <td>9</td>\n      <td>0.010909</td>\n      <td>0.038841</td>\n      <td>0.729205</td>\n      <td>00:05</td>\n    </tr>\n  </tbody>\n</table>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"markdown","source":"## Visualize the filters present in CNN"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.preprocessing import minmax_scale\n\ndef visualize_first_layer(learn, save_name=None):\n    conv1 = list(learn.model.children())[0][0]\n    if isinstance(conv1, torch.nn.modules.container.Sequential):\n        conv1 = conv1[0] # for some models, 1 layer inside\n    weights = conv1.weight.data.cpu().numpy()\n    weights_shape = weights.shape\n    weights = minmax_scale(weights.ravel()).reshape(weights_shape)\n    fig, axes = plt.subplots(8, 8, figsize=(8,8))\n    for i, ax in enumerate(axes.flat):\n        ax.imshow(np.rollaxis(weights[i], 0, 3))\n        ax.get_xaxis().set_visible(False)\n        ax.get_yaxis().set_visible(False)\n    if save_name:\n        fig.savefig(str(save_name))\n\nvisualize_first_layer(learn)","execution_count":82,"outputs":[{"output_type":"stream","text":"Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n","name":"stderr"},{"output_type":"display_data","data":{"text/plain":"<Figure size 576x576 with 64 Axes>","image/png":"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\n"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.save('fat2019_fastai_cnn2d_stage-2')\nlearn.export()","execution_count":83,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Create a submission file"},{"metadata":{"trusted":true},"cell_type":"code","source":"CUR_X_FILES, CUR_X = list(test_df.fname.values), X_test\n\ntest = ImageList.from_csv(WORK/'image', Path('../..')/CSV_SUBMISSION, folder='test')\nlearn = load_learner(WORK/'image', test=test)\npreds, _ = learn.TTA(ds_type=DatasetType.Test) ","execution_count":84,"outputs":[{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":""},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"learn.data.classes","execution_count":85,"outputs":[{"output_type":"execute_result","execution_count":85,"data":{"text/plain":"['Accelerating_and_revving_and_vroom',\n 'Accordion',\n 'Acoustic_guitar',\n 'Applause',\n 'Bark',\n 'Bass_drum',\n 'Bass_guitar',\n 'Bathtub_(filling_or_washing)',\n 'Bicycle_bell',\n 'Burping_and_eructation',\n 'Bus',\n 'Buzz',\n 'Car_passing_by',\n 'Cheering',\n 'Chewing_and_mastication',\n 'Child_speech_and_kid_speaking',\n 'Chink_and_clink',\n 'Chirp_and_tweet',\n 'Church_bell',\n 'Clapping',\n 'Computer_keyboard',\n 'Crackle',\n 'Cricket',\n 'Crowd',\n 'Cupboard_open_or_close',\n 'Cutlery_and_silverware',\n 'Dishes_and_pots_and_pans',\n 'Drawer_open_or_close',\n 'Drip',\n 'Electric_guitar',\n 'Fart',\n 'Female_singing',\n 'Female_speech_and_woman_speaking',\n 'Fill_(with_liquid)',\n 'Finger_snapping',\n 'Frying_(food)',\n 'Gasp',\n 'Glockenspiel',\n 'Gong',\n 'Gurgling',\n 'Harmonica',\n 'Hi-hat',\n 'Hiss',\n 'Keys_jangling',\n 'Knock',\n 'Male_singing',\n 'Male_speech_and_man_speaking',\n 'Marimba_and_xylophone',\n 'Mechanical_fan',\n 'Meow',\n 'Microwave_oven',\n 'Motorcycle',\n 'Printer',\n 'Purr',\n 'Race_car_and_auto_racing',\n 'Raindrop',\n 'Run',\n 'Scissors',\n 'Screaming',\n 'Shatter',\n 'Sigh',\n 'Sink_(filling_or_washing)',\n 'Skateboard',\n 'Slam',\n 'Sneeze',\n 'Squeak',\n 'Stream',\n 'Strum',\n 'Tap',\n 'Tick-tock',\n 