use dict instead of class

2026-10-03 12:51:38 +08:00 · 2022-11-28 23:13:27 +01:00
1 parent f6e7d77fe4
commit 4e78dd7dc5
@@ -1,4 +1,3 @@
-# +
 from typing import Any, Dict, Iterable, List, Optional

 import torch
@@ -32,7 +31,6 @@ from gluonts.transform import (
    ValidationSplitSampler,
    VstackFeatures,
 )
-from torchscale.architecture.config import EncoderDecoderConfig

 from lightning_module import TorchscaleLightningModule
 from module import TorchscaleModel
@@ -60,7 +58,7 @@ class TorchscaleEstimator(PyTorchLightningEstimator):
        freq: str,
        prediction_length: int,
        # Torchscale arguments
-        enc_dec_config: EncoderDecoderConfig,
+        enc_dec_config: Dict[str, Any],
        input_size: int = 1,
        context_length: Optional[int] = None,
        num_feat_dynamic_real: int = 0,
@@ -287,7 +287,7 @@ class TorchscaleModel(nn.Module):
        num_feat_static_cat: int,
        cardinality: List[int],
        # torchscale config
-        enc_dec_config: EncoderDecoderConfig,
+        enc_dec_config: Dict[str, Any],
        input_size: int = 1,
        embedding_dimension: Optional[List[int]] = None,
        distr_output: DistributionOutput = StudentTOutput(),
@@ -328,11 +328,12 @@ class TorchscaleModel(nn.Module):
        self.distr_output = distr_output
        self.param_proj = distr_output.get_args_proj(d_model)

-        enc_dec_config.encoder_embed_dim = d_model
-        enc_dec_config.decoder_embed_dim = d_model
+        config = EncoderDecoderConfig(**enc_dec_config)
+        config.encoder_embed_dim = d_model
+        config.decoder_embed_dim = d_model

-        self.encoder = Encoder(enc_dec_config)
-        self.decoder = Decoder(enc_dec_config)
+        self.encoder = Encoder(config)
+        self.decoder = Decoder(config)

        # attention_args["dropout"] = dropout
        # attention_args["causal"] = False
@@ -565,7 +566,7 @@ class TorchscaleModel(nn.Module):
            future_time_feat,
        )

-        enc_out = self.encoder(src=encoder_inputs)
+        enc_out = self.encoder(encoder_inputs)

        params = self.param_proj(enc_out.transpose(0, 1))  # (B, T, D)
        distr = self.output_distribution(params, trailing_n=1)
@@ -584,7 +585,7 @@ class TorchscaleModel(nn.Module):
            repeats=self.num_parallel_samples, dim=0
        )
        repeated_enc_out = enc_out.repeat_interleave(
-            repeats=self.num_parallel_samples, dim=0
+            repeats=self.num_parallel_samples, dim=1
        )

