From 5ceb57789cf632400a04d646a43776b854e01d4a Mon Sep 17 00:00:00 2001
From: BING GONG <b.gong@fz-juelich.de>
Date: Thu, 9 Jun 2022 10:50:26 +0200
Subject: [PATCH] update the hparameters for weatherbench model
---
.../weatherBench/model_hparams_template.json | 6 ++++--
.../models/weatherBench3DCNN.py | 18 +++++++-----------
2 files changed, 11 insertions(+), 13 deletions(-)
diff --git a/video_prediction_tools/hparams/era5/weatherBench/model_hparams_template.json b/video_prediction_tools/hparams/era5/weatherBench/model_hparams_template.json
index 4f3a43f1..219a4caf 100644
--- a/video_prediction_tools/hparams/era5/weatherBench/model_hparams_template.json
+++ b/video_prediction_tools/hparams/era5/weatherBench/model_hparams_template.json
@@ -1,12 +1,14 @@
{
"batch_size": 4,
- "lr": 0.001,
+ "lr": 0.0001,
"max_epochs":20,
"context_frames":12,
"loss_fun":"mse",
"opt_var": "0",
- "shuffle_on_val":true
+ "shuffle_on_val":true,
+ "filters": [64, 64, 64, 64, 2],
+ "kernels": [5, 5, 5, 5, 5]
}
diff --git a/video_prediction_tools/model_modules/video_prediction/models/weatherBench3DCNN.py b/video_prediction_tools/model_modules/video_prediction/models/weatherBench3DCNN.py
index ca7b6f0b..ac172074 100644
--- a/video_prediction_tools/model_modules/video_prediction/models/weatherBench3DCNN.py
+++ b/video_prediction_tools/model_modules/video_prediction/models/weatherBench3DCNN.py
@@ -24,14 +24,11 @@ class WeatherBenchModel(object):
self.hparams = self.parse_hparams()
self.learning_rate = self.hparams.lr
self.filters = self.hparams.filters
- self.kernels = self.hparams.kernes
+ self.kernels = self.hparams.kernels
self.context_frames = self.hparams.context_frames
- self.sequence_length = self.hparams.sequence_length
- self.predict_frames = self.sequence_length- self.context_frames
self.max_epochs = self.hparams.max_epochs
self.loss_fun = self.hparams.loss_fun
self.batch_size = self.hparams.batch_size
- self.recon_weight = self.hparams.recon_weight
self.outputs = {}
self.total_loss = None
@@ -60,15 +57,13 @@ class WeatherBenchModel(object):
"""
hparams = dict(
context_frames =12,
- sequence_length =24,
max_epochs = 20,
batch_size = 40,
lr = 0.001,
loss_fun = "mse",
shuffle_on_val= True,
- filter = 4,
- kernels = 4,
-
+ filter = [64, 64, 64, 64, 2],
+ kernels = [5, 5, 5, 5, 5]
)
return hparams
@@ -85,8 +80,10 @@ class WeatherBenchModel(object):
x_hat = self.build_model(x, self.filters, self.kernels, dr=0)
# Loss
self.total_loss = l1_loss(x[...,0], x_hat[...,0])
+
# Optimizer
- self.train_op = tf.train.AdamOptimizer(learning_rate = self.learning_rate).minimize(self.total_loss, var_list=self.gen_vars)
+ self.train_op = tf.train.AdamOptimizer(
+ learning_rate = self.learning_rate).minimize(self.total_loss, global_step = self.global_step)
# outputs
self.outputs["total_loss"] = self.total_loss
@@ -111,7 +108,7 @@ class WeatherBenchModel(object):
class PeriodicPadding2D(object):
- def __init__(self, x, pad_width):
+ def __init__(self, pad_width):
self.pad_width = pad_width
@@ -127,7 +124,6 @@ class PeriodicPadding2D(object):
return inputs_padded
-
class PeriodicConv2D(object):
def __init__(self, filters, kernel_size, conv_kwargs={}):
--
GitLab