'Toilet_flush',\n 'Traffic_noise_and_roadway_noise',\n 'Trickle_and_dribble',\n 'Walk_and_footsteps',\n 'Water_tap_and_faucet',\n 'Waves_and_surf',\n 'Whispering',\n 'Writing',\n 'Yell',\n 'Zipper_(clothing)']"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"test_df[learn.data.classes] = preds\ntest_df.to_csv('submission.csv', index=False)\ntest_df.head()","execution_count":86,"outputs":[{"output_type":"execute_result","execution_count":86,"data":{"text/plain":"          fname        ...          Zipper_(clothing)\n0  000ccb97.wav        ...               3.227212e-03\n1  0012633b.wav        ...               7.518468e-03\n2  001ed5f1.wav        ...               1.794452e-02\n3  00294be0.wav        ...               8.182196e-02\n4  003fde7a.wav        ...               1.304035e-07\n\n[5 rows x 81 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>fname</th>\n      <th>Accelerating_and_revving_and_vroom</th>\n      <th>Accordion</th>\n      <th>Acoustic_guitar</th>\n      <th>Applause</th>\n      <th>Bark</th>\n      <th>Bass_drum</th>\n      <th>Bass_guitar</th>\n      <th>Bathtub_(filling_or_washing)</th>\n      <th>Bicycle_bell</th>\n      <th>Burping_and_eructation</th>\n      <th>Bus</th>\n      <th>Buzz</th>\n      <th>Car_passing_by</th>\n      <th>Cheering</th>\n      <th>Chewing_and_mastication</th>\n      <th>Child_speech_and_kid_speaking</th>\n      <th>Chink_and_clink</th>\n      <th>Chirp_and_tweet</th>\n      <th>Church_bell</th>\n      <th>Clapping</th>\n      <th>Computer_keyboard</th>\n      <th>Crackle</th>\n      <th>Cricket</th>\n      <th>Crowd</th>\n      <th>Cupboard_open_or_close</th>\n      <th>Cutlery_and_silverware</th>\n      <th>Dishes_and_pots_and_pans</th>\n      <th>Drawer_open_or_close</th>\n      <th>Drip</th>\n      <th>Electric_guitar</th>\n      <th>Fart</th>\n      <th>Female_singing</th>\n      <th>Female_speech_and_woman_speaking</th>\n      <th>Fill_(with_liquid)</th>\n      <th>Finger_snapping</th>\n      <th>Frying_(food)</th>\n      <th>Gasp</th>\n      <th>Glockenspiel</th>\n      <th>Gong</th>\n      <th>...</th>\n      <th>Harmonica</th>\n      <th>Hi-hat</th>\n      <th>Hiss</th>\n      <th>Keys_jangling</th>\n      <th>Knock</th>\n      <th>Male_singing</th>\n      <th>Male_speech_and_man_speaking</th>\n      <th>Marimba_and_xylophone</th>\n      <th>Mechanical_fan</th>\n      <th>Meow</th>\n      <th>Microwave_oven</th>\n      <th>Motorcycle</th>\n      <th>Printer</th>\n      <th>Purr</th>\n      <th>Race_car_and_auto_racing</th>\n      <th>Raindrop</th>\n      <th>Run</th>\n      <th>Scissors</th>\n      <th>Screaming</th>\n      <th>Shatter</th>\n      <th>Sigh</th>\n      <th>Sink_(filling_or_washing)</th>\n      <th>Skateboard</th>\n      <th>Slam</th>\n      <th>Sneeze</th>\n      <th>Squeak</th>\n      <th>Stream</th>\n      <th>Strum</th>\n      <th>Tap</th>\n      <th>Tick-tock</th>\n      <th>Toilet_flush</th>\n      <th>Traffic_noise_and_roadway_noise</th>\n      <th>Trickle_and_dribble</th>\n      <th>Walk_and_footsteps</th>\n      <th>Water_tap_and_faucet</th>\n      <th>Waves_and_surf</th>\n      <th>Whispering</th>\n      <th>Writing</th>\n      <th>Yell</th>\n      <th>Zipper_(clothing)</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>000ccb97.wav</td>\n      <td>0.000017</td>\n      <td>4.957211e-08</td>\n      <td>7.655426e-08</td>\n      <td>4.309760e-06</td>\n      <td>0.000002</td>\n      <td>0.003011</td>\n      <td>1.819878e-07</td>\n      <td>1.281406e-04</td>\n      <td>0.000126</td>\n      <td>9.111455e-07</td>\n      <td>0.000007</td>\n      <td>0.000055</td>\n      <td>0.000003</td>\n      <td>1.741197e-05</td>\n      <td>1.437585e-02</td>\n      <td>4.362807e-06</td>\n      <td>0.000038</td>\n      <td>0.002682</td>\n      <td>0.000002</td>\n      <td>2.949590e-04</td>\n      <td>0.000059</td>\n      <td>0.001324</td>\n      <td>0.000234</td>\n      <td>3.163131e-05</td>\n      <td>4.716621e-06</td>\n      <td>0.000913</td>\n      <td>0.000009</td>\n      <td>1.550476e-04</td>\n      <td>0.001653</td>\n      <td>4.856985e-09</td>\n      <td>2.355506e-06</td>\n      <td>1.066238e-06</td>\n      <td>1.552990e-04</td>\n      <td>0.000722</td>\n      <td>6.829734e-05</td>\n      <td>0.000108</td>\n      <td>5.899618e-06</td>\n      <td>1.620020e-04</td>\n      <td>0.000002</td>\n      <td>...</td>\n      <td>1.452745e-05</td>\n      <td>1.353045e-03</td>\n      <td>0.088189</td>\n      <td>0.515897</td>\n      <td>3.187808e-07</td>\n      <td>5.653332e-07</td>\n      <td>4.179234e-07</td>\n      <td>1.287194e-07</td>\n      <td>0.000008</td>\n      <td>1.579049e-06</td>\n      <td>0.000004</td>\n      <td>0.000033</td>\n      <td>0.000046</td>\n      <td>6.957810e-07</td>\n      <td>1.301940e-07</td>\n      <td>1.769494e-04</td>\n      <td>0.000205</td>\n      <td>0.085184</td>\n      <td>1.520260e-04</td>\n      <td>0.068440</td>\n      <td>0.000017</td>\n      <td>0.000238</td>\n      <td>8.393439e-06</td>\n      <td>0.000008</td>\n      <td>3.721510e-04</td>\n      <td>0.000130</td>\n      <td>0.000138</td>\n      <td>5.863234e-09</td>\n      <td>0.000021</td>\n      <td>0.000027</td>\n      <td>0.000867</td>\n      <td>0.000002</td>\n      <td>3.688895e-04</td>\n      <td>2.442428e-04</td>\n      <td>0.000228</td>\n      <td>5.299786e-05</td>\n      <td>1.005708e-04</td>\n      <td>0.001447</td>\n      <td>1.107540e-04</td>\n      <td>3.227212e-03</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0012633b.wav</td>\n      <td>0.068209</td>\n      <td>8.694149e-05</td>\n      <td>1.983406e-04</td>\n      <td>4.812185e-03</td>\n      <td>0.005927</td>\n      <td>0.001050</td>\n      <td>1.023339e-04</td>\n      <td>1.196936e-02</td>\n      <td>0.000179</td>\n      <td>1.251880e-03</td>\n      <td>0.004990</td>\n      <td>0.005936</td>\n      <td>0.006875</td>\n      <td>1.493555e-03</td>\n      <td>5.773605e-03</td>\n      <td>2.321765e-03</td>\n      <td>0.000642</td>\n      <td>0.005627</td>\n      <td>0.001593</td>\n      <td>6.751783e-04</td>\n      <td>0.000596</td>\n      <td>0.000155</td>\n      <td>0.001166</td>\n      <td>8.370757e-03</td>\n      <td>1.723875e-03</td>\n      <td>0.002133</td>\n      <td>0.002657</td>\n      <td>9.642729e-03</td>\n      <td>0.002239</td>\n      <td>1.482380e-04</td>\n      <td>9.246521e-05</td>\n      <td>9.067098e-04</td>\n      <td>1.769290e-03</td>\n      <td>0.008835</td>\n      <td>3.373356e-04</td>\n      <td>0.020270</td>\n      <td>4.185357e-04</td>\n      <td>1.730709e-04</td>\n      <td>0.001810</td>\n      <td>...