        future_samples = []
@@ -35,7 +35,7 @@
     "name": "stderr",
     "output_type": "stream",
     "text": [
-      "2022-11-28 19:48:37.174077: 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:  SSE3 SSE4.1 SSE4.2 AVX AVX2 FMA\n",
+      "2022-11-28 23:05:45.287845: 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:  SSE3 SSE4.1 SSE4.2 AVX AVX2 FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
     ]
    }
@@ -46,7 +46,6 @@
    "from gluonts.evaluation import make_evaluation_predictions, Evaluator\n",
    "from pytorch_lightning.loggers import CSVLogger\n",
    "from datasets import load_dataset\n",
-    "from torchscale.architecture.config import EncoderDecoderConfig\n",
    "\n",
    "from estimator import TorchscaleEstimator"
   ]
@@ -68,7 +67,7 @@
   "metadata": {},
   "outputs": [],
   "source": [
-    "enc_dec_config = EncoderDecoderConfig(\n",
+    "enc_dec_config = dict(\n",
    "    encoder_attention_heads=2,\n",
    "    decoder_attention_heads=2,\n",
    "    encoder_layers=4,\n",
@@ -80,7 +79,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 15,
   "id": "1717d0d2",
   "metadata": {},
   "outputs": [],
@@ -99,7 +98,7 @@
    "        \n",
    "        batch_size=256,\n",
    "        num_batches_per_epoch=100,\n",
-    "        trainer_kwargs=dict(gpus=\"1\", max_epochs=50, logger=CSVLogger(\".\", \"lightning_logs/\")),\n",
+    "        trainer_kwargs=dict(accelerator='gpu', devices='1', max_epochs=50, logger=CSVLogger(\".\", \"lightning_logs/\")),\n",
    "    )"
   ]
  },
@@ -108,7 +107,7 @@
   "execution_count": null,
   "id": "c77b420c",
   "metadata": {
-    "scrolled": true
+    "scrolled": false
   },
   "outputs": [
    {
@@ -117,8 +116,6 @@
     "text": [
      "/home/kashif/.env/pytorch/lib/python3.10/site-packages/pytorch_lightning/utilities/parsing.py:262: UserWarning: Attribute 'model' is an instance of `nn.Module` and is already saved during checkpointing. It is recommended to ignore them using `self.save_hyperparameters(ignore=['model'])`.\n",
      "  rank_zero_warn(\n",
-      "/home/kashif/.env/pytorch/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/accelerator_connector.py:446: LightningDeprecationWarning: Setting `Trainer(gpus='1')` is deprecated in v1.7 and will be removed in v2.0. Please use `Trainer(accelerator='gpu', devices='1')` instead.\n",
-      "  rank_zero_deprecation(\n",
      "GPU available: True (cuda), used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
@@ -142,7 +139,7 @@
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "093dab1c2d694f2b879622f8a21f139e",
+       "model_id": "a197e41cbd984592a31e541a6ef43a59",
       "version_major": 2,
       "version_minor": 0
      },
@@ -157,17 +154,31 @@
     "name": "stderr",
     "output_type": "stream",
     "text": [
-      "Epoch 0, global step 100: 'train_loss' reached 6.82088 (best 6.82088), saving model to './lightning_logs/version_10/checkpoints/epoch=0-step=100.ckpt' as top 1\n",
-      "Epoch 1, global step 200: 'train_loss' reached 5.84754 (best 5.84754), saving model to './lightning_logs/version_10/checkpoints/epoch=1-step=200.ckpt' as top 1\n",
-      "Epoch 2, global step 300: 'train_loss' reached 5.61930 (best 5.61930), saving model to './lightning_logs/version_10/checkpoints/epoch=2-step=300.ckpt' as top 1\n",
-      "Epoch 3, global step 400: 'train_loss' reached 5.47171 (best 5.47171), saving model to './lightning_logs/version_10/checkpoints/epoch=3-step=400.ckpt' as top 1\n",
-      "Epoch 4, global step 500: 'train_loss' reached 5.35223 (best 5.35223), saving model to './lightning_logs/version_10/checkpoints/epoch=4-step=500.ckpt' as top 1\n",
-      "Epoch 5, global step 600: 'train_loss' reached 5.30912 (best 5.30912), saving model to './lightning_logs/version_10/checkpoints/epoch=5-step=600.ckpt' as top 1\n",
-      "Epoch 6, global step 700: 'train_loss' reached 5.25711 (best 5.25711), saving model to './lightning_logs/version_10/checkpoints/epoch=6-step=700.ckpt' as top 1\n",
-      "Epoch 7, global step 800: 'train_loss' was not in top 1\n",
-      "Epoch 8, global step 900: 'train_loss' reached 5.22801 (best 5.22801), saving model to './lightning_logs/version_10/checkpoints/epoch=8-step=900.ckpt' as top 1\n",
-      "Epoch 9, global step 1000: 'train_loss' reached 5.16079 (best 5.16079), saving model to './lightning_logs/version_10/checkpoints/epoch=9-step=1000.ckpt' as top 1\n",
-      "Epoch 10, global step 1100: 'train_loss' was not in top 1\n"
