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jupyter: identity test

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status: FAILED, as usual....!
Don't worry though, 'cause we has a *planses*..... MUHAHAHAHAHAHAHA
* cue evil laugh *
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Starbeamrainbowlabs 2022-12-09 18:07:56 +00:00
parent cf9e8aa237
commit 7fd7c750d6
Signed by: sbrl
GPG key ID: 1BE5172E637709C2
1 changed files with 26 additions and 40 deletions
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66
aimodel/src/rainfallwater_identity_TEST.ipynb
View file

@ -2,19 +2,10 @@
"cells": [ "cells": [
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 6,
"id": "1f6fdebf-69c5-46ab-a5a8-f9c91f000ff3", "id": "1f6fdebf-69c5-46ab-a5a8-f9c91f000ff3",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [],
{
"name": "stderr",
"output_type": "stream",
"text": [
"2022-12-09 15:49:31.909879: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\n",
"2022-12-09 15:49:31.909893: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\n"
]
}
],
"source": [ "source": [
"import os\n", "import os\n",
"\n", "\n",
@ -28,7 +19,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": 7,
"id": "07093079", "id": "07093079",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -42,7 +33,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": 8,
"id": "f4466ac9", "id": "f4466ac9",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -52,27 +43,7 @@
"text": [ "text": [
"RAINFALL channels 1 width 64 height 64 HEIGHTMAP_INPUT False\n", "RAINFALL channels 1 width 64 height 64 HEIGHTMAP_INPUT False\n",
"convnext:shape IN x (None, 64, 64, 1)\n", "convnext:shape IN x (None, 64, 64, 1)\n",
"DEBUG:convnext shape x (None, 64, 64, 1)\n" "DEBUG:convnext shape x (None, 64, 64, 1)\n",
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"2022-12-09 15:49:34.026632: E tensorflow/stream_executor/cuda/cuda_driver.cc:271] failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW\n",
"2022-12-09 15:49:34.026670: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: SIMVIS-CO45428A\n",
"2022-12-09 15:49:34.026678: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: SIMVIS-CO45428A\n",
"2022-12-09 15:49:34.026772: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:200] libcuda reported version is: 510.108.3\n",
"2022-12-09 15:49:34.026795: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:204] kernel reported version is: 510.85.2\n",
"2022-12-09 15:49:34.026801: E tensorflow/stream_executor/cuda/cuda_diagnostics.cc:313] kernel version 510.85.2 does not match DSO version 510.108.3 -- cannot find working devices in this configuration\n",
"2022-12-09 15:49:34.027072: I tensorflow/core/platform/cpu_feature_guard.cc:193] 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"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"DEBUG:model ENCODER output_shape (None, 512)\n", "DEBUG:model ENCODER output_shape (None, 512)\n",
"DEBUG:model BOTTLENECK:stack2image output_shape (None, 4, 4, 512)\n" "DEBUG:model BOTTLENECK:stack2image output_shape (None, 4, 4, 512)\n"
] ]
@ -81,8 +52,8 @@
"name": "stderr", "name": "stderr",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"2022-12-09 15:49:37.559 | WARNING | lib.ai.model_rainfallwater_mono:model_rainfallwater_mono:70 - Warning: TODO implement attention from https://ieeexplore.ieee.org/document/9076883\n", "2022-12-09 17:35:07.608 | WARNING | lib.ai.model_rainfallwater_mono:model_rainfallwater_mono:70 - Warning: TODO implement attention from https://ieeexplore.ieee.org/document/9076883\n",
