From 850522987972d133f1dad335a1e162bfac57afae Mon Sep 17 00:00:00 2001 From: Antoine Lhermitte Date: Mon, 19 May 2025 09:41:35 +0200 Subject: [PATCH] Created using Colab --- lab1/PT_Part2_Music_Generation.ipynb | 209 +++++++++++++-------------- 1 file changed, 98 insertions(+), 111 deletions(-) diff --git a/lab1/PT_Part2_Music_Generation.ipynb b/lab1/PT_Part2_Music_Generation.ipynb index 10675b1..6472dcd 100644 --- a/lab1/PT_Part2_Music_Generation.ipynb +++ b/lab1/PT_Part2_Music_Generation.ipynb @@ -76,37 +76,11 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": { - "id": "riVZCVK65QTH", - "outputId": "17c9c851-7bf9-4982-c1e2-d8ff6af8179b", - "colab": { - "base_uri": "https://localhost:8080/" - } + "id": "riVZCVK65QTH" }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.8/2.8 MB\u001b[0m \u001b[31m71.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", - 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"\u001b[2K \u001b[91m━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.8/127.9 MB\u001b[0m \u001b[31m137.3 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m" - ] - } - ], + "outputs": [], "source": [ "!pip install comet_ml > /dev/null 2>&1\n", "import comet_ml\n", @@ -155,13 +129,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": { "id": "P7dFnP5q3Jve", "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "8dd11f48-56d4-4bb9-b7e2-378b30c2ec2c" + "outputId": "a8c08c56-45d5-44f9-e494-3146cec64c68" }, "outputs": [ { @@ -205,14 +179,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": { "id": "11toYzhEEKDz", "colab": { "base_uri": "https://localhost:8080/", "height": 62 }, - "outputId": "f350f8b9-4707-4eba-ae38-2e4780d41503" + "outputId": "ad6513c2-a810-49c1-cda3-967d24dc4e0d" }, "outputs": [ { @@ -231,7 +205,7 @@ ] }, "metadata": {}, - "execution_count": 4 + "execution_count": 5 } ], "source": [ @@ -250,13 +224,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": { "id": "IlCgQBRVymwR", "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "4c1555b3-09af-4c36-dfee-bf0180da9189" + "outputId": "360e91e3-1351-4981-d64a-b990cc847db4" }, "outputs": [ { @@ -304,7 +278,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": { "id": "IalZLbvOzf-F" }, @@ -334,13 +308,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": { "id": "FYyNlCNXymwY", "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "99322275-ceb6-4958-a3ff-a922fc8f6399" + "outputId": "ea79a0a6-e42b-4acd-d9f9-4449f31ade3e" }, "outputs": [ { @@ -382,7 +356,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": { "id": "g-LnKyu4dczc" }, @@ -416,13 +390,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": { "id": "l1VKcQHcymwb", "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "e473e251-cb38-4474-d423-102540fb7d74" + "outputId": "c3b10a78-4f92-4584-d9ed-d60e5b09e660" }, "outputs": [ { @@ -456,13 +430,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": { "id": "LF-N8F7BoDRi", "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "58dd551b-c2de-47ae-ccef-b51827c32325" + "outputId": "cc573ead-2800-4f62-f754-51b01a562a94" }, "outputs": [ { @@ -471,6 +445,14 @@ "text": [ "Batch function works correctly!\n" ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + ":16: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at /pytorch/torch/csrc/utils/tensor_new.cpp:254.)\n", + " x_batch = torch.tensor(input_batch, dtype=torch.long)\n" + ] } ], "source": [ @@ -515,13 +497,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": { "id": "0eBu9WZG84i0", "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "0f0892cd-3dc5-4b91-f103-561f020f68bc" + "outputId": "a311863c-bae0-4abd-afa0-259df383ffcd" }, "outputs": [ { @@ -529,20 +511,20 @@ "name": "stdout", "text": [ "Step 0\n", - " input: 74 (np.str_('s'))\n", - " expected output: 0 (np.str_('\\n'))\n", + " input: 31 (np.str_('F'))\n", + " expected output: 26 (np.str_('A'))\n", "Step 1\n", - " input: 0 (np.str_('\\n'))\n", - " expected output: 51 (np.str_('Z'))\n", + " input: 26 (np.str_('A'))\n", + " expected output: 31 (np.str_('F'))\n", "Step 2\n", - " input: 51 (np.str_('Z'))\n", - " expected output: 22 (np.str_(':'))\n", - "Step 3\n", - " input: 22 (np.str_(':'))\n", + " input: 31 (np.str_('F'))\n", " expected output: 1 (np.str_(' '))\n", - "Step 4\n", + "Step 3\n", " input: 1 (np.str_(' '))\n", - " expected output: 64 (np.str_('i'))\n" + " expected output: 27 (np.str_('B'))\n", + "Step 4\n", + " input: 27 (np.str_('B'))\n", + " expected output: 31 (np.str_('F'))\n" ] } ], @@ -612,7 +594,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": { "id": "8DsWzojvkbc7" }, @@ -667,13 +649,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": { "id": "MtCrdfzEI2N0", "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "3b9089b9-308d-4d81-d867-b56e759b8472" + "outputId": "d4a1e3fe-b8f1-496c-8241-5276ec3deced" }, "outputs": [ { @@ -719,13 +701,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": { "id": "C-_70kKAPrPU", "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "aa0ce1f3-0f54-4e86-90af-821f8bfd8ba1" + "outputId": "d60bc4e1-526e-4762-edec-2a263e45eca8" }, "outputs": [ { @@ -767,29 +749,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": { "id": "4V4MfFg0RQJg", "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "3aa0b188-ee08-4134-9520-5fbf89f0f399" + "outputId": "02177f4c-e851-4175-ac49-2aeed87bf8c3" }, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ - "array([46, 1, 28, 7, 31, 39, 66, 5, 74, 40, 20, 42, 79, 35, 67, 33, 10,\n", - " 54, 68, 39, 39, 23, 42, 26, 55, 17, 65, 49, 22, 43, 26, 9, 42, 49,\n", - " 13, 44, 61, 39, 5, 3, 58, 22, 82, 10, 75, 73, 34, 19, 19, 67, 16,\n", - " 62, 70, 61, 46, 78, 73, 24, 57, 24, 52, 11, 47, 12, 10, 7, 30, 21,\n", - " 4, 20, 81, 27, 66, 52, 62, 44, 71, 46, 27, 61, 12, 30, 60, 71, 11,\n", - " 74, 15, 70, 78, 25, 32, 11, 74, 41, 44, 3, 72, 58, 29, 48])" + "array([55, 45, 9, 77, 71, 25, 37, 21, 35, 8, 21, 37, 66, 61, 4, 14, 65,\n", + " 21, 55, 62, 73, 82, 9, 18, 40, 82, 47, 65, 75, 67, 64, 71, 67, 65,\n", + " 62, 37, 8, 43, 39, 76, 28, 40, 33, 66, 82, 10, 50, 49, 12, 80, 13,\n", + " 6, 1, 26, 44, 0, 48, 22, 2, 64, 2, 33, 24, 73, 19, 12, 60, 10,\n", + " 11, 1, 75, 3, 9, 61, 25, 15, 71, 70, 50, 36, 27, 54, 35, 21, 27,\n", + " 8, 21, 58, 70, 47, 28, 46, 55, 14, 30, 10, 29, 6, 41, 76])" ] }, "metadata": {}, - "execution_count": 31 + "execution_count": 16 } ], "source": [ @@ -809,13 +791,13 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": { "id": "xWcFwPwLSo05", "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "70fc3bd5-53a4-4338-cbce-15b3eaa93dce" + "outputId": "bb8e5bf4-858d-45b3-9c5b-a12178664389" }, "outputs": [ { @@ -823,10 +805,10 @@ "name": "stdout", "text": [ "Input: \n", - " 'dB BA:|!\\nBd|gdBd gagf|edef gdBd|gdBd gagf|edef g2ef|!\\ngdBd gdBd|gbaf gdBd|gfga gfed|egfa gd|]!\\nBd|eg'\n", + " \"G|EAAG ABAG|EAAG A2cd|!\\ne3c d3B|c3A B2AG|EGGF GAGE|DGGF G2:|!\\n\\nX:277\\nT:Paddy Cronin's\\nZ: id:dc-reel-\"\n", "\n", "Next Char Predictions: \n", - " 'U C)FNk\\'sO8QxJlH.^mNNG/sPS\"qcDW'\n" + " '_T-vp>L9J,9Lkf#2j9_gr|-6O|VjtlipljgL,RNuCOHk|.YX0y1( AS\\nW:!i!H=r70e./ t\"-f>3poYKB^J9B,9coVCU_2E.D(Pu'\n" ] } ], @@ -864,7 +846,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": { "id": "4HrXTACTdzY-" }, @@ -915,16 +897,16 @@ "colab": { "base_uri": "https://localhost:8080/" }, - "outputId": "06349219-e25f-4034-866b-170b4453af3a" + "outputId": "3a2ea7f6-6c10-4bcf-97de-aa8d93ca8bc0" }, - "execution_count": null, + "execution_count": 19, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Prediction shape: torch.Size([32, 100, 83]) # (batch_size, sequence_length, vocab_size)\n", - "scalar_loss: 4.415239334106445\n" + "scalar_loss: 4.413219451904297\n" ] } ] @@ -940,7 +922,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": { "id": "JQWUUhKotkAY" }, @@ -978,7 +960,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": { "id": "MBsN1vvxInmN" }, @@ -1018,48 +1000,53 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": { "id": "F31vzJ_u66cb", "colab": { - "base_uri": "https://localhost:8080/" + "base_uri": "https://localhost:8080/", + "height": 936 }, - "outputId": "a42d7aed-7f33-4107-8adf-65a4df0b33fa" + "outputId": "e868a96e-5a88-4c20-8bfc-1610cec0fb3a" }, "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" 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"\u001b[1;38;5;39mCOMET INFO:\u001b[0m loss [3300] : (0.6035333871841431, 5.203954696655273)\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m Others:\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m notebook_url : https://colab.research.google.com/notebook#fileId=https%3A%2F%2Fgithub.com%2FMITDeepLearning%2Fintrotodeeplearning%2Fblob%2Fmaster%2Flab1%2FPT_Part2_Music_Generation.ipynb\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m Parameters:\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m batch_size : 8\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m embedding_dim : 256\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m hidden_size : 1024\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m learning_rate : 0.005\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m num_training_iterations : 3000\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m seq_length : 100\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m Uploads:\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m environment details : 1\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m filename : 1\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m installed packages : 1\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m notebook : 1\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m os packages : 1\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m source_code : 1\n", - "\u001b[1;38;5;39mCOMET INFO:\u001b[0m \n", - "\u001b[1;38;5;214mCOMET WARNING:\u001b[0m As you are running in a Jupyter environment, you will need to call `experiment.end()` when finished to ensure all metrics and code are logged before exiting.\n" + "100%|██████████| 3000/3000 [01:07<00:00, 44.23it/s]\n", + "\u001b[1;38;5;39mCOMET INFO:\u001b[0m Uploading 111 metrics, params and output messages\n" ] + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "True" + ] + }, + "metadata": {}, + "execution_count": 22 + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" 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