From ec852842734ff1f749e028c109288cf389e72734 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Laure=CE=B7t?= Date: Wed, 13 Apr 2022 09:13:39 +0200 Subject: [PATCH 1/2] fix: typo --- n7tensorflow.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/n7tensorflow.sh b/n7tensorflow.sh index 57f953f..c634bb5 100644 --- a/n7tensorflow.sh +++ b/n7tensorflow.sh @@ -8,7 +8,7 @@ export LD_LIBRARY_PATH=/applications/matlabr2021b/bin/glnxa64/:$LD_LIBRARY_PATH # on installe un environnement virtuel python python3 -m venv .env source .env/bin/activate -python -m pip install pip tensorflow matplotlib numpy sklearn ipykernel jupterlab +python -m pip install pip tensorflow matplotlib numpy sklearn ipykernel jupyterlab # on inscrit le venv dans la liste des kernels ipython python -m ipykernel install --user --name=.env From 8aa27ce006de9183272889e3100881120309d130 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Laure=CE=B7t?= Date: Wed, 13 Apr 2022 09:24:48 +0200 Subject: [PATCH 2/2] feat: sauvegarde d'un premier model --- models/rot_25e/keras_metadata.pb | 13 ++ models/rot_25e/saved_model.pb | Bin 0 -> 153063 bytes .../variables/variables.data-00000-of-00001 | Bin 0 -> 11935127 bytes models/rot_25e/variables/variables.index | Bin 0 -> 2754 bytes src/notebook.ipynb | 158 +++++++++++------- 5 files changed, 109 insertions(+), 62 deletions(-) create mode 100644 models/rot_25e/keras_metadata.pb create mode 100644 models/rot_25e/saved_model.pb create mode 100644 models/rot_25e/variables/variables.data-00000-of-00001 create mode 100644 models/rot_25e/variables/variables.index diff --git a/models/rot_25e/keras_metadata.pb b/models/rot_25e/keras_metadata.pb new file mode 100644 index 0000000..e5de57d --- /dev/null +++ b/models/rot_25e/keras_metadata.pb @@ -0,0 +1,13 @@ + +Oroot"_tf_keras_sequential*O{"name": "sequential_1", "trainable": true, "expects_training_arg": true, "dtype": "float32", "batch_input_shape": null, "must_restore_from_config": false, "class_name": "Sequential", 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\n", - " conv2d_2 (Conv2D) (None, 9, 21, 92) 53084 \n", + " conv2d_4 (Conv2D) (None, 22, 47, 64) 18496 \n", " \n", - " max_pooling2d_2 (MaxPooling (None, 4, 10, 92) 0 \n", + " max_pooling2d_4 (MaxPooling (None, 11, 23, 64) 0 \n", " 2D) \n", " \n", - " flatten (Flatten) (None, 3680) 0 \n", + " conv2d_5 (Conv2D) (None, 9, 21, 92) 53084 \n", " \n", - " dense (Dense) (None, 250) 920250 \n", + " max_pooling2d_5 (MaxPooling (None, 4, 10, 92) 0 \n", + " 2D) \n", " \n", - " dense_1 (Dense) (None, 4) 1004 \n", + " flatten_1 (Flatten) (None, 3680) 0 \n", + " \n", + " dense_2 (Dense) (None, 250) 920250 \n", + " \n", + " dense_3 (Dense) (None, 4) 1004 \n", " \n", "=================================================================\n", "Total params: 993,730\n", @@ -188,53 +197,63 @@ "name": "stderr", "output_type": "stream", "text": [ - "2022-04-06 08:11:35.469372: I tensorflow/core/platform/cpu_feature_guard.cc:151] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA\n", - "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n", - "2022-04-06 08:11:36.213690: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1525] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 1538 MB memory: -> device: 0, name: Quadro K620, pci bus id: 0000:03:00.0, compute capability: 5.0\n", - "2022-04-06 08:11:37.102887: W tensorflow/core/framework/cpu_allocator_impl.cc:82] Allocation of 204000000 exceeds 10% of free system memory.