"2022-12-09 15:49:37.613 | INFO | lib.ai.model_rainfallwater_mono:model_rainfallwater_mono:80 - learning_rate: None\n" "2022-12-09 17:35:07.656 | INFO | lib.ai.model_rainfallwater_mono:model_rainfallwater_mono:80 - learning_rate: None\n"
] ]
} }
], ],
@ -97,7 +68,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": 9,
"id": "78c633e1", "id": "78c633e1",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -120,7 +91,7 @@
"for item in dataset_labels:\n", "for item in dataset_labels:\n",
"\tprint(\"cells\", 64*64, \"cells/2\", (64*64)/2, \"shape+\", item.shape, tf.math.reduce_sum(tf.math.argmax(item, axis=-1)))\n", "\tprint(\"cells\", 64*64, \"cells/2\", (64*64)/2, \"shape+\", item.shape, tf.math.reduce_sum(tf.math.argmax(item, axis=-1)))\n",
"\tbreak\n", "\tbreak\n",
"dataset = tf.data.Dataset.zip((dataset, dataset_labels)) \\\n", "dataset = tf.data.Dataset.zip((dataset_labels, dataset_labels)) \\\n",
"\t.repeat(64 * 64) \\\n", "\t.repeat(64 * 64) \\\n",
"\t.batch(64) \\\n", "\t.batch(64) \\\n",
"\t.prefetch(tf.data.AUTOTUNE)\n" "\t.prefetch(tf.data.AUTOTUNE)\n"
@ -128,7 +99,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": 10,
"id": "3dbc95eb", "id": "3dbc95eb",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -136,7 +107,22 @@
"name": "stdout", "name": "stdout",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"Epoch 1/50\n" "Epoch 1/50\n",
"WARNING:tensorflow:Model was constructed with shape (None, 64, 64, 1) for input KerasTensor(type_spec=TensorSpec(shape=(None, 64, 64, 1), dtype=tf.float32, name='input_3'), name='input_3', description=\"created by layer 'input_3'\"), but it was called on an input with incompatible shape (None, 64, 64, 2).\n",
"WARNING:tensorflow:Model was constructed with shape (None, 64, 64, 1) for input KerasTensor(type_spec=TensorSpec(shape=(None, 64, 64, 1), dtype=tf.float32, name='input_4'), name='input_4', description=\"created by layer 'input_4'\"), but it was called on an input with incompatible shape (None, 64, 64, 2).\n"
]
},
{
"ename": "ValueError",
"evalue": "in user code:\n\n File \"/home/bryan-smithl/.local/lib/python3.10/site-packages/keras/engine/training.py\", line 1051, in train_function *\n return step_function(self, iterator)\n File \"/home/bryan-smithl/.local/lib/python3.10/site-packages/keras/engine/training.py\", line 1040, in step_function **\n outputs = model.distribute_strategy.run(run_step, args=(data,))\n File \"/home/bryan-smithl/.local/lib/python3.10/site-packages/keras/engine/training.py\", line 1030, in run_step **\n outputs = model.train_step(data)\n File \"/home/bryan-smithl/.local/lib/python3.10/site-packages/keras/engine/training.py\", line 889, in train_step\n y_pred = self(x, training=True)\n File \"/home/bryan-smithl/.local/lib/python3.10/site-packages/keras/utils/traceback_utils.py\", line 67, in error_handler\n raise e.with_traceback(filtered_tb) from None\n File \"/home/bryan-smithl/.local/lib/python3.10/site-packages/keras/engine/input_spec.py\", line 248, in assert_input_compatibility\n raise ValueError(\n\n ValueError: Exception encountered when calling layer \"convnext1\" (type Functional).\n \n Input 0 of layer \"downsample_layers.0.0_conv\" is incompatible with the layer: expected axis -1 of input shape to have value 1, but received input with shape (None, 64, 64, 2)\n \n Call arguments received by layer \"convnext1\" (type Functional):\n • inputs=tf.Tensor(shape=(None, 64, 64, 2), dtype=float32)\n • training=True\n • mask=None\n",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn [10], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m model\u001b[39m.