+      "Epoch 0, global step 100: 'train_loss' reached 6.56327 (best 6.56327), saving model to './lightning_logs/version_20/checkpoints/epoch=0-step=100.ckpt' as top 1\n",
+      "Epoch 1, global step 200: 'train_loss' reached 5.91539 (best 5.91539), saving model to './lightning_logs/version_20/checkpoints/epoch=1-step=200.ckpt' as top 1\n",
+      "Epoch 2, global step 300: 'train_loss' reached 5.66458 (best 5.66458), saving model to './lightning_logs/version_20/checkpoints/epoch=2-step=300.ckpt' as top 1\n",
+      "Epoch 3, global step 400: 'train_loss' reached 5.46733 (best 5.46733), saving model to './lightning_logs/version_20/checkpoints/epoch=3-step=400.ckpt' as top 1\n",
+      "Epoch 4, global step 500: 'train_loss' reached 5.36346 (best 5.36346), saving model to './lightning_logs/version_20/checkpoints/epoch=4-step=500.ckpt' as top 1\n",
+      "Epoch 5, global step 600: 'train_loss' reached 5.27607 (best 5.27607), saving model to './lightning_logs/version_20/checkpoints/epoch=5-step=600.ckpt' as top 1\n",
+      "Epoch 6, global step 700: 'train_loss' reached 5.25226 (best 5.25226), saving model to './lightning_logs/version_20/checkpoints/epoch=6-step=700.ckpt' as top 1\n",
+      "Epoch 7, global step 800: 'train_loss' reached 5.20599 (best 5.20599), saving model to './lightning_logs/version_20/checkpoints/epoch=7-step=800.ckpt' as top 1\n",
+      "Epoch 8, global step 900: 'train_loss' was not in top 1\n",
+      "Epoch 9, global step 1000: 'train_loss' reached 5.16118 (best 5.16118), saving model to './lightning_logs/version_20/checkpoints/epoch=9-step=1000.ckpt' as top 1\n",
+      "Epoch 10, global step 1100: 'train_loss' was not in top 1\n",
+      "Epoch 11, global step 1200: 'train_loss' reached 5.15817 (best 5.15817), saving model to './lightning_logs/version_20/checkpoints/epoch=11-step=1200.ckpt' as top 1\n",
+      "Epoch 12, global step 1300: 'train_loss' reached 5.15382 (best 5.15382), saving model to './lightning_logs/version_20/checkpoints/epoch=12-step=1300.ckpt' as top 1\n",
+      "Epoch 13, global step 1400: 'train_loss' reached 5.11824 (best 5.11824), saving model to './lightning_logs/version_20/checkpoints/epoch=13-step=1400.ckpt' as top 1\n",
+      "Epoch 14, global step 1500: 'train_loss' was not in top 1\n",
+      "Epoch 15, global step 1600: 'train_loss' was not in top 1\n",
+      "Epoch 16, global step 1700: 'train_loss' was not in top 1\n",
+      "Epoch 17, global step 1800: 'train_loss' reached 5.10534 (best 5.10534), saving model to './lightning_logs/version_20/checkpoints/epoch=17-step=1800.ckpt' as top 1\n",
+      "Epoch 18, global step 1900: 'train_loss' reached 5.09408 (best 5.09408), saving model to './lightning_logs/version_20/checkpoints/epoch=18-step=1900.ckpt' as top 1\n",
+      "Epoch 19, global step 2000: 'train_loss' reached 5.07192 (best 5.07192), saving model to './lightning_logs/version_20/checkpoints/epoch=19-step=2000.ckpt' as top 1\n",
+      "Epoch 20, global step 2100: 'train_loss' was not in top 1\n",
+      "Epoch 21, global step 2200: 'train_loss' was not in top 1\n",
+      "Epoch 22, global step 2300: 'train_loss' was not in top 1\n",
+      "Epoch 23, global step 2400: 'train_loss' was not in top 1\n",
+      "Epoch 24, global step 2500: 'train_loss' was not in top 1\n"
     ]
    }
   ],
@@ -182,9 +193,11 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
   "id": "f8a362b6",
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
   "outputs": [],
   "source": [
    "forecast_it, ts_it = make_evaluation_predictions(\n",
@@ -195,7 +208,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
   "id": "5fdc12da",
   "metadata": {},
   "outputs": [],
@@ -205,7 +218,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
   "id": "4b7d3409",
   "metadata": {},
   "outputs": [],
@@ -215,7 +228,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
   "id": "9b154bde",
   "metadata": {},
   "outputs": [],
@@ -225,7 +238,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
   "id": "0fdec8a7",
   "metadata": {},
   "outputs": [
@@ -233,8 +246,7 @@
     "name": "stderr",
     "output_type": "stream",
     "text": [
-      "\n",
-      "Running evaluation: 2247it [00:00, 3399.98it/s]\n",
+      "Running evaluation: 2247it [00:00, 3771.68it/s]\n",
      "/home/kashif/.env/pytorch/lib/python3.10/site-packages/pandas/core/dtypes/astype.py:170: UserWarning: Warning: converting a masked element to nan.\n",