\n", - "2022-04-06 08:11:37.327551: W tensorflow/core/framework/cpu_allocator_impl.cc:82] Allocation of 204000000 exceeds 10% of free system memory.\n" + "2022-04-13 09:18:16.270030: W tensorflow/core/framework/cpu_allocator_impl.cc:82] Allocation of 204000000 exceeds 10% of free system memory.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Epoch 1/10\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "2022-04-06 08:11:38.606991: I tensorflow/stream_executor/cuda/cuda_dnn.cc:368] Loaded cuDNN version 8100\n", - "2022-04-06 08:11:39.092316: W tensorflow/stream_executor/gpu/asm_compiler.cc:111] *** WARNING *** You are using ptxas 10.1.243, which is older than 11.1. ptxas before 11.1 is known to miscompile XLA code, leading to incorrect results or invalid-address errors.\n", - "\n", - "You may not need to update to CUDA 11.1; cherry-picking the ptxas binary is often sufficient.\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "136/136 [==============================] - 8s 38ms/step - loss: 1.3213 - accuracy: 0.3459 - val_loss: 2.0370 - val_accuracy: 0.0000e+00\n", - "Epoch 2/10\n", - "136/136 [==============================] - 5s 35ms/step - loss: 1.2617 - accuracy: 0.5968 - val_loss: 2.0015 - val_accuracy: 0.0000e+00\n", - "Epoch 3/10\n", - "136/136 [==============================] - 5s 35ms/step - loss: 1.1950 - accuracy: 0.7044 - val_loss: 2.0601 - val_accuracy: 0.0000e+00\n", - "Epoch 4/10\n", - "136/136 [==============================] - 5s 35ms/step - loss: 1.1062 - accuracy: 0.7488 - val_loss: 1.9844 - val_accuracy: 0.0000e+00\n", - "Epoch 5/10\n", - "136/136 [==============================] - 5s 35ms/step - loss: 0.9996 - accuracy: 0.7671 - val_loss: 1.9182 - val_accuracy: 0.0000e+00\n", - "Epoch 6/10\n", - "136/136 [==============================] - 5s 35ms/step - loss: 0.8900 - accuracy: 0.7841 - val_loss: 1.8775 - val_accuracy: 0.0000e+00\n", - "Epoch 7/10\n", - "136/136 [==============================] - 5s 36ms/step - loss: 0.7846 - accuracy: 0.7979 - val_loss: 1.6075 - val_accuracy: 0.0050\n", - "Epoch 8/10\n", - "136/136 [==============================] - 5s 35ms/step - loss: 0.6920 - accuracy: 0.8165 - val_loss: 1.3300 - val_accuracy: 0.2317\n", - "Epoch 9/10\n", - "136/136 [==============================] - 5s 35ms/step - loss: 0.6098 - accuracy: 0.8512 - val_loss: 1.3028 - val_accuracy: 0.2817\n", - "Epoch 10/10\n", - "136/136 [==============================] - 5s 35ms/step - loss: 0.5365 - accuracy: 0.8791 - val_loss: 1.2423 - val_accuracy: 0.3483\n" + "Epoch 1/25\n", + "107/107 [==============================] - 7s 53ms/step - loss: 1.3220 - accuracy: 0.3903 - val_loss: 2.0543 - val_accuracy: 0.0000e+00\n", + "Epoch 2/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 1.2738 - accuracy: 0.6326 - val_loss: 2.1303 - val_accuracy: 0.0000e+00\n", + "Epoch 3/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 1.2292 - accuracy: 0.6809 - val_loss: 2.1268 - val_accuracy: 0.0000e+00\n", + "Epoch 4/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 1.1699 - accuracy: 0.7018 - val_loss: 1.9158 - val_accuracy: 0.0000e+00\n", + "Epoch 5/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 1.0963 - accuracy: 0.7341 - val_loss: 2.0677 - val_accuracy: 0.0000e+00\n", + "Epoch 6/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 1.0136 - accuracy: 0.7565 - val_loss: 1.9291 - val_accuracy: 0.0000e+00\n", + "Epoch 