From 689e4df4aa3804261b64fda82945b92782e5e2cf Mon Sep 17 00:00:00 2001 From: k Date: Thu, 31 Jul 2025 14:23:34 -0400 Subject: [PATCH] cleanup/rewrite --- data.py | 65 +++++++ model.py | 27 ++- music.ipynb | 478 ---------------------------------------------------- show.py | 26 +++ train.ipynb | 163 ++++++++++++++++++ 5 files changed, 277 insertions(+), 482 deletions(-) create mode 100644 data.py delete mode 100644 music.ipynb create mode 100644 show.py create mode 100644 train.ipynb diff --git a/data.py b/data.py new file mode 100644 index 0000000..94faec5 --- /dev/null +++ b/data.py @@ -0,0 +1,65 @@ +import librosa +import numpy as np +from pathlib import Path +from multiprocessing import Pool, cpu_count + +SAMPLE_RATE = 22050 + +def process_file(file_path): + """ + Load 10 second chunks single song. + """ + y, sr = librosa.load(file_path, mono=True, sr=SAMPLE_RATE) + size = int(SAMPLE_RATE * 10) + sample_len = len(y) + + file_chunks = [] + for start_pos in range(0, sample_len, size): + end = start_pos + size + if end <= sample_len: + chunk = y[start_pos:end] + file_chunks.append(chunk) + return file_chunks + +def load(): + """ + Load 10 second chunks of songs. + """ + audio = [] + files = list(Path("./data/").glob("*.mp3")) + with Pool(cpu_count()) as pool: + chunk_list = pool.map(process_file, files) + for l in chunk_list: + audio.extend(l) + return audio + +def audio_split(audio): + """ + Split 10 seconds of audio to 2 5 second clips + """ + size = int(SAMPLE_RATE*5) + x = audio[:size] + y = audio[size:size*2] + + x = librosa.feature.melspectrogram(y=x, sr=SAMPLE_RATE) + y = librosa.feature.melspectrogram(y=y, sr=SAMPLE_RATE) + + ma,mi = x.max(), x.min() + x = (x - mi) / (ma - mi) + + ma,mi = y.max(), y.min() + y = (y - mi) / (ma - mi) + + return x,y + +def detaset(chunks): + """ + convert 10 second chunks to dataset + """ + x,y=[],[] + with Pool(cpu_count()) as pool: + audio_list = pool.map(audio_split,chunks) + for (ax,ay) in audio_list: + x.append(ax) + y.append(ay) + return x,y diff --git a/model.py b/model.py index b4e3857..532fdec 100644 --- a/model.py +++ b/model.py @@ -1,11 +1,11 @@ from tinygrad import Tensor, nn import numpy as np -class Model: +class Gen: def __init__(self, input_channels=1, height=128, width=216, latent_dim=32): self.w = width // 8 self.h = height // 8 - self.flattened_size = 128 * self.h * self.w + self.flattened_size = 256 * self.h * self.w # Encoder self.e1 = nn.Conv2d(input_channels, 64, kernel_size=3, stride=2, padding=1) @@ -61,5 +61,24 @@ class Model: x = x.reshape(shape=(-1, 256, self.h, self.w)) x = self.d1(x).relu() x = self.d2(x).relu() - x = self.d3(x) - return x \ No newline at end of file + x = self.d3(x).sigmoid() + return x + +class Check(): + def __init__(self, input_channels=1, height=128, width=216): + self.w = width // 8 + self.h = height // 8 + self.flattened_size = 256 * self.h * self.w + + self.d1 = nn.Conv2d(input_channels, 64, kernel_size=3, stride=2, padding=1) + self.d2 = nn.Conv2d(64, 128, kernel_size=3, stride=2, padding=1) + self.d3 = nn.Conv2d(128, 256, kernel_size=3, stride=2, padding=1) + self.fc = nn.Linear(self.flattened_size, 1) + + + def __call__(self, x: Tensor) -> Tensor: + x = self.d1(x).leakyrelu(0.2) + x = self.d2(x).leakyrelu(0.2) + x = self.d3(x).leakyrelu(0.2) + x = x.reshape(shape=(-1, self.flattened_size)) + return self.fc(x) \ No newline at end of file diff --git a/music.ipynb b/music.ipynb deleted file mode 100644 index b170103..0000000 --- a/music.ipynb +++ /dev/null @@ -1,478 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "7a4b3fe0-37b7-4dcc-928e-5d5981eb62bd", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "%load_ext tensorboard\n", - "import librosa\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "from pathlib import Path\n", - "import IPython.display as ipd" - ] - }, - { - "cell_type": "markdown", - "id": "25beb189-d3c5-4ba2-a31d-f692685291fc", - "metadata": {}, - "source": [ - "# prep" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "8e45206f-7e1f-4a47-852f-39849a395a53", - "metadata": {}, - "outputs": [], - "source": [ - "SAMPLE_RATE = 22050" - ] - }, - { - "cell_type": "code", - "execution_count": 112, - "id": "dc03a57f-8739-4f5e-a1c9-3db7a48e26de", - "metadata": {}, - "outputs": [], - "source": [ - "def load():\n", - " \"\"\"\n", - " Load 10 second chunks of songs\n", - " \"\"\"\n", - "\n", - " files = list(Path(\"./data/\").glob(\"*.mp3\"))\n", - " chunks = []\n", - " for file in files:\n", - " y, sr = librosa.load(file, mono=True,sr=SAMPLE_RATE)\n", - " size = int(SAMPLE_RATE * 10)\n", - " sampleLen = len(y)\n", - " \n", - " for startPos in range(0,sampleLen,size):\n", - " end = startPos+size\n", - " if end > sampleLen:\n", - " pass\n", - " chunk = y[startPos:end]\n", - " #chunk = librosa.effects.preemphasis(chunk) \n", - " chunks.append(chunk)\n", - " return chunks" - ] - }, - { - "cell_type": "code", - "execution_count": 113, - "id": "8b9851bc-9b90-4404-acbe-6568282d864b", - "metadata": {}, - "outputs": [], - "source": [ - "def dataset(chunks):\n", - " x,y = [],[]\n", - " size = int(SAMPLE_RATE*5)\n", - " for chunk in chunks:\n", - " Ax = chunk[:size]\n", - " Ay = chunk[size:size*2]\n", - " if(len(Ax) == size and len(Ay) == size):\n", - " Ax = librosa.feature.melspectrogram(y=Ax, sr=SAMPLE_RATE)\n", - " Ay = librosa.feature.melspectrogram(y=Ay, sr=SAMPLE_RATE)\n", - " ma,mi = Ax.max(), Ax.min()\n", - " Ax = (Ax - mi) / (ma - mi)\n", - " \n", - " ma,mi = Ay.max(), Ay.min()\n", - " Ay = (Ay - mi) / (ma - mi)\n", - " x.append(Ax)\n", - " y.append(Ay)\n", - " return x,y" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "d953fafa-b119-4aa4-b17b-8606c0b366b1", - "metadata": {}, - "outputs": [], - "source": [ - "def showSpec(spec):\n", - " plt.figure(figsize=(10, 4))\n", - " librosa.display.specshow(spec, sr=SAMPLE_RATE,\n", - " x_axis='time', y_axis='mel',\n", - " cmap='viridis')\n", - " plt.colorbar(format='%+2.0f dB')\n", - " plt.title('Mel spectrogram')\n", - " plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "5a744602-e8ea-4c79-883a-1472c15df3ae", - "metadata": {}, - "outputs": [], - "source": [ - "def playSpec(spec):\n", - " S = librosa.feature.inverse.mel_to_stft(spec, sr=SAMPLE_RATE)\n", - " audio = librosa.griffinlim(S,n_iter=25,momentum=0.99)\n", - " audio = librosa.effects.preemphasis(audio) # Reapply pre-emphasis\n", - "\n", - " plt.figure(figsize=(12,4))\n", - " plt.plot(audio)\n", - " plt.title('waveform')\n", - " plt.show()\n", - "\n", - " display(ipd.Audio(audio,rate=SAMPLE_RATE))" - ] - }, - { - "cell_type": "markdown", - "id": "2488eaeb-a378-42dd-bd4a-b9290c445026", - "metadata": {}, - "source": [ - "# Load Data" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "f411e54e-2a7d-4dfe-be90-457e2a9455a7", - "metadata": {}, - "outputs": [], - "source": [ - "chunks = load()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "1c942a3f-8072-41b3-bb16-1ccb9812b505", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "3385\n" - ] - } - ], - "source": [ - "x,y = dataset(chunks)\n", - "print(len(x))" - ] - }, - { - "cell_type": "code", - "execution_count": 80, - "id": "39241f9b-8cc0-40cf-96dc-1be6d3ff2fb7", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "image/png": 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2bdvaK4QbO6OiJCQkKD09XZKUnp6u3Nxcpaamat68eRozZoxX+yBgAQAAABzikimX7A2DaHf9xMREJSYmWq+jo6PVunVrK3A4Venp6QoPD9fq1auVlpYmSTp06JA2b96sfv36nXDb0NBQScdqfbxFwAIAAAAEsfz8fOXn52vLli2SpA0bNiguLk5paWkegU+V2NhYjR49WuPHj1dSUpKSk5M1adKkWjs6KCkpUX5+vqRjKWFPP/20oqKilJmZ6XX5CFgAAAAAh7jkkqse2zSm1157TU899ZT1+tJLL5UkzZ49W6NGjap1m2nTpqmoqEhDhgxRXFycxo0bp4KCghrrzZw5UzNnzpQktWjRQt27d9fixYtrbe9SF8O0k4QWxAoLC5WQkKAMDaUNCwAAgB+qMI9qhRapoKDAq7YeTqr6LrnzP23r1ei+/Vm7/PK8nEANCwAAAOAQJ9qwNDUELAAAAIBDXDJVScBiCwELAAAA4BBqWOyzl0AHAAAAAA6ihgUAAABwSKVpqtJmn1d2129qCFgAAAAAh7iOT3a3CWYELAAAAIBDKuvR6N7u+k0NAQsAAADgkErz2GR3m2BGwAIAAAA4hJQw++glDAAAAIDfooYFAAAAcIhLhipl2N4mmBGwAAAAAA5xmccmu9sEMwIWAAAAwCGV9ahhsbt+U0PAAgAAADiEgMU+nza6r6io0BNPPKEOHTooOjpaZ5xxhn7729/K5aruC2HBggW64oor1LJlSxmGofXr19fYz9atW3XttdeqVatWio+P1/Dhw7V3717r79u3b9fo0aOt43Ts2FGTJ09WeXm5E6cJAAAASJJcplGvKZj5NGD5/e9/r9dee02vvvqq/v3vf+u5557TtGnT9Morr1jrFBcX6+KLL9azzz5b6z6Ki4uVmZkpwzC0bNkyff755yovL9fgwYOtwOc///mPXC6X/vd//1cbN27USy+9pNdee00TJ0505DwBAAAA1I9PU8K+/PJLDR06VIMGDZIknX766XrnnXf01VdfWevceuutko7VktTm888/1/bt27Vu3TrFx8dLkmbPnq3ExEQtW7ZM/fv318CBAzVw4EBrmzPOOEObNm3Sn/70Jz3//PONdHYAAACAJ1LC7PNpDcsll1yiTz75RJs3b5Ykff3111q1apWuuuoqr/dRVlYmwzAUGRlpLYuKilJISIhWrVpV53YFBQVKTEw84X4LCws9JgAAAOBUVCqkXlMw8+nZP/bYY7rpppt01llnKTw8XOedd56ys7N10003eb2Piy66SM2aNdNjjz2mkpISFRcXa/z48XK5XNqzZ0+t22zdulWvvPKKsrKy6tzv1KlTlZCQYE3t27e3fX4AAACAO7Me7VdM2rD4zrx58/Tmm2/q7bff1tq1azV37lw9//zzmjt3rtf7aNWqlebPn68PPvhAsbGxSkhIUEFBgc4//3yFhobWWH/37t0aOHCgbrjhBo0ZM6bO/U6YMEEFBQXWtHPnznqdIwAAAFClKiXM7hTMfNqGZfz48Xr88cf1m9/8RpLUrVs37dixQ1OnTtXIkSO93k9mZqa2bt2q/fv3KywsTM2bN1dKSoo6dOjgsd7u3bt12WWXqXfv3nr99ddPuM/IyEiPNDMAAADgVFWaIao07dUZVDJwpO+UlJQoJMTzDQsNDfXo1tiOli1bSpKWLVumffv2aciQIdbfdu3apcsuu0w9e/bU7NmzaxwXAAAAgP/xacAyePBgPfPMM0pLS9M555yjdevW6cUXX9Qdd9xhrXPw4EH98MMP2r17tyRp06ZNkqSUlBSlpKRIOtYrWJcuXdSqVSt9+eWXevDBB/XQQw+pc+fOko7VrGRkZCgtLU3PP/+8fvrpJ2v/VfsAAAAAGptLhlw2W2W4FNxVLD4NWF555RX9z//8j+69917t27dPbdq00d13360nn3zSWuf999/X7bffbr2uSh+bPHmypkyZIulYEDNhwgQdPHhQp59+uiZNmqSHHnrI2mbJkiXasmWLtmzZonbt2nmUwTSD+wYAAACAc+jW2D7D5Bu7VwoLC5WQkKAMDVWYEe7r4gAAAOAXKsyjWqFFKigosMbn8xdV3yUXft1JzeJqdgx1IsWHK3Xtud/75Xk5wac1LAAAAEAwOZYSZq/GxO76TQ0BCwAAAOAQVz0Gggz2Nix0lQUAAADAb1HDAgAAADikfuOwBHcNCwELAAAA4BCXQujW2CYCFgAAAMAhlaahStNmt8Y2129qCFgAAAAAh1TWo9F9JTUsAAAAAJzgMkPkstmGxRXkbVjoJQwAAACA36KGBQAAAHAIKWH2EbAAAAAADnHJfiN6V+MUJWAQsAAAAAAOqV+3xsHdioOABQAAAHBI/QaOJGABAAAA4ACXDLlkNyUsuMdhCe5wDQAAAIBfo4YFAAAAcAgpYfYRsAAAAAAOqV+3xgQsAAAAABzgMg257HZrbHP9poaABQAAAHCIqx41LHRrDAAAAMARLjNELpttUuyu39QE99kDAAAA8GvUsAAAAAAOqZShSpvjqthdv6khYAEAAAAcQkqYfQQsAAAAgEMqZb/GpLJxihIwgjtcAwAAABxUVcNidwoEGRkZys7ObvD9BsbZAwAAAE1A1Uj3dqfG9PrrrysjI0Px8fEyDEM///xzg+w3IyNDhmHIMAyFhIQoOTlZN9xwg3bs2GFrPwQsAAAAQBOWkZGhOXPm1Pn3kpISDRw4UBMnTmzwY995553as2ePdu3apUWLFmnnzp265ZZbbO2DNiwAAACAQ0wZctlsw2I2ci9hVWlcK1as8Hqb4uJi3XPPPVqwYIHi4uL0yCOP1LpeTEyMUlJSJEmpqakaO3assrKybJWPGhYAAADAIaeSElZYWOgxlZWV+ew8xo8fr+XLl2vhwoVasmSJVqxYoby8vBNuc/DgQc2fP1+9evWydSwCFgAAAMAhLtOo1yRJ7du3V0JCgjVNnTrVJ+dQVFSk3NxcPf/88xowYIC6deumuXPnqrKyZn9mM2bMUGxsrJo1a6akpCRt2rRJs2bNsnU8AhYAAADAIZUKqdckSTt37lRBQYE1TZgwodZj5OTkKDY21po+++wzZWVl1VhWX1u3blV5ebl69+5tLUtMTFTnzp1rrDtixAitX79eX3/9tVatWqX09HRlZmbq8OHDXh+PNiwAAACAQ9xrTOxsI0nx8fGKj48/6fpZWVkaPny49XrEiBG67rrrNGzYMGtZ27ZtbZXBnWmaXq+bkJCg9PR0SVJ6erpyc3OVmpqqefPmacyYMV7tg4AFAAAAaEISExOVmJhovY6Ojlbr1q2twOFUpaenKzw8XKtXr1ZaWpok6dChQ9q8ebP69et3wm1DQ0MlSaWlpV4fj4AFAAAAcIhLIXLZbJVhd3278vPzlZ+fry1btkiSNmzYoLi4OKWlpXkEPlViY2M1evRojR8/XklJSUpOTtakSZMUElKznCUlJcrPz5ck7d27V08//bSioqKUmZnpdfkIWAAAAACHVJqGKm2mhNld367XXntNTz31lPX60ksvlSTNnj1bo0aNqnWbadOmqaioSEOGDFFcXJzGjRungoKCGuvNnDlTM2fOlCS1aNFC3bt31+LFi2tt71IXw7SThBbECgsLlZCQoAwNVZgR7uviAAAA4BcqzKNaoUUqKCjwqq2Hk6q+S9796XWKjLX3XbKs6Kj+99L3/PK8nEANCwAAAOAQ0wyRy7SX4mXaXL+pCe6zBwAAAODXqGEBAAAAHFIpQ5Wy2YbF5vpNDQELAAAA4BCXqXqMw9JIhQkQBCwAAACAQ1z1aMNid/2mhoAFAAAAcIhLhlw2U7zsrt/UELAAAAAADvHHcVj8XXDXLwEAAADwa9SwAAAAAA6hDYt9fnP2U6dOlWEYys7OtpaZpqkpU6aoTZs2io6OVkZGhjZu3Oix3datW3XttdeqVatWio+P1/Dhw7V3794a+//HP/6hXr16KTo6Wi1bttSwYcMa+5QAAAAADy4Zcpk2pyBvw+IXAcuaNWv0+uuvq3v37h7Ln3vuOb344ot69dVXtWbNGqWkpGjAgAE6fPiwJKm4uFiZmZkyDEPLli3T559/rvLycg0ePFgul8vaz3vvvadbb71Vt99+u77++mt9/vnnuvnmmx09RwAAAMA83ujezmQGecDi85SwoqIijRgxQjNnztTTTz9tLTdNU9OnT9ekSZOs2pC5c+cqOTlZb7/9tu6++259/vnn2r59u9atW6f4+HhJ0uzZs5WYmKhly5apf//+qqio0IMPPqhp06Zp9OjR1v47d+7s7IkCAAAg6FXVmtjdJpj5vIZl7NixGjRokPr37++xfNu2bcrPz1dmZqa1LDIyUv369dMXX3whSSorK5NhGIqMjLTWiYqKUkhIiFatWiVJWrt2rXbt2qWQkBCdd955Sk1N1ZVXXlkjteyXysrKVFhY6DEBAAAAp6KqDYvdKZj59OzfffddrV27VlOnTq3xt/z8fElScnKyx/Lk5GTrbxdddJGaNWumxx57TCUlJSouLtb48ePlcrm0Z88eSdJ///tfSdKUKVP0xBNP6O9//7tatGihfv366eDBg3WWberUqUpISLCm9u3bN8g5AwAAAPCezwKWnTt36sEHH9Sbb76pqKioOtczDM8qMNM0rWWtWrXS/Pnz9cEHHyg2NlYJCQkqKCjQ+eefr9DQUEmy2rJMmjRJ1113nXr27KnZs2fLMAzNnz+/zuNOmDBBBQUF1rRz585TPWUAAAAEOdsN7uuRQtbU+KwNS15envbt26eePXtayyorK/Xpp5/q1Vdf1aZNmyQdq2lJTU211tm3b59HrUtmZqa2bt2q/fv3KywsTM2bN1dKSoo6dOggSda2Z599trVNZGSkzjjjDP3www91li8yMtIj1QwAAAA4VYx0b5/Palguv/xybdiwQevXr7emCy64QCNGjND69et1xhlnKCUlRUuXLrW2KS8v18qVK9WnT58a+2vZsqWaN2+uZcuWad++fRoyZIgkqWfPnoqMjLQCIEk6evSotm/frtNOO63xTxQAAAA4jhoW+3xWwxIXF6euXbt6LGvWrJmSkpKs5dnZ2crJyVGnTp3UqVMn5eTkKCYmxqNL4tmzZ6tLly5q1aqVvvzySz344IN66KGHrF7A4uPjlZWVpcmTJ6t9+/Y67bTTNG3aNEnSDTfc4NDZAgAAAPQSVh8+79b4RB599FGVlpbq3nvv1aFDh9SrVy8tWbJEcXFx1jqbNm3ShAkTdPDgQZ1++umaNGmSHnroIY/9TJs2TWFhYbr11ltVWlqqXr16admyZWrRooXTpwQAAIAgRsBin2GapunrQgSCwsJCJSQkKENDFWaE+7o4AAAA+IUK86hWaJEKCgqsMfr8RdV3ySs+vEvhzSJsbXu0uFwfX/m6X56XE/y6hgUAAABoSqhhsY+ABQAAAHCIKfu9fgV7OhQBCwAAAOAQaljsI2ABAAAAHELAYh8BCwAAAOAQAhb7fDZwJAAAAACcDDUsAAAAgEOoYbGPgAUAAABwiGkaMm0GIHbXb2oIWAAAAACHuGTY7tbY7vpNDQELAAAA4BBSwuwjYAEAAAAcQkqYffQSBgAAAMBvUcMCAAAAOISUMPsIWAAAAACHkBJmHwELAAAA4BCzHjUsBCwAAAAAHGFKMk372wQzAhYAAADAIS4ZMhiHxRZ6CQMAAADgt6hhAQAAABxCo3v7CFgAAAAAh7hMQwbdGttCwAIAAAA4xDTr0eg+yFvdE7AAAAAADiElzD4CFgAAAMAhBCz20UsYAAAAAL9FDQsAAADgEBrd20fAAgAAADiERvf2EbAAAAAADjkWsNhtw9JIhQkQBCwAAACAQ2h0bx8BCwAAAOAQ8/hkd5tgRi9hAAAAAPwWAQsAAADgkKqUMLtTIMjIyFB2dnaD75eABQAAAHCKWc+pEb3++uvKyMhQfHy8DMPQzz//3CD7zcjIkGEYMgxDISEhSk5O1g033KAdO3bY2g8BCwAAAOCU+tSunGINS0ZGhubMmVPn30tKSjRw4EBNnDjxlI5TmzvvvFN79uzRrl27tGjRIu3cuVO33HKLrX3Q6B4AAABwiD+Ow1KVxrVixQqvtykuLtY999yjBQsWKC4uTo888kit68XExCglJUWSlJqaqrFjxyorK8tW+ahhAQAAABxyKm1YCgsLPaaysjKfncf48eO1fPlyLVy4UEuWLNGKFSuUl5d3wm0OHjyo+fPnq1evXraORcACAAAABID27dsrISHBmqZOneqTchQVFSk3N1fPP/+8BgwYoG7dumnu3LmqrKysse6MGTMUGxurZs2aKSkpSZs2bdKsWbNsHY+ABQAAAHBKVZsUu5OknTt3qqCgwJomTJhQ6yFycnIUGxtrTZ999pmysrJqLKuvrVu3qry8XL1797aWJSYmqnPnzjXWHTFihNavX6+vv/5aq1atUnp6ujIzM3X48GGvj0cbFgAAAMAhp9KGJT4+XvHx8SddPysrS8OHD7dejxgxQtddd52GDRtmLWvbtq29QniUx/sTSEhIUHp6uiQpPT1dubm5Sk1N1bx58zRmzBiv9kHAAgAAADjFgaHuExMTlZiYaL2Ojo5W69atrcDhVKWnpys8PFyrV69WWlqaJOnQoUPavHmz+vXrd8JtQ0NDJUmlpaVeH4+ABQAAAHBIfQaCbOyBI/Pz85Wfn68tW7ZIkjZs2KC4uDilpaV5BD5VYmNjNXr0aI0fP15JSUlKTk7WpEmTFBJSs7VJSUmJ8vPzJUl79+7V008/raioKGVmZnpdPgIWAAAAwEmN3E2xXa+99pqeeuop6/Wll14qSZo9e7ZGjRpV6zbTpk1TUVGRhgwZori4OI0bN04FBQU11ps5c6ZmzpwpSWrRooW6d++uxYsX19repS6GaScJLYgVFhYqISFBGRqqMCPc18UBAADAL1SYR7VCi1RQUOBVWw8nVX2XTHv9SYVER9na1lV6RD/c9Vu/PC8nUMMCAAAAOMQfU8L8HQELAAAA4BQHGt03NQQsAAAAgGOM45PdbYKXTweOnDp1qn71q18pLi5OrVu31jXXXKNNmzZ5rGOapqZMmaI2bdooOjpaGRkZ2rhxY637M01TV155pQzD0N/+9jePv23evFlDhw5Vy5YtFR8fr4svvljLly9vrFNzjhFSPQEAAMC/mfWcgphPv+WuXLlSY8eO1erVq7V06VJVVFQoMzNTxcXF1jrPPfecXnzxRb366qtas2aNUlJSNGDAgFpHx5w+fboMo/YIdNCgQaqoqNCyZcuUl5enHj166Oqrr7a6WQMAAAAaHQGLbT5NCfvoo488Xs+ePVutW7dWXl6eLr30UpmmqenTp2vSpEnWyJxz585VcnKy3n77bd19993Wtl9//bVefPFFrVmzRqmpqR773b9/v7Zs2aJZs2ape/fukqRnn31WM2bM0MaNG5WSktLIZ9qITJevSwAAAAA0Gr/KI6rqu7lqgJpt27YpPz/fY2CZyMhI9evXT1988YW1rKSkRDfddJNeffXVWoOPpKQkdenSRX/+859VXFysiooK/e///q+Sk5PVs2fPWstSVlamwsJCjwkAAAA4JaZRvymI+U2je9M09fDDD+uSSy5R165dJclK10pOTvZYNzk5WTt27LBeP/TQQ+rTp4+GDh1a674Nw9DSpUs1dOhQxcXFKSQkRMnJyfroo4/UvHnzWreZOnWqxwA6AAAAwKkyzWOT3W2Cmd/UsNx333365ptv9M4779T42y/bpZimaS17//33tWzZMk2fPr3OfZumqXvvvVetW7fWZ599pv/7v//T0KFDdfXVV2vPnj21bjNhwgQVFBRY086dO+t/cgAAAIBEG5Z68IuA5f7779f777+v5cuXq127dtbyqvSuXzaM37dvn1XrsmzZMm3dulXNmzdXWFiYwsKOVRpdd911ysjIsNb5+9//rnfffVcXX3yxzj//fM2YMUPR0dGaO3durWWKjIxUfHy8xwTAYfSCh2DAfY6mjPu7JlLCbPPp3WOapu677z4tWLBAy5YtU4cOHTz+3qFDB6WkpGjp0qXWsvLycq1cuVJ9+vSRJD3++OP65ptvtH79emuSpJdeekmzZ8+WdKyNiySFhHiebkhIiFwuGq0DAADAGYZZvymY+bQNy9ixY/X2229r0aJFiouLs2pSEhISFB0dLcMwlJ2drZycHHXq1EmdOnVSTk6OYmJidPPNN0s6VgtTW0P7tLQ0KwDq3bu3WrRooZEjR+rJJ59UdHS0Zs6cqW3btmnQoEHOnXADMUJDa11uVlY6XBKgcRkh1b8omS63HxzoHQ9NwfFfnD3ucx7jaGI8vrOY7vc6Nzu859OA5U9/+pMkWalbVWbPnq1Ro0ZJkh599FGVlpbq3nvv1aFDh9SrVy8tWbJEcXFxXh+nZcuW+uijjzRp0iT9+te/1tGjR3XOOedo0aJFOvfccxvqdAAAAIATq0+bFGpYfMf0ossDwzA0ZcoUTZky5ZT2e8EFF+jjjz+2UzwAAACgYdWnTUqQt2Hxm26NYYNbwzUjvPotNEtLfVEaoNF4pBK4JfCaFaSEoekwwsKtedPl9oMbqY9oAjzT2KvngzoljBoW2whYAAAAAKcQsNhGwBKA6vxVwqBRMpoWj3udLjHR1Bx/Tgf1L81o8syKo9UveI6jnghYAAAAAKdQw2JbvULdH374QWVlZTWWu1wu/fDDD6dcKNhgumqfgKbAfcAx7m80NbUNpsd9jibMrKy0pqDGwJG21StgOf3003X++edr69atHst/+umnGoM/AgAAADiGgSPtq3cyYZcuXXThhRfqk08+8VjuTVfFOEVuv8DxawWaMrPiaPXEvY6mpuo57nafA02Nx7ObGsRjzHpOQaxeAYthGJoxY4aeeOIJDRo0SC+//LLH3wAAAACgIdSr0X1VLcpDDz2ks846SzfddJO++eYbPfnkkw1aOAAAAADB7ZR7Cbvyyiv1xRdfaMiQIfq///u/higTAAAA0CQZst8mJdjzl+qVEtavXz9FRERYr88++2z961//UosWLWjDAgAAANSFXsJss1XDUlhYKElatGiRx2tJCg8P1wcffNCARQMAAACaGMZhsc1WwNK8eXOvGtVX0osPAAAAUBMBi222Apbly5db86Zp6qqrrtIbb7yhtm3bNnjBAAAAgKamPuOqBPs4LLYCln79+nm8Dg0N1UUXXaQzzjijQQsFAAAAAFID9BIGAAAAwEukhNlGwAIAAAA4hYDFtlMOWBjZHgAAAPAObVjssxWwDBs2zOP1kSNHlJWVpWbNmnksX7BgwamXDAAAAGhq6jOuCuOweC8hIcHj9S233NKghQEAAACaNFLCbLMVsMyePbuxygEAAAAANdDoHgAAAHAIbVjsI2ABAAAAnEJKmG0ELAAAAIBT6lHDQsACAAAAwBnUsNhGwAIAAAA4hYDFthBfFwAAAAAA6kINCwAAAOAQegmzj4AlEBkhbrPVI5+alZW+KA3QaIzQUGvedLk9rU2XD0oDNLDjz3Ke42jKeI6jIRCwAAAAAE6hDYttBCwByP3XCn6ZQ5NmuDez4/5G0+TxCzTPcTQ1Hlkh1bUqZhDf6qSE2UfAAgAAADgpyAMQuwhYApFb3qfpoqM3NGHkOANAYOM5jgZAwAIAAAA4hTYsthGwBCD3fGeFVb+FZsVRH5QGaDxGRET1vFtuv6u83BfFARpUVRvEuu5z2rOgKfD4zuLWniWY72/asNhHwAIAAAA4hRoW22gAAQAAADikqobF7hQIMjIylJ2d3eD7JWAJQGZlZfVUftSagKbGPFpRPbnd90BTYLpMmS5TriNl1lS1zGOAPSCAeXxnqThqTUHNrOfUiMrKynT//ferZcuWatasmYYMGaIff/zxlPebkZEhwzBkGIZCQkKUnJysG264QTt27LC1HwIWAAAAoAnLyMjQnDlz6vx7dna2Fi5cqHfffVerVq1SUVGRrr76alU2wI+Ed955p/bs2aNdu3Zp0aJF2rlzp2655RZb+yBgCUB1/gJnhFRPQFNguqonoKniPkew4HvKMX5Ww1JQUKDc3Fy98MIL6t+/v8477zy9+eab2rBhg/75z3/WuV1xcbFuu+02xcbGKjU1VS+88EKt68XExCglJUWpqam66KKLNHbsWK1du9ZWGYP8jgEAAACccyptWAoLCz2msrKyUy5PXl6ejh49qszMTGtZmzZt1LVrV33xxRd1bjd+/HgtX75cCxcu1JIlS7RixQrl5eWd8FgHDx7U/Pnz1atXL1tlJGAJdO6/zPErXeML1F+HArXcbsjtR1DgOd74msDzMGBxfx9zCjUs7du3V0JCgjVNnTr1lIuTn5+viIgItWjRwmN5cnKy8vPza92mqKhIubm5ev755zVgwAB169ZNc+fOrTWFbMaMGYqNjVWzZs2UlJSkTZs2adasWbbKyKcVAAAAcMopBCw7d+5UQUGBNU2YMKHWQ+Tk5Cg2NtaaPvvsM2VlZdVYdsJimqYMw6j1b1u3blV5ebl69+5tLUtMTFTnzp1rrDtixAitX79eX3/9tVatWqX09HRlZmbq8OHDJzy+O8ZhCUCh8XHWvBERbs1XHjxkzdOTUiMJ9l+FHOA+yFhIQrw1b5YeseZdpaWOlgloDCHHB4wMiW1mLav8+Wdrnud4I+E57qiQuLhal1cWFFa/CLL35FQGjoyPj1d8fPyJV5aUlZWl4cOHW69HjBih6667TsOGDbOWtW3bVpKUkpKi8vJyHTp0yKOWZd++ferTp0+t+zdN708gISFB6enpkqT09HTl5uYqNTVV8+bN05gxY7zaBzUsAAAAQBOSmJio9PR0a4qOjlbr1q1rLJOknj17Kjw8XEuXLrW237Nnj7799ts6A5b09HSFh4dr9erV1rJDhw5p8+bNJy1b6PEfJktt/Pjo04Dl008/1eDBg9WmTRsZhqG//e1vHn83TVNTpkxRmzZtFB0drYyMDG3cuNH6+8GDB3X//ferc+fOiomJUVpamh544AEVFBTUeryysjL16NFDhmFo/fr1jXhmjczlsib3cSqMsHBrAjwEat6wy6yeDMOajNBQj5oYICCFGFKIIbOiwpqq7m3ubwS0utoJVVZaU1Df637WS1hCQoJGjx6tcePG6ZNPPtG6det0yy23qFu3burfv3+t28TGxmr06NEaP368PvnkE3377bcaNWqUQkJqhhYlJSXKz89Xfn6+vv76a917772KioryaOR/Mj4NWIqLi3Xuuefq1VdfrfXvzz33nF588UW9+uqrWrNmjVJSUjRgwAAr52337t3avXu3nn/+eW3YsEFz5szRRx99pNGjR9e6v0cffVRt2rRptPMBAAAATsQfR7p/6aWXdM0112j48OG6+OKLFRMTow8++MCqDanNtGnTdOmll2rIkCHq37+/LrnkEvXs2bPGejNnzlRqaqpSU1N12WWX6aefftLixYtrbe9SF8O0k4TWiAzD0MKFC3XNNddIOla70qZNG2VnZ+uxxx6TdKyGJDk5Wb///e91991317qf+fPn65ZbblFxcbHCwqqb6Hz44Yd6+OGH9d577+mcc87RunXr1KNHD6/LV1hYqISEBGVoqMIM39ZghLrng7rdSB45/mVHBAQijzYsbve6WV5ePX+8G0dy/BHIQo6nYxjH27JIkumWIuFyu+eBgOJWsxLq1hZRbs9sl9t3loYc+b7CPKoVWqSCggKv2no4qeq7ZJexOQqNjLK1bWXZEf37jxP98ryc4LeN7rdt26b8/HyP6qLIyEj169dPX3zxRZ0BS9Ub6R6s7N27V3feeaf+9re/KSYmxqvjl5WVefRtXVhYeIK1nWW697kdjFWpaNLcuy12D8IV4tZTifXPkIAFgcs8WnFshq660dS4pR+bJSXVy/nOckx9UryC/DHht43uq/p9Tk5O9lh+oj6hDxw4oN/97ncewYxpmho1apSysrJ0wQUXeH38qVOnevRz3b59+3qcBQAAAFDNqOcUzPw2YKnyy/6f6+oTurCwUIMGDdLZZ5+tyZMnW8tfeeUVFRYW1tlPdV0mTJjg0c/1zp0763cCjcBjAD23yVVebk1Ak+DWWYBZXl49VRxt0BQCwCdqGfTXdbTCmoCmxr2joKrnOM9yeMNvA5aUlBRJqlGbsm/fvhq1LocPH9bAgQMVGxurhQsXKjy8uo3JsmXLtHr1akVGRiosLMzqB/qCCy7QyJEj6zx+ZGSk1de1t31eAwAAACfkZ72EBQK/DVg6dOiglJQUjz6hy8vLtXLlSo8+oQsLC5WZmamIiAi9//77iorybMT08ssv6+uvv9b69eu1fv16LV68WJI0b948PfPMM86cTAMzQgxrqu0XuoDruhbwgkfNItCEeNzbPMfRlHF/S/LPXsL8nU8b3RcVFWnLli3W623btmn9+vVKTExUWlqasrOzlZOTo06dOqlTp07KyclRTEyMbr75ZknHalYyMzNVUlKiN998U4WFhVbj+FatWik0NFRpaWkex4yNjZUkdezYUe3atXPoTAEAAADR6L4efBqwfPXVV7rsssus1w8//LAkaeTIkZozZ44effRRlZaW6t5779WhQ4fUq1cvLVmyRHHHuzrNy8vTv/71L0myUr2qbNu2TaeffrozJwIAAAB4K8gDELv8ZhwWf+dP47C492/uPmaFx5gUQV7diibC/V5369aY8VdOwH1kaZ4DAcHjOe6e8sj71zj4jDjL4ed4IIzD0vWuHIVG2ByHpfyIvn09eMdh8ds2LAAAAADgtwNHAgAAAE0ObVhsI2AJcKSBOSxQUwkCtdxu6B0Mdaq6vwP03vbQFM4BqAPP8WPq0+sXvYQBAAAAcAY1LLYRsAAAAAAOoYbFPgKWAOTey4Z7qo9ZQSoBmpY6e8EDahNoqY9V5XUvt7jPG5tnT1U+LEiQcH+Ou38ug/raU8NiG72EAQAAAPBb1LAAAAAATqGGxTYClgDnUbXtw3LAvzWFFIimcA5O4DoB8CuBkJ7pMNqw2EfAAgAAADiFGhbbCFgAAAAAhximKcO0F4HYXb+pIWAJQO69JTEIE7wRqPeJWXHU10UAGs/xVBl6eHRWoD4PAxU9PNaCGhbb6CUMAAAAgN+ihgUAAABwCI3u7SNgCXT0vuGsQL3egVpu2BaU6S7c37CD+wW+RkqYbQQsAAAAgEOoYbGPgAUAAABwCjUsthGwBDrDrd8EqrnR1HB/28d1Cjzc5wgW3OuSqGGpD3oJAwAAAOC3qGEBAAAAnEJKmG0ELAHOCDGseZOxmdCUkUqAJsrjOe7iPkcT4/bs5jtLtWBP8bKLgAUAAABwimkem+xuE8QIWAAAAACH0OjePgKWABeUg8QhOJEegybK4znOfY4mjO8sqC8CFgAAAMApNLq3jYAFAAAAcIjhOjbZ3SaYEbAEOtIH0JRxfyMYcJ+jKeP+rokaFtsIWAAAAACH0OjePgIWAAAAwCl0a2wbAQtgR6AOXhio5YZ9wfxeB/O5w3vcJ0DAIWABAAAAHEJKmH0ELAAAAIBTaHRvGwELACCwuaf4AICfo4bFPgIWAAAAwCk0ureNgCXQ0XjQWYF6jQO13LDPX9/rqmdVY5TPX8/ZWzzHncU19h3udUnUsNQH9egAAAAA/BY1LAAAAIBTaHRvGwELAP9VV2PqIE4lCCRGaKjbi2PvpVnBe/dLRohhzZsuUmbQxLg9xz3u9UpfFMY/kBJmHwELAAAA4BSXeWyyu00QI2ABAAAAnEJKmG0ELIGOlAE0ZdzfAc2sdM/5COL8j5PwvE5AE+P2HA/mNDB3huqREtYoJQkc9BIGAAAA4JRlZGQoOzu7wfdLwAIAAAA4pWrgSLtTIyorK9P999+vli1bqlmzZhoyZIh+/PHHU95vRkaGDMOQYRgKCQlRcnKybrjhBu3YscPWfghYgABkhIZaU0hERK2TERZuTTJCqqd6HzTE3tTA59nQ+waABsGzCTZV9RJmdzoVGRkZmjNnTp1/z87O1sKFC/Xuu+9q1apVKioq0tVXX63KBkhZvfPOO7Vnzx7t2rVLixYt0s6dO3XLLbfY2gefLgAAAMApZj2nRlJQUKDc3Fy98MIL6t+/v8477zy9+eab2rBhg/75z3/WuV1xcbFuu+02xcbGKjU1VS+88EKt68XExCglJUWpqam66KKLNHbsWK1du9ZWGf06YJkyZYpVjVQ1paSkWH9fsGCBrrjiCrVs2VKGYWj9+vUe2x88eFD333+/OnfurJiYGKWlpemBBx5QQUGBw2cCAAAASIZp1muSpMLCQo+prKzslMuTl5eno0ePKjMz01rWpk0bde3aVV988UWd240fP17Lly/XwoULtWTJEq1YsUJ5eXknPNbBgwc1f/589erVy1YZ/TpgkaRzzjlHe/bssaYNGzZYfysuLtbFF1+sZ599ttZtd+/erd27d+v555/Xhg0bNGfOHH300UcaPXq0U8VHU+MnVf+my6yeKitPOjXQQaunU1nH1iGrzxNe8pN7FDbwngW2Bn7uNWnc68e46jlJat++vRISEqxp6tSpp1yc/Px8RUREqEWLFh7Lk5OTlZ+fX+s2RUVFys3N1fPPP68BAwaoW7dumjt3bq0pZDNmzFBsbKyaNWumpKQkbdq0SbNmzbJVRr/v1jgsLMyjVsXdrbfeKknavn17rX/v2rWr3nvvPet1x44d9cwzz+iWW25RRUWFwsL8/vQBAAAASdLOnTsVHx9vvY6MjKx1vZycHOXk5FivS0tLtXr1at13333Wsg8//FB9+/at81imacowau9QeevWrSovL1fv3r2tZYmJiercuXONdUeMGKFJkyZJkvbu3aucnBxlZmYqLy9PcXFxdR7fnd9/Y//+++/Vpk0bRUZGqlevXsrJydEZZ5xR7/0VFBQoPj7+pMFKWVmZRzVbYWFhvY8JAAAASPJI8bKzjSTFx8d7BCx1ycrK0vDhw63XI0aM0HXXXadhw4ZZy9q2bStJSklJUXl5uQ4dOuRRy7Jv3z716dOn1v2bNsqfkJCg9PR0SVJ6erpyc3OVmpqqefPmacyYMV7tw6/r5Hr16qU///nP+vjjjzVz5kzl5+erT58+OnDgQL32d+DAAf3ud7/T3XfffdJ1p06d6lHl1r59+3odE02LEWJYk0+5pSDUmQbmtk6Dl9s9BaIx0yGcOk4TEpQ9qzVSL3VoQtzuDY8eFNH4+FzW5ECj+8TERKWnp1tTdHS0WrduXWOZJPXs2VPh4eFaunSptf2ePXv07bff1hmwpKenKzw8XKtXr7aWHTp0SJs3bz5p2UJDQyUdq/Xxll/XsFx55ZXWfLdu3dS7d2917NhRc+fO1cMPP2xrX4WFhRo0aJDOPvtsTZ48+aTrT5gwweMYhYWFBC0AAAA4NfUZV6URx2FJSEjQ6NGjNW7cOCUlJSkxMVGPPPKIunXrpv79+9e6TWxsrEaPHq3x48crKSlJycnJmjRpkkJCagamJSUlVluYvXv36umnn1ZUVJRHI/+T8euA5ZeaNWumbt266fvvv7e13eHDhzVw4EDFxsZq4cKFCg8/+a8qkZGRdeYFAgAAAPVRn3FVTnUclpN56aWXFBYWpuHDh6u0tFSXX3655syZY9WG1GbatGkqKirSkCFDFBcXp3HjxtXaE+/MmTM1c+ZMSVKLFi3UvXt3LV68uNb2LnUJqIClrKxM//73v0/YQOiXCgsLdcUVVygyMlLvv/++oqKiGrGEaJLcq7E9qrQbqPetxuJWVvfUB48et0ivahrc32u3fy4N1kNcgHBPeTQD6dT5HDrK4z5xf6bzPjQ+rvExPqhhWbFixQn/HhUVpVdeeUWvvPKK1/uMjY3VX/7yF/3lL3+xlo0fP97Wcb3l1wHLI488osGDBystLU379u3T008/rcLCQo0cOVLSsb6cf/jhB+3evVuStGnTJknHGg+lpKTo8OHDyszMVElJid58802rz2pJatWq1QmjRgAAAAC+59cBy48//qibbrpJ+/fvV6tWrXTRRRdp9erVOu200yRJ77//vm6//XZr/d/85jeSpMmTJ2vKlCnKy8vTv/71L0myeieosm3bNp1++unOnAgAAAAgyXAdm+xuE8z8OmB59913T/j3UaNGadSoUXX+PSMjw1a3awCAwOPzXvvg/9xSkRiI1mGkgdXkZ43uA4FfBywAAABAk1KPboptr9/EELAAAAAADjmVgSODFQELcDLuqQSN2fNQI/ZW49FbFNXzTVowvtek+MAW989FkHxG4GdICbONYUcBAAAA+C1qWAAAAACnmJLsVu4FdwULAUvAY9Crxuc+KF9jDkzX0O+fU6ls8D2PFJfg6zGrtl7CuOdRF1II4Wu0YbGPgAUAAABwiql6tGFplJIEDAIWAAAAwCk0ureNgAU4Cfd0k5DoaGveVVpqzXv0zOQv3FLZQqIirXnzaEX1fMVRR4tkGymP3nFPW4yIqF4eSO/1KTBCQ4/NhFX/SzNLj1Sv4O/3Dve5o0LcPiPuz+6m/BnxKaOO/p2C+V53SbKbvRvEl0uilzAAAAAAfowaFgAAAMAhNLq3j4AlENVVvYpG4d6jjN+ngblz7yWsvNxtcQA99II5ZcAOf3qvfZDe5Dqe+mYE6qCZgVTWJsA99SugnoeBivu7Jtqw2EbAAgAAADiFgMU2AhYAAADAKQQsthGwBCL36lXSwxpfExiA0e/T1+pC70m2+fy9rut9qu1Z1VDv6fH9BOrnk/vcWT7/jNjhzf947pnAQy9htvFtFwAAAIDfooYFAAAAcAi9hNlHwBKISANzVlMY9IqUk+DhR++1NaCjJCMs/NiMe4plXT001VHuutavOo7ZUL2E1fKZdx9A1nbPUnbKUtf754vUoED9X+Pvz7iTfUabwv8cnBhtWGwjYAEAAACc4jIlw2YAEuRdcBOwBCK3X1ncf8E0Xf7zy2pTFRJe/ZFxuY134ZfcfqXzKPfxMSskBdR9Yv1CL7df0gOo/I3K/b2OiLDmPe5RH1wr9xqPxm3ofOw56PE8rDiF863lWjVmg3732ps6j+mLe70pfb7cPiMe94kvxu452XGa0nX/Bc/vLG5fwJvwOdeKGhbbCFgAAAAAx9QjYFFwBywBmqAKAAAAIBhQw9KQvGnsaqcxnRfrulepejYKrWejvpOVye5+mkA1r/t1NdzSbQzH0l3qx6Pc0dHV864Sa/6U0mYc4JEq434vNYH7qrEYUZHWfIjbdfL7FMZTYN0nYdX/0syKoz4qjX11Pcf9qQOFpsSIqE4vlXvWpJ8/DwMWnQjUREqYbQQsAAAAgFNcpmyneNHoHgAAAIAjTJf9GqZgrpESAUv91VbF2dA3X1198NeRJuCRBlaXk5W7ofvdbwJVwR5jScTFVs+79bbVqClh9U0Lce8VJ9Itlc0tNahB0mYacawGj+ta12cgGJzkffdI/3NLCZP79WvCKWE6/hkNcUt9NMvKquf9MGXTg/tz3M+LGqjcPyMhzWKseZfcU2T9MI3wVFLN3fnJ/1y//yw6hZQw2whYAAAAAKeQEmZbkP1MCQAAACCQUMNilxFSd/Wr3TSV+qa12K3aPdlxGup87Aig3m88Brcy3HrwqWOwtwbRENfeo1etOs6hIZxKmoKd/Z2st7uGTm1szFTJBuZxj7r1lOUxb1dDX8NGZKVtuvf+hMbXUM/xqv049b/A7XPhnvJbb3V8VuoaELT++z6VsjbAeZ5MHe+f5//Qkz9XbF23Wu5Bw3RJ/p55RkqYbQQsAAAAgFNM1SNgaZSSBAwCFgAAAMAp1LDYRsBil+mS5KcpTH6eWtUkuKdTNXRqlbsGeC89quHDq1NljHCH0mYa4n48WcqJnfSxUxGgn61TSnep7zl70aOhrX14USbTdTwVJLz2VB/HeiZqzF4R/TwtsUHKZ3cfNq6rWVeD5YZICavrvmyQ287fc5ts8uKZYO+61VzZDISu9lz1+C7pCsz/Qw2FgAUAAABwCjUstvn5TzYAAAAAghk1LIGoCQzGGEjc00nMxHhr3mhePYikvtvitoGfvA/ug9ElxFnzrnYtrXlj7X+O/d0fB0yT/Oda+jv36xQdZc1WpLWy5kPyDlvzrsYcRLIh3jPbg/Ae++Wxwu3edv/n5vrhx1Mvk1flaMT7lc/CqXG/fjHVA4y62lZ/Roz1xdWr++szMRD5ezqjL1DDYhsBCwAAAOAUBo60jYAFAAAAcIhpumTarDW1u35TQ8BiV20DR/rLTdTQA/V5k3p2sh4/AmiAyDq5lbu4Q3VK2E89qj8+HfIPWPMVB6rn/UVl8+oUiG1Dmlnznfa3lSRV/He700VCI6lsXv3+br0hxpo/8+fTq1f69+ZTP5AfpXmYRyskSQfOqT5fo0uaNd/yL/us+QZJh3Pq3ANo8NJA4oqvfh7uGFydLnvGz+2t+Yot/3W0TEEjUL8HNDTTtF9jQkoYAAAAAEeY9UgJC/KAhZ9sAAAAAPgtaljqy5fVmk4d25vjnGydJlD96z4AXVhp9fl0y6xOq9l4tLM13/7FtZIkV9kRL3beeL8ZGCHVA1uGFFenwbTsUd0Tzqb7UiVJZ06uTmOrPFzdm9QJdt4AJfTCye4f0mQk/eK9Lqvu3ah1l5+s+f88lmDNdxmXZM3XO4XRjz7bRmiEJCm8tPoXyMQxO6z5ov3nWfPRf//Kmq/3gJK+OHc/ut4Bye1ZYZRXWPMVZ5ZY8/+5v7U13/mpQ9Z85cHqedSDU/eu9R6H2K68cJzLJRl2e0MM7mcAAQsAAADgFFLCbCNgAQAAABxiulwybdaw0EsYbAmJjlSIEaGQhOreomQYdW/wS3bWrYtbLzdVveNIkuE2GJZC3FJlXG43eVUKRIjNVJq61neP+KvOzf0c3f/uNm8eLqouUlGx2zr+94E03XryiPzyP9b8pvndrflvH/uTNX92+D2SpNP/sNFaVllYnWblnr7jnm7mkd4U0gD3iRvz++3WfPhr1eWe/dJrkqSR0XdZy7o8u9uad+3bX70P93vNvXx1pWU1xDm4p+w0RPpXA19Xv+H2mTO3VKdCRU3vas1/9sZL1nzm61nW/OmPN7fmXT/sqt7P8YHzQqLdnivu92uo/6TjVX2OElf8YC37LqOtNb/hjy9b8/0Tsq35xIXfWvOukurUICMiono+7Pi/SfdnoPsz7lTuqcrjzzv3+zys+t+y+/PBmy8rxvHPiK+/2Bhun9W6ymI0wOfZfd+17c/j2G7PcXNb9UCip73RxZof86f/Z81PjLremu/y2+r1zePPcvd0Qo/PSJjbZ6Su/5vu909d/y9rU9v/2xMtr22duo5R13Z1Hd/OumVuPfO5f17Cw2vf9mT7duf2/cYsKT1+6HKp4OSb+hQ1LLb5z38cAAAAAPgFalgAAAAAp7hMyaCGxQ7DNIPnCsyYMUPTpk3Tnj17dM4552j69Onq27evV9sWFhYqISFBl4VdrzAjXCFRkfUrRAOkhJkV1ak57tXcRoRb9ap7VXR9e8KpizdV0Sdhllf3ZORVb1r+wi3tIDS2eoC+XaO7WfMpQ46lpRTMrh6ELOmT7bXvL9ztNwP36vHQOtJPTsb9/ahwe9/dUtLM0urrfXDYsXJf++g/rWWvfZlhzZ/1anW6nrG9Ol3IcDt3RVanz3jcd3ZShtzPsdItjcOtrB77q0qV8UjN8eJ4IV6kYlQt9+bR6M17Y+cR657aZeN9N9zS9cz9B6vny8qs+YJrzrXmx06Zb81P3TjQmk+dXv1ehn+7/di+3dPA3NKVvEohccrRY88TV0H1fR6S1MKa//fUNtZ8/y7VaZ3/mVqdMhe70m0wTffnatX5u6f6eKRy2jx39/vh+LPZPFr9PDQi3f63eHNPn+wZ7E0akbuGeC/tpDmdyjFPtm/3/bqnDrmlJLv/Py0eWJ0u2yK7OrXy2/WnW/Nnzio8NvMft4El63quuBfFm/Qwf/k61sApYR698bmt7/FsaYBzrzpOhVmuZaXzVFBQoPj4+JNs5ayq75K/jrhBYcZJUuJ+ocI8qmXl8/3yvJwQNClh8+bNU3Z2tiZNmqR169apb9++uvLKK/XDDz+cfGMAAACgAZgus15TIMjIyFB2dnaD7zdoApYXX3xRo0eP1pgxY9SlSxdNnz5d7du315/+9KeTbwwAAAA0BNNVv6kRlZWV6f7771fLli3VrFkzDRkyRD/++OPJNzyJjIwMGYYhwzAUEhKi5ORk3XDDDdqxY8fJN3YTFClh5eXliomJ0fz583Xttddayx988EGtX79eK1eurLFNWVmZytzSKQoLC9W+fXtlaKjtajw0fe5V21U9yBlRUdYy9xQE996IHPvFpK6eeo6X273XOyMmxpp3uQ2Y5ioNoNS9IOPea5vHPeXei1It96jkmd5nHvzZmq8sLqmxj4Dilr4Z4pZ6GdI8wW2d6uvm+rmwej6Q0lTRYDw+I3Fx1cvjY61583jaoXvPjwH7GWmiKsyjWqFFfpk6VZUSlmFcW6+UsBXmwnqfV0ZGhkaNGqVRo0bV+vd77rlHH3zwgebMmaOkpCSNGzdOBw8eVF5enkLd0/e8OE6PHj00ffp06/WZZ56p3/72tzJNUzt27FB2drbCw8P12Wefeb3foKhh2b9/vyorK5WcnOyxPDk5Wfn5+bVuM3XqVCUkJFhT+/bta10PAAAACFQFBQXKzc3VCy+8oP79++u8887Tm2++qQ0bNuif//xnndsVFxfrtttuU2xsrFJTU/XCCy/Uul5MTIxSUlKUmpqqiy66SGPHjtXatWttlTGoegkzftE4zDTNGsuqTJgwQQ8//LD1uqCgQGlpaarQUdtdZ6PpM9x+YQtxHetz3nC5j0VQ3Q+9yzzqttzHNSzHl1eVWZIMV/UvKa46yg3/YphuNSxmHTUstdyjkmS4qv8NuN+nlVXvd8D+euxWw+J2TdzP3aOGhXs96Hl8Rkz3z0h1tkXVZ6TS/R4J2M9I01ShY++NPycQVZhltu+bqvMqLCz0WB4ZGanIyHp2BHVcXl6ejh49qszMTGtZmzZt1LVrV33xxRe64oorat1u/PjxWr58uRYuXKiUlBRNnDhReXl56tGjR53HOnjwoObPn69evXrZKmNQBCwtW7ZUaGhojdqUffv21ah1qfLLG6DqBlmlxY1XUAQu947YDtW5lv+pKrd7mQOp/DjGm44A67pHm+r77f5dxS1G0U9OFwQBw/0z8nMd8wgYhw8fVkJCwslXdFBERIRSUlK0Kr9+3yVjY2NrZPxMnjxZU6ZMOaVy5efnKyIiQi1atPBYfqJMpKKiIuXm5urPf/6zBgwYIEmaO3eu2rVrV2PdGTNm6I033pBpmiopKdGZZ56pjz/+2FYZgyJgiYiIUM+ePbV06VKPNixLly7V0KFDvdpHmzZt9N133+nss8/Wzp07/S4v0p9UtffhOp0c18o7XCfvcJ28w3XyDtfJO1wn7zlxrUzT1OHDh9WmTZuTr+ywqKgobdu2TeXl5SdfuRa1ZQbVVbuSk5OjnJwc63VpaalWr16t++67z1r24YcfnnB4jxNlIm3dulXl5eXq3bu3tSwxMVGdO3euse6IESM0adIkSdLevXuVk5OjzMxM5eXlKc6tvdiJBEXAIkkPP/ywbr31Vl1wwQXq3bu3Xn/9df3www/KysryavuQkBC1bdtWkhQfH89DyQtcJ+9xrbzDdfIO18k7XCfvcJ28w3XyXmNfK3+rWXEXFRWlKLdOeRpLVlaWhg8fbr0eMWKErrvuOg0bNsxaVvW9NiUlReXl5Tp06JBHLcu+ffvUp0+fWvdvJ+UuISFB6enpkqT09HTl5uYqNTVV8+bN05gxY7zaR9AELDfeeKMOHDig3/72t9qzZ4+6du2qxYsX67TTTvN10QAAAIAGk5iYqMTEROt1dHS0WrdubQUO7nr27Knw8HAtXbrUCnL27Nmjb7/9Vs8991yt+09PT1d4eLhWr16ttLQ0SdKhQ4e0efNm9evX74Rlq+p1rLS01OvzCZqARZLuvfde3Xvvvb4uBgAAAOAXEhISNHr0aI0bN05JSUlKTEzUI488om7duql///61bhMbG6vRo0dr/PjxSkpKUnJysiZNmqSQkJodEJeUlFhtYfbu3aunn35aUVFRHo38TyaoApZTFRkZqcmTJ59ybwxNHdfJe1wr73CdvMN18g7XyTtcJ+9wnbzHtfJfL730ksLCwjR8+HCVlpbq8ssv15w5c044Bsu0adNUVFSkIUOGKC4uTuPGjVNBQUGN9WbOnKmZM2dKklq0aKHu3btr8eLFtbZ3qUtQDBwJAAAAIDAFxcCRAAAAAAITAQsAAAAAv0XAAgAAAMBvEbAAAAAA8FsELDbMmDFDHTp0UFRUlHr27KnPPvvM10XyGbvXoqysTJMmTdJpp52myMhIdezYUbNmzXKotL7x6aefavDgwWrTpo0Mw9Df/va3E66/YMECDRgwQK1atVJ8fLx69+6tjz/+2JnC+pDd6yRJb731ls4991zFxMQoNTVVt99+uw4cOND4hfWhqVOn6le/+pXi4uLUunVrXXPNNdq0aZPX23/++ecKCwtTjx49Gq+Qfu5Pf/qTunfvbg1a17t3b3344Ye+LpZP1OdaBONz/JemTp0qwzCUnZ1d5zrB+ix35811koLzWY76IWDx0rx585Sdna1JkyZp3bp16tu3r6688kr98MMPvi6a4+pzLYYPH65PPvlEubm52rRpk9555x2dddZZDpbaecXFxTr33HP16quverX+p59+qgEDBmjx4sXKy8vTZZddpsGDB2vdunWNXFLfsnudVq1apdtuu02jR4/Wxo0bNX/+fK1Zs8br0XID1cqVKzV27FitXr1aS5cuVUVFhTIzM1VcXHzSbQsKCnTbbbfp8ssvd6Ck/qtdu3Z69tln9dVXX+mrr77Sr3/9aw0dOlQbN270ddEcV59rEYzPcXdr1qzR66+/ru7du59wvWB9llfx9joF67Mc9WTCKxdeeKGZlZXlseyss84yH3/8cR+VyHfsXosPP/zQTEhIMA8cOOBE8fySJHPhwoW2tzv77LPNp556quEL5Ke8uU7Tpk0zzzjjDI9lL7/8stmuXbtGLJn/2bdvnynJXLly5UnXvfHGG80nnnjCnDx5snnuuec2fuECSIsWLcw33njD18XwCye6FsH+HD98+LDZqVMnc+nSpWa/fv3MBx980Nb2wfIst3OdeJbDDmpYvFBeXq68vLwaI3JmZmbqiy++8FGpfKM+1+L999/XBRdcoOeee05t27bVmWeeqUceeUSlpaVOFDlguVwuHT58WImJib4uil/p06ePfvzxRy1evFimaWrv3r3661//qkGDBvm6aI6qGpzrZPfH7NmztXXrVk2ePNmJYgWMyspKvfvuuyouLlbv3r19XRyf8uZaBPtzfOzYsRo0aFCdo36fSDA9y+1cJ57lsIOR7r2wf/9+VVZWKjk52WN5cnKy8vPzfVQq36jPtfjvf/+rVatWKSoqSgsXLtT+/ft177336uDBg0GX/2zHCy+8oOLiYg0fPtzXRfErffr00VtvvaUbb7xRR44cUUVFhYYMGaJXXnnF10VzjGmaevjhh3XJJZeoa9euda73/fff6/HHH9dnn32msDAe95K0YcMG9e7dW0eOHFFsbKwWLlyos88+29fF8gk71yKYn+Pvvvuu1q5dqzVr1tRr+2B5ltu9TjzLYQc1LDYYhuHx2jTNGsuChZ1r4XK5ZBiG3nrrLV144YW66qqr9OKLL2rOnDlB8+ucXe+8846mTJmiefPmqXXr1r4ujl/57rvv9MADD+jJJ59UXl6ePvroI23btk1ZWVm+Lppj7rvvPn3zzTd655136lynsrJSN998s5566imdeeaZDpbOv3Xu3Fnr16/X6tWrdc8992jkyJH67rvvfF0sn7BzLYL1Ob5z5049+OCDevPNNxUVFWV7+2B5ltfnOvEshy0+TUgLEGVlZWZoaKi5YMECj+UPPPCAeemll/qoVL5Rn2tx2223mR07dvRY9t1335mSzM2bNzdaWf2JbLRheffdd83o6Gjz73//e+MWyg95c51uueUW8/rrr/dY9tlnn5mSzN27dzdi6fzDfffdZ7Zr187873//e8L1Dh06ZEoyQ0NDrckwDGvZJ5984lCJ/dvll19u3nXXXb4uhl840bUI1uf4woULa3yOJJmGYZihoaFmRUVFndsG07O8Ptcp2J/lsIcaFi9ERESoZ8+eWrp0qcfypUuXqk+fPj4qlW/U51pcfPHF2r17t4qKiqxlmzdvVkhIiNq1a9eo5Q0077zzjkaNGqW3336bPN46lJSUKCTE89EVGhoq6VhNX1Nlmqbuu+8+LViwQMuWLVOHDh1OuH58fLw2bNig9evXW1NWVpb1q3qvXr0cKrl/M01TZWVlvi6GXzjRtQjW5/jll19e43N0wQUXaMSIEVq/fr317PmlYHuW1+c6BeuzHPXk03ApgLz77rtmeHi4mZuba3733Xdmdna22axZM3P79u2+LprjTnYtHn/8cfPWW2+11j98+LDZrl078/rrrzc3btxorly50uzUqZM5ZswYX52CIw4fPmyuW7fOXLdunSnJfPHFF81169aZO3bsME2z5nV6++23zbCwMPOPf/yjuWfPHmv6+eeffXUKjrB7nWbPnm2GhYWZM2bMMLdu3WquWrXKvOCCC8wLL7zQV6fgiHvuucdMSEgwV6xY4XF/lJSUWOv88lr9UrD3EjZhwgTz008/Nbdt22Z+88035sSJE82QkBBzyZIlvi6a4052LXiO1+2XvV/xLK/dya5TsD7LUT8ELDb88Y9/NE877TQzIiLCPP/8873qTrSpOtG1GDlypNmvXz+P9f/973+b/fv3N6Ojo8127dqZDz/8sMcXraZo+fLlpqQa08iRI03TrHmd+vXrd8L1myq718k0j3V9efbZZ5vR0dFmamqqOWLECPPHH390vvAOqu0aSTJnz55trVPbtXIX7AHLHXfcYT23WrVqZV5++eVBGayY5smvBc/xuv3yizjP8tqd7DqZZnA+y1E/hmlS7wYAAADAP9GGBQAAAIDfImABAAAA4LcIWAAAAAD4LQIWAAAAAH6LgAUAAACA3yJgAQAAAOC3CFgAAAAA+C0CFgAAAAB+i4AFAJqwKVOmqEePHr4uBgAA9cZI9wAQoAzDOOHfR44cqVdffVVlZWVKSkpyqFQAADQsAhYACFD5+fnW/Lx58/Tkk09q06ZN1rLo6GglJCT4omgAADQYUsIAIEClpKRYU0JCggzDqLHslylho0aN0jXXXKOcnBwlJyerefPmeuqpp1RRUaHx48crMTFR7dq106xZszyOtWvXLt14441q0aKFkpKSNHToUG3fvt3ZEwYABCUCFgAIMsuWLdPu3bv16aef6sUXX9SUKVN09dVXq0WLFvrXv/6lrKwsZWVlaefOnZKkkpISXXbZZYqNjdWnn36qVatWKTY2VgMHDlR5ebmPzwYA0NQRsABAkElMTNTLL7+szp0764477lDnzp1VUlKiiRMnqlOnTpowYYIiIiL0+eefS5LeffddhYSE6I033lC3bt3UpUsXzZ49Wz/88INWrFjh25MBADR5Yb4uAADAWeecc45CQqp/r0pOTlbXrl2t16GhoUpKStK+ffskSXl5edqyZYvi4uI89nPkyBFt3brVmUIDAIIWAQsABJnw8HCP14Zh1LrM5XJJklwul3r27Km33nqrxr5atWrVeAUFAEAELACAkzj//PM1b948tW7dWvHx8b4uDgAgyNCGBQBwQiNGjFDLli01dOhQffbZZ9q2bZtWrlypBx98UD/++KOviwcAaOIIWAAAJxQTE6NPP/1UaWlpGjZsmLp06aI77rhDpaWl1LgAABodA0cCAAAA8FvUsAAAAADwWwQsAAAAAPwWAQsAAAAAv0XAAgAAAMBvEbAAAAAA8FsELAAAAAD8FgELAAAAAL9FwAIAAADAbxGwAAAAAPBbBCwAAAAA/BYBCwAAAAC/9f8BvA1IzgFWgrYAAAAASUVORK5CYII=", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#verify loaded data\n", - "sample=x[420]\n", - "showSpec(sample)\n", - "playSpec(sample)" - ] - }, - { - "cell_type": "code", - "execution_count": 85, - "id": "03accbb9-48b7-40d9-85be-9ed6a92d2e86", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The autoreload extension is already loaded. To reload it, use:\n", - " %reload_ext autoreload\n" - ] - } - ], - "source": [ - "from tinygrad import TinyJit, Device, Tensor, nn\n", - "from tinygrad.nn.state import safe_save, get_state_dict\n", - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": 271, - "id": "bcf1bec0-be3f-411b-8324-7877f0ead016", - "metadata": {}, - "outputs": [], - "source": [ - "import model as m\n", - "import importlib\n", - "importlib.reload(m)\n", - "model = m.Model(latent_dim=16)\n", - "optimizer = nn.optim.AdamW(nn.state.get_parameters(model), lr=1e-4)" - ] - }, - { - "cell_type": "code", - "execution_count": 272, - "id": "ea3a98ca-756b-4658-9c4a-3cbc36c61cdc", - "metadata": {}, - "outputs": [], - "source": [ - "@TinyJit\n", - "def jit_step(X: Tensor, Y: Tensor,epoch) -> Tensor:\n", - " Tensor.training = True\n", - " optimizer.zero_grad()\n", - " _, loss = model.__Lcall__(X,Y,epoch)\n", - " loss.backward()\n", - " optimizer.step()\n", - " return loss.realize()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 279, - "id": "fb21b4bd-73b5-48be-99bd-6099a7a7e30c", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "--- Starting Epoch 0 rate of 0---\n", - "\n", - "--- Starting Epoch 1 rate of 0.024080323055386543---\n", - "\n", - "--- Starting Epoch 2 rate of 0.02331373281776905---\n", - "\n", - "--- Starting Epoch 3 rate of 0.023173624649643898---\n", - "\n", - "--- Starting Epoch 4 rate of 0.02290959469974041---\n", - "\n", - "--- Starting Epoch 5 rate of 0.022660640999674797---\n", - "\n", - "--- Starting Epoch 6 rate of 0.022699641063809395---\n", - "\n", - "--- Starting Epoch 7 rate of 0.022513432428240776---\n" - ] - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mKeyboardInterrupt\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[279]\u001b[39m\u001b[32m, line 22\u001b[39m\n\u001b[32m 20\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m(tx.shape != eshape \u001b[38;5;129;01mor\u001b[39;00m ty.shape != eshape):\n\u001b[32m 21\u001b[39m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m22\u001b[39m l+=\u001b[43mjit_step\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtx\u001b[49m\u001b[43m,\u001b[49m\u001b[43mty\u001b[49m\u001b[43m,\u001b[49m\u001b[43me\u001b[49m\u001b[43m)\u001b[49m.numpy()\n\u001b[32m 23\u001b[39m l /= BACH_SIZE\n", - "\u001b[36mFile \u001b[39m\u001b[32m/nix/store/khnvx4lwxjcrq6n0kllvbry5q64v8dcz-python3.12-tinygrad-0.10.2/lib/python3.12/site-packages/tinygrad/engine/jit.py:310\u001b[39m, in \u001b[36mTinyJit.