</td>\n      <td>4.782971e-03</td>\n      <td>1.007321e-03</td>\n      <td>0.136533</td>\n      <td>0.000223</td>\n      <td>2.632641e-03</td>\n      <td>7.744425e-04</td>\n      <td>5.962143e-04</td>\n      <td>3.867998e-05</td>\n      <td>0.000931</td>\n      <td>7.055469e-03</td>\n      <td>0.009872</td>\n      <td>0.102550</td>\n      <td>0.004940</td>\n      <td>4.343483e-03</td>\n      <td>3.283585e-03</td>\n      <td>2.352174e-03</td>\n      <td>0.000311</td>\n      <td>0.003569</td>\n      <td>4.131315e-03</td>\n      <td>0.021620</td>\n      <td>0.002286</td>\n      <td>0.031734</td>\n      <td>8.255991e-03</td>\n      <td>0.002611</td>\n      <td>2.774552e-02</td>\n      <td>0.002738</td>\n      <td>0.001663</td>\n      <td>5.525880e-05</td>\n      <td>0.001137</td>\n      <td>0.000399</td>\n      <td>0.147110</td>\n      <td>0.003779</td>\n      <td>2.564362e-03</td>\n      <td>2.669580e-02</td>\n      <td>0.016831</td>\n      <td>2.192326e-03</td>\n      <td>1.245004e-02</td>\n      <td>0.003447</td>\n      <td>8.224636e-04</td>\n      <td>7.518468e-03</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>001ed5f1.wav</td>\n      <td>0.000596</td>\n      <td>7.195477e-08</td>\n      <td>2.558392e-06</td>\n      <td>9.265258e-07</td>\n      <td>0.000182</td>\n      <td>0.002064</td>\n      <td>3.355299e-06</td>\n      <td>3.019740e-03</td>\n      <td>0.000148</td>\n      <td>1.021936e-05</td>\n      <td>0.000256</td>\n      <td>0.000199</td>\n      <td>0.000058</td>\n      <td>1.169047e-06</td>\n      <td>1.369214e-02</td>\n      <td>7.301209e-05</td>\n      <td>0.000513</td>\n      <td>0.000362</td>\n      <td>0.000044</td>\n      <td>4.949805e-04</td>\n      <td>0.000375</td>\n      <td>0.000371</td>\n      <td>0.000003</td>\n      <td>1.240640e-05</td>\n      <td>1.005655e-02</td>\n      <td>0.007059</td>\n      <td>0.001475</td>\n      <td>1.202236e-01</td>\n      <td>0.000074</td>\n      <td>9.519759e-04</td>\n      <td>4.817496e-04</td>\n      <td>6.243046e-07</td>\n      <td>5.766283e-05</td>\n      <td>0.000106</td>\n      <td>5.413607e-05</td>\n      <td>0.000058</td>\n      <td>1.437974e-05</td>\n      <td>9.712230e-08</td>\n      <td>0.000007</td>\n      <td>...</td>\n      <td>1.797322e-06</td>\n      <td>1.425831e-03</td>\n      <td>0.000853</td>\n      <td>0.001947</td>\n      <td>6.253343e-03</td>\n      <td>5.429454e-06</td>\n      <td>8.287760e-04</td>\n      <td>1.282256e-06</td>\n      <td>0.000182</td>\n      <td>1.119743e-04</td>\n      <td>0.011892</td>\n      <td>0.000095</td>\n      <td>0.052253</td>\n      <td>3.041823e-04</td>\n      <td>1.290412e-04</td>\n      <td>3.776683e-04</td>\n      <td>0.138262</td>\n      <td>0.054346</td>\n      <td>8.014998e-07</td>\n      <td>0.001836</td>\n      <td>0.000003</td>\n      <td>0.000592</td>\n      <td>5.475947e-05</td>\n      <td>0.030549</td>\n      <td>1.558618e-03</td>\n      <td>0.068759</td>\n      <td>0.000042</td>\n      <td>1.920874e-06</td>\n      <td>0.004326</td>\n      <td>0.001867</td>\n      <td>0.000567</td>\n      <td>0.000131</td>\n      <td>1.460644e-05</td>\n      <td>1.043550e-01</td>\n      <td>0.000244</td>\n      <td>3.773181e-04</td>\n      <td>6.556379e-05</td>\n      <td>0.003050</td>\n      <td>3.716608e-06</td>\n      <td>1.794452e-02</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>00294be0.wav</td>\n      <td>0.000094</td>\n      <td>1.886235e-07</td>\n      <td>4.070549e-07</td>\n      <td>1.771349e-08</td>\n      <td>0.000454</td>\n      <td>0.000022</td>\n      <td>2.258444e-06</td>\n      <td>8.174217e-05</td>\n      <td>0.000495</td>\n      <td>2.299016e-04</td>\n      <td>0.000113</td>\n      <td>0.004140</td>\n      <td>0.000035</td>\n      <td>2.648558e-08</td>\n      <td>1.126179e-02</td>\n      <td>5.589966e-06</td>\n      <td>0.000022</td>\n      <td>0.000257</td>\n      <td>0.000017</td>\n      <td>6.984734e-08</td>\n      <td>0.001927</td>\n      <td>0.001973</td>\n      <td>0.033595</td>\n      <td>4.665621e-08</td>\n      <td>5.700369e-05</td>\n      <td>0.000962</td>\n      <td>0.000056</td>\n      <td>3.366605e-05</td>\n      <td>0.000284</td>\n      <td>8.820550e-09</td>\n      <td>2.002913e-06</td>\n      <td>4.080193e-07</td>\n      <td>1.173362e-04</td>\n      <td>0.000149</td>\n      <td>5.769972e-08</td>\n      <td>0.001351</td>\n      <td>3.087737e-07</td>\n      <td>5.296133e-08</td>\n      <td>0.000004</td>\n      <td>...</td>\n      <td>7.809427e-07</td>\n      <td>5.632608e-08</td>\n      <td>0.060790</td>\n      <td>0.005714</td>\n      <td>9.181195e-06</td>\n      <td>6.520521e-07</td>\n      <td>2.279050e-04</td>\n      <td>4.771155e-07</td>\n      <td>0.000645</td>\n      <td>8.113625e-03</td>\n      <td>0.000002</td>\n      <td>0.000303</td>\n      <td>0.000761</td>\n      <td>6.251854e-01</td>\n      <td>1.017776e-07</td>\n      <td>8.389987e-05</td>\n      <td>0.000202</td>\n      <td>0.000940</td>\n      <td>1.218544e-08</td>\n      <td>0.000022</td>\n      <td>0.000009</td>\n      <td>0.000427</td>\n      <td>1.823598e-06</td>\n      <td>0.000192</td>\n      <td>1.270740e-05</td>\n      <td>0.000562</td>\n      <td>0.000488</td>\n      <td>9.880604e-07</td>\n      <td>0.000002</td>\n      <td>0.000996</td>\n      <td>0.000013</td>\n      <td>0.000021</td>\n      <td>1.271347e-04</td>\n      <td>6.838135e-03</td>\n      <td>0.000390</td>\n      <td>1.252712e-03</td>\n      <td>1.434606e-04</td>\n      <td>0.068207</td>\n      <td>2.067815e-08</td>\n      <td>8.182196e-02</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>003fde7a.wav</td>\n      <td>0.000015</td>\n      <td>9.919409e-07</td>\n      <td>6.158269e-05</td>\n      <td>5.044285e-06</td>\n      <td>0.000056</td>\n      <td>0.000005</td>\n      <td>2.051063e-05</td>\n      <td>6.898385e-07</td>\n      <td>0.481820</td>\n      <td>6.997161e-07</td>\n      <td>0.000058</td>\n      <td>0.000006</td>\n      <td>0.000158</td>\n      <td>2.332741e-06</td>\n      <td>2.837005e-07</td>\n      <td>5.611856e-09</td>\n      <td>0.000711</td>\n      <td>0.000714</td>\n      <td>0.000077</td>\n      <td>7.982639e-05</td>\n      <td>0.000045</td>\n      <td>0.000018</td>\n      <td>0.000163</td>\n      <td>3.644377e-06</td>\n      <td>4.174321e-07</td>\n      <td>0.000056</td>\n      <td>0.000116</td>\n      <td>3.107264e-07</td>\n      <td>0.000006</td>\n      <td>1.534098e-06</td>\n      <td>5.105346e-10</td>\n      <td>1.049766e-04</td>\n      <td>1.297756e-07</td>\n      <td>0.000003</td>\n      <td>1.303927e-04</td>\n      <td>0.000005</td>\n      <td>8.821159e-08</td>\n      <td>2.244720e-01</td>\n      <td>0.000167</td>\n      <td>...