\u001b[39mfit(\n\u001b[1;32m 2\u001b[0m \tdataset,\n\u001b[1;32m 3\u001b[0m \tepochs\u001b[39m=\u001b[39m\u001b[39m50\u001b[39m,\n\u001b[1;32m 4\u001b[0m \tcallbacks\u001b[39m=\u001b[39mmake_callbacks(\u001b[39m\"\u001b[39m\u001b[39m/tmp/x/mono_segment_TEST\u001b[39m\u001b[39m\"\u001b[39m, model)\n\u001b[1;32m 5\u001b[0m )\n",
"File \u001b[0;32m~/.local/lib/python3.10/site-packages/keras/utils/traceback_utils.py:67\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 65\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mException\u001b[39;00m \u001b[39mas\u001b[39;00m e: \u001b[39m# pylint: disable=broad-except\u001b[39;00m\n\u001b[1;32m 66\u001b[0m filtered_tb \u001b[39m=\u001b[39m _process_traceback_frames(e\u001b[39m.\u001b[39m__traceback__)\n\u001b[0;32m---> 67\u001b[0m \u001b[39mraise\u001b[39;00m e\u001b[39m.\u001b[39mwith_traceback(filtered_tb) \u001b[39mfrom\u001b[39;00m \u001b[39mNone\u001b[39m\n\u001b[1;32m 68\u001b[0m \u001b[39mfinally\u001b[39;00m:\n\u001b[1;32m 69\u001b[0m \u001b[39mdel\u001b[39;00m filtered_tb\n",
"File \u001b[0;32m/tmp/__autograph_generated_filey37nprp8.py:15\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__train_function\u001b[0;34m(iterator)\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m 14\u001b[0m do_return \u001b[39m=\u001b[39m \u001b[39mTrue\u001b[39;00m\n\u001b[0;32m---> 15\u001b[0m retval_ \u001b[39m=\u001b[39m ag__\u001b[39m.\u001b[39mconverted_call(ag__\u001b[39m.\u001b[39mld(step_function), (ag__\u001b[39m.\u001b[39mld(\u001b[39mself\u001b[39m), ag__\u001b[39m.\u001b[39mld(iterator)), \u001b[39mNone\u001b[39;00m, fscope)\n\u001b[1;32m 16\u001b[0m \u001b[39mexcept\u001b[39;00m:\n\u001b[1;32m 17\u001b[0m do_return \u001b[39m=\u001b[39m \u001b[39mFalse\u001b[39;00m\n",
"\u001b[0;31mValueError\u001b[0m: in user code:\n\n File \"/home/bryan-smithl/.local/lib/python3.10/site-packages/keras/engine/training.py\", line 1051, in train_function *\n return step_function(self, iterator)\n File \"/home/bryan-smithl/.local/lib/python3.10/site-packages/keras/engine/training.py\", line 1040, in step_function **\n outputs = model.distribute_strategy.run(run_step, args=(data,))\n File \"/home/bryan-smithl/.local/lib/python3.10/site-packages/keras/engine/training.py\", line 1030, in run_step **\n outputs = model.train_step(data)\n File \"/home/bryan-smithl/.local/lib/python3.10/site-packages/keras/engine/training.py\", line 889, in train_step\n y_pred = self(x, training=True)\n File \"/home/bryan-smithl/.local/lib/python3.10/site-packages/keras/utils/traceback_utils.py\", line 67, in error_handler\n raise e.with_traceback(filtered_tb) from None\n File \"/home/bryan-smithl/.local/lib/python3.10/site-packages/keras/engine/input_spec.py\", line 248, in assert_input_compatibility\n raise ValueError(\n\n ValueError: Exception encountered when calling layer \"convnext1\" (type Functional).\n \n Input 0 of layer \"downsample_layers.0.0_conv\" is incompatible with the layer: expected axis -1 of input shape to have value 1, but received input with shape (None, 64, 64, 2)\n \n Call arguments received by layer \"convnext1\" (type Functional):\n • inputs=tf.Tensor(shape=(None, 64, 64, 2), dtype=float32)\n • training=True\n • mask=None\n"
] ]
} }
], ],