__call__\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m 307\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m.captured.expected_names == names, \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33margs mismatch in JIT: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m.captured.expected_names\u001b[38;5;132;01m=}\u001b[39;00m\u001b[33m != \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnames\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 308\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m.captured.expected_st_vars_dtype_device == st_vars_dtype_device, \\\n\u001b[32m 309\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33margs mismatch in JIT: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m.captured.expected_st_vars_dtype_device\u001b[38;5;132;01m=}\u001b[39;00m\u001b[33m != \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mst_vars_dtype_device\u001b[38;5;132;01m=}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m--> \u001b[39m\u001b[32m310\u001b[39m ret = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mcaptured\u001b[49m\u001b[43m(\u001b[49m\u001b[43minput_buffers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvar_vals\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 312\u001b[39m \u001b[38;5;28mself\u001b[39m.cnt += \u001b[32m1\u001b[39m\n\u001b[32m 313\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m ret\n", - "\u001b[36mFile \u001b[39m\u001b[32m/nix/store/khnvx4lwxjcrq6n0kllvbry5q64v8dcz-python3.12-tinygrad-0.10.2/lib/python3.12/site-packages/tinygrad/engine/jit.py:190\u001b[39m, in \u001b[36mCapturedJit.__call__\u001b[39m\u001b[34m(self, input_buffers, var_vals)\u001b[39m\n\u001b[32m 187\u001b[39m \u001b[38;5;28mself\u001b[39m._first_run = \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[32m 189\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m DEBUG >= \u001b[32m1\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m._jit_cache) >= \u001b[32m10\u001b[39m: \u001b[38;5;28mprint\u001b[39m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mjit execs \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m._jit_cache)\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m kernels\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m--> \u001b[39m\u001b[32m190\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m ei \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m._jit_cache: \u001b[43mei\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvar_vals\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mjit\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[32m 191\u001b[39m \u001b[38;5;28mself\u001b[39m._clear_inputs()\n\u001b[32m 192\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m.ret\n", - "\u001b[36mFile \u001b[39m\u001b[32m/nix/store/khnvx4lwxjcrq6n0kllvbry5q64v8dcz-python3.12-tinygrad-0.10.2/lib/python3.12/site-packages/tinygrad/engine/realize.py:127\u001b[39m, in \u001b[36mExecItem.run\u001b[39m\u001b[34m(self, _var_vals, wait, jit, do_update_stats)\u001b[39m\n\u001b[32m 125\u001b[39m var_vals = {} \u001b[38;5;28;01mif\u001b[39;00m _var_vals \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m _var_vals\n\u001b[32m 126\u001b[39m bufs = [cast(Buffer, x) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m.bufs] \u001b[38;5;28;01mif\u001b[39;00m jit \u001b[38;5;28;01melse\u001b[39;00m [cast(Buffer, x).ensure_allocated() \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m.bufs]\n\u001b[32m--> \u001b[39m\u001b[32m127\u001b[39m et = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mprg\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbufs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvar_vals\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwait\u001b[49m\u001b[43m=\u001b[49m\u001b[43mwait\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mDEBUG\u001b[49m\u001b[43m \u001b[49m\u001b[43m>\u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[32;43m2\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m 128\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m do_update_stats:\n\u001b[32m 129\u001b[39m GlobalCounters.kernel_count += \u001b[32m1\u001b[39m\n", - "\u001b[36mFile \u001b[39m\u001b[32m/nix/store/khnvx4lwxjcrq6n0kllvbry5q64v8dcz-python3.12-tinygrad-0.10.2/lib/python3.12/site-packages/tinygrad/engine/realize.py:67\u001b[39m, in \u001b[36mCompiledRunner.__call__\u001b[39m\u001b[34m(self, rawbufs, var_vals, wait)\u001b[39m\n\u001b[32m 65\u001b[39m lra[\u001b[33m'\u001b[39m\u001b[33mlocal_size\u001b[39m\u001b[33m'\u001b[39m] = \u001b[38;5;28mtuple\u001b[39m(local_size)\n\u001b[32m 66\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(local_size) == \u001b[32m3\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mlocal size must have len 3\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m---> \u001b[39m\u001b[32m67\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_prg\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43m[\u001b[49m\u001b[43mx\u001b[49m\u001b[43m.\u001b[49m\u001b[43m_buf\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mrawbufs\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mlra\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvals\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mvar_vals\u001b[49m\u001b[43m[\u001b[49m\u001b[43mk\u001b[49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mp\u001b[49m\u001b[43m.\u001b[49m\u001b[43mvars\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwait\u001b[49m\u001b[43m=\u001b[49m\u001b[43mwait\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m/nix/store/khnvx4lwxjcrq6n0kllvbry5q64v8dcz-python3.12-tinygrad-0.10.2/lib/python3.12/site-packages/tinygrad/runtime/ops_gpu.py:52\u001b[39m, in \u001b[36mCLProgram.__call__\u001b[39m\u001b[34m(self, global_size, local_size, vals, wait, *bufs)\u001b[39m\n\u001b[32m 50\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m local_size \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m: global_size = cast(\u001b[38;5;28mtuple\u001b[39m[\u001b[38;5;28mint\u001b[39m,\u001b[38;5;28mint\u001b[39m,\u001b[38;5;28mint\u001b[39m], \u001b[38;5;28mtuple\u001b[39m(\u001b[38;5;28mint\u001b[39m(g*l) \u001b[38;5;28;01mfor\u001b[39;00m g,l \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(global_size, local_size)))\n\u001b[32m 51\u001b[39m event = cl.cl_event() \u001b[38;5;28;01mif\u001b[39;00m wait \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m52\u001b[39m check(\u001b[43mcl\u001b[49m\u001b[43m.\u001b[49m\u001b[43mclEnqueueNDRangeKernel\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mdev\u001b[49m\u001b[43m.\u001b[49m\u001b[43mqueue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mkernel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mglobal_size\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mctypes\u001b[49m\u001b[43m.