diff --git a/.github/workflows/basic-tests-old-pytorch.yml b/.github/workflows/basic-tests-old-pytorch.yml index 6c5eac5..7f76fc9 100644 --- a/.github/workflows/basic-tests-old-pytorch.yml +++ b/.github/workflows/basic-tests-old-pytorch.yml @@ -1,4 +1,4 @@ -name: Test PyTorch 2.0 and 2.6 +name: Test PyTorch 2.2 and 2.6 on: push: @@ -23,7 +23,7 @@ jobs: runs-on: ubuntu-latest strategy: matrix: - pytorch-version: [ 2.0.1, 2.6.0 ] + pytorch-version: [ 2.3.0, 2.6.0 ] steps: - uses: actions/checkout@v4 @@ -35,10 +35,10 @@ jobs: - name: Install dependencies run: | - python -m pip install --upgrade pip + python -m pip install --upgrade pip setuptools wheel pip install pytest nbval - if [ -f requirements.txt ]; then pip install -r requirements.txt; fi pip install torch==${{ matrix.pytorch-version }} + pip install -r requirements.txt pip install -r ch05/07_gpt_to_llama/tests/test-requirements-extra.txt - name: Test Selected Python Scripts diff --git a/ch05/01_main-chapter-code/ch05.ipynb b/ch05/01_main-chapter-code/ch05.ipynb index 32e739a..fdc2dfa 100644 --- a/ch05/01_main-chapter-code/ch05.ipynb +++ b/ch05/01_main-chapter-code/ch05.ipynb @@ -40,11 +40,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "matplotlib version: 3.9.0\n", - "numpy version: 1.26.4\n", - "tiktoken version: 0.7.0\n", - "torch version: 2.4.0\n", - "tensorflow version: 2.16.1\n" + "matplotlib version: 3.10.0\n", + "numpy version: 2.0.2\n", + "tiktoken version: 0.8.0\n", + "torch version: 2.6.0\n", + "tensorflow version: 2.18.0\n" ] } ], @@ -1135,7 +1135,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Training loss: 10.987583584255642\n", + "Training loss: 10.98758347829183\n", "Validation loss: 10.98110580444336\n" ] } @@ -1373,7 +1373,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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", 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", "text/plain": [ "
" ] @@ -2159,8 +2159,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "TensorFlow version: 2.16.1\n", - "tqdm version: 4.66.4\n" + "TensorFlow version: 2.18.0\n", + "tqdm version: 4.67.1\n" ] } ], @@ -2528,7 +2528,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.16" } }, "nbformat": 4, diff --git a/ch06/01_main-chapter-code/ch06.ipynb b/ch06/01_main-chapter-code/ch06.ipynb index 788069e..9674947 100644 --- a/ch06/01_main-chapter-code/ch06.ipynb +++ b/ch06/01_main-chapter-code/ch06.ipynb @@ -48,24 +48,24 @@ "name": "stdout", "output_type": "stream", "text": [ - "matplotlib version: 3.9.0\n", - "numpy version: 1.26.4\n", - "tiktoken version: 0.7.0\n", - "torch version: 2.4.0\n", - "tensorflow version: 2.16.1\n", - "pandas version: 2.2.2\n" + "matplotlib version: 3.10.0\n", + "numpy version: 2.0.2\n", + "tiktoken version: 0.8.0\n", + "torch version: 2.6.0\n", + "tensorflow version: 2.18.0\n", + "pandas version: 2.2.3\n" ] } ], "source": [ "from importlib.metadata import version\n", "\n", - "pkgs = [\"matplotlib\",\n", - " \"numpy\",\n", - " \"tiktoken\",\n", - " \"torch\",\n", - " \"tensorflow\", # For OpenAI's pretrained weights\n", - " \"pandas\" # Dataset loading\n", + "pkgs = [\"matplotlib\", # Plotting library\n", + " \"numpy\", # PyTorch & TensorFlow dependency\n", + " \"tiktoken\", # Tokenizer\n", + " \"torch\", # Deep learning library\n", + " \"tensorflow\", # For OpenAI's pretrained weights\n", + " \"pandas\" # Dataset loading\n", " ]\n", "for p in pkgs:\n", " print(f\"{p} version: {version(p)}\")" @@ -624,7 +624,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "id": "uQl0Psdmx15D", "metadata": { "id": "uQl0Psdmx15D" @@ -687,7 +687,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 10, "id": "74c3c463-8763-4cc0-9320-41c7eaad8ab7", "metadata": { "colab": { @@ -724,7 +724,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, "id": "d7791b52-af18-4ac4-afa9-b921068e383e", "metadata": { "id": "d7791b52-af18-4ac4-afa9-b921068e383e" @@ -785,7 +785,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 12, "id": "uzj85f8ou82h", "metadata": { "colab": { @@ -825,7 +825,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 13, "id": "bb0c502d-a75e-4248-8ea0-196e2b00c61e", "metadata": { "id": "bb0c502d-a75e-4248-8ea0-196e2b00c61e" @@ -862,7 +862,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 14, "id": "8681adc0-6f02-4e75-b01a-a6ab75d05542", "metadata": { "colab": { @@ -913,7 +913,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 15, "id": "4dee6882-4c3a-4964-af15-fa31f86ad047", "metadata": {}, "outputs": [ @@ -946,7 +946,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 16, "id": "IZfw-TYD2zTj", "metadata": { "colab": { @@ -994,7 +994,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 17, "id": "2992d779-f9fb-4812-a117-553eb790a5a9", "metadata": { "id": "2992d779-f9fb-4812-a117-553eb790a5a9" @@ -1029,7 +1029,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 18, "id": "022a649a-44f5-466c-8a8e-326c063384f5", "metadata": { "colab": { @@ -1040,16 +1040,16 @@ }, "outputs": [ { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "checkpoint: 100%|███████████████████████████| 77.0/77.0 [00:00<00:00, 24.2kiB/s]\n", - "encoder.json: 100%|███████████████████████| 1.04M/1.04M [00:00<00:00, 2.53MiB/s]\n", - "hparams.json: 100%|█████████████████████████| 90.0/90.0 [00:00<00:00, 37.4kiB/s]\n", - "model.ckpt.data-00000-of-00001: 100%|███████| 498M/498M [00:24<00:00, 20.7MiB/s]\n", - "model.ckpt.index: 100%|████████████████████| 5.21k/5.21k [00:00<00:00, 924kiB/s]\n", - "model.ckpt.meta: 100%|██████████████████████| 471k/471k [00:00<00:00, 1.89MiB/s]\n", - "vocab.bpe: 100%|████████████████████████████| 456k/456k [00:00<00:00, 1.79MiB/s]\n" + "File already exists and is up-to-date: gpt2/124M/checkpoint\n", + "File already exists and is up-to-date: gpt2/124M/encoder.json\n", + "File already exists and is up-to-date: gpt2/124M/hparams.json\n", + "File already exists and is up-to-date: gpt2/124M/model.ckpt.data-00000-of-00001\n", + "File already exists and is up-to-date: gpt2/124M/model.ckpt.index\n", + "File already exists and is up-to-date: gpt2/124M/model.ckpt.meta\n", + "File already exists and is up-to-date: gpt2/124M/vocab.bpe\n" ] } ], @@ -1075,7 +1075,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 19, "id": "d8ac25ff-74b1-4149-8dc5-4c429d464330", "metadata": {}, "outputs": [ @@ -1119,7 +1119,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 20, "id": "94224aa9-c95a-4f8a-a420-76d01e3a800c", "metadata": {}, "outputs": [ @@ -1188,7 +1188,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 21, "id": "b23aff91-6bd0-48da-88f6-353657e6c981", "metadata": { "colab": { @@ -1458,7 +1458,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 22, "id": "fkMWFl-0etea", "metadata": { "id": "fkMWFl-0etea" @@ -1481,7 +1481,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 23, "id": "7e759fa0-0f69-41be-b576-17e5f20e04cb", "metadata": {}, "outputs": [], @@ -1512,7 +1512,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 24, "id": "2aedc120-5ee3-48f6-92f2-ad9304ebcdc7", "metadata": { "id": "2aedc120-5ee3-48f6-92f2-ad9304ebcdc7" @@ -1537,7 +1537,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 25, "id": "f645c06a-7df6-451c-ad3f-eafb18224ebc", "metadata": { "colab": { @@ -1573,7 +1573,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 26, "id": "48dc84f1-85cc-4609-9cee-94ff539f00f4", "metadata": { "colab": { @@ -1634,7 +1634,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 27, "id": "49383a8c-41d5-4dab-98f1-238bca0c2ed7", "metadata": { "colab": { @@ -1698,7 +1698,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 28, "id": "c77faab1-3461-4118-866a-6171f2b89aa0", "metadata": {}, "outputs": [ @@ -1724,7 +1724,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 29, "id": "b81efa92-9be1-4b9e-8790-ce1fc7b17f01", "metadata": {}, "outputs": [ @@ -1752,7 +1752,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 30, "id": "f9f9ad66-4969-4501-8239-3ccdb37e71a2", "metadata": {}, "outputs": [ @@ -1781,7 +1781,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 31, "id": "3ecf9572-aed0-4a21-9c3b-7f9f2aec5f23", "metadata": {}, "outputs": [], @@ -1819,7 +1819,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 32, "id": "390e5255-8427-488c-adef-e1c10ab4fb26", "metadata": {}, "outputs": [ @@ -1885,7 +1885,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 33, "id": "2f1e9547-806c-41a9-8aba-3b2822baabe4", "metadata": { "id": "2f1e9547-806c-41a9-8aba-3b2822baabe4" @@ -1909,7 +1909,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 34, "id": "b7b83e10-5720-45e7-ac5e-369417ca846b", "metadata": {}, "outputs": [], @@ -1944,7 +1944,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 35, "id": "f6f00e53-5beb-4e64-b147-f26fd481c6ff", "metadata": { "colab": { @@ -2015,7 +2015,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 36, "id": "Csbr60to50FL", "metadata": { "id": "Csbr60to50FL" @@ -2071,7 +2071,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 37, "id": "bcc7bc04-6aa6-4516-a147-460e2f466eab", "metadata": {}, "outputs": [], @@ -2096,7 +2096,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 38, "id": "X7kU3aAj7vTJ", "metadata": { "colab": { @@ -2128,7 +2128,7 @@ "Ep 5 (Step 000550): Train loss 0.207, Val loss 0.143\n", "Ep 5 (Step 000600): Train loss 0.083, Val loss 0.074\n", "Training accuracy: 100.00% | Validation accuracy: 97.50%\n", - "Training completed in 5.38 minutes.\n" + "Training completed in 5.31 minutes.\n" ] } ], @@ -2162,7 +2162,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 39, "id": "cURgnDqdCeka", "metadata": { "id": "cURgnDqdCeka" @@ -2193,7 +2193,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 40, "id": "OIqRt466DiGk", "metadata": { "colab": { @@ -2206,7 +2206,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -2234,7 +2234,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 41, "id": "yz8BIsaF0TUo", "metadata": { "colab": { @@ -2247,7 +2247,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -2275,7 +2275,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 42, "id": "UHWaJFrjY0zW", "metadata": { "colab": { @@ -2343,7 +2343,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 43, "id": "aHdn6xvL-IW5", "metadata": { "id": "aHdn6xvL-IW5" @@ -2385,7 +2385,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 44, "id": "apU_pf51AWSV", "metadata": { "colab": { @@ -2416,7 +2416,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 45, "id": "1g5VTOo_Ajs5", "metadata": { "colab": { @@ -2455,7 +2455,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 46, "id": "mYnX-gI1CfQY", "metadata": { "id": "mYnX-gI1CfQY" @@ -2475,7 +2475,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 47, "id": "cc4e68a5-d492-493b-87ef-45c475f353f5", "metadata": {}, "outputs": [ @@ -2485,7 +2485,7 @@ "" ] }, - "execution_count": 45, + "execution_count": 47, "metadata": {}, "output_type": "execute_result" } @@ -2537,7 +2537,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.16" } }, "nbformat": 4, diff --git a/ch07/01_main-chapter-code/ch07.ipynb b/ch07/01_main-chapter-code/ch07.ipynb index cc741a1..e6d3127 100644 --- a/ch07/01_main-chapter-code/ch07.ipynb +++ b/ch07/01_main-chapter-code/ch07.ipynb @@ -41,18 +41,19 @@ "base_uri": "https://localhost:8080/" }, "id": "4e19327b-6c02-4881-ad02-9b6d3ec0b1b4", - "outputId": "9d937b84-d8f8-4ce9-cc3c-211188f49a10" + "outputId": "bcdfe2cb-d084-4920-d703-503131aabec3" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "matplotlib version: 3.7.1\n", - "tiktoken version: 0.7.0\n", - "torch version: 2.4.0\n", - "tqdm version: 4.66.4\n", - "tensorflow version: 2.15.0\n" + "numpy version: 2.0.2\n", + "matplotlib version: 3.10.0\n", + "tiktoken version: 0.8.0\n", + "torch version: 2.5.1+cu124\n", + "tqdm version: 4.67.1\n", + "tensorflow version: 2.18.0\n" ] } ], @@ -60,6 +61,7 @@ "from importlib.metadata import version\n", "\n", "pkgs = [\n", + " \"numpy\", # PyTorch & TensorFlow dependency\n", " \"matplotlib\", # Plotting library\n", " \"tiktoken\", # Tokenizer\n", " \"torch\", # Deep learning library\n", @@ -153,7 +155,7 @@ "base_uri": "https://localhost:8080/" }, "id": "0G3axLw6kY1N", - "outputId": "a5f70eb8-6248-4834-e7ae-6105e94e5afa" + "outputId": "07e1e4f9-026c-48c1-8a06-f2bfb1fb354e" }, "outputs": [ { @@ -177,7 +179,7 @@ " text_data = response.read().decode(\"utf-8\")\n", " with open(file_path, \"w\", encoding=\"utf-8\") as file:\n", " file.write(text_data)\n", - " \n", + "\n", " # The book originally contained this unnecessary \"else\" clause:\n", " #else:\n", " # with open(file_path, \"r\", encoding=\"utf-8\") as file:\n", @@ -218,7 +220,7 @@ "base_uri": "https://localhost:8080/" }, "id": "-LiuBMsHkzQV", - "outputId": "cc742019-b8d7-40f9-b21a-6a5ddf821377" + "outputId": "a4ee5c2d-db53-4a80-e5ee-0bbcf6fe0450" }, "outputs": [ { @@ -253,7 +255,7 @@ "base_uri": "https://localhost:8080/" }, "id": "uFInFxDDk2Je", - "outputId": "70241295-a9ec-4b7d-caf5-ab6f267e3271" + "outputId": "b4f84027-bb9e-4e51-b79e-1329c8bff093" }, "outputs": [ { @@ -341,7 +343,7 @@ "base_uri": "https://localhost:8080/" }, "id": "F9UQRfjzo4Js", - "outputId": "13ec7abf-ad94-4e26-860d-6a39a344f31f" + "outputId": "7b615d35-2a5f-474d-9292-a69bc3850e16" }, "outputs": [ { @@ -387,7 +389,7 @@ "base_uri": "https://localhost:8080/" }, "id": "a3891fa9-f738-41cd-946c-80ef9a99c346", - "outputId": "d6be5713-1293-4a70-c8c8-a86ea8e95817" + "outputId": "2142c5a4-b594-49c5-affe-2d963a7bd46b" }, "outputs": [ { @@ -448,7 +450,7 @@ "base_uri": "https://localhost:8080/" }, "id": "-zf6oht6bIUQ", - "outputId": "bb5fe8e5-1ce5-4fca-a430-76ecf42e99ef" + "outputId": "657ec5c6-4caa-4d1a-ba2e-23acd755ab07" }, "outputs": [ { @@ -565,7 +567,7 @@ "base_uri": "https://localhost:8080/" }, "id": "ff24fe1a-5746-461c-ad3d-b6d84a1a7c96", - "outputId": "4d63f8b8-b4ad-45d9-9e93-c9dd8c2b7706" + "outputId": "ac44227b-9ec2-4131-9df8-89caa6e879ca" }, "outputs": [ { @@ -656,7 +658,7 @@ "base_uri": "https://localhost:8080/" }, "id": "8fb02373-59b3-4f3a-b1d1-8181a2432645", - "outputId": "8705ca9a-e999-4f70-9db8-1ad084eba7bb" + "outputId": "93d987b9-e3ca-4857-9b28-b67d515a94d8" }, "outputs": [ { @@ -763,7 +765,7 @@ "base_uri": "https://localhost:8080/" }, "id": "6eb2bce3-28a7-4f39-9d4b-5e972d69066c", - "outputId": "b9ceae14-13c2-49f7-f4a4-b503f3db3009" + "outputId": "3d104439-c328-431b-ef7c-2639d86c2135" }, "outputs": [ { @@ -883,7 +885,7 @@ "base_uri": "https://localhost:8080/" }, "id": "cdf5eec4-9ebe-4be0-9fca-9a47bee88fdc", - "outputId": "a5501547-239d-431d-fb04-da7fa2ffad79" + "outputId": "e8f709b9-f4c5-428a-a6ac-2a4c1b9358ba" }, "outputs": [ { @@ -926,7 +928,7 @@ "base_uri": "https://localhost:8080/" }, "id": "W2jvh-OP9MFV", - "outputId": "b5cd858e-7c58-4a21-c5a7-e72768bd301c" + "outputId": "ccb3a703-59a7-4258-8841-57959a016e31" }, "outputs": [ { @@ -968,7 +970,7 @@ "base_uri": "https://localhost:8080/" }, "id": "nvVMuil89v9N", - "outputId": "e4a07b99-a23c-4404-ccdb-5f93c39f3b09" + "outputId": "6d4683d4-5bfc-4a8c-de2a-95ecb2e716b9" }, "outputs": [ { @@ -1010,7 +1012,7 @@ "base_uri": "https://localhost:8080/" }, "id": "RTyB1vah9p56", - "outputId": "28c16387-1d9c-48a7-eda7-aa270864683d" + "outputId": "da05302e-3fe0-439e-d1ed-82066bceb122" }, "outputs": [ { @@ -1113,7 +1115,7 @@ "base_uri": "https://localhost:8080/" }, "id": "etpqqWh8phKc", - "outputId": "925faf3a-6df4-4ad0-f276-f328493619c3" + "outputId": "b4391c33-1a89-455b-faaa-5f874b6eb409" }, "outputs": [ { @@ -1247,7 +1249,7 @@ "base_uri": "https://localhost:8080/" }, "id": "GGs1AI3vHpnX", - "outputId": "53a9695d-87cb-4d7c-8b43-1561dfa68ba0" + "outputId": "f6a74c8b-1af3-4bc1-b48c-eda64b0200d1" }, "outputs": [ { @@ -1400,7 +1402,7 @@ "base_uri": "https://localhost:8080/" }, "id": "21b8fd02-014f-4481-9b71-5bfee8f9dfcd", - "outputId": "ce919ecd-5ded-453c-a312-10cf55c13da7" + "outputId": "1b8ad342-2b5b-4f12-ad1a-3cb2a6c712ff" }, "outputs": [ { @@ -1441,7 +1443,7 @@ "base_uri": "https://localhost:8080/" }, "id": "51649ab4-1a7e-4a9e-92c5-950a24fde211", - "outputId": "fdf486f3-e99d-4891-9814-afc9e4991020" + "outputId": "5e8c23f8-6a05-4c13-9f92-373b75b57ea6" }, "outputs": [ { @@ -1512,27 +1514,27 @@ "base_uri": "https://localhost:8080/" }, "id": "0d249d67-5eba-414e-9bd2-972ebf01329d", - "outputId": "3f08f5e1-ca7c-406d-e2ae-1b5fcafad3f2" + "outputId": "386ebd49-51d7-4a62-c590-91cdccce5fb8" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "2024-07-25 02:22:49.969483: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n", - "2024-07-25 02:22:50.023103: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", - "2024-07-25 02:22:50.023136: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", - "2024-07-25 02:22:50.024611: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", - "2024-07-25 02:22:50.033304: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", + "2025-02-08 23:37:19.420934: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n", + "2025-02-08 23:37:19.439459: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n", + "E0000 00:00:1739057839.462005 4402 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "E0000 00:00:1739057839.468845 4402 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", + "2025-02-08 23:37:19.492335: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n", "To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", - "2024-07-25 02:22:51.282247: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", - "checkpoint: 100%|██████████| 77.0/77.0 [00:00<00:00, 169kiB/s]\n", - "encoder.json: 100%|██████████| 1.04M/1.04M [00:00<00:00, 2.43MiB/s]\n", - "hparams.json: 100%|██████████| 91.0/91.0 [00:00<00:00, 168kiB/s]\n", - "model.ckpt.data-00000-of-00001: 100%|██████████| 1.42G/1.42G [00:56<00:00, 25.0MiB/s]\n", - "model.ckpt.index: 100%|██████████| 10.4k/10.4k [00:00<00:00, 16.5MiB/s]\n", - "model.ckpt.meta: 100%|██████████| 927k/927k [00:00<00:00, 1.96MiB/s]\n", - "vocab.bpe: 100%|██████████| 456k/456k [00:00<00:00, 1.53MiB/s]\n" + "checkpoint: 100%|██████████| 77.0/77.0 [00:00<00:00, 125kiB/s]\n", + "encoder.json: 100%|██████████| 1.04M/1.04M [00:00<00:00, 5.37MiB/s]\n", + "hparams.json: 100%|██████████| 91.0/91.0 [00:00<00:00, 161kiB/s]\n", + "model.ckpt.data-00000-of-00001: 100%|██████████| 1.42G/1.42G [01:00<00:00, 23.6MiB/s]\n", + "model.ckpt.index: 100%|██████████| 10.4k/10.4k [00:00<00:00, 17.5MiB/s]\n", + "model.ckpt.meta: 100%|██████████| 927k/927k [00:00<00:00, 6.38MiB/s]\n", + "vocab.bpe: 100%|██████████| 456k/456k [00:00<00:00, 2.69MiB/s]\n" ] } ], @@ -1589,7 +1591,7 @@ "base_uri": "https://localhost:8080/" }, "id": "7bd32b7c-5b44-4d25-a09f-46836802ca74", - "outputId": "30d4fbd9-7d22-4545-cfc5-c5749cc0bd93" + "outputId": "c1276a91-e7da-495b-be0f-70a96872dbe6" }, "outputs": [ { @@ -1655,7 +1657,7 @@ "base_uri": "https://localhost:8080/" }, "id": "ba4a55bf-a245-48d8-beda-2838a58fb5ba", - "outputId": "b46de9b3-98f0-45e4-a9ae-86870c3244a1" + "outputId": "3e231f03-c5dc-4397-8778-4995731176a3" }, "outputs": [ { @@ -1747,15 +1749,15 @@ "base_uri": "https://localhost:8080/" }, "id": "d99fc6f8-63b2-43da-adbb-a7b6b92c8dd5", - "outputId": "36fdf03b-6fa6-46c3-c77d-ecc99e886265" + "outputId": "a3f5e1b0-093a-4c51-e7fc-c9cac48c2ea2" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Training loss: 3.82590970993042\n", - "Validation loss: 3.761933755874634\n" + "Training loss: 3.8259087562561036\n", + "Validation loss: 3.761933708190918\n" ] } ], @@ -1817,7 +1819,7 @@ "base_uri": "https://localhost:8080/" }, "id": "78bcf83a-1fff-4540-97c1-765c4016d5e3", - "outputId": "cea0618c-56ca-418a-c972-bcc060362727" + "outputId": "ecb9a3dd-97c0-492d-8a51-fbd175bb139b" }, "outputs": [ { @@ -1825,55 +1827,55 @@ "output_type": "stream", "text": [ "Ep 1 (Step 000000): Train loss 2.637, Val loss 2.626\n", - "Ep 1 (Step 000005): Train loss 1.174, Val loss 1.102\n", + "Ep 1 (Step 000005): Train loss 1.174, Val loss 1.103\n", "Ep 1 (Step 000010): Train loss 0.872, Val loss 0.944\n", "Ep 1 (Step 000015): Train loss 0.857, Val loss 0.906\n", "Ep 1 (Step 000020): Train loss 0.776, Val loss 0.881\n", "Ep 1 (Step 000025): Train loss 0.754, Val loss 0.859\n", - "Ep 1 (Step 000030): Train loss 0.799, Val loss 0.836\n", - "Ep 1 (Step 000035): Train loss 0.714, Val loss 0.808\n", + "Ep 1 (Step 000030): Train loss 0.800, Val loss 0.836\n", + "Ep 1 (Step 000035): Train loss 0.714, Val loss 0.809\n", "Ep 1 (Step 000040): Train loss 0.672, Val loss 0.806\n", "Ep 1 (Step 000045): Train loss 0.633, Val loss 0.789\n", - "Ep 1 (Step 000050): Train loss 0.663, Val loss 0.783\n", + "Ep 1 (Step 000050): Train loss 0.663, Val loss 0.782\n", "Ep 1 (Step 000055): Train loss 0.760, Val loss 0.763\n", "Ep 1 (Step 