</td>\n      <td>1.998905e-05</td>\n      <td>1.853883e-07</td>\n      <td>0.000012</td>\n      <td>0.000008</td>\n      <td>1.493578e-05</td>\n      <td>3.683696e-07</td>\n      <td>1.476443e-08</td>\n      <td>4.861561e-02</td>\n      <td>0.000003</td>\n      <td>6.451831e-07</td>\n      <td>0.000917</td>\n      <td>0.000003</td>\n      <td>0.000110</td>\n      <td>4.034235e-07</td>\n      <td>7.029019e-08</td>\n      <td>6.810114e-07</td>\n      <td>0.000004</td>\n      <td>0.000001</td>\n      <td>1.469857e-07</td>\n      <td>0.000005</td>\n      <td>0.000008</td>\n      <td>0.000015</td>\n      <td>3.415113e-08</td>\n      <td>0.000001</td>\n      <td>3.625892e-07</td>\n      <td>0.000002</td>\n      <td>0.000014</td>\n      <td>4.937187e-05</td>\n      <td>0.001020</td>\n      <td>0.000135</td>\n      <td>0.000065</td>\n      <td>0.000002</td>\n      <td>2.058448e-07</td>\n      <td>8.572486e-07</td>\n      <td>0.000005</td>\n      <td>1.431024e-07</td>\n      <td>1.643736e-07</td>\n      <td>0.000005</td>\n      <td>3.901603e-08</td>\n      <td>1.304035e-07</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"CUR_X_FILES, CUR_X = list(df.fname.values), X_train\nlearn = cnn_learner(data, models.resnet18, pretrained=False, metrics=[lwlrap])\nlearn.load('fat2019_fastai_cnn2d_stage-2');","execution_count":87,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Using Grad CAM method to visualize the CNN features"},{"metadata":{"trusted":true},"cell_type":"code","source":"from fastai.callbacks.hooks import *\n\ndef visualize_cnn_by_cam(learn, data_index):\n    x, _y = learn.data.valid_ds[data_index]\n    y = _y.data\n    \n    if not isinstance(y, (list, np.ndarray)): # single label -> one hot encoding\n        y = np.eye(learn.data.valid_ds.c)[y]\n        \n    m = learn.model.eval()\n    xb,_ = learn.data.one_item(x)\n    xb_im = Image(learn.data.denorm(xb)[0])\n    xb = xb.cuda()\n    \n    def hooked_backward(cat):\n        with hook_output(m[0]) as hook_a:\n            with hook_output(m[0], grad = True) as hook_g:\n                preds = m(xb)\n                preds[0,int(cat)].backward()\n        return hook_a,hook_g\n    \n    def show_heatmap(img, hm, label):\n        _,axs = plt.subplots(1, 2)\n        axs[0].set_title(label)\n        img.show(axs[0])\n        axs[1].set_title(f'CAM of {label}')\n        img.show(axs[1])\n        axs[1].imshow(hm, alpha=0.6, extent=(0,img.shape[0],img.shape[0],0),\n                      interpolation='bilinear', cmap='magma');\n        plt.show()\n        \n    for y_i in np.where(y > 0)[0]:\n        hook_a, hook_g = hooked_backward(cat = y_i)\n        acts = hook_a.stored[0].cpu()\n        grad = hook_g.stored[0][0].cpu()\n        grad_chan = grad.mean(1).mean(1)\n        mult = (acts*grad_chan[...,None,None]).mean(0)\n        show_heatmap(img=xb_im, hm=mult, label=str(learn.data.valid_ds.y[data_index]))\n        \nfor idx in range(10):\n    visualize_cnn_by_cam(learn, idx)","execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 2 Axes>","image/png":"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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure 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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure 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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure 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\n"},"metadata":{}}]}],"metadata":{"kernelspec":{"display_name":"Python 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