7/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.9253 - accuracy: 0.7576 - val_loss: 1.6652 - val_accuracy: 0.0000e+00\n", + "Epoch 8/25\n", + "107/107 [==============================] - 5s 45ms/step - loss: 0.8374 - accuracy: 0.7747 - val_loss: 1.4636 - val_accuracy: 0.0900\n", + "Epoch 9/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.7552 - accuracy: 0.8062 - val_loss: 1.2919 - val_accuracy: 0.3367\n", + "Epoch 10/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.6764 - accuracy: 0.8291 - val_loss: 1.3526 - val_accuracy: 0.2433\n", + "Epoch 11/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.6065 - accuracy: 0.8615 - val_loss: 1.2225 - val_accuracy: 0.4283\n", + "Epoch 12/25\n", + "107/107 [==============================] - 5s 45ms/step - loss: 0.5430 - accuracy: 0.8835 - val_loss: 1.0812 - val_accuracy: 0.5650\n", + "Epoch 13/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.4836 - accuracy: 0.9018 - val_loss: 0.8907 - val_accuracy: 0.6800\n", + "Epoch 14/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.4339 - accuracy: 0.9168 - val_loss: 0.8441 - val_accuracy: 0.7067\n", + "Epoch 15/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.3885 - accuracy: 0.9285 - val_loss: 0.7766 - val_accuracy: 0.7267\n", + "Epoch 16/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.3484 - accuracy: 0.9391 - val_loss: 0.5861 - val_accuracy: 0.8150\n", + "Epoch 17/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.3132 - accuracy: 0.9465 - val_loss: 0.6687 - val_accuracy: 0.7617\n", + "Epoch 18/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.2832 - accuracy: 0.9521 - val_loss: 0.5753 - val_accuracy: 0.8117\n", + "Epoch 19/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.2548 - accuracy: 0.9582 - val_loss: 0.5588 - val_accuracy: 0.8167\n", + "Epoch 20/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.2325 - accuracy: 0.9588 - val_loss: 0.4732 - val_accuracy: 0.8400\n", + "Epoch 21/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.2105 - accuracy: 0.9641 - val_loss: 0.4320 - val_accuracy: 0.8617\n", + "Epoch 22/25\n", + "107/107 [==============================] - 5s 45ms/step - loss: 0.1913 - accuracy: 0.9668 - val_loss: 0.3733 - val_accuracy: 0.8833\n", + "Epoch 23/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.1743 - accuracy: 0.9715 - val_loss: 0.3615 - val_accuracy: 0.8800\n", + "Epoch 24/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.1591 - accuracy: 0.9738 - val_loss: 0.3121 - val_accuracy: 0.9083\n", + "Epoch 25/25\n", + "107/107 [==============================] - 5s 44ms/step - loss: 0.1454 - accuracy: 0.9797 - val_loss: 0.2854 - val_accuracy: 0.9167\n" ] } ], @@ -262,7 +281,7 @@ "\n", "adam = optimizers.Adam(learning_rate=7e-6)\n", "model.compile(optimizer=adam, loss=\"sparse_categorical_crossentropy\", metrics=[\"accuracy\"])\n", - "history = model.fit(x, y, validation_split=0.15, epochs=10, batch_size=25)\n" + "history = model.fit(x, y, validation_split=0.15, epochs=25)\n" ] }, { @@ -552,12 +571,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2022-04-13 09:21:03.332590: W tensorflow/python/util/util.cc:368] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "INFO:tensorflow:Assets written to: ../models/rot_25e.model/assets\n" + ] + } + ], "source": [ "# Save the weights\n", - "model.save('../models/model')" + "# model.save('models/rot_25e')" ] } ],

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