000060): Train loss 0.719, Val loss 0.743\n", "Ep 1 (Step 000065): Train loss 0.653, Val loss 0.735\n", - "Ep 1 (Step 000070): Train loss 0.532, Val loss 0.729\n", - "Ep 1 (Step 000075): Train loss 0.569, Val loss 0.728\n", - "Ep 1 (Step 000080): Train loss 0.605, Val loss 0.725\n", - "Ep 1 (Step 000085): Train loss 0.509, Val loss 0.709\n", - "Ep 1 (Step 000090): Train loss 0.562, Val loss 0.691\n", - "Ep 1 (Step 000095): Train loss 0.500, Val loss 0.681\n", - "Ep 1 (Step 000100): Train loss 0.503, Val loss 0.677\n", - "Ep 1 (Step 000105): Train loss 0.564, Val loss 0.670\n", - "Ep 1 (Step 000110): Train loss 0.555, Val loss 0.666\n", - "Ep 1 (Step 000115): Train loss 0.508, Val loss 0.664\n", + "Ep 1 (Step 000070): Train loss 0.536, Val loss 0.732\n", + "Ep 1 (Step 000075): Train loss 0.569, Val loss 0.739\n", + "Ep 1 (Step 000080): Train loss 0.603, Val loss 0.734\n", + "Ep 1 (Step 000085): Train loss 0.518, Val loss 0.717\n", + "Ep 1 (Step 000090): Train loss 0.575, Val loss 0.699\n", + "Ep 1 (Step 000095): Train loss 0.505, Val loss 0.689\n", + "Ep 1 (Step 000100): Train loss 0.507, Val loss 0.683\n", + "Ep 1 (Step 000105): Train loss 0.570, Val loss 0.676\n", + "Ep 1 (Step 000110): Train loss 0.564, Val loss 0.671\n", + "Ep 1 (Step 000115): Train loss 0.522, Val loss 0.666\n", "Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: Convert the active sentence to passive: 'The chef cooks the meal every day.' ### Response: The meal is prepared every day by the chef.<|endoftext|>The following is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: Convert the active sentence to passive:\n", - "Ep 2 (Step 000120): Train loss 0.435, Val loss 0.672\n", - "Ep 2 (Step 000125): Train loss 0.451, Val loss 0.687\n", - "Ep 2 (Step 000130): Train loss 0.447, Val loss 0.683\n", - "Ep 2 (Step 000135): Train loss 0.405, Val loss 0.682\n", - "Ep 2 (Step 000140): Train loss 0.409, Val loss 0.681\n", - "Ep 2 (Step 000145): Train loss 0.369, Val loss 0.680\n", - "Ep 2 (Step 000150): Train loss 0.382, Val loss 0.675\n", - "Ep 2 (Step 000155): Train loss 0.413, Val loss 0.675\n", - "Ep 2 (Step 000160): Train loss 0.415, Val loss 0.683\n", - "Ep 2 (Step 000165): Train loss 0.379, Val loss 0.686\n", - "Ep 2 (Step 000170): Train loss 0.323, Val loss 0.681\n", - "Ep 2 (Step 000175): Train loss 0.337, Val loss 0.669\n", - "Ep 2 (Step 000180): Train loss 0.392, Val loss 0.656\n", - "Ep 2 (Step 000185): Train loss 0.415, Val loss 0.657\n", - "Ep 2 (Step 000190): Train loss 0.340, Val loss 0.648\n", - "Ep 2 (Step 000195): Train loss 0.330, Val loss 0.634\n", - "Ep 2 (Step 000200): Train loss 0.310, Val loss 0.634\n", - "Ep 2 (Step 000205): Train loss 0.352, Val loss 0.630\n", - "Ep 2 (Step 000210): Train loss 0.367, Val loss 0.630\n", - "Ep 2 (Step 000215): Train loss 0.394, Val loss 0.635\n", - "Ep 2 (Step 000220): Train loss 0.299, Val loss 0.648\n", - "Ep 2 (Step 000225): Train loss 0.346, Val loss 0.661\n", - "Ep 2 (Step 000230): Train loss 0.292, Val loss 0.659\n", + "Ep 2 (Step 000120): Train loss 0.439, Val loss 0.671\n", + "Ep 2 (Step 000125): Train loss 0.454, Val loss 0.685\n", + "Ep 2 (Step 000130): Train loss 0.448, Val loss 0.681\n", + "Ep 2 (Step 000135): Train loss 0.406, Val loss 0.678\n", + "Ep 2 (Step 000140): Train loss 0.412, Val loss 0.678\n", + "Ep 2 (Step 000145): Train loss 0.372, Val loss 0.680\n", + "Ep 2 (Step 000150): Train loss 0.381, Val loss 0.674\n", + "Ep 2 (Step 000155): Train loss 0.419, Val loss 0.672\n", + "Ep 2 (Step 000160): Train loss 0.417, Val loss 0.680\n", + "Ep 2 (Step 000165): Train loss 0.383, Val loss 0.683\n", + "Ep 2 (Step 000170): Train loss 0.328, Val loss 0.679\n", + "Ep 2 (Step 000175): Train loss 0.334, Val loss 0.668\n", + "Ep 2 (Step 000180): Train loss 0.391, Val loss 0.656\n", + "Ep 2 (Step 000185): Train loss 0.418, Val loss 0.657\n", + "Ep 2 (Step 000190): Train loss 0.341, Val loss 0.648\n", + "Ep 2 (Step 000195): Train loss 0.330, Val loss 0.633\n", + "Ep 2 (Step 000200): Train loss 0.313, Val loss 0.631\n", + "Ep 2 (Step 000205): Train loss 0.354, Val loss 0.628\n", + "Ep 2 (Step 000210): Train loss 0.365, Val loss 0.629\n", + "Ep 2 (Step 000215): Train loss 0.394, Val loss 0.634\n", + "Ep 2 (Step 000220): Train loss 0.301, Val loss 0.647\n", + "Ep 2 (Step 000225): Train loss 0.347, Val loss 0.661\n", + "Ep 2 (Step 000230): Train loss 0.297, Val loss 0.659\n", "Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: Convert the active sentence to passive: 'The chef cooks the meal every day.' ### Response: The meal is cooked every day by the chef.<|endoftext|>The following is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: What is the capital of the United Kingdom\n", - "Training completed in 1.84 minutes.\n" + "Training completed in 0.93 minutes.\n" ] } ], @@ -1918,15 +1920,15 @@ "metadata": { "colab": { "base_uri": "https://localhost:8080/", - "height": 308 + "height": 306 }, "id": "4acd368b-1403-4807-a218-9102e35bfdbb", - "outputId": "680da58a-9bd7-402d-ac95-470a4a29a6c4" + "outputId": "2f5c99e0-7ed0-4f42-d67c-e07c375e6158" }, "outputs": [ { "data": { - "image/png": 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\n", 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SExPN9Wjfvj179uyx+M9x5T/PlUTRvn17i2NcKXPlGLfj8+rSpQt79uwhISHBvLRu3ZrBgwebX9eWugLExsZe96jd4cOHqVevHgBhYWEEBgZaxJGZmcnmzZst6puens727dvNZVavXo3RaKRdu3bmMuvXr6eoqMiivo0bN8bLy8tcprTPpLJyc3PRai3/RNnZ2WE0GmtdXa9VnepWllgq60qSPnLkCCtXrsTHx8die22qa4XYrBtbDTV37lyl0+lUXFyc2r9/v3r22WeVp6enRY9hW3v++eeVh4eHWrt2rUpKSjIvubm55jLPPfecCg0NVatXr1bbtm1T7du3V+3btzdvv/LIUrdu3VRCQoJavny58vPzu+EjS+PGjVMHDhxQM2fOvOEjS7f787q613dtq+uWLVuUvb29evvtt9WRI0fU999/r/R6vfruu+/MZd59913l6empfvnlF7V792718MMP3/CxnpiYGLV582b1559/qvDwcItHXdLT01VAQIB64okn1N69e9XcuXOVXq+/7lEXe3t7NW3aNHXgwAH1xhtvWPXxrKFDh6o6deqYH8/6+eefla+vr3rllVdqRV2zsrLUzp071c6dOxWgPvzwQ7Vz505zT+fqVLeyxFLRuhYWFqqHHnpIhYSEqISEBIu/WVf34K4pda0Kkqgr4NNPP1WhoaHK0dFRtW3bVv3111+2DskCcMNl9uzZ5jJ5eXnqhRdeUF5eXkqv16t+/fqppKQki+OcPHlS9ezZUzk7OytfX1/10ksvqaKiIosya9asUS1atFCOjo6qQYMGFue44nZ/Xtcm6tpW119//VU1a9ZM6XQ6FRERob788kuL7UajUb3++usqICBA6XQ61aVLF3Xo0CGLMpcuXVKDBg1Srq6uyt3dXT355JMqKyvLosyuXbvUPffco3Q6napTp4569913r4vlxx9/VHfddZdydHRUTZs2Vb/99pvV6pmZmalefPFFFRoaqpycnFSDBg3UhAkTLP541+S6rlmz5ob/T4cOHVrt6laWWCpa1xMnTtz0b9aaNWtqXF2rgkapq4b5EUIIIUS1IveohRBCiGpMErUQQghRjUmiFkIIIaoxSdRCCCFENSaJWgghhKjGJFELIYQQ1Zgk6goqKChg0qRJFBQU2DqUKncn1RXurPpKXWuvO6m+tb2u8hx1BWVmZuLh4UFGRobFmLS10Z1UV7iz6it1rb3upPrW9rpKi1oIIYSoxiRRCyGEENXYHTcfdXFxMTt37iQgIOC6mXnKIysrC4CzZ8+SmZlprfCqpTuprnBn1VfqWnvdSfWtiXU1Go2kpKQQExODvX3pqfiOu0e9detW2rZta+swhBBCCLZs2UKbNm1KLXPHtagDAgIA04cTFBRk42iEEELciZKSkmjbtq05J5XmjkvUVy53BwUFERISYuNohBBC3MnKcgtWOpMJIYQQ1ZgkaiGEEKIak0QthBBCVGN33D1qIYQojcFgoKioyNZhiBrOwcEBOzs7qxxLEnUl7D2bwbn0PKLrehLg7mTrcIQQlaCUIjk5mfT0dFuHImoJT09PAgMD0Wg0lTqOJOpKeHPJfracSGXG4zE82DzY1uEIISrhSpL29/dHr9dX+o+ruHMppcjNzeX8+fMAlX4UWBJ1JXRS22hrtwtNkhYkUQtRYxkMBnOS9vHxsXU4ohZwdnYG4Pz58/j7+1fqMrh0JquEjnmreNlhPi4p22wdihCiEq7ck9br9TaORNQmV36fKtvnQRJ1JRidvEwvclNtG4gQwirkcrewJmv9PkmirgTl7A2AJj/NxpEIIYSorSRRV4LWxXQvy7FQErUQovaoX78+06dPL3P5tWvXotFoqrzHfFxcHJ6enlV6jurIpol6ypQptGnTBjc3N/z9/enbty+HDh0qdZ+4uDg0Go3F4uRkm0ejHNx8AdAVZtjk/EKIO9u1fwuvXSZNmlSh427dupVnn322zOU7dOhAUlISHh4eFTqfKJ1Ne32vW7eOESNG0KZNG4qLi/m///s/unXrxv79+3Fxcbnpfu7u7hYJ3Vb3lXTupkStN0iiFkLcfklJSebX8+bNY+LEiRZ/G11dXc2vlVIYDIZbzn0M4OfnV644HB0dCQwMLNc+ouxs2qJevnw5w4YNo2nTpkRHRxMXF0diYiLbt28vdT+NRkNgYKB5Kcs0YVXBxcMfADdjzZioXAhRu1z9d9DDw8Pib+PBgwdxc3Nj2bJltGrVCp1Ox59//smxY8d4+OGHCQgIwNXVlTZt2rBy5UqL41576Vuj0fD111/Tr18/9Ho94eHhLF682Lz92kvfVy5Rr1ixgsjISFxdXenRo4fFF4vi4mJGjx6Np6cnPj4+vPrqqwwdOpS+ffuW6zOYNWsWDRs2xNHRkcaNG/Ptt9+atymlmDRpEqGhoeh0OoKDgxk9erR5+2effUZ4eDhOTk4EBATwyCOPlOvct0u1ukedkWFqmXp7e5daLjs7m3r16lG3bl0efvhh9u3bdzvCu46rt+lbpydZ5BUabBKDEKJqKKXILSy2yaKUslo9/vWvf/Huu+9y4MABmjdvTnZ2Nr169WLVqlXs3LmTHj160KdPHxITE0s9zuTJkxk4cCC7d++mV69eDB48mNTUmz/xkpuby7Rp0/j2229Zv349iYmJvPzyy+bt7733Ht9//z2zZ89mw4YNZGZmsmjRonLVbeHChbz44ou89NJL7N27l3/84x88+eSTrFmzBoAFCxbw0Ucf8cUXX3DkyBEWLVpEVFQUANu2bWP06NG8+eabHDp0iOXLl3PvvfeW6/y3S7UZ8MRoNDJmzBhiY2Np1qzZTcs1btyYb775hubNm5ORkcG0adPo0KED+/btu+H80gUFBRQUFJjfZ2VlWS1mF09Ti9pFU8DZzCzq+Hpa7dhCCNvKKzLQZOIKm5x7/5vd0Tta58/zm2++yQMPPGB+7+3tTXR0tPn9W2+9xcKFC1m8eDEjR4686XGGDRvGoEGDAHjnnXf45JNP2LJlCz169Lhh+aKiIj7//HMaNmwIwMiRI3nzzTfN2z/99FPGjx9Pv379AJgxYwZLly4tV92mTZvGsGHDeOGFFwAYO3Ysf/31F9OmTeO+++4jMTGRwMBAunbtioODA6GhobRt2xaAxMREXFxcePDBB3Fzc6NevXrExMSU6/y3S7VpUY8YMYK9e/cyd+7cUsu1b9+eIUOG0KJFCzp16sTPP/+Mn58fX3zxxQ3LT5kyBQ8PD/PSpEkTq8WscfKk+PJHmJWaYrXjCiGEtbRu3drifXZ2Ni+//DKRkZF4enri6urKgQMHbtmibt68ufm1i4sL7u7u5iEyb0Sv15uTNJiG0bxSPiMjg5SUFHPSBLCzs6NVq1blqtuBAweIjY21WBcbG8uBAwcAePTRR8nLy6NBgwYMHz6chQsXUlxcDMADDzxAvXr1aNCgAU888QTff/89ubm55Tr/7VItWtQjR45kyZIlrF+//oat4tI4ODgQExPD0aNHb7h9/PjxjB071vz+7Nmz1kvWGg3ZGjc8VQbZ6ReAxtY5rhDC5pwd7Nj/Znebndtaru2Y+/LLLxMfH8+0adNo1KgRzs7OPPLIIxQWFpZ6HAcHB4v3Go0Go9FYrvLWvKRfFnXr1uXQoUOsXLmS+Ph4XnjhBaZOncq6detwc3Njx44drF27lt9//52JEycyadIktm7dWu0eAbNpi1opxciRI1m4cCGrV68mLCys3McwGAzs2bPnpoOe63Q63N3dzYubm1tlw7aQY+cOQEHGzb9ZCiFqHo1Gg97R3iZLVT7JsmHDBoYNG0a/fv2IiooiMDCQkydPVtn5bsTDw4OAgAC2bt1qXmcwGNixY0e5jhMZGcmGDRss1m3YsMGiMebs7EyfPn345JNPWLt2LZs2bWLPnj0A2Nvb07VrV95//312797NyZMnWb16dSVqVjVs2qIeMWIEc+bM4ZdffsHNzY3k5GTA9I94ZUDzIUOGUKdOHaZMmQKY7rfcfffdNGrUiPT0dKZOncqpU6d45plnbFKH87r6ZBZqyMiXzmRCiOovPDycn3/+mT59+qDRaHj99ddLbRlXlVGjRjFlyhQaNWpEREQEn376KWlpaeX6kjJu3DgGDhxITEwMXbt25ddff+Xnn38292KPi4vDYDDQrl079Ho93333Hc7OztSrV48lS5Zw/Phx7r33Xry8vFi6dClGo5HGjavflVGbJupZs2YB0LlzZ4v1s2fPZtiwYYDphr9WW9LwT0tLY/jw4SQnJ+Pl5UWrVq3YuHGjVe89l8eC8Cl891cio3WN6GWTCIQQouw+/PBDnnrqKTp06ICvry+vvvoqmZm3/xHTV199leTkZIYMGYKdnR3PPvss3bt3L9csU3379uXjjz9m2rRpvPjii4SFhTF79mxzTvH09OTdd99l7NixGAwGoqKi+PXXX/Hx8cHT05Off/6ZSZMmkZ+fT3h4OD/88ANNmzatohpXnEbd7psGNnbmzBnq1q3L6dOny30//EY+/P0Qn6w+yt/vDuXffaOsEKEQ4nbLz8/nxIkThIWF2Wykwzud0WgkMjKSgQMH8tZbb9k6HKso7feqPLmoWnQmq8m8XBwBSMup3DRmQghxJzl16hS///47nTp1oqCggBkzZnDixAkef/xxW4dW7VSbx7Nqquapy1nl+BIPnvvY1qEIIUSNodVqiYuLo02bNsTGxrJnzx5WrlxJZGSkrUOrdqRFXUludgYaapO4UHDW1qEIIUSNUbdu3et6bIsbk0RdScZGD/DYH/kU2gey0NbBCCGEqHUkUVeSm38om1UkDnmmh/ltNZOXEEKI2knuUVeSt97UmazIoMguKLZxNEIIIWobaVFXkrO2mCcdV+JqyCQt617cnBxuvZMQQghRRpKoK0uj5Q3tN6CFPekTwM+6Q5QKIYS4s8ml78qycyBHowcgJ03G+xZCCGFdkqitIEdrmpgjL+OCjSMRQojy69y5M2PGjDG/r1+/PtOnTy91H41Gw6JFiyp9bmsdpzSTJk2iRYsWVXqOqiSJ2gryHDwAKMq6aONIhBB3kj59+tCjR48bbvvjjz/QaDTs3r273MfdunUrzz77bGXDs3CzZJmUlETPnj2teq7aRhK1FRQ5egJQnH3JtoEIIe4oTz/9NPHx8Zw5c+a6bbNnz6Z169Y0b9683Mf18/NDr9dbI8RbCgwMRKfT3ZZz1VSSqK2gWOcNgMpLtXEkQog7yYMPPoifnx9xcXEW67Ozs5k/fz5PP/00ly5dYtCgQdSpUwe9Xk9UVBQ//PBDqce99tL3kSNHuPfee3FycqJJkybEx8dft8+rr77KXXfdhV6vp0GDBrz++usUFZnmQIiLi2Py5Mns2rULjUaDRqMxx3ztpe89e/Zw//334+zsjI+PD88++yzZ2dnm7cOGDaNv375MmzaNoKAgfHx8GDFihPlcZWE0GnnzzTcJCQlBp9PRokULli9fbt5eWFjIyJEjCQoKwsnJiXr16pmnWlZKMWnSJEJDQ9HpdAQHBzN69Ogyn7sipNe3FShnLwC0kqiFqH0Kc8q/j50O7C7/eTUUg6EANFpwcL71cR1dynwae3t7hgwZQlxcHBMmTDAPuDR//nwMBgODBg0iOzubVq1a8eqrr+Lu7s5vv/3GE088QcOGDWnbtu0tz2E0Gunfvz8BAQFs3ryZjIwMi/vZV7i5uREXF0dwcDB79uxh+PDhuLm58corr/DYY4+xd+9eli9fbp4r2sPD47pj5OTk0L17d9q3b8/WrVs5f/48zzzzDCNHjrT4MrJmzRqCgoJYs2YNR48e5bHHHqNFixYMHz68TJ/bxx9/zAcffMAXX3xBTEwM33zzDQ899BD79u0jPDycTz75hMWLF/Pjjz8SGhrK6dOnOX36NAALFizgo48+Yu7cuTRt2pTk5GR27dpVpvNWlCRqK9C6mFrUDgXptg1ECGF97wSXf59H46BpP9Prg7/C/GFQ7x548reSMtOjIPcGt8smZZTrVE899RRTp05l3bp15nmYZ8+ezYABA/Dw8MDDw4OXX37ZXH7UqFGsWLGCH3/8sUyJeuXKlRw8eJAVK1YQHGz6LN55553r7iu/9tpr5tf169fn5ZdfZu7cubzyyis4Ozvj6uqKvb09gYGBNz3XnDlzyM/P53//+x8uLqYvLDNmzKBPnz689957BAQEAODl5cWMGTOws7MjIiKC3r17s2rVqjIn6mnTpvHqq6/yt7/9DYD33nuPNWvWMH36dGbOnEliYiLh4eHcc889aDQa6tWrZ943MTGRwMBAunbtioODA6GhoWX6HCtDLn1bgYOrLwC6onTbBiKEuONERETQoUMHvvnmGwCOHj3KH3/8wdNPPw2AwWDgrbfeIioqCm9vb1xdXVmxYgWJiYllOv6BAweoW7euOUkDtG/f/rpy8+bNIzY2lsDAQFxdXXnttdfKfI6rzxUdHW1O0gCxsbEYjUYOHTpkXte0aVPs7OzM74OCgjh/vmyPx2ZmZnLu3DliY2Mt1sfGxnLgwAHAdHk9ISGBxo0bM3r0aH7//XdzuUcffZS8vDwaNGjA8OHDWbhwIcXFVTsqpbSorUDnbkrUzsXl+yYshKgB/u9c+fexu6pzVEQf0zE017SLxuypXFxXefrppxk1ahQzZ85k9uzZNGzYkE6dOgEwdepUPv74Y6ZPn05UVBQuLi6MGTOGwsJCq51/06ZNDB48mMmTJ9O9e3c8PDyYO3cuH3zwgdXOcTUHB8sRIDUaDUaj0WrHb9myJSdOnGDZsmWsXLmSgQMH0rVrV3766Sfq1q3LoUOHWLlyJfHx8bzwwgvmKxrXxmUt0qK2Ar2nPwBuxiyMRmXjaIQQVuXoUv7F7qo2kJ29ad3V96dLO24FDBw4EK1Wy5w5c/jf//7HU089Zb5fvWHDBh5++GH+/ve/Ex0dTYMGDTh8+HCZjx0ZGcnp06dJSkoyr/vrr78symzcuJF69eoxYcIEWrduTXh4OKdOnbKsrqMjBoPhlufatWsXOTkl9+83bNiAVqulcePGZY65NO7u7gQHB183xeaGDRto0qSJRbnHHnuMr776innz5rFgwQJSU039kJydnenTpw+ffPIJa9euZdOmTezZY70vXteSFrUVuHiZErWnJovM/CI8L0/UIYQQt4OrqyuPPfYY48ePJzMzk2HDhpm3hYeH89NPP7Fx40a8vLz48MMPSUlJsUhKpenatSt33XUXQ4cOZerUqWRmZjJhwgSLMuHh4SQmJjJ37lzatGnDb7/9xsKFlhP/1q9fnxMnTpCQkEBISAhubm7XPZY1ePBg3njjDYYOHcqkSZO4cOECo0aN4oknnjDfn7aGcePG8cYbb9CwYUNatGjB7NmzSUhI4Pvvvwfgww8/JCgoiJiYGLRaLfPnzycwMBBPT0/i4uIwGAy0a9cOvV7Pd999h7Ozs8V9bGuTFrUVOLr5k6x8SFI+pOZY73KSEEKU1dNPP01aWhrdu3e3uJ/82muv0bJlS7p3707nzp0JDAykb9++ZT6uVqtl4cKF5OXl0bZtW5555hnefvttizIPPfQQ//znPxk5ciQtWrRg48aNvP766xZlBgwYQI8ePbjvvvvw8/O74SNier2eFStWkJqaSps2bXjkkUfo0qULM2bMKN+HcQujR49m7NixvPTSS0RFRbF8+XIWL15MeHg4YOrB/v7779O6dWvatGnDyZMnWbp0KVqtFk9PT7766itiY2Np3rw5K1eu5Ndff8XHx8eqMV5No5S6o67Vnjlzhrp163L69GlCQkKsdtyO76/mdGoeC55vT6t63lY7rhCi6uXn53PixAnCwsJwcnKydTiilijt96o8uUha1FZyZV7q1JyyP3QvhBBC3IokaivxcjEl6rRcufQthBDCeiRRW8mI9GmsdhyL85kNty4shBBClJEkaivxNV6kgTYZY1ayrUMRQghRi9g0UU+ZMoU2bdrg5uaGv78/ffv2tRh95mbmz59PREQETk5OREVFsXTp0tsQbem2NRrNwILX2ekQY+tQhBBC1CI2TdTr1q1jxIgR/PXXX8THx1NUVES3bt0sHna/1saNGxk0aBBPP/00O3fupG/fvvTt25e9e/fexsivVxTYki0qkjMFFRuwQAhhe9Yc3UoIa/0+2XTAk6unFQPTVGj+/v5s376de++994b7fPzxx/To0YNx48YB8NZbbxEfH8+MGTP4/PPPqzzmm/F2MQ0dJ53JhKh5HB0d0Wq1nDt3Dj8/PxwdHc0jewlRXkopCgsLuXDhAlqtFkfHyg2CVa1GJsvIMI2V7e198+eQN23axNixYy3Wde/e3WI+U1sIKjrDE3a/o80IBDrYNBYhRPlotVrCwsJISkri3LkKjO0txA3o9XpCQ0PRait38braJGqj0ciYMWOIjY2lWbNmNy2XnJx83VByAQEBJCffuBNXQUEBBQUF5vdZWVnWCfgaAVl7ecshjk35zYHxVXIOIUTVcXR0JDQ0lOLi4luOSS3ErdjZ2WFvb2+VKzPVJlGPGDGCvXv38ueff1r1uFOmTGHy5MlWPeaNOHv4AeBqzKTYYMTeTjrUC1HTaDQaHBwcqmwWJCEqolpkk5EjR7JkyRLWrFlzy6HUAgMDSUlJsViXkpJy08nIx48fT0ZGhnnZv3+/1eK+2pWJObw02WTkyehkQgghrMOmiVopxciRI1m4cCGrV68mLCzslvu0b9+eVatWWayLj4+/4UTmADqdDnd3d/Pi5uZmldivZe9iGpDdiyzpUCaEEMJqbHrpe8SIEcyZM4dffvkFNzc3831mDw8PnJ1Nc7cOGTKEOnXqMGXKFABefPFFOnXqxAcffEDv3r2ZO3cu27Zt48svv7RZPQDQmzrAuWgKSMvMBv+q+UIghBDizmLTFvWsWbPIyMigc+fOBAUFmZd58+aZyyQmJlpMWN6hQwfmzJnDl19+SXR0ND/99BOLFi0qtQPabaHzwHD548xOO2/bWIQQQtQaNm1Rl2WGzbVr11637tFHH+XRRx+tgogqQaslV+uGmzGDvIwLto5GCCFELVEtOpPVFrn2HgAUZF20cSRCCCFqC0nUVlTo6AmAQRK1EEIIK5FEbUXFTl4AqLxUG0cihBCitpBEbU2XE7VGErUQQggrkURtRZrLz1LbF6TbNhAhhBC1hiRqK7LzCOas8iG9SIYfFEIIYR3VZqzv2qCozXPcvz4SN+wZZutghBBC1ArSorYibxfTnKNZBcUUFssE9EIIISpPErUVuTs5oL08o1m6jPcthBDCCuTStxVps86ySDcJo7GY1NyO+Ls72TokIYQQNZy0qK3JzpHmHKa55gSpWXm2jkYIIUQtIC1qa3L2ZqrnRLakwLBcmZNaCCFE5UmL2prs7Dnq04mtKoLUPIOtoxFCCFELSKK2sis9v9NypDOZEEKIypNL31YWU7gDB7sdaC5pgHBbhyOEEKKGkxa1lbW/MI83Hf6Ld2qCrUMRQghRC0iitjLl5A2AJi/NxpEIIYSoDSRRW5nGxZSo7QslUQshhKg8SdRWZu/qC4CuMN22gQghhKgVJFFbmc7NDwDn4gwbRyKEEKI2kERtZc6epha1u8oir1CepRZCCFE5FUrUp0+f5syZM+b3W7ZsYcyYMXz55ZdWC6ymcnI3tag9ySZNJuYQQghRSRVK1I8//jhr1qwBIDk5mQceeIAtW7YwYcIE3nzzTasGWNNo9KbOZN6aLFJl0BMhhBCVVKFEvXfvXtq2bQvAjz/+SLNmzdi4cSPff/89cXFx1oyv5nE2JWpPskjLKbBxMEIIIWq6CiXqoqIidDodACtXruShhx4CICIigqSkJOtFVxNdblE7agxkZqTbNhYhhBA1XoUSddOmTfn888/5448/iI+Pp0ePHgCcO3cOHx8fqwZY4zjoKdSYxvvOyzhv42CEEELUdBVK1O+99x5ffPEFnTt3ZtCgQURHRwOwePFi8yXxsli/fj19+vQhODgYjUbDokWLSi2/du1aNBrNdUtycnJFqlE1NBry7D0AKMi8aONghBBC1HQVmpSjc+fOXLx4kczMTLy8vMzrn332WfR6fZmPk5OTQ3R0NE899RT9+/cv836HDh3C3d3d/N7f37/M+94O2U5BZBUqcvLybB2KEEKIGq5CiTovLw+llDlJnzp1ioULFxIZGUn37t3LfJyePXvSs2fPcp/f398fT0/Pcu93u/x+9/+Y/Ot+emuCbB2KEEKIGq5Cl74ffvhh/ve//wGQnp5Ou3bt+OCDD+jbty+zZs2yaoA30qJFC4KCgnjggQfYsGFDqWULCgrIzMw0L1lZWVUen8xJLYQQwloqlKh37NhBx44dAfjpp58ICAjg1KlT/O9//+OTTz6xaoBXCwoK4vPPP2fBggUsWLCAunXr0rlzZ3bs2HHTfaZMmYKHh4d5adKkSZXFd4WX3pSo5TlqIYQQlVWhS9+5ubm4ubkB8Pvvv9O/f3+0Wi133303p06dsmqAV2vcuDGNGzc2v+/QoQPHjh3jo48+4ttvv73hPuPHj2fs2LHm92fPnq3yZN3g7GIWOc5kc1Yb4N4qPZcQQojarUIt6kaNGrFo0SJOnz7NihUr6NatGwDnz5+36OR1O7Rt25ajR4/edLtOp8Pd3d28XPmCUZVcVRYttMcILkpEKVXl5xNCCFF7VShRT5w4kZdffpn69evTtm1b2rdvD5ha1zExMVYN8FYSEhIICqpenbacmvRmeOFYPi16mByZmEMIIUQlVOjS9yOPPMI999xDUlKS+RlqgC5dutCvX78yHyc7O9uiNXzixAkSEhLw9vYmNDSU8ePHc/bsWXPHtenTpxMWFkbTpk3Jz8/n66+/ZvXq1fz+++8VqUaVcQoM5w+7tuQXGUnLKcRVV6GPWQghhKhYogYIDAwkMDDQPItWSEhIuQY7Adi2bRv33Xef+f2Ve8lDhw4lLi6OpKQkEhMTzdsLCwt56aWXOHv2LHq9nubNm7Ny5UqLY1QX3npHzmXkk5pTSF3vsj9bLoQQQlytQonaaDTy73//mw8++IDs7GwA3NzceOmll5gwYQJabdmuqHfu3LnUe7jXTvDxyiuv8Morr1Qk5NurMJe+9hvJtLtEam4bW0cjhBCiBqtQop4wYQL/+c9/ePfdd4mNjQXgzz//ZNKkSeTn5/P2229bNcgapzifV3KmgQMszBoNVK+R04QQQtQcFUrU//3vf/n666/Ns2YBNG/enDp16vDCCy9IonbyxIgWLUZy0y8ADWwdkRBCiBqqQr2+U1NTiYiIuG59REQEqamplQ6qxtNqybM3PaZWmHnBxsEIIYSoySqUqKOjo5kxY8Z162fMmEHz5s0rHVRtUOBgmkGrKPuSjSMRQghRk1Xo0vf7779P7969WblypfkZ6k2bNnH69GmWLl1q1QBrqmKdF+SdQuXIFQYhhBAVV6EWdadOnTh8+DD9+vUjPT2d9PR0+vfvz759+246lOedxuh0efrPfEnUQgghKq7Cz1EHBwdf12ls165d/Oc//+HLL7+sdGA1ncbFBwD7/DQbRyKEEKImq1CLWtya/eVErStMt20gQgghajRJ1FXE0d0XAOfiDIxGmZhDCCFExUiiriJOlxO1B1lk5RfbOBohhBA1VbnuUffv37/U7enp6ZWJpVZxcDUlai9NNqm5hXjoHWwckRBCiJqoXInaw8PjltuHDBlSqYBqDb03AJ5kk5pTSJivi40DEkIIUROVK1HPnj27quKoffQ+5GmcyUNHWk6hraMRQghRQ8k96qriH8nzoYt5sPAdUnMlUQshhKgYSdRVyFvvCCAtaiGEEBUmiboKebmYErW0qIUQQlSUJOoqNODMuyxyfB1N0i5bhyKEEKKGkkRdheoVnaCF9hiJJ4+RUyDPUgshhCg/SdRVSN9zEhOc/o8thWEs3ZNk63CEEELUQJKoq5CmUReC2w3gIh7M337G1uEIIYSogSRRV7H+Leug1cCWE6mcupRj63CEEELUMJKoq9KlYwSdXMy44D0A/CStaiGEEOUkiboq5VyAhc/y/KUpdNFuZ8H2MzKTlhBCiHKRRF2VQu+Gu0cAMM3xS4ozkth47JKNgxJCCFGTSKKual3fgMDmeJHFhw6f8dO2U7aOSAghRA1i00S9fv16+vTpQ3BwMBqNhkWLFt1yn7Vr19KyZUt0Oh2NGjUiLi6uyuOsFHsdPPINBntn7rHbR8j+r8jIK7J1VEIIIWoImybqnJwcoqOjmTlzZpnKnzhxgt69e3PfffeRkJDAmDFjeOaZZ1ixYkUVR1pJvuFoe74HwIvaH9m0vprHK4QQotoo1zSX1tazZ0969uxZ5vKff/45YWFhfPDBBwBERkby559/8tFHH9G9e/eqCtMqNC2HcGzzrzQ8H0/0lpehcyfQudk6LCGEENVcjbpHvWnTJrp27Wqxrnv37mzatOmm+xQUFJCZmWlesrKyqjrMG9NocH90JmeVL0GGJDIXvGibOIQQQtQoNSpRJycnExAQYLEuICCAzMxM8vLybrjPlClT8PDwMC9NmjS5HaHekJ9fAN8Gv4ZBaXA/vAB2/2izWIQQQtQMNSpRV8T48ePJyMgwL/v377dpPC1ie/JJcX8A1JKxkHrCpvEIIYSo3mpUog4MDCQlJcViXUpKCu7u7jg7O99wH51Oh7u7u3lxc7PtfeH7I/yZoxvIVuNdaAqzYMEzYDTaNCYhhBDVV41K1O3bt2fVqlUW6+Lj42nfvr2NIio/R3stD8bUZUzhCM47BMM9/wRtjfpnEEIIcRvZNENkZ2eTkJBAQkICYHr8KiEhgcTERMB02XrIkCHm8s899xzHjx/nlVde4eDBg3z22Wf8+OOP/POf/7RF+BX2aKu6nMWPTrlTSQvtVrLhxyGwcjJkX7BdcEIIIaoVmybqbdu2ERMTQ0xMDABjx44lJiaGiRMnApCUlGRO2gBhYWH89ttvxMfHEx0dzQcffMDXX39d7R/NulaTYHeaBruTZ9DwS8JZ08rUE7D/F9jwMWg0JYXz0kHJ+OBCCHGnsulz1J07d0aVkoRuNOpY586d2blzZxVGdXs82iqEfef2M3/7GYbFhoFrAAz4D1w6Ci6+JQXnPg4Zp6Hu3VC3LYS0gYBmYGfTfzohhBC3ify1t5GHWtTh7aUH2Hcuk/3nMmkS7A5Rj1gWys+EczuhKBfSE2HP5ce5HPQQ3BLqtoGQtqYEfnVyF0IIUWtIorYRbxdHukYGsGxvMjPXHuXJDvUJ9dHj56pDc+XSt5M7vHwETm+GM1vh9BY4sw0KMuDUn6blCvc6ENgcgppDzN/BM9Q2FRNCCGFVkqht6NHWISzbm8xvu5P4bXcSAM4OdoR66wn10VPPW089Hz0t6rYmqnMX005GI1w8DGe2XE7cW+HCQcg8a1oOL4PGvUoS9aFlcPJPuKsHhHW0UU2FEEJUlCRqG+p8lz+j72/EtlNpnLqUS1JGHnlFBg6lZHEoxXKo07/fHcqEXk1wdrQD/wjT0vJyj/j8TEjZC0m7IXkP+EeW7HjwN9j5rWkWryuJOucS/DENglpAUDT4hoPW7vZUWgghRLlIorYhrVbD2G6Nze8Li42cScvlVGouiZdyOXUpl2MXsll3+ALf/ZXIxmOX+PixGKJCPCwP5OQO9TqYlms17mVK0g3vL1l3bif89VnJewc9BMdcPkas6Z63o4uVayuEEKIiNKq0bte10JkzZ6hbty6nT58mJCTE1uGUyR9HLvDy/F2kZBZgr9Xwzwfu4rlODbHTam69840k7zW1ss8lmFrgRTmW27X2lok79G5w8rjhoYQQQpRfeXKRJOoaIi2nkP9buIdle5MBaFvfmw8GRlPXW1+5AxsNpJ/ejy55K85n/4KTGyDzjGUZjRaaPAyPxpWs++lpKMiCnu+Bd5hpXfJe0/1y7zDwbgjOnpWLTQghaqny5CK59F1DeLk48tnglvy0/QyTFu9jy8lUen38B2/2bUrfFnVKeoqXkdGoWH/kAnM2J7Lq4HlcdSF88OhbdO0fAGmn4NRGOLXBtKQev360tONrIPcSPDC5ZN2BX2HduyXv9T7g3cCUtH0agqs/6NxNl+qdPE2v9d7yaJkQQpRCWtQ1UOKlXP75YwLbT6UB0Lt5EANa1qFZHQ/83ZxK3fd8Vj7zt53hhy2JnEm7fmrQ4R3DeKVHBA52Vw1al5kEuRchMKpk3d6foTAbIh8qaTlvj4Nd8yD1GGRbTp5yU3XbwdO/l7z/7SWwd4K7nwePmvnvI4QQtyKXvktRGxI1QLHByGdrj/HxqiMYjCX/hP5uOqLqeNC0jgdRdTxoVsedADcnNh2/xPebT/H7vhSKL5d3d7JnQKsQHm1Vl5+2n+GbDaYpN2NCPfl0UAwhXpW4rF6QbWqJpx67/PM45KZCfoapl3pBhul1aHt4fJ5pH0MxvBMEhkJ4cRd41Tet3/IVRQdXkOQURmCjljgGNwPfu0yd5IQQogaSRF2K2pKor9h1Op3/bjrJnjMZHLuQjfEG/5rODnbkFRnM71uGevJ4u3o82DwIJ4eSx7JW7Evm5fm7yMovxsPZgQ8ejaZrk4CqrYBSJWObF+XDrjlw8Qh0e9s8q1jWt3/H7divFrsZNfZofBuh8W8CAU3Av4npsTS3YHAo/aqCEELYmiTqUtS2RH213MJiDiRlsudMBnvPZbL3bAZHzmdjMCrcdPb0janD4+1CiQxyv+kxTqfmMnLODnadyQBucin8NvrzyEU+/e5HwosPE6k9TbjmNBGa07hrcm++k4MeWj8F3d82vS/Kh99fM90L7/yvknLHVkPmOdA6mMZO1zqAMpha/PkZN17qtYeuk0z7Gw2w6AXTo2zd/g2Ol69AXDgMxXmme/M61yr5XIQQNZt0JrtD6R3taVXPm1b1vM3r8osMnLyUQ6i3Hr3jrf+563rrmf9cB95ddpBvNpzgqz9OsO1UWuUvhVfA3C2JvLZoL8XGehjrt+Cff2/FiYs5vLfjDFt37yW48DiNNWdorD1NtMNZ6qsz2Kki09joV8u9CFu/AjtHy0S9+UvTSG7l4Rte8rowB3bPNb3u/k7J+g3TIeF702vXQFNHOu8G4NPI9Non3PTe3rF85xZC3JEkUddyTg52RATevAV9I472Wib2aUK7Bt6Mm7+LnYnp9Jz+Bw+1CKZ/yxBahnqWu5d5eRiNivdWHOSLdccB6NsimPceaY7O3g4fVx2t63tT8FBT1hy8wKKdZ5l98DyFuUZAUde5iLH3+NKnVcOSX257J7h3nCmxXi04xtSCNhSBsdj0U6Mx9Uh3cjc9O37t4lsyQA1ae3jgLdMXg6vvl9vrTD3ecy9BdrJpObXB8txae1Oy9mtsOmbYvdCgk5U/SSFEbSCXvkWpTqfmMuqHnSScTjevC/N1oX9MHfrG1Kn8c9zXyCs08M95CSzfZ3pefEzXcF7sEl7qF4P03EJ+25PEfzee5HBKNgARgW5M7NOEDg1t+OhXXhpcutyh7tKxyz+Pmu7BF2Zblm37D+j1vul1VrJpelP3OvDYtyVlEjebOtq5+IHOzXTJ3dFVpjwVogaSe9SlkERdfgajYtOxS/y84wzL9iZbdExrF+bNgJYh9IwKxM3JoVLnOZ+Vz/D/bmPXmQwc7bS890gU/WLK/m9UbDDyw5ZEPog/THpuEQA9mgYyoXek1b9QVIpSpnvjFw7ChUOmn3d1h4jepu3ndsKXncEtCF46WLLfNz0gcdP1x7N3upy0LyduR5fLz6t7mIaQbf6oqVxRPhxaalrf8P6STnz5maYWvoNzyTpryUuH9FOmaVrTLv9MP2V6nZ9h6vjn4GI6t4OzafKY9i9cjjcPVr0Fdg5w/+slX0iOroTUE6ZbGRrt5Zg1N/6pjKYvNx51oeF9pv2NRlg/FYxFcM/Ykr4FyXtNE9vo3E1fhJwu/9Q6mMbC19qDxs7cyfE6SsHZHZCfBvU7llxlObQMjq0xxXFlKS4wXcExFJiu5thfrr+D3vSZeNWH2BdLjn10ZcmIgTJKYK0giboUkqgrJ6egmOV7k1mw4wybjl/iym+Pk4OWLhEBPNg8iPsi/C16k9+KUopdZzIY8f0Ozqbn4al34MsnWtM2zPvWO99Aem4hH8Uf5rvNiRiMCkd7Lc92bMAL9zUs0316m8tLM40QZyyGpn1L1i8YDud2QM4F0+NvynDTQ5jFjikZlCbtJHwcbUoKryWXlPnuETgaD2hMicLRxZS8riR98zrXy+tdTM+/R/Yx7Z+bCr+NNSWev31/g+OWQ+un4MGPTK9zLsHUBqbXE1NLJo6Z/yTs+7l8x418qOTqhFIw2dP0+uWj4Opner10HGz5smzHu5K0wzrC3xeUrP93oKkj4dWPF8a/Yeq3UB5BLeAf60ref9wC0k7Ak8tNHRoBEn6ALV+Aiz+4BZquwLgHg0edktc6t/Kd905WePkW1pXfs8Ic0zo7B9OXQjtH0zYrfZmVzmSiyrjoTM9eD2gVwtn0PBbtPMuCHWc4fiGH3/Yk8dueJFwc7ejaJIAHmwdz712+6OyvT9pn0nLZeOwSm45dYuOxi6RkFgCmy+rfDGtDmG/FJwXx1Dsy+eFmPN6uHpN/3cfGY5eYseYoP20/w+SHm9K9aWCFj31bOHtB5IPXrx/wVclrpUwts8Ic02X0wpyS1wXZUHC553pQC8t96sWakszVzJ3vlGnc96IcuOZ2/nVa55QkamWEfQtNr42Gkj90Ln4lPz1DwbOe6afX5Z96H1PLsjDH1HouyisZjhZMne3u+afpC8DVs7uFtDZ9SSkuNJ0bZarbdT8x/VG1czS1RK/QaKD106ZjXt2hzy3I9HkVZJqGx83PNLV4b8RYDFzu13C1gCaXW83FJevCOpo+cztH0/nsrlrsdaaEX5x/+TPINb2+drQ+v8amsm5X/e5eOmq6+lIanbspYTt7mz4r30bw8MyS7bN7m64i/G2OKXaAE3+YrgK4+Jj+jfS+pnjcg01fAGrqTHtF+aa6pp00/Z7e1a1k24y2cPEQPL8RApqa1u34Fpa/ankMO0d4/ZpRGm8DaVGLSlNKsfdsJkt2n2PJ7iTOppeMeObmZE/3poH0igoku8DApmMX2XjsEqcuWfbMdrTXcn9jf6b0j8LLxXq9oZVS/L4/hX//tp/TqXloNPDhwOhyXVKv9YxGU4IovJykr7QkzK+vWYpyIKSNafx3MCXMbd+YWtrRg0ouUedcMl3GrckzsRUXmpKysdj05cBovOp1sekPt5uNvvilnYTzB02jAGYlm8bozzx3eTlr+qJ2rWtb6tOjTLcjnlll+gIEsH4arH7rxufU2ptuI3jVM33x8qpveu3dEIJblJQrzCn5clKFHU8BUwLOSzOdMy8VMs6YlsyzJa8zzpie/rjCJxxGbSt5/0UnSEqAQfOgcQ/Tuo0z4PcJludycIEJ56wStlz6LoUk6qqllGJHYjpLdp9j6Z4kc0v5WnZaDc1DPOjQ0IfYhr60rOdVrsvl5ZVfZGDyr/v5YUsiWg18MiiGB5sHV9n5hLC5gmzISjIlqfx0U+J09oL695SUObvd1Lr0jyy5TH5iPRyJN93SyL0IORdNt1syz5nu69+IXySM+Kvk/UfNIOM0DF8NdVqZ1v31Ofwx7fK4BQ5XXVJ2KFkHppa/Uqaf7sGWHSq/Hwjn98OA/0BoO9O6zV/CsnFl+0wcXExXc/zugoH/K1mfdtJ079/Zy7K8UpefCCksuVJy5VZJJcmlb2EzGo2GVvW8aFXPi9d7N2HryVSW7E5i9cHzuDs7ENvQhw6NfGhT37vSnc/Kw8nBjrf7NsNoVMzbdpoX5yZgr9XSo1k1vwwuREXpXEEXbvns/7WuJNGrhd1rWq5lNJgSf9rJyx0DL3cKTDtpGh/gaoZC00+7q66OFWSZEn555IZZvs9ONn0BuPpqgaPedPvA0cWUbD1CTIt7nZLXV947e924hX+lP8G1NJqSLxXY7sqQtKjFHcVoVLz80y5+3nEWBzsNswa3qvQwqZn5Raw/fIGV+1PYeOwSne7yY9JDTXHRyfdgcYcqyjMlawcXy1sh2SmXW6ZFptb5ldeGy681GlNPfi7/dHSxHF8gaZephevTqKT3u9F4eb8qvsRuZdKiFuImtFoNUx+JptigWLzrHC98v4Mvh7Sic2P/ch3ndGouKw+ksOrAef46fsk80QnA/O1n2JGYxozHW5Y6XKsQtdaVx+2u5uJjWiojKPr6dTd7XK4WkUQt7jh2Wg0fDoymyGBk2d5knv12O7OHtSG20c0HRzEYFQmn01h98DyrDpznYHKWxfaGfi50bRJARKAb7y07xLELOfSduYE3+jRlUNu6ZRrJ7VByFjPWHOVwchajujSid1SQ1UeAMxoVS/cmcTApC73ODledPa46e1wu/7zy2sfF0aqd+oQQFSeXvsUdq7DYyAvf72DlgRScHLTEPdmWuxuUfOO/lF3AusMXWHvoAuuPXDAPogKmZN+6nhcPNAmgS2SAxeNkqTmFjP0xgbWHTPfj+kQH806/Zje9J38oOYtPVh3htz1JFus7hvvy1sPNqF+JR9Wu9seRC7yz9CAHkjLLVL5tfW/6t6xDr+ZBuN/G/gRC3AlqXK/vmTNnMnXqVJKTk4mOjubTTz+lbdu2NywbFxfHk08+abFOp9ORn59fpnNJohZXKyg28I9vt7P20AX0jna80y+Kk5dyWHPoArvPpHP1/w53J3s63uXHA5EBdG7sh6f+5i1Oo1Hx1R/HeX/FIQxGRX0fPTMeb0mzOiWjSh1MzuSTVUdYuqdk8JGezQIJ83Xh6z9OUGgw4miv5flODXm+c8MK94o/kJTJlGUHWX/Y9MXBTWfPg9FBFBsU2QXF5iWnoJjsfNPrzPyS54B19lq6NQ1kQMs63NPIF3sbzaQmRG1SoxL1vHnzGDJkCJ9//jnt2rVj+vTpzJ8/n0OHDuHvf/19w7i4OF588UUOHTpkXqfRaAgIKFuHIEnU4lr5RQaG/28bfxy5eN22JkHu3Bfhx32N/WlR17PcSWr7qTRGzdnBuYx8HO20vP5gJK3re/PJqiMs21uSoHtFBTLq/nDzPe0TF3OY+Mtec0z1ffS8+XAz7r2r7I+GJGXk8eHvh/lpxxmUAgc7DX+/ux6j7g/H+xaXtZMy8li08xwLdpzh6PmSccn93HT0i6lD/5Z1yj3ZixCiRI1K1O3ataNNmzbMmDEDAKPRSN26dRk1ahT/+te/risfFxfHmDFjSE9Pr9D5JFGLG8krNPD899vZcSqN2Ea+3NfYn06N/Qhwd6r0sdNzC3l5/m5WHki5blvvqCBGdWl0w6SnlOK3PUm8+et+zmeZnkfv3TyI13s3IdDj5nFl5Rfx+bpj/OfPE+QXGc3neaVHY+r5lO8yulKKPWczWLD9DIt3nSPtqsv/vaICmdKvOR56uSwuRHnVmERdWFiIXq/np59+om/fvub1Q4cOJT09nV9++eW6feLi4njmmWeoU6cORqORli1b8s4779C0adMynVMStbAFpRT/+fME7y0/SLFR0SsqiNH3h9M48NZjMWflF/Fh/GH+u/EkRgXODnb4uekoNhgpNiqKjYoigxGDUVFsUBQZjeZL9m3qe/F/vSKJCfUq/SRlUFhsZO2h8yzYcYZVB85TbFQEezjx8aAY2tSv2LjsQtypaszjWRcvXsRgMFx32TogIICDBw/ecJ/GjRvzzTff0Lx5czIyMpg2bRodOnRg3759N6xsQUEBBQUlo2NlZWVdV0aIqqbRaHimYwMeuPzMdnlatm5ODrzRpykDWobw2qK9JJxOJzE1t9R9Gvi58K8eETzQJMBqPccdL9+r7tY0kN1n0hn9w05OXsrlsS82MbpLOCPvayT3r4WoAjXu8az27dvTvn178/sOHToQGRnJF198wVtvXT8+7ZQpU5g8efLtDFGImyrvpeerNavjwc/Pd2DfuUwKDUbstRrs7TQ42Gmx02pw0GqxtzOt83PVWf3Rrqs1D/FkyeiOTPxlLz/vOMv0lUfYePQSH/2tBXU8nW99ACFEmdn066+vry92dnakpFjeu0tJSSEwsGxDOzo4OBATE8PRo0dvuH38+PFkZGSYl/3791c6biFsRavVEBXiQat6XkTX9aRpsAd3BbjR0M+VUB89wZ7O+Ls5VWmSvsJVZ8+HA1sw/bEWuDjaseVkKr0+/oPle5NuuW9GXhGnU3O5lF1AfpGBavDwiRDVlk1b1I6OjrRq1YpVq1aZ71EbjUZWrVrFyJEjy3QMg8HAnj176NWr1w2363Q6dDqd+X1mZtmeIRVClE3fmDrEhHoy+oed7DqTwXPf7eDxdqE8c08Y59LzSUzNJTE1l9OXfyam5pKRZzm5g71Wg97Rzjzgil5nj6ezA/dH+PNQdLAMviLuaDbv9T1v3jyGDh3KF198Qdu2bZk+fTo//vgjBw8eJCAggCFDhlCnTh2mTJkCwJtvvsndd99No0aNSE9PZ+rUqSxatIjt27fTpEmTW55POpMJUTUKi418GH+Yz9cdK1N5nb2WgmLjLcs52GnoEhHAgFYhdG7sh4PcBxe1QI3pTAbw2GOPceHCBSZOnEhycjItWrRg+fLl5g5miYmJaK8ayzUtLY3hw4eTnJyMl5cXrVq1YuPGjWVK0kKIquNor+VfPSOIbeTD+J/3cCGrgFBvPXW99RY/Q731hHg546Kzx2BU5BQWk1tgMA+6klNQTE6hgVOXcvh5x1n2J2WyfF8yy/cl4+PiyMMt6jCgVR2aBnvcNJYig5GcgmKcHe3Q2Vt/+tQrj63F708hLbcQe60WrcbUP0Cr0WCnBTutFjuNBl83Rzrd5UeIl97qcVSGUoozaXlsPZnKufQ8HmwebLVR8IR12bxFfbtJi1qIqnflz4o17pUfSMpkwfYzLEo4x8Xskic4IgLdqOPpTNaVUdUu/8zKLza31PWOdnRvGsjDLYIrPaqa0ahIOJPOsj1JLN2TzNn0vHLtHxHoRpdIf+6PCKBFXU/stLd3tieDUXEwOZNtJ9PYcjKVbSdTLeaLd3awY3yvCP7erh7a2xzbnajGPEdtC5KohaiZig1G1h+5wE/bz7By/3kKDbe+bH41HxdHejcP4uEWdWgZ6lmmLxFGo2JHYhpL9ySzbG8SSRklQxXrHe24L8Kfhn6uGI0Kg1IYjJZLsVFx9HwW20+lcdUEa3i7ONK5sR9dIgLoeJdvlY2lXmQwsnDnWX7bncSOU2lkFRRbbLe/3DlRA+xITAfgnka+vPdI8xrRe18pRWJqLn8dv8Rfx1PRO9rxzwfuwtdVd+udbUwSdSkkUQtR86XnFrL64HmKDEZcdQ646OxwcyqZBcxN54BeZ8fuMxksTjjLkt1JXMopNO9f19uZh6PrcO9dfuQWFpOaU8il7EIu5RRyKbvA9D6nkDNpuVzMLtnPVWdPl0h/ejYLotNdfjg7lu2yelpOIesOX2DVwfOsPXSerKvGUne00zKgVR2e69SwUo/vXa3YYGRRwjk+XX2EU5dKnrl31dnTsp4Xbep50SbMm+gQT5wd7TAaFd/+dYopyw6QX2TETWfPxD5NeKRVyG15gqA8Tqfmsun4JVNyPnaJcxmW8zwEezjxxROtiQq5+a2R6kASdSkkUQtx5yk2GPnz6EUWJ5xjxb5kcgoNZd7XTWfPA00C6BkVRMdw3wpPjnJFkcHI9lNprDqQwqqD5zl+IQcArQYeig5mxH2NCA+49Yh1N2IwKhbvOssnq45y4qLpuD4ujjx1Txid7vIjMsi91Evuxy9k89L8Xey83LruGhnAO/2b4e9W+aF0y0IpRVpuEReyCjiflc+FrILLrwtIycwn4XQ6Z9Isbzk42GmIDvGkXQNvlu1J5vjFHHT2Wt4b0Jy+MXVuS9wVIYm6FJKohbiz5RUaWHkghV8SzrL/XCYeekd8XR3xdjEtvq46vF0c8XFxxNdNR9Ng9yrpkHbF1pOpzFh9lHWXZzcD6NE0kJH3N7KYba00BqNpXPiPVx7m2OXE76V34LlODXmifT30jmXvN2wwKr5Yf4yP4g9TZFB46R14u18UvaKCylexMlBKkXA6nV8SzrHqYArJGfkUGUpPSfZaDc1DPGjf0Ie7G/jQqp6XuX4ZeUWMmbuTNZenmH323ga82iOiTP0BMvOL2HTsEo38XWno51r5yt2CJOpSSKIWQlRHe85kMHPNUZbvK5lVrdNdfoy4rxGN/F3JKSgmt9Bg7iWfU1hMbmExaTlF/LAlkSOXZznz1DswvGMDhnaoj6uu4g/2HEjKZOyPu8zzl4d4OePnpsPX1bT4uZq+yFx5H+ThRLCnc5mS4vEL2SxKOMfihLOcvHT9cLheegf83HT4uzld/mk6R3iAK23qe+NSSr0MRsUHvx/is7WmxwQ7hvvy6aCYG05Lq5Ri95kM5mxOZPGuc+QVma60dLrLj6fuCePecN8qu/QviboUkqiFENXZ4ZQsPltzlMW7zll0QLsVdyd7hndswLDY+rhZqXNaYbGRT1cf4bO1xzCUIRhHey31ffSE+boQ5utKA18XwvxcCPN1wWhU/Lo7iV8SzrL7TIZ5H2cHOx5oEsDDLYKJDHLH11WHo33ln5Vfsvsc4+bvJq/IQD0fPV8+0do8CU52QTG/JJxlzuZE9p0rGQSrjqcz5zLyzJPaNPJ3ZViH+vRvWadcVyXKQhJ1KSRRCyFqglOXcvh83TEWbD9LocGIk4MWF0d79Do7009HO9Mobo52RNXxYEiH+lXWe/xCVgGJqTlcyCrkYnZByXL5/YXsApLS88vcE99Oq6FjuC99W9ThgSYBpbaQK2P/uUyG/28bZ9Pz0DvaMb5XJPvPZbI44ay5n4KjvZZezQJ5vF092tT3IjE1l7iNJ5m/7QzZl3vJezg7MKhtKEPa1yPYSr3hJVGXQhK1EKImKTIYLw+iUr16X1/LYFScS8/j+MUcTlzI5sTFHNPrizmcTTe1UmNCPenbog69mwfdtkeoUnMKGfH9DjYdv2SxvoGvC4+3C2VAy5AbDlGblV/E/G1niNt40jxbnZ1WQ89mgbx2iznhy0ISdSkkUQshxO2VX2Qgr9BgszHbiwxG3l12kHlbT3NfhD+Ptw3l7gbeZbr/bDAqVh88zzd/nmDT8Uu46ezZ9H9dKnX/H2rYEKJCCCFqNycHu0o/1lYZDnZaXn+wCa8/WP6hpu20Gh5oEsADTQLYfy6TYxeyK52ky0sStRBCCFEGTYLdaRLsftvPK9PQCCGEENWYJGohhBCiGpNELYQQQlRjkqiFEEKIakwStRBCCFGN3XG9vo1G08g5SUlJNo5ECCHEnepKDrqSk0pzxyXqlJQUANq2bWvjSIQQQtzpUlJSCA0NLbXMHTcyWXFxMTt37iQgIACttnJX/rOysmjSpAn79+/Hza1i88cKURPJ7764E1nz995oNJKSkkJMTAz29qW3me+4RG1NmZmZeHh4kJGRgbv77X8IXghbkd99cSey1e+9dCYTQgghqjFJ1EIIIUQ1Jom6EnQ6HW+88QY63e2Zrk2I6kJ+98WdyFa/93KPWgghhKjGpEUthBBCVGOSqIUQQohqTBK1EEIIUY1Joq6EmTNnUr9+fZycnGjXrh1btmyxdUhCVKn169fTp08fgoOD0Wg0LFq0yNYhCVHlpkyZQps2bXBzc8Pf35++ffty6NCh23Z+SdQVNG/ePMaOHcsbb7zBjh07iI6Opnv37pw/f97WoQlRZXJycoiOjmbmzJm2DkWI22bdunWMGDGCv/76i/j4eIqKiujWrRs5OTm35fzS67uC2rVrR5s2bZgxYwZgGg6ubt26jBo1in/96182jk6IqqfRaFi4cCF9+/a1dShC3FYXLlzA39+fdevWce+991b5+aRFXQGFhYVs376drl27mtdptVq6du3Kpk2bbBiZEEKIqpaRkQGAt7f3bTmfJOoKuHjxIgaDgYCAAIv1AQEBJCcn2ygqIYQQVc1oNDJmzBhiY2Np1qzZbTnnHTfNpRBCCFFRI0aMYO/evfz555+37ZySqCvA19cXOzs789zWV6SkpBAYGGijqIQQQlSlkSNHsmTJEtavX09ISMhtO69c+q4AR0dHWrVqxapVq8zrjEYjq1aton379jaMTAghhLUppRg5ciQLFy5k9erVhIWF3dbzS4u6gsaOHcvQoUNp3bo1bdu2Zfr06eTk5PDkk0/aOjQhqkx2djZHjx41vz9x4gQJCQl4e3sTGhpqw8iEqDojRoxgzpw5/PLLL7i5uZn7Inl4eODs7Fzl55fHsyphxowZTJ06leTkZFq0aMEnn3xCu3btbB2WEFVm7dq13HfffdetHzp0KHFxcbc/ICFuA41Gc8P1s2fPZtiwYVV/fknUQgghRPUl96iFEEKIakwStRBCCFGNSaIWQgghqjFJ1EIIIUQ1JolaCCGEqMYkUQshhBDVmCRqIYQQohqTRC2EEEJUY5KohRBVRqPRsGjRIluHIUSNJolaiFpq2LBhaDSa65YePXrYOjQhRDnIpBxC1GI9evRg9uzZFut0Op2NohFCVIS0qIWoxXQ6HYGBgRaLl5cXYLosPWvWLHr27ImzszMNGjTgp59+sth/z5493H///Tg7O+Pj48Ozzz5Ldna2RZlvvvmGpk2botPpCAoKYuTIkRbbL168SL9+/dDr9YSHh7N48WLztrS0NAYPHoyfnx/Ozs6Eh4df98VCiDudJGoh7mCvv/46AwYMYNeuXQwePJi//e1vHDhwAICcnBy6d++Ol5cXW7duZf78+axcudIiEc+aNYsRI0bw7LPPsmfPHhYvXkyjRo0szjF58mQGDhzI7t276dWrF4MHDyY1NdV8/v3797Ns2TIOHDjArFmz8PX1vX0fgBA1gRJC1EpDhw5VdnZ2ysXFxWJ5++23lVJKAeq5556z2Kddu3bq+eefV0op9eWXXyovLy+VnZ1t3v7bb78prVarkpOTlVJKBQcHqwkTJtw0BkC99tpr5vfZ2dkKUMuWLVNKKdWnTx/15JNPWqfCQtRSco9aiFrsvvvuY9asWRbrvL29za/bt29vsa19+/YkJCQAcODAAaKjo3FxcTFvj42NxWg0cujQITQaDefOnaNLly6lxtC8eXPzaxcXF9zd3Tl//jwAzz//PAMGDGDHjh1069aNvn370qFDhwrVVYjaShK1ELWYi4vLdZeircXZ2blM5RwcHCzeazQajEYjAD179uTUqVMsXbqU+Ph4unTpwogRI5g2bZrV4xWippJ71ELcwf7666/r3kdGRgIQGRnJrl27yMnJMW/fsGEDWq2Wxo0b4+bmRv369Vm1alWlYvDz82Po0KF89913TJ8+nS+//LJSxxOitpEWtRC1WEFBAcnJyRbr7O3tzR225s+fT+vWrbnnnnv4/vvv2bJlC//5z38AGDx4MG+88QZDhw5l0qRJXLhwgVGjRvHEE08QEBAAwKRJk3juuefw9/enZ8+eZGVlsWHDBkaNGlWm+CZOnEirVq1o2rQpBQUFLFmyxPxFQQhhIolaiFps+fLlBAUFWaxr3LgxBw8eBEw9sufOncsLL7xAUFAQP/zwA02aNAFAr9ezYsUKXnzxRdq0aYNer2fAgAF8+OGH5mMNHTqU/Px8PvroI15++WV8fX155JFHyhyfo6Mj48eP5+TJkzg7O9OxY0fmzp1rhZoLUXtolFLK1kEIIW4/jUbDwoUL6du3r61DEUKUQu5RCyGEENWYJGohhBCiGpN71ELcoeSulxA1g7SohRBCiGpMErUQQghRjUmiFkIIIaoxSdRCCCFENSaJWgghhKjGJFELIYQQ1ZgkaiGEEKIak0QthBBCVGOSqIUQQohq7P8B1Sh5DnsXWQkAAAAASUVORK5CYII=\n", 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" ] @@ -1994,7 +1996,7 @@ "base_uri": "https://localhost:8080/" }, "id": "VQ2NZMbfucAc", - "outputId": "8416b4ac-1993-4628-dea6-7789cdc8926c" + "outputId": "066c56ff-b52a-4ee6-eae7-1bddfc74d0c1" }, "outputs": [ { @@ -2097,14 +2099,14 @@ "base_uri": "https://localhost:8080/" }, "id": "-PNGKzY4snKP", - "outputId": "0453dfb3-51cd-49e2-9e63-f65b606c3478" + "outputId": "37b22a62-9860-40b7-c46f-b297782b944c" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 110/110 [01:11<00:00, 1.54it/s]\n" + "100%|██████████| 110/110 [01:20<00:00, 1.37it/s]\n" ] } ], @@ -2151,7 +2153,7 @@ "base_uri": "https://localhost:8080/" }, "id": "u-AvCCMTnPSE", - "outputId": "ce3b2545-8990-4446-e44c-a945e0049c06" + "outputId": "7bcd9600-1446-4829-b773-5259b13d256a" }, "outputs": [ { @@ -2185,7 +2187,7 @@ "base_uri": "https://localhost:8080/" }, "id": "8cBU0iHmVfOI", - "outputId": "d6e7f226-9310-43f5-f31f-adc3a893a8e9", + "outputId": "135849ed-9acd-43a2-f438-053d07dae9b2", "scrolled": true }, "outputs": [ @@ -2335,7 +2337,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "026e8570-071e-48a2-aa38-64d7be35f288", "metadata": { "colab": { @@ -2374,7 +2376,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "723c9b00-e3cd-4092-83c3-6e48b5cf65b0", "metadata": { "id": "723c9b00-e3cd-4092-83c3-6e48b5cf65b0" @@ -2418,10 +2420,11 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "e3ae0e10-2b28-42ce-8ea2-d9366a58088f", "metadata": { - "id": "e3ae0e10-2b28-42ce-8ea2-d9366a58088f" + "id": "e3ae0e10-2b28-42ce-8ea2-d9366a58088f", + "outputId": "cc43acb3-8216-43cf-c77d-71d4089dc96c" }, "outputs": [ { @@ -2510,10 +2513,11 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "86b839d4-064d-4178-b2d7-01691b452e5e", "metadata": { - "id": "86b839d4-064d-4178-b2d7-01691b452e5e" + "id": "86b839d4-064d-4178-b2d7-01691b452e5e", + "outputId": "1c755ee1-bded-4450-9b84-1466724f389a" }, "outputs": [ { @@ -2611,10 +2615,11 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "9d7bca69-97c4-47a5-9aa0-32f116fa37eb", "metadata": { - "id": "9d7bca69-97c4-47a5-9aa0-32f116fa37eb" + "id": "9d7bca69-97c4-47a5-9aa0-32f116fa37eb", + "outputId": "110223c0-90ca-481d-b2d2-f6ac46d3c4f0" }, "outputs": [ { @@ -2749,7 +2754,9 @@ { "cell_type": "markdown", "id": "b9cc51ec-e06c-4470-b626-48401a037851", - "metadata": {}, + "metadata": { + "id": "b9cc51ec-e06c-4470-b626-48401a037851" + }, "source": [ "## What's next?\n", "\n", @@ -2785,7 +2792,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.16" } }, "nbformat": 4, diff --git a/requirements.txt b/requirements.txt index 82c291b..f1bbb7b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,9 +1,9 @@ -torch >= 2.0.1 # all +torch >= 2.3.0 # all jupyterlab >= 4.0 # all tiktoken >= 0.5.1 # ch02; ch04; ch05 matplotlib >= 3.7.1 # ch04; ch05 -tensorflow >= 2.15.0 # ch05 +tensorflow >= 2.18.0 # ch05 tqdm >= 4.66.1 # ch05; ch07 -numpy >= 1.25, < 2.0 # dependency of several other libraries like torch and pandas +numpy >= 1.26, < 2.1 # dependency of several other libraries like torch and pandas pandas >= 2.2.1 # ch06 psutil >= 5.9.5 # ch07; already installed automatically as dependency of torch