\u001b[49m\u001b[43mc_size_t\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mglobal_size\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43mglobal_size\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mctypes\u001b[49m\u001b[43m.\u001b[49m\u001b[43mc_size_t\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mlocal_size\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43mlocal_size\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mlocal_size\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[32;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mevent\u001b[49m\u001b[43m)\u001b[49m) \u001b[38;5;66;03m# noqa: E501\u001b[39;00m\n\u001b[32m 53\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m wait:\n\u001b[32m 54\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m event \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n", - "\u001b[31mKeyboardInterrupt\u001b[39m: " - ] - } - ], - "source": [ - "#_ = jit_step(Tensor(x[0]).reshape(1, 1, 128, 216), Tensor(y[0]).reshape(1, 1, 128, 216))\n", - "size = 200 #len(x)\n", - "\n", - "x_np, y_np = np.stack(x), np.stack(y)\n", - "x_np = np.expand_dims(x_np, axis=1)\n", - "y_np = np.expand_dims(y_np, axis=1)\n", - "x_np.shape\n", - "BACH_SIZE=6\n", - "l=0\n", - "\n", - "eshape = (BACH_SIZE, 1, 128, 216)\n", - "for e in range(0,12):\n", - " print(f\"\\n--- Starting Epoch {e} rate of {l}---\")\n", - " l=0\n", - " permutation = np.random.permutation(size)\n", - " x_np = x_np[permutation]\n", - " y_np = y_np[permutation]\n", - " for i in range(0,size,BACH_SIZE):\n", - " tx,ty=Tensor(x_np[i:i+BACH_SIZE]),Tensor(y_np[i:i+BACH_SIZE])\n", - " if(tx.shape != eshape or ty.shape != eshape):\n", - " continue\n", - " l+=jit_step(tx,ty,e).numpy()\n", - " l /= BACH_SIZE\n" - ] - }, - { - "cell_type": "code", - "execution_count": 280, - "id": "6d55371c-38f5-4c1f-9676-a95c4d2fc130", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "out = model(Tensor(x_np[40:41])).realize().numpy()[0][0]*5\n", - "#out = y[40]\n", - "showSpec(out)\n", - "playSpec(out)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f85e7708-a370-4257-877a-9d26db7ddb56", - "metadata": {}, - "outputs": [], - "source": [ - "type(x[0])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "34d1240c-f98a-4071-84cb-054f509f044f", - "metadata": {}, - "outputs": [], - "source": [ - "print(len(x))" - ] - }, - { - "cell_type": "code", - "execution_count": 163, - "id": "df25973f-4b37-474b-ba03-db675438a976", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.float32(0.0)" - ] - }, - "execution_count": 163, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "x_np.min()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2ae47ee9-42a8-41e4-8535-148292ce0049", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "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": "3.12.11" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/show.py b/show.py new file mode 100644 index 0000000..086ffe4 --- /dev/null +++ b/show.py @@ -0,0 +1,26 @@ +import matplotlib.pyplot as plt +import IPython.display as ipd +import librosa + + +SAMPLE_RATE = 22050 + +def showSpec(spec): + plt.figure(figsize=(10, 4)) + librosa.display.specshow(spec, sr=SAMPLE_RATE, + x_axis='time', y_axis='mel', + cmap='viridis') + plt.colorbar(format='%+2.0f dB') + plt.title('Mel spectrogram') + plt.show() + +def playSpec(spec): + S = librosa.feature.inverse.mel_to_stft(spec, sr=SAMPLE_RATE) + audio = librosa.griffinlim(S,n_iter=25,momentum=0.99) + + plt.figure(figsize=(12,4)) + plt.plot(audio) + plt.title('waveform') + plt.show() + + display(ipd.Audio(audio,rate=SAMPLE_RATE)) diff --git a/train.ipynb b/train.ipynb new file mode 100644 index 0000000..96a7088 --- /dev/null +++ b/train.ipynb @@ -0,0 +1,163 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "0", + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "import data\n", + "import show\n", + "import model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1", + "metadata": {}, + "outputs": [], + "source": [ + "x,y = data.detaset(data.load())\n", + "len(x)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2", + "metadata": { + "editable": true, + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "sample=x[420]\n", + "show.showSpec(sample)\n", + "show.playSpec(sample)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3", + "metadata": {}, + "outputs": [], + "source": [ + "from tinygrad import nn\n", + "gen = model.Gen()\n", + "optimizer = nn.optim.AdamW(nn.state.get_parameters(gen), lr=1e-4)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4", + "metadata": {}, + "outputs": [], + "source": [ + "@TinyJit\n", + "def jit_step(X: Tensor, Y: Tensor,epoch) -> Tensor:\n", + " Tensor.training = True\n", + " optimizer.zero_grad()\n", + " _, loss = gen.__Lcall__(X,Y,epoch)\n", + " loss.backward()\n", + " optimizer.step()\n", + " return loss.realize()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "x_np, y_np = np.stack(x), np.stack(y)\n", + "x_np = np.expand_dims(x_np, axis=1)\n", + "y_np = np.expand_dims(y_np, axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6", + "metadata": { + "editable": true, + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "size=len(x)\n", + "BACH_SIZE=32\n", + "eshape = (BACH_SIZE, 1, 128, 216)\n", + "\n", + "for e in range(0,12):\n", + " print(f\"\\n--- Starting Epoch {e} ---\\n\")\n", + " l=0\n", + " \n", + " permutation = np.random.permutation(size)\n", + " x_np = x_np[permutation]\n", + " y_np = y_np[permutation]\n", + " \n", + " for i in range(0,size,BACH_SIZE):\n", + " tx,ty=Tensor(x_np[i:i+BACH_SIZE]),Tensor(y_np[i:i+BACH_SIZE])\n", + " if(tx.shape != eshape or ty.shape != eshape):\n", + " continue\n", + " l+=jit_step(tx,ty,e).numpy()\n", + " \n", + " l /= (size/BACH_SIZE)\n", + " print(f\"loss of {l}\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7", + "metadata": { + "editable": true, + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "from tinygrad.nn.state import safe_save, get_state_dict\n", + "safe_save(get_state_dict(gen),\"music.safetensors\")" + ] + } + ], + "metadata": { + "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": "3.12.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}