      "  return arr.astype(dtype, copy=True)\n"
     ]
@@ -246,59 +258,59 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
   "id": "7f28f4d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
-       "{'MSE': 10018107.873432416,\n",
-       " 'abs_error': 26035099.499095917,\n",
+       "{'MSE': 28224175.008797746,\n",
+       " 'abs_error': 37351447.05586052,\n",
       " 'abs_target_sum': 128632956.0,\n",
       " 'abs_target_mean': 2385.272140631954,\n",
       " 'seasonal_error': 189.49338196116761,\n",
-       " 'MASE': 2.4701614804361784,\n",
-       " 'MAPE': 0.25477670689181103,\n",
-       " 'sMAPE': 0.24819572961811426,\n",
-       " 'MSIS': 20.209983280943216,\n",
-       " 'QuantileLoss[0.1]': 11107718.37581723,\n",
-       " 'Coverage[0.1]': 0.1886774959204866,\n",
-       " 'QuantileLoss[0.2]': 17534385.729109436,\n",
-       " 'Coverage[0.2]': 0.2506860999851654,\n",
-       " 'QuantileLoss[0.3]': 21799774.12036043,\n",
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-       " 'QuantileLoss[0.4]': 24542475.651297044,\n",
-       " 'Coverage[0.4]': 0.3366525738021065,\n",
-       " 'QuantileLoss[0.5]': 26035099.4930306,\n",
-       " 'Coverage[0.5]': 0.37475893784305,\n",
-       " 'QuantileLoss[0.6]': 26299950.11746931,\n",
-       " 'Coverage[0.6]': 0.4088785046728972,\n",
-       " 'QuantileLoss[0.7]': 24979193.32426689,\n",
-       " 'Coverage[0.7]': 0.4523809523809524,\n",
-       " 'QuantileLoss[0.8]': 21707479.345738567,\n",
-       " 'Coverage[0.8]': 0.5081590268506158,\n",
-       " 'QuantileLoss[0.9]': 15351255.969729993,\n",
-       " 'Coverage[0.9]': 0.6027110221035455,\n",
-       " 'RMSE': 3165.1394714028665,\n",
-       " 'NRMSE': 1.3269510918633773,\n",
-       " 'ND': 0.20239836126517932,\n",
-       " 'wQuantileLoss[0.1]': 0.08635204166354717,\n",
-       " 'wQuantileLoss[0.2]': 0.13631332338432334,\n",
-       " 'wQuantileLoss[0.3]': 0.16947269811913854,\n",
-       " 'wQuantileLoss[0.4]': 0.19079461760403799,\n",
-       " 'wQuantileLoss[0.5]': 0.2023983612180272,\n",
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-       " 'mean_absolute_QuantileLoss': 21039703.56964661,\n",
-       " 'mean_wQuantileLoss': 0.1635638659322002,\n",
-       " 'MAE_Coverage': 0.15104954754487465,\n",
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+       " 'MAPE': 0.30876189776929736,\n",
+       " 'sMAPE': 0.3119385377116399,\n",
+       " 'MSIS': 26.850209888001007,\n",
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+       " 'QuantileLoss[0.4]': 34646364.46083483,\n",
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+       " 'QuantileLoss[0.5]': 37351446.74963215,\n",
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+       " 'QuantileLoss[0.6]': 38735412.66370968,\n",
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+       " 'QuantileLoss[0.7]': 38193044.51865159,\n",
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+       " 'QuantileLoss[0.8]': 35495781.72468124,\n",
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+       " 'QuantileLoss[0.9]': 29017368.437739775,\n",
+       " 'Coverage[0.9]': 0.6522771102210354,\n",
+       " 'RMSE': 5312.642940081494,\n",
+       " 'NRMSE': 2.227269102582971,\n",
+       " 'ND': 0.2903722981835271,\n",
+       " 'wQuantileLoss[0.1]': 0.12838358950141798,\n",
+       " 'wQuantileLoss[0.2]': 0.19155256038305457,\n",
+       " 'wQuantileLoss[0.3]': 0.23713488612749123,\n",
+       " 'wQuantileLoss[0.4]': 0.2693428304705587,\n",
+       " 'wQuantileLoss[0.5]': 0.29037229580289015,\n",
+       " 'wQuantileLoss[0.6]': 0.30113132643635804,\n",
+       " 'wQuantileLoss[0.7]': 0.29691492527507174,\n",
+       " 'wQuantileLoss[0.8]': 0.27594624914536864,\n",
+       " 'wQuantileLoss[0.9]': 0.22558269155953917,\n",
+       " 'mean_absolute_QuantileLoss': 31677456.957716737,\n",
+       " 'mean_wQuantileLoss': 0.2462623727446389,\n",
+       " 'MAE_Coverage': 0.13158944436203004,\n",
       " 'OWA': nan}"
      ]
     },
-     "execution_count": 14,
+     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
@@ -309,13 +321,13 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
   "id": "cc3f804d",
   "metadata": {},
   "outputs": [
    {
     "data": {
-      "image/png": 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truncated
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truncated
      "text/plain": [
       "<Figure size 2000x1500 with